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  • Zhu Yesen, Wang Jingkun, Wang Chong, Zhuang Tiegang, Shen Yusheng, Wang Jun
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    Based on the practical needs of offshore photovoltaic systems, various floating wave-dissipation structures were designed and tested in a two-dimensional large-scale wave tank under irregular wave conditions. Time-domain response signals were measured, and the wave transmission coefficient, reflection coefficient, and wave energy dissipation coefficient were analyzed. The study demonstrates that compared to single-floating-box breakwater, increasing the width of a single floating box, adding additional floating boxes, and incorporating vertical insert plates or wing plates on the bottom can significantly enhance wave energy dissipation and improve wave attenuation. For the designed double-floating-boxes structure, each 0.5 m increase in the slanted wing depth reduces the transmission coefficient by an average of 15%. Additionally, installing a porous plate between the pontoons further reduces the transmission coefficient. Under irregular waves with an effective wave height of 2 m, the wave energy transmitted through the dual-pontoon floating breakwater with wing plates and porous insert plates is only 12% left, meeting the wave attenuation requirements for offshore floating photovoltaic power stations.
  • Zhang Tao, Bai Wenlong, Zhang Li, Han Qinglin, Li Yunfei, Zhang Yafei
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    To address the issues of low voltage gain and high voltage stress existing in traditional quasi-Z-source DC-DC converters, a high-gain soft-switching quasi-Z-source DC-DC converter (HGSS-QZS) is proposed. By adjusting both the turns ratio of the three-winding coupled inductor and the duty cycle of the switch, the boost capability and the flexibility of gain adjustment are improved. A clamping circuit is employed to absorb the leakage energy of the coupled inductor, reducing the voltage spikes caused by leakage inductance. Firstly, the operating principle of the HGSS-QZS converter is analyzed in detail, and voltage gain, device voltage and current stress, and efficiency losses are derived. Next, parameter design is carried out and compared with existing converters, demonstrating that the HGSS-QZS converter offers high voltage gain, low voltage stress on components, soft-switching capability, and high efficiency. Finally, a 200 W experimental prototype was built, and the validity and feasibility of the HGSS-QZS converter were verified through simulation and experimental comparison.
  • Shi Hongyan, Li Shangda, Pan Duotao, Wang Guogang
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    In order to improve the fault diagnosis accuracy of neural networks for photovoltaic arrays, a method for photovoltaic array fault diagnosis is proposed to obtain data through simulation and perform VMD decomposition, and to use an improved cauchy-osprey-mapping team-based optimization(COMTBO) for bidirectional long short-term memory(BiLSTM) network. Firstly, a photovoltaic array model is built in Matlab/Simulink software environment for data feature analysis, simulating photovoltaic array faults, and introducing more fault features to form fault data. Variational mode decomposition (VMD) is used to decompose the fault data into multiple components, and the modal component corresponding to the maximum energy is selected as the input quantity. Then, a COMTBO algorithm that integrates chaotic mapping, osprey optimization algorithm (OOA), and cauchy mutation strategy is proposed to optimize the parameters of BiLSTM. A VMD-COMTBO BiLSTM neural network model is constructed to achieve a fault diagnosis rate of 98% for photovoltaic arrays. In actual experiments, the accuracy rate also reaches over 99%.
  • Zhou Honglian, Liao Mengke, Maimaiti Aili·Wupuer, Cui Yong, Zheng Jian, Wu Wenying
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    In the context of constructing a new-type power system dominated by renewable energy, this study introduces an electricity-carbon coupling operational decision-making mechanism for photovoltaic power generation clusters. The goal is to fully utilize the potential of large-scale grid-connected photovoltaic power generation in supporting energy conservation and carbon reduction, while also enhancing the operational efficiency of power systems through the unified management of photovoltaic power stations. The design and theoretical analysis are concentrated on three key aspects: 1) Photovoltaic cluster partitioning methods that consider electricity-carbon indicators; 2) The construction of a critical path analysis model for the impact of photovoltaic clusters on system electricity-carbon indicators; 3) The establishment of an efficiency decision-making framework for electricity-carbon coupling operations within photovoltaic cluster models. Finally, the paper outlines future research priorities. The proposed approach establishes a foundation for analyzing how photovoltaic clusters can support low-carbon operational efficiency, provides analytical methods to clarify carbon emission responsibilities across operational stages and identify management weaknesses, and offers a reference for system operation mode adjustments and low-carbon dispatch decision-making.
  • Lu Ting, Guo Qian, Wei Dong, Wang Chongxi
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    Based on the equivalent circuit of solar cells, a model for the I-V output characteristics of photovoltaic strings is established. By using numerical solutions, a method for calculating the model parameters and maximum power point under any ambient temperature and irradiance is proposed. Furthermore, a time series output characteristics model of photovoltaic strings is developed. For faults such as aging, potential-induced degradation (PID), micro-cracks, and hotspots, the differential change patterns under different types and degrees of faults are studied. According to the variation characteristics of the time series and global maximum power point curves, fault features are identified and extracted to distinguish fault types and describe fault severity. Simulation and experimental results show that the established model and proposed method can accurately fit the measured data. The calculated model parameters and global maximum power points under various irradiance levels and ambient temperatures exhibit distinct variation patterns. The proposed fault feature metrics can effectively differentiate fault types and describe changes in fault severity.
  • Li Hengjie, Long Xianhua, Zhou Yun, Feng Donghan, Ma Xiping
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    For accuracy limitations in photovoltaic (PV) power prediction due to the intermittent and stochastic nature of PV power generation, this study proposes a short-term PV power prediction model based on spatio-temporal dual-stream networks and multi-attention. The model integrates networks ModernTCN, ITransformer, GRU, and TimesNet networks, effectively exploring the spatial distribution characteristics and temporal dynamics of PV power generation. In addition, the model fuses extracted features, and generates feature vectors rich in Spatio-Temporal information by an iterative cross-attention feature mechanism. Experimental results demonstrate that the model is superior to the current mainstream timing series models in terms of prediction accuracy.
  • Wen Xiankui, He Mingjun, Zhou Ke, Li Xiaojiang, Tang Qian
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    This article proposes a cluster partitioning method based on median and mean as calculation indicators and using BIRCH clustering algorithm to address the problems of limited raw data and information in power prediction of distributed photovoltaics. On the basis of cluster division, cluster accumulation method is adopted to predict the photovoltaic power of each cluster using multiple models, and then the prediction results of all clusters are integrated to achieve distributed photovoltaic area prediction. This article combines data from 18 distributed photovoltaic power stations in a certain region of Guizhou Province for simulation analysis. The experimental results show that the proposed algorithm has high accuracy and the proposed method can meet the practical application requirements.
  • Dou Zhenlan, Wu Songmei, Guo Hui, Zhang Chunyan, Wang Fei
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    To enhance the accuracy of PV power forecasting, this paper proposes a combined forecasting model for PV power based on CEEMDAN and a serial CNN-GRU network. Firstly, considering the impact of PV power fluctuations on the forecasting results, CEEMDAN is used to decompose the original PV power into several subsequences to reduce the non-stationarity of the sequence. Each subsequence’s sample entropy(SE) is then calculated to measure its complexity, and subsequences with similar SE values are regrouped to reduce computational load. Secondly, to overcome the limitations of a single neural network in learning the historical characteristics of PV power, a serial CNN-GRU hybrid neural network is proposed to explore the spatiotemporal features of PV powerfully. Each subsequence is input into the serial CNN-GRU network to obtain the forecasting results, and the predicted values of the subsequences are summed to yield the final PV power forecasting results. Finally, case studies on PV power plants in two regions are conducted, with comparative validation against LSTM, GRU, CEEMDAN-LSTM, CEEMDAN-GRU, and the serial CNN-GRU models. The results show that the proposed model achieves superior forecasting accuracy and generalization capability.
  • Lyu Jianguo, Zhou Yuanqiong, Wu Pengtao, Xie Qun, Xu Zhiqiang, Hu Yi
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    To further address the voltage fluctuations and limit violations caused by the grid-connection of high-penetration photovoltaic (PV) plants, a fast reactive voltage control method for photovoltaic virtual synchronous generators (VSG) based on model predictive control (MPC) is proposed. Firstly, a dynamic model of VSG-based reactive power-voltage control is established based on its reactive power-voltage characteristics. Then, a discrete reactive power-voltage state-space incremental equation is formulated using the MPC framework. This model predicts the required reactive power capacity sequence by considering the future grid voltage error over a prediction horizon, and continuously updates and tracks the optimal solution through rolling optimization and feedback correction to minimize the deviation between the future grid voltage output and the reference trajectory, and the fast reactive power-voltage control for the PV VSG system is achieved. Besides, the closed-loop system stability of this model is analyzed. Suitable weighting coefficients are determined by calculating the system eigenvalues to ensure convergence. Finally, a simulation model of a PV plant interconnected into a two-area transmission network is established to verify the correctness and effectiveness of the proposed control method.
  • Chen Jiming, Guo Jin, Liu Jing, Huang Lei, Song Junzhi
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    In this work, a maximum power tracking method based on average power estimation is proposed to solve the problem of insufficient accuracy of traditional maximum power point tracking algorithm in floating photovoltaic environment. And a simulation model is built in Matlab/Simulink software to verify the effectiveness of this method. Finally, the results show that the maximum power tracking method based on average power estimation demonstrates superior dynamic tracking ability and higher accuracy, compared with the perturbation and observe method and particle swarm optimization algorithm.
  • Li Mengyang, Chen Liu, Shi Meng, Zhao Yujiao
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    To address the issue of low prediction accuracy caused by the strong randomness and high volatility of photovoltaic power generation, a hybrid prediction model based on aggregated mode decomposition(AMD), temporal convolutional network (TCN) and bidirectional gated recurrent unit (BiGRU) is proposed. In view of the randomness and high volatility of photovoltaic power generation, a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is used to decompose the original photovoltaic sequence data for the first time, and a series of sub-sequences with different frequencies are obtained. Sample entropy (SE) is used to segment the molecular sequence, retaining the low-frequency and medium-frequency components of the signal. The high-frequency components obtained by CEEMDAN is decomposed secondarily by successive variational mode decomposition (SVMD) to reduce the sequence instability. Finally, the TCN-BiGRU model is used to predict each component, and final photovoltaic power prediction result is obtained by superimposing the prediction of each component. Experiments based on the analysis of arithmetic instances demonstrate that the forecasting accuracy and stability of the proposed hybrid prediction model outperform other approaches in photovoltaic power forecasting.
  • Chen Xintang, Zhou Heng, Wei Jianpeng, Li Dahua, Meng Jiabao
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    Based on a photovoltaic bracket optimization project, a full-scale photovoltaic bracket structure is fabricated in order to study its bearing capacity under wind load. A static loading test, along with numerical simulations, is performed to evaluate the mechanical properties of the structure. Furthermore, the force response of the structure under negative wind pressure conditions is examined. The results indicate that the structural members remain within the material yield stress limits, and their deflections satisfy the code requirements. The finite element simulation closely matches the experimental results, validating the accuracy of the simulation method. In conclusion, the photovoltaic bracket structure exhibits adequate bearing capacity under 140% of the design load, with local instability of the steel beam identified as the primary mode of structural failure.
  • Xu Guimin, Song Yuhang, Xiangli Mengqiao, Yang Yalong, Duan Chendong
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    This paper presents a method based on an improved sparrow search algorithm (ISSA) and optimized random forest (RF) model, aiming to improve the accuracy of fault diagnosis in photovoltaic arrays. Firstly, the photovoltaic fault data set is constructed by building a photovoltaic array to simulate five fault conditions and extracting fault vectors. Secondly, the optimization comparison among sparrow search algorithm (ISSA), grey wolf optimization (GWO), particle swarm optimization (PSO) and ISSA by test function is performed. The results indicate that ISSA is better than other algorithms in terms of mean value and standard deviation, showing better robustness. Then, the performance of ISSA-RF is analyzed using the simulation data set of photovoltaic array fault. It can be found that the overall accuracy of ISSA-RF reaches 97.06%, which is 6.94 percentage points higher than the traditional RF model. Finally, the data set under five different working conditions including open circuit, short circuit, shade, aging and normal operation are collected for testing ISSA-RF. The research outcomes prove that this model has high classification efficiency and accuracy, and its performance is superior to other models.
  • Yu Zhongming, Zhang Yu, Lu Ketong, Chen Keyu, Liu Zhijian, Dai Xin
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    To improve the accuracy of fault diagnosis for photovoltaic (PV) arrays, this study proposes a hybrid fault diagnosis model combining the improved honey badger algorithm(IHBA) with the bidirectional long short-term memory (BiLSTM) network. Different from feature engineering oriented to power prediction, this paper focuses on fault identification, and systematically extracts three types of features covering basic, discrete and distributional statistics from the current-voltage and power-voltage characteristic curves of PV arrays, forming a 10-dimensional comprehensive feature vector.Aiming at the defects of the original Honey Badger Algorithm such as premature convergence and insufficient search efficiency, the IHBA is improved in three aspects: Tent chaos mapping is adopted to optimize the initial population distribution; a dynamic adaptive control factor is designed to balance the search process; and the pinhole imaging reverse learning strategy is introduced to enhance the global optimization ability. Benchmark function tests demonstrate that the IHBA outperforms the comparative algorithms in both convergence speed and solution accuracy. On this basis, the IHBA is utilized to automatically optimize the hyperparameters of the BiLSTM network, overcoming the blindness of manual parameter tuning and significantly enhancing the model’s modeling capability and generalization for high-dimensional nonlinear fault features. Finally, on the simulation dataset containing five operational states including normal, open-circuit, short-circuit, partial shading and aging, the IHBA-BiLSTM model achieves a fault diagnosis accuracy of 97.1014%. Its performance comprehensively surpasses that of the comparative models such as support vector machine (SVM), extreme learning machine (ELM), long short-term memory (LSTM) network and models integrated with other intelligent optimization algorithms, confirming that the proposed method possesses both high precision and strong robustness in the diagnosis of multiple types of faults in PV arrays.
  • Ye Jianying, Liu Zhaoqi, Li Zhouchen, Lin Bo, Liu Lei, Chen Yingting
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    To address the issue of insufficient accuracy in ultra-short-term power prediction using historical data in the field of photovoltaic power generation, an ultra-short-term PV power prediction method is proposed, which integrates numerical weather prediction (NWP) similarity day and multi-head attention-long and short-term memory network (MHA-LSTM). The correlation coefficient method is used to analyze the inherent relationship between PV power and meteorological information, combing the meteorological factors that are highly correlated with PV power in the historical data, constructing the variable matrix of key meteorological information, and carrying out the segmentation process in order to carry out a more fine-grained analysis of similar days. A multi-head self-attention mechanism is introduced to automatically capture the complex functional relationships embedded in the NWP data, and the data information enhanced by the multi-head self-attention mechanism is processed by using a long- and short-term memory neural network (LSTM) to obtain more accurate ultrashort-term prediction results. Finally, a number of different weather types are selected to compare and analyze the prediction accuracy of the algorithm, and the experimental results show that the prediction method proposed in this paper achieves a significant improvement in prediction accuracy compared with the traditional algorithm, which verifies the effectiveness and accuracy of the method.
  • Tang Shufeng, Yu Hui, Wang Xin, Guo Xiaodong, Chang Hong
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    In order to solve the problem that the performance of the existing photovoltaic (PV) modules cleaning manipulators is not high in the common working space. An improved Harris Hawks Optimization algorithm was proposed to optimize the size of the manipulators. The orthogonal crossover operator is introduced into the algorithm, which makes the local search ability stronger. According to the actual PV modules installation parameters of the power plant, the constraint index of the workspace is established, and the global performance index and the structure length index of the common workspace are taken as the objective function. The simulation results show that the optimized algorithm is faster, and the two proposed indicators are increased by 21.27% and 8.72% respectively, and the time required for the optimized robotic arm to reach the target position is shortened by 21.7% compared with the previous optimization under the same operating environment, which improves the flexibility of the manipulators and improves the efficiency of PV modules cleaning.
  • Sun Xieyao, Sun Junhai, Zhu Xianyuan, Li Chunqiu
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    Traditional infrared photovoltaic module defect detection methods often suffer from low accuracy and slow processing speeds. To address these limitations, we propose WD_YOLOv8, an improved infrared photovoltaic module defect detection method based on YOLOv8. First, we introduced the Wise Intersection over Union v2 loss function to replace the Complete-IoU loss function used in the original algorithm, thereby enhancing detection precision. Additionally, the v2 loss function improved the balance between precision (P) and recall (R), optimizing overall detection performance. Second, DySample up-sampling was incorporated into the feature fusion network (Neck) to maintain a high detection frame rate. Experimental results show that the improved model increases metrics P, mAP@0.5, and F1-score by 0.3, 1.5, and 2.6 percentage points, respectively, in the infrared pseudo-color photovoltaic module defect detection scenarios. Moreover, in infrared grayscale photovoltaic module defect detection scenarios, these metrics improve by 18.6, 7.7, and 5.1 percentage points, respectively. These findings indicate that the proposed algorithm exhibits strong robustness and adaptability in infrared imaging applications.
  • Mi Wei, Jiang Xu, Chao Zibo, Pan Fengwen, Lei Yu
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    To address the limitations of traditional photovoltaic (PV) power prediction models in terms of forecasting accuracy and generalization capability, this paper designs and implements a prediction model that couples PCC, LSTM and XGBoost algorithms. Firstly, PCC is utilized to filter multi-dimensional features that influence PV power generation, thus constructing an optimized input feature set. Secondly, LSTM network is employed to model the long-term dependencies within the time series data, providing an initial power prediction. Concurrently, the XGBoost algorithm is introduced to model and predict the non-linear features of PV power generation. Finally, this paper lies in enhancing prediction accuracy and generalization capabilities by integrating the prediction results from LSTM and XGBoost models. Experimental results demonstrate that the proposed fusion model exhibits higher accuracy and stability in mid-and long-term PV power rolling forecasts, significantly outperforming traditional methods. Therefore, the proposed PCC-LSTM-XGBoost model offers a novel technical approach for accurate PV power prediction, making it particularly suitable for forecasting PV station power under various climatic conditions.
  • Hu Bangjie, Wang Liang, Yang Shitao, Cheng Shi, Wang Pei
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    Concentrating solar power (CSP) generation, which encompasses both energy storage and power generation capabilities, has emerged as a grid-friendly renewable energy technology and has become a standard configuration within wind and solar power bases. To further enhance the profitability and consumption of CSP-PV operators, this paper primarily focuses on the impact of the startup and dynamic switching conditions of subsystems such as receiver, heat storage, power generation, and electric heater using molten salt on the performance of CSP-PV hybrid power plants. Aiming to optimize the income generated by the hybrid plant, a multi-time-scale dynamic optimization output model is established. This model also incorporates the power system’s optimal scheduling for day-ahead and intra-day, and the optimized output is then used as the declared power output curve. An optimal scheduling model, aimed at reducing the comprehensive operating costs of the power system, has been established. Finally, the measured data of a power system in a certain region of Northwest China is taken as an example for analysis. The case analysis shows that compared to traditional scheduling strategies and profit-maximization strategies, this peak regulation-oriented strategy increases the total power plant revenue by 13.48% and 6.67% respectively, while reducing the curtailment rates of wind and solar power in the power system by 1.39% and 0.5% respectively.
  • Huang Jiguang, Chen Can, Zhang Zheng, Zhang Heng, Cheng Chao, Chen Haiping
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    Researches on enhancing the evaporation performance of solar interfacial evaporators are reviewed with evaporation rate and evaporation efficiency as two evaluation indicators. Six methods, including light absorption enhancement, thermal management, water transport control, evaporation enthalpy reduction, other energy utilization, and salt resistance strategies, are summarized. The principles and main means of each method are outlined. Finally, the current urgent problems that need to be solved in solar interface evaporation technology are given for future research directions.
  • Dai Zengli, Dai Shaomeng, Wei Yuan
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    Based on a concentrated solar power (CSP) molten salt thermal energy storage project, this study takes the foundation of the hot molten salt tank as the research object. Two temperature field models are established for the molten salt tank foundation, corresponding to forced ventilation and natural ventilation, respectively. Taking wind speed, ambient temperature, altitude, ventilation duct diameter and insulation layer thickness as key factors, the variation trend of the maximum soil surface temperature under the tank foundation with these factors is analyzed. Under both forced and natural ventilation modes, ambient temperature and altitude exert similar effects on the foundation soil temperature: the maximum soil surface temperature at the bottom of the molten salt tank foundation rises with increasing ambient temperature and altitude. In the forced ventilation mode, the enhanced forced convective heat transfer leads to a significant reduction in the foundation soil temperature. Under the highest ambient temperature condition, the soil surface temperature of the tank foundation can barely meet the design requirements in the natural ventilation mode. For natural ventilation, increasing the insulation layer thickness and ventilation duct diameter is the primary measure to lower the soil surface temperature.
  • Fan Man, Shi Zhengping, Liu Yingshan, Kong Xiangfei, Li Han, Yuan Jianjuan
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    To synergistically optimize the solar heat storage and supply system, a system energy consumption model was established using TRNSYS software for an expressway serving area building. Taking economy and comfort as objective functions and thermal comfort zones as constraints, a Pareto optimal solution set for the system configurations was obtained. Subsequently, the optimal configuration was determined using the TOPSIS entropy weight method. Compared to the initial design parameters group, under the premise of meeting the requirements of thermal comfort, the system’s annual life cycle cost is decreased by 18.58% and the COP is increased by 27.64%, offering dual advantages of saving investment and operating costs.
  • Yang Lizhi, Tian Jianyan, Ji Zhengxiong, Dai Yuanyuan, Liu Shuwei
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    In order to solve the problems of heating mode selection and operation optimization for heating systems combined with solar thermal collectors and heat pumps, a control optimization method combining digital twin and model predictive control was proposed for the multi-source synergistic and complementary heating system. Firstly, the MSSCHS state space model was constructed, which can describe the switching of heating modes. Then multiple heating mode switching strategies and corresponding virtual entities were constructed to simulate the multiple scenarios of heating mode switching in each control period. By comparing the results obtained from the virtual operation optimization of each virtual entity, the optimal heating mode switching strategy and equipment operating powers were selected to control the multi-source synergistic and complementary heating system. Finally, a large number of simulation analyses were conducted on the operation of the heating system, verifying that the proposed method has better heating economy and stability.
  • Shuai Zhenfeng, Ge Dianhui, Lei Xiandao, Zhang Junfeng, Shen Yajun, Wang Yueshe
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    This paper establishes thermal and stress models for molten salt storage tanks, and investigates the effects of the support stiffness of tank walls and bottom plates on the mechanical properties of storage tanks under the action of thermal-mechanical coupling and variable liquid levels. The results show that the temperature distribution of storage tanks with different liquid levels is roughly consistent, and the maximum temperature difference of approximately 4 ℃ exists at the position of the outward-extending weld of the bottom plate and the connection position of the dome roof. Hydrostatic pressure mainly affects the settlement of the tank body, with the maximum settlement amount being about 0.2 m under the full-load condition. Thermal stress mainly affects the radial displacement of the tank body, and the maximum radial displacement is approximately 0.28 m. Increasing the stiffness of the tank bottom is conducive to reducing the settlement and stress of the tank body, and the optimal design stiffness of the bottom is 5 MPa/m. The deformation of the tank body is insensitive to the change of tank wall stiffness, and the increase of tank wall stiffness leads to a sharp increase in stress. Therefore, it is not advisable to restrict the radial displacement of the tank body caused by thermal stress. The research results of this paper can provide theoretical guidance for the design of practical large-scale high-temperature molten salt storage tanks.
  • Zhang Lei, Li Yuanqi, Yang Liu, Zhu Yiyun, Sang Guochen, Han Qingqing
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    The reflection spectra in the ultraviolet, visible and near-infrared bands and the surface temperatures of nine light-colored coatings were tested to explore the influence mechanism of color on the absorption characteristics of solar radiation and clarify the correlation between the absorption characteristics and surface temperature of the coatings. The results show that the difference between the maximum and minimum values of the solar absorption coefficients of the nine coatings is 0.1539. Hue has a significant impact on the waveform of the reflection spectrum curve in the visible band and the reflectance in the near-infrared band. The larger the hue value, the trough of the reflection spectrum curve shifts towards the low wavelength, indicating a stronger absorption on short-waveband radiant energy. Saturation affects the fluctuation amplitude of the spectral curve in the visible band. Coatings with high saturation have a stronger reflection property for radiant energy at the peak and a stronger absorption property for radiant energy at the trough. In addition, the larger the solar radiation absorption coefficient, the higher the surface temperature of the coating. Also, the spectral wavelength characteristics in the visible light band affect the solar radiation absorption of the coating. When the low-reflectivity band of the coating is wider and the solar radiation density in the high-reflectivity band is lower, the surface temperature of the coating is higher.
  • Tong Tongtong, Mi Xiaoling, Xue Gangqiang, Yang Dutang, Li Xiaobo
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    A method for measuring the concentrated spot flux distribution on the receiver in a solar power tower plant is proposed. The spot samples of some heliostats on the diffuse reflection target are photographed by the CCD cameras, and the flux distribution of the spots on the receiver surface reflected from the heliostats in the whole solar field is mapped, so as to realize the measurement of the flux distribution of the concentrated spot on the receiver. The method combines the advantages of indirect measurement method and numerical simulation. The principle of the method is introduced in detail, and the test is carried out in a 50 MW solar power tower plant in Qinghai Province, which verifies the feasibility of the method. The experimental results indicate that the method can locate the area where the flux of the concentrated spot deviates. A typical measured concentrated spot is compared with the design value. 80% of the receiver panels have an average flux density deviation less than 5%, and most of the panels with large deviations are on the south side. The maximum average deviation is 12.9%, and the maximum peak deviation is 18.9%. The energy spill loss is expected to reduce about 1% after adjusting the heliostats that produces deviation.
  • Fan Jing, Shen Yanbo, Wang Tingting, Hu Yueming, Jia Beixi
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    This study evaluates the accuracy of three widely used solar radiation datasets(NASA, Solargis, and Meteonorm)for solar resource assessment in China. The evaluation is conducted by comparing their monthly global horizontal irradiance (GHI) estimates against high-quality ground-based measurements from 99 meteorological stations across China. A comprehensive index-based evaluation framework was established to identify the optimal datasets for each region and derive corresponding error correction coefficients. The results show that the spatial distributions of GHI from Solargis and Meteonorm align more closely with observations than those from NASA. The most significant discrepancies are observed in Northwest China, Xizang and Sichuan Province. Error analysis indicates that Meteonorm achieves the highest correlation coefficient (R) (R ≥ 0.98 at 75% of the stations) and the smallest error accounting for all error metrics, including root mean square error, mean absolute error, and mean relative error. Solargis demonstrates moderate accuracy, while NASA exhibits the largest error. A significant correlation is identified between latitude and mean relative error. Solargis tends to overestimate GHI at lower-latitude and underestimate at higher latitudes, whereas Meteonorm displays the opposite trend. Based on the results of error analysis, this study constructs a comprehensive index evaluation method, screens out the optimal data types of 99 stations, and spatially interpolates them to the national scale. The findings suggest that Meteonorm is preferred in 55% of China’s regions, followed by Solargis in 27% and NASA in 18%. The mean relative error of the optimized dataset is confined to a range of -4.5% to 5.9%. To improve the accuracy of solar energy assessments, the following calibration is recommended: GHI values should be increased by 1%-5% in northern regions, Xizang, and western Sichuan, and decreased by 1%-6% in southern Xinjiang, Qinghai, Central China, and South China.
  • Huang Yang, Li Cuina, Wang Xiang, Dai Tie, Shi Rui, Sun Hao
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    A multi-temporal and spatial scale evaluation of Himawari-9 shortwave radiation data is conducted using hourly total radiation measurements from 136 ground-based radiation stations across China in 2023. The results show that: 1) On a national average diurnal variation, during 08:00—18:00, the correlation coefficient (Corr) between the Himawari-9 shortwave radiation data and the ground-based radiation data exceeds 0.85, displaying a unimodal distribution. The highest correlation occurs at 09:00 and 10:00, both reaching 0.95, while the lowest occurs at 19:00, with a value of 0.77. The root mean square error (RMSE) also shows a unimodal pattern, with the highest RMSE at 15:00, reaching 119.19 W/m², and the lowest at 08:00, only reaching 49.73 W/m². The bias exhibits a bimodal distribution, with peaks at 10:00 and 15:00. The highest bias occurs at 15:00, reaching 49.63 W/m², and at 10:00 it is 18.46 W/m². The lowest bias is observed at 19:00, with a value of 0.04 W/m². 2) On a national average annual variation, the correlation coefficient displays a bimodal distribution, but there is little variation between months. The two peak values appear in April and October, both at 0.96. The RMSE shows a unimodal distribution, peaking in summer (July-August) with values exceeding 100 W/m², while lower values are observed in autumn and winter. The bias follows a unimodal distribution, with the highest values in spring. In March and April, the bias exceeds 25 W/m², and the lowest value occurs in December, at 6.68 W/m². 3) Spatially, higher correlation values are concentrated in central and eastern China, while lower values are found at some stations in northern and plateau regions. Central and eastern regions are low RMSE areas, where Himawari-9 shortwave radiation data exceeds ground-based radiation data, while western, northern, and plateau regions are high RMSE areas, where Himawari-9 shortwave radiation data is lower than ground-based radiation data. 4) Further analysis of the impact of altitude on the quality of Himawari-9 shortwave radiation data shows that, overall, as altitude increases, the correlation coefficient decreases, and RMSE increases. In regions below 2000 m, Himawari-9 shortwave radiation data generally exceeds ground-based measurements, while in regions above 2000 m, Himawari-9 shortwave radiation data tends to overestimate low irradiance and underestimate high irradiance. Grouping by satellite zenith angle reveals that, in low- to mid-altitude regions, RMSE shows a single-valley distribution. At zenith angles between 20° and 25°, RMSE is the lowest. When the zenith angle is below 20°, the bias is negative, but as the zenith angle increases, the bias becomes positive and gradually increases. In high-altitude regions, there is little difference when the zenith angle is below 35°, but when it exceeds 35°, the correlation coefficient is the lowest, and RMSE is the highest.
  • An Yuan, Shi Zonglian, Feng Haotong, Zhao Tingyu, Li Yang
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    In order to achieve high consumption of new energy and reduce carbon emissions, this article closely links the power grid with heating network through electrolysis of water for hydrogen production and hydrogen methanation technology, as well as electric boilers and gas turbines, and other equipment. Firstly, model each unit in the integrated energy system. Secondly, introduce demand side response and divide it into price based demand response and substitution based demand response. Then, considering the energy flow characteristics of the system, constraints are imposed on the operating conditions of each unit. Finally, considering reliability, economy, environmental friendliness, and abandonment rate, a multi-objective comprehensive energy system capacity allocation strategy is established. On this basis, the commercial solver CPLEX in Matlab is used to solve the capacity configuration of the model, and the impact on the system capacity configuration with and without demand response and energy storage is analyzed. The reliability and economy of the configured capacity are verified using severe weather conditions. The results show that the capacity configuration can still have good economy and high wind and solar energy consumption rate with minimal load loss under adverse conditions.
  • Xu Wenhao, Ji Liang, Hong Qiteng, Han Jiaxuan, Chang Xiao, Zhi Huiqiang
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    When asymmetric voltage drops occur in the power grid, inverter type new energy stations (NES) may face a series of risks such as voltage drops and current exceeding limits, which can lead to serious consequences such as station disconnection from the grid. The main drawback of traditional coordination control methods among new energy stations is that the control objective is single and heavily relies on real-time communication. In response to the above issues, this article proposes a multi-objective voltage support coordination control strategy among new energy stations based on digital twins. Firstly, carry out multi-objective coordinated control technology among new energy stations, considering the safety of inverter operation, to achieve multi-objective control such as maximizing support for grid voltage and reducing grid imbalance. Then, a new energy digital twin model considering control characteristics is established, and multi-objective coordinated control technology among new energy stations is implemented based on the digital twin model, effectively reducing the dependence of coordinated control on real-time communication and improving the response speed of coordinated control. Finally, based on the real-time simulation platform RTDS/RSCAD for power systems, a coordinated control testing platform based on digital twins is built, and the effectiveness of the method is verified.
  • Lu Guoqiang, Wang Kai, An Na, Wang Zhaolei
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    Aiming at the problem of insufficient reactive power support capacity of new energy stations under the increasing proportion of DC new energy power generation resources such as photovoltaic and energy storage connected to the power grid, a distributed collaborative optimization method for transient reactive power of new energy stations based on graph convolutional network (GCN) and bidirectional long short-term memory network (BiLSTM) is proposed. Firstly, by constructing the equivalent model of the new energy station system with multiple reactive power resource access, the transient reactive power characteristics of the new energy station under the access of multiple reactive power resources are studied, and the transient reactive power model of the new energy station is established. Then, with the optimization objective of the operating cost of reactive power resources in new energy stations, the transient reactive power collaborative optimization model of new energy stations is established, and the optimization model is solved by combining BiLSTM-GCN. Finally, the near-field simulation system model of new energy station is built, and the effectiveness of the transient reactive power collaborative optimization method proposed in this paper is verified by simulation.
  • Yu Songyuan, Ao Yun, Wu Ruxin, Wei Le, Xu Yuhan, Zhang Junsong
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    As the coupling and interaction between heterogeneous energy sources in the integrated energy system deepen, operational risks are becoming increasingly significant. To mitigate the impact of extreme disaster events on the system, a line sequence repairing method of the integrated energy system aimed at enhancing resilience is proposed. Firstly, branch state variables are introduced. An islanding partitioning model based on fictitious flow is established, ensuring the continuous supply of critical loads. Secondly, a two-stage line sequence repairing model is developed. In the first stage, the objective is to minimize costs related to load curtailment, switch operation, wind and solar power curtailment penalties, coupling component operation, and start-stop, thereby formulating a plan for network reconstruction and islanding. In the second stage, the goal is to minimize post-repair power loss at node loads to determine the optimal repair sequence. Finally, a test system consisting of an IEEE 33-node system, an 11-node gas network, and a 6-node heat network and an actual integrated energy system are used for simulation verification. The results demonstrate that through dynamic cycles of network reconstruction, islanding partitioning, and temporal repairs, the system achieves efficient recovery, reduces load loss throughout the fault process, and enhances system resilience under extreme weather.
  • Pang Shuailei, Zhang Junbo, Li Zhixuan, Yang Ziqian, Tang Wangqianyun
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    This paper firstly analyzes the shifting process of the system operating point during fault recovery using dynamic vector diagrams, revealing the mechanism of transient overvoltage caused by the dynamic process of PLL. Subsequently, it analyzes the PLL control characteristics and proposes a parameter tuning method for suppressing transient overvoltage by incorporating overvoltage constraints. Finally, the conclusions and effectiveness of the proposed method are validated through PSCAD/EMTDC simulations.
  • Yu Shui, Han Fuhong, Luo Yuchen, Sun Shengkun
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    As the proportion of heating venlt lation air conditioning(HVAC) energy consumption in the overall energy consumption of buildings continues to increase, improving energy consumption prediction capability is an important technical measure for enhancing the fine management of building energy consumption and achieving carbon neutrality in the building sector. This paper proposes a Transformer-based multi-scale fusion network model for predicting HVAC energy consumption in buildings. By introducing a multi-scale pyramid module and a temporal convolutional network structure, the model effectively captures both local and global temporal features, thereby improving prediction accuracy. Experimental results show that the model outperforms traditional single models in prediction performance, with a significant reduction in root mean square error (RMSE) and mean absolute error (MAE), and a determination coefficient (R2) of 0.9826. This model provides an efficient and accurate prediction tool for building energy consumption management and contributes to more efficient building energy management and energy-saving strategies.
  • Gao Fengyang, Pei Shuping, Zha Pengtang, Gao Jianning, Zhuang Shengxian
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    To address the imbalance between high penetration of renewable energy in microgrids and the power supply-demand, a low-carbon optimization scheduling strategy considering network reconfiguration and Demand Response (DR) is proposed. Firstly, network reconfiguration is utilized to optimize microgrid operation, effectively improving voltage deviation, reducing total costs, and minimizing active power losses, employing the Bitterling Fish Optimization (BFO) algorithm to construct a low-carbon optimization scheduling model for microgrids with high renewable energy integration. Secondly, an incentive-based demand response scheme and reconfiguration method are integrated into day-ahead scheduling, minimizing fuel costs for traditional distributed generation and the costs for purchasing power from the grid, thus maximizing microgrid operational profits. Finally, the proposed scheduling strategy is validated using the IEEE 33-node system. The results demonstrate that the proposed strategy effectively reduces the load peak-to-valley difference and enhances the stability, economy, and environmental protection performance of the system.
  • Luo Xi, Wu Hui, Wang Yupan, Li Tingting
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    In order to solve the problem of the connection between the initial planning scheme and the later system operation in the long-term planning, based on the energy consumption characteristics of agglomeration-promotion-type rural areas, a multi-stage planning model for integrated energy systems in such areas was established using a village in the Guanzhong Plain as a case study, considering optimal construction sequencing, and the results show that: 1) Compared to the single-phase planning approach, the multi-phase planning approach, which takes into account the optimal construction timing, resulted in a 38.9% increase in the residual value of the energy system equipment, a 5% reduction in operating costs, a 4.5% reduction in life cycle costs, and an increase in the environmental benefits of the system.2) The increase of the energy load highlights the superiority of the multi-stage planning method, and the rural areas with a fast development speed are especially suitable for adopting the multi-stage method for the planning of the integrated energy system.3) After adopting the multi-stage planning method, the life cycle cost of the energy systems in the typical representative regions of severe cold, cold, hot-summer and cold-winter, and hot-summer and warm-winter decreased by 5.01%, 4.51%, 4.30%, and 0.21% respectively compared with the single-stage planning situation. If the multi-stage planning method is adopted for the energy system planning in severe cold, cold, and hot-summer and cold-winter regions, the economic benefits of the system can be significantly improved, while the improvement in economic benefits in hot-summer and warm-winter regions is limited.
  • Jiang Chengyu, Shi Ruifeng, Ning Jin, Jia Limin
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    To enhance the utilization rate of renewable energy in microgrid systems and achieve reductions in both wind and solar curtailment as well as carbon emissions through energy interconnection among multiple microgrids, this paper proposes a low-carbon optimal scheduling model for a multi-microgrid system that integrates regional thermal and electrical networks, incorporating a carbon-green certificate trading mechanism. Firstly, the mathematical model of microgrids in the context of electrical-thermal coupled multi-microgrid interconnection scenarios is systematically analyzed. Then, based on the introduction of the carbon-green certificate trading mechanism, a planning model for the electrical-thermal coupled multi-microgrid interconnection system is developed, with the objective of minimizing the overall system cost. An optimization strategy using the mixed-integer programming method solved by the CPLEX solver is proposed. Finally, the model’s effectiveness is validated through a case study of a typical scenario in western China. The research findings demonstrate that the proposed model can effectively enhance the renewable energy absorption capacity of the multi-microgrid system, reduce carbon emissions, and achieve optimal overall system economic performance.
  • Yue Gaili, Feng Lishi, Xiang Fuwei, Du Guanghui
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    Aiming at the problem of accelerated battery aging due to high current stress in DC microgrid energy storage system, the peak current optimization of DAB converter under double phase shift modulation is investigated. Firstly, the commutation process and operating characteristics of the DAB converter under double phase-shift modulation are analyzed. Then, in order to reduce the current stress during voltage mismatch, the study takes the peak current expression as the objective function, constructs a mathematical model using the KKT condition, and solves the optimal shift ratios for the four operating modes of the Buck mode under double phase-shift modulation. The optimal shift ratio is substituted into the boundary conditions of each mode, and the local optimal power transfer range of current stress is derived. By comparing the magnitude of the current stress of the four modes, the current stress optimization scheme suitable for the full power range adaptive ZVS mode is constructed to ensure that the current stress reaches the optimal level in the full power range. Finally, it is experimentally verified that the adaptive ZVS mode modulation has less current stress compared with SPS modulation and full ZVS mode modulation during voltage mismatch operation.
  • Zhao Zhihua, Ni Huan
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    Aiming at the multi-microgrid system model considering the output of electric vehicles, photovoltaics and wind power, an economic optimization scheduling structure for multi microgrid systems based on deep reinforcement learning is established with the minimization of the total operating cost of the system as the objective function, and the state, action, reward function and neural network structure of the improved SAC algorithm are designed by using the framework of the improved SAC algorithm. After simulation and comparative analysis, the scheduling strategy obtained by the algorithm reduces the total operating cost.
  • Yang Huixian, Kuang Honghai, Li Zilong, Xu Yuhao, Cao Shipeng
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    To reduce the uncertainty of clean energy and improve the economic efficiency of microgrid scheduling, a scheduling model is established with the objective of minimizing microgrid operating costs and environmental management costs. Firstly, a new dynamic electricity price adjustment mechanism is proposed by integrating time-of-use electricity pricing and the absorption of clean energy, and then demand response is introduced to optimize the load comprehensively. Secondly, an improved grey wolf optimizer (IGWO) is adopted, which is based on the fusion of cosine law variation convergence factor, adaptive inertia weight, and Cauchy mutation. The IGWO is compared with other mature algorithms using typical test functions. Finally, simulation results show that using the IGWO algorithm to solve the price-based demand response model for wind and solar power integration can achieve optimal daily output and significantly reduce the total operating cost, thus verifying the feasibility and economic viability of the proposed research.
  • Xu Tiantian, Du Yida, Zhou Xiaotong, Tan Zhongfu
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    In order to address the operational uncertainty of the wind-solar-hydrogen-storage-methanol coupling system and the coordination of interests among multiple stakeholders, the paper proposes a multi-objective operation optimization and benefit equilibrium model for the wind-solar-hydrogen-storage-methanol coupling system, taking into account risk preferences. Firstly, the multi-objective operation optimization model is constructed based on the information gap decision theory with different risk preferences, taking into account the three-dimensional objectives of economy, consumption, and stability. Secondly, a multi-dimensional factor hierarchical benefit equilibrium model is constructed based on the improved Shapley value method. Consequently, an illustrative analysis is conducted employing the wind-solar-hydrogen-storage-methanol coupling system in a park, and the results demonstrate that the constructed operation optimization model can effectively address the impact of uncertainty, while the benefit equilibrium model can achieve the equitable distribution of benefits among multiple entities. This validates the model’s credibility and substantiates the efficacy of the wind-solar-hydrogen-storage-methanol coupling system.
  • Li Wenxi, Xu Gang, Wang Yi
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    With the frequent occurrence of extreme meteorological events, the uncertainty of power supply increases, and the existing multi-energy microgrid dispatching model cannot effectively guarantee power supply, which also leads to high economic losses. Therefore, to solve this problem, a minimum cost toughness (day ahead) dispatching model of multi-energy microgrid under extreme weather is proposed. According to the load demand and emergency measures in the next 24 under extreme weather, the scarcity of data and the high volatility of renewable energy output power in this case are considered, and multi-energy coordinated power supply scheduling is completed at the minimum cost to ensure the continuous and stable operation of the system. It is proved that the model has the minimum cost in scheduling and its local uniqueness in mechanism, and "marginal optimality" is proposed as the rationality test method of the model output. Experimental analysis shows that in extreme weather, the traditional model will lead to the mismatch between scheduling strategy and actual supply and demand, increasing the economic loss caused by temporary coordination, but in extreme weather, the minimum cost resilient scheduling model of multi-energy microgrid can effectively reduce the power supply gap, shorten the gap time to 0.8, and reduce the total economic loss by 25.8% compared with the traditional model.
  • Fan Shijie, Shou Haonan, Miao Weipao, Zhu Haibo, Li Chun, Yue Minnan
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    The development of super-large wind turbines will lead to the contradiction between the blade quality and structural performance requirements of blades. Therefore, referring to the leaf vein structure of plant blade, a bionic internal rib configuration for 15 MW wind turbine blade is proposed, and combined with the pavement design to realize the lightweight and structural reinforcement of the blade design. The modal, stiffness, strength and stability of the blade are analyzed by the one-way fluid-solid coupling. The results show that the bionic internal rib configuration can improve the blade flapwise and torsion stiffness, avoiding the collision between the blade and the tower, but the edgewise stiffness is reduced; the surface stress of the bionic blade is improved compared with that of the conventional blade, but they do not reach the limit of the material; the buckling factor of the bionic blade is improved, and the overall buckling of the blade does not occur, so it meets the stability requirements.
  • Liu Mingjun, Wang Shuangchuan, Dong Zengshou
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    A remaining useful life prediction method based on the Wiener process and an improved particle filter is proposed to address the challenge of accurately estimating the remaining life of wind turbine slewing bearings due to their accelerated degradation under harsh environmental conditions and sudden operational scenarios. Firstly, the mutation point in the degradation process is identified using a mutation point detection method, and the traditional particle filter algorithm is improved. Secondly, the state space model with mutation points is constructed using a nonlinear Wiener process, and the probability density function of the remaining useful life and the parameter update formula are derived. Finally, data from wind turbine slewing bearings are used as an example to verify the effectiveness and superiority of the proposed method.
  • Liu Xin, Wang Hanbo, Liu Yingming, Wang Liming, Sun Lingyu
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    To reduce the accumulated fatigue load on the main shaft during frequency response for each doubly-fed wind turbine (DFWT) within a wind farm operating under a virtual synchronous generator (VSG) control strategy, a damping coefficient allocation strategy considering main shaft fatigue load is proposed. First, a load-frequency control model quantifying the dynamic relationship between power variation and frequency variation is established. Second, a discretized model relating the VSG control strategy’s damping coefficient to shaft torque and grid frequency during energy transfer is derived. Based on this model, unit operating status, and grid frequency, an objective function and its constraints are formulated to minimize shaft fatigue load across the wind farm. Finally, the fmincon algorithm within the VSG station controller is employed to solve for the equivalent damping coefficients of each unit online. These equivalent damping coefficients are then converted into damping coefficients allocated to each unit. Simulation results validate the superiority of the proposed allocation strategy.
  • Lin Changfeng, Chen Junling, Li Jinwei, Zhao Xueming, Feng Youquan
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    In order to consider shear effect influence of the prefabricated concrete tower for segmented wind turbine , a formula for calculating the warping shear coefficient of one segment with arbitrary geometric dimensions is derived. The finite element models of concrete towers with 2-6 segments are established to compare the twist angles of numerical analyses, the code’s method, the warping shear formula, and the Vlasov theory, respectively. The results show that the warping shear coefficient is negatively related to the center angle of the segment and positively related to the ratio of thickness to radius. The shear effect of the tube with fewer segments or a smaller ratio of thickness to radius is more significant. The code’s method and the Vlasov theory will greatly underestimate the torsional deformation of the segment. In certain cases, it will be only 52% and 21% of the numerical results. The proposed method considering the warping shear coefficient is not only safer, but also generally consistent with the numerical results. The deviation can be reduced by more than 30% than the code’s method under specific cases.
  • Zhang Xiaotao, Ma Jianlong, Su Hongjie, Li Qiuyan, Zhao Mingbo, Gao Zhiying
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    Based on the NREL 5 MW wind turbine model, the simulation calculations of wind turbine blade loads under different average wind speeds, turbulence intensities and wind shear indices are carried out, and analyzing the effects of the blade loads on the combined moments in the swing and oscillation direction of blade loads and swing oscillations under various wind conditions. At the same time, a back-propagation (BP) neural network is established, and a prediction model is used to predict the complex coupling relationship of “average wind speed, turbulence intensity, wind shear index-blade load” The accuracy and reliability of the BP prediction model are compared with those of radial basis function (RBF)neural network , long and short-term memory (LSTM) neural network and support vector machine (SVM). The results show that the turbulence intensity has a small effect on the average blade load, and has a great effect on the blade ultimate load and equivalent fatigue load in the high wind speed range; the wind shear index has a more obvious effect on the average load and ultimate load in the high wind speed condition; and has the greatest effect on the equivalent fatigue load in the rated wind speed range. Meanwhile, the BP neural network load prediction model has better accuracy than that of RBF, SVM and LSTM models, which verifies the feasibility and accuracy of the prediction model .
  • Guan Xin, Hua Yu, Liu Bo, Zong Longlong, Kong Dechen, Tang Hao
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    The structural dynamic characteristics of offshore wind turbines are directly related to the operational safety and equipment reliability of in-service wind turbines, but because of the complex working environment, a single load analysis cannot reflect the structural dynamic characteristics of its actual operating state. In this paper, considering the distinctive configuration attributes of 5-megawatt marine wind energy generators, Kaimal wind speed spectrum is used to establish a three-dimensional model of Marine turbulent flow field, and Kärnä ice force spectrum is combined to build a floating ice mathematical model, and the working conditions of the actual operating environment of offshore wind turbines are reproduced through the arrangement and combination of multiple working conditions. Combined with OpenFAST and EDEM discrete element analysis method, the dynamic response characteristics of wind turbines under wind, wave and ice loads are studied. The results show that the transverse and longitudinal dispositions of the tower top and the transverse and longitudinal bending moments of the tower are greater than that of the single load, but the cumulative fatigue damage caused by the coupling load is smaller than that of the single load.
  • Tian Xu, Han Qingpeng, Zhu Rui, Yuan Binxia, Yang Tongguang, Wang Bo
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    The icing of wind turbine blades can result in decreased wind energy utilization coefficients and accelerated component fatigue. Based on this, this paper conducts a study on the aerodynamic characteristics of the NACA4415 airfoil using numerical simulation methods. Variation of lift and drag coefficient and the distribution of surrounding flow field after the wing profile icing under different incoming wind speeds are analyzed. As icing time increases, the lift coefficient gradually decreases and then stabilizes, while the drag coefficient increases with intermittent fluctuations. Furthermore, a simulation study on de-icing of the airfoil is conducted using the piezoelectric vibration method. Through harmonic response analysis, the influence of piezoelectric element thickness and spacing on de-icing effectiveness is evaluated, resulting in the optimal piezoelectric element thickness and spacing being determined as 0.5 mm and 3.0 mm, respectively. Thermal analysis is also performed to calculate the changes in temperature, elastic stress, and elastic strain. As icing time extends, the average temperature of the ice mass increases exponentially, leading to an approximately linear increase in the elastic stress and elastic strain of the ice coverage.
  • Liu Haoyue, Ren Hehe, Ke Shitang, Qiu Jiaqi
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    Based on the super-resolution reconstruction technique in machine learning, this paper proposes a hybrid downsampling skip connection (DSC)/multi-scale (MS) model for super-resolution reconstruction of three-dimensional typhoon wind fields, and conducts research on super-resolution reconstruction of three-dimensional wind fields across different grid scales. Through comparative analysis of errors in the overall typhoon flow field, average wind profiles in different spatial regions, and radial wind speed distributions, the results indicate that wind fields at kilometer-scale and below can effectively reconstruct refined three-dimensional typhoon wind fields, while reconstruction errors are relatively larger for wind fields above kilometer-scale. This study preliminarily achieves a transition in typhoon wind field reconstruction from kilometer-scale to hectometer-scale.
  • Chen Xiangmin, Lei Hanlin, Zhang Kang, Li Yonghui, Li Bo, Yao Peng
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    The fault diagnosis of speed increasing gearbox is of great significance for ensuring the reliable operation of doubly fed wind turbines. However, traditional method cannot fully extract the global information and the recognition accuracy is low under the operating conditions of speed increasing gearbox. In order to tackle this issue an intelligent fault diagnosis technique for the wind turbine's speed-increasing gearbox is proposed in this paper, based on advanced mobile ViT. In this method, the Gram matrix is used to convert the one-dimensional data into a two-dimensional image in the data preprocessing module, which maintains the dependence of the signal on time. Then, heterogeneous kernel-based convolutions (HetConv) are employed to extract the fault local information and also provide spatial position bias, and then the Vision transformer (ViT) with Self-Attention is utilized to extract the global features of the fault information. Finally, fault identification is executed according to the output of the fully connected layer. The experimental results show that the average accuracy of the proposed method is high than 99%, which is better than other commonly used networks. Moreover, the number of model parameters is lower, and the model is smaller.
  • Zhao Fengyu, Sun Hongyue, Ding Weiye, Ai Congfang
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    In recent years, with the widespread application of semi-submersible platforms in offshore engineering, there have been numerous innovations in the mooring systems. Among these, the multi-segmented mooring system has demonstrated good effectiveness in reducing platform dynamic responses. To improve the stability and safety of the OC4 offshore wind turbine under the combined action of wind, waves, and currents, a mooring system combining the multi-segmented mooring with the original OC4 platform mooring system was established, with different configurations of weights and buoys. Using the FAST to AQWA (F2A) to investigate the motion response of the OC4 wind turbine platform with four different mooring systems, and the fatigue damage of the mooring system was analyzed based on T-N curves. The results show that compared to the original mooring system, the clump weight mooring system has better suppression of the motion response and low-frequency resonance response of the floating wind turbine platform, but it slightly increases the wave-frequency resonance response; The buoy mooring system can significantly reduce mooring tension and the multi-segmented mooring system demonstrates good fatigue resistance. The numerical simulation results of the multi-segmented mooring system provide scientific reference for the development of mooring systems for floating offshore wind turbines.
  • Li Hao, Tan Jianjun, Zhu Caichao, Fei Wenjun, Sun Zhangdong, Wang Hongxia
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    Considering the effects of dynamic rotational speed and meshing load of the planet gear during start-up, a 5-degree-of-freedom frictional dynamics model of coupled journal and bidirectional thrust bearings is established to investigate the lubrication performance during the start-up phase. The equivalent boundary conditions for the planet gear during start-up are derived from a multi-body dynamics model of the wind turbine gearbox. The impacts of pressure coupling boundaries, thrust bearings, and axial clearance on the lubrication performance of the coupled bearings are analyzed and validated through experiments. The results indicate that, under the influence of dynamic meshing load from the planet gear, the journal bearing experiences slight asperity contact at the conclusion of the start-up phase, with film pressure alternating between single and double peaks. The maximum film pressure is enhanced by the pressure coupling boundary. The bidirectional thrust bearing can mitigate misalignment and eccentricity in the load direction, while potentially increasing them in the non-load direction. Insufficient axial clearance can lead to a significant increase in maximum film pressure and fluctuation of the thrust bearing, as well as a reduction in the load balancing performance of the thrust pads.
  • Wang Chengyu, Wan Shuting, Wang Yilong, Deng Chao, Tian Siyu, Hu Xiaoli
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    This paper focuses on the NREL 1.5 MW wind turbine and conducts one-way fluid-structure interaction calculations based on the ANSYS platform to explore the impact of blade icing conditions on the aerodynamic characteristics of the wind turbine, considering wind shear and tower shadow effects. Firstly, a geometric model of the wind turbine is established and verified. By comparing four operating conditions—constant wind speed, wind shear, constant wind speed with tower shadow effect, and wind shear with tower shadow effect—the influence of these conditions on the pressure distribution of the turbine blade airfoil is analyzed. Subsequently, the variations in aerodynamic characteristics such as torque, lift, and overturning moment of the iced blades and the wind wheel under these four conditions are further investigated. The research results indicate that wind shear and tower shadow effects significantly impact the aerodynamic performance of iced blades, particularly exhibiting noticeable abrupt changes in the pressure difference at the trailing edge airfoil. Additionally, wind shear and tower shadow effects cause 3P fluctuations in the torque, lift, and overturning moment of the iced blades, with each moment reaching extreme values when the blade rotates to an azimuth angle of 180°.
  • Xu Jun, Wang Dan, He Zeyu, Tang Weiwei, He Guangling, Wu Qiang
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    This study focuses on a large hybrid tower wind turbine with a hub height of 160 m. Using a subsystem integrated simulation strategy, comprehensive research on its nonlinear dynamic response is conducted with the aid of Simpack, Matlab/Simulink, and OpenSees software platforms. Initially, a multibody dynamic model of the rotor-nacelle subsystem is established, followed by nonlinear finite element modeling of the hybrid tower subsystem, with special consideration given to the coupling effects of aerodynamic loads. An integrated dynamic simulation model is developed using a client-server architecture combined with TCP/IP communication technology, and its correctness is verified. The study further investigates the influence of material nonlinearity and P-Δ effects on the dynamic response. By comparing displacement and stress calculation results, it is demonstrated that nonlinear characteristics have a mon-negligible impact on the dynamic response of large hybrid tower wind turbines, and such effects should be carefully considered in numerical simulations.
  • Yu Aiqing, Yang Feixiang, Wang Han, Gu Rui, Wang Yufei, Xue Hua
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    Considering the severity of modal aliasing in frequency division within offshore wind farms, a method for configuring hybrid energy storage capacity is proposed, based on an improved artificial protozoa optimizer (APO) integrated with successive variational mode decomposition (SVMD). In this method, SVMD is adopted to decompose the discrepancy between raw wind power and grid-connected power, with the compensatory power for the electro-hydrogen hybrid energy storage system being determined through a combination of fast Fourier transform and maximizing spectral entropy difference. The hybrid system consists of a super-capacitor system and a hydrogen storage system encompassing a desalination unit, electrolyzer, hydrogen storage tank, and fuel cell. With the dual objectives of minimizing the overall cost of the energy storage system and maximizing the stabilization of offshore wind power fluctuations, a capacity allocation optimization model is formulated and solved using the refined APO algorithm. Simulation analysis validates the efficacy and economic viability of the proposed method in stabilizing these fluctuations.
  • Kong Xianzheng, Huang Guoyong, Deng Weiquan, Liu Fabing
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    To address the limited accuracy of multi-step wind speed predictions using conventional methods, this paper proposes a hybrid model that integrates Singular Spectrum Analysis (SSA) and Variational Mode Decomposition (VMD) with a Time Convolutional Network (TCN)-Informer architecture. Firstly, SSA is used to suppress noise in the original wind speed data and reduce its instability. Next, VMD is employed to reduce the complexity of the wind speed sequence, with each component then input into TCN's feature extraction module to capture temporal features and enhance local information representation. Finally, by fusing temporal and spatial features from each modal component and inputting them into Informer's self-attention model, long-term dependence relationships are modeled to obtain multi-step wind speed predictions. The proposed model was validated using measured wind speed data from a meteorological tower at a wind farm in Yunnan province, China. The results show that the MAPE for 6-step and 12-step predictions were only 1.63% and 2.25%, respectively, demonstrating significantly accuracy in short-term multi-step wind speed prediction.
  • Wang Haijun, Wu Mengdi, Guo Yaohua, Yi Likun, Xu Ying
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    Based on an actual engineering prototype, a 1∶40 secant piled bucket foundation model was designed, and indoor model tests were conducted in homogeneous sand. The bearing capacity of the foundation and the instability mode of the foundation were studied under horizontal bending moment load and vertical load. Finite element modeling and analysis of the same size scaled model were compared. The results showed that: 1) under the action of horizontal bending moment load, the bite pile skirt has good integrity with the internal soil, and the instability mode of the foundation is mainly characterized by large rigid body rotation and a small amount of overall horizontal sliding; The deviation between the ultimate bearing capacity results of the same size model test and finite element analysis during foundation instability is 4.9%. The soil pressure on the rear wall of the cylinder gradually increases, while the soil pressure on the front wall of the cylinder first increases and then decreases. The soil pressure is relatively high at about one-third of the burial depth, indicating that the foundation has undergone translational and rotational movements. 2) Under the action of vertical load, the skirt of the cylindrical foundation and the bearing platform drive the internal soil to deform together, and the foundation mainly undergoes overall shear failure. The deviation between the ultimate bearing capacity results of the test and finite element analysis during foundation instability is 6.05%, and the soil pressure on the cylinder side first decreases and then increases.
  • Huang Wei, Liu Bin, Li Huokun, Huang Jun, Huang Ziyang
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    To improve the forecast accuracy of wind power and the generalization performance of the hybrid model, this paper proposes a hybrid medium-short-term wind power forecast model based on variational mode decomposition (VMD) coupled with bidirectional time convolutional network (BiTCN), bidirectional long short-term memory network (BiLSTM), and Attention mechanism. Furthermore, the model uses the improved crested porcupine optimizer (ICPO) to optimize the VMD decomposition parameters and the parameters of the hybrid model. Firstly, the ICPO is used to optimize the core VMD parameters (K value and penalty coefficient α), and the original wind power sequence is decomposed by VMD. Then, the ICPO is introduced to automatically optimize the hyperparameters of the BiTCN-BiLSTM-Attention deep learning model, and the ICPO-BiTCN-BiLSTM-Attention forecast model is established for each component after decomposition. Finally, the prediction values of each component are superimposed to obtain the final prediction value. The verification of a certain wind farm instance indicates that compared with the single forecast models and the conventional combination models, the coupling model proposed in this paper achieves remarkable enhancements in both prediction accuracy and generalization performance.
  • Li Zhenkun, Geng Lujun, Yang Xin’gang, Zhang Yajun, Wei Shurong
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    With the steady promotion of green and clean energy and the rapid development of deep-sea wind power technology, the application of multiple energy storage in deep-sea wind power clusters is expected to become a key technology to solve the problems of far offshore, high cost, difficult to send out as well as power fluctuations in stochastic and strong, etc. The application of multiple energy storage in deep-sea wind power clusters is expected to become a key technology to solve the problems. In order to solve this problem, this paper takes into account the coupling characteristics of electric-hydrogen multiple energy storage and the optimization of the capacity of the shared flexible direct transmission system, and proposes a planning and operation strategy for the electric-hydrogen multiple energy storage to relieve the capacity of the flexible direct transmission system in the deep-sea wind power cluster. Firstly, an energy management strategy for electric-hydrogen multiple storage is formulated based on the optimization of flexo-direct transmission system capacity and electric-hydrogen storage charging/discharging power constraints and storage state constraints; secondly, an optimization model of deep-sea wind cluster-multiple storage system configuration is established on the basis of this strategy with the objective of maximising the total system benefit of deep-sea wind clusters taking into account the multiple storage; and then, a data aggregation and optimization model is developed to solve the problem of large fluctuation of the output of offshore wind power. The data are clustered and analysed to obtain the typical wind power output scenarios and reduce the impact of extreme data. Finally, taking an offshore wind power cluster in the eastern part of China as an example, computational analysis is carried out through actual data to compare and analyse the configuration results as well as costs and benefits under five scenarios. The results of the calculation example show that the configuration scheme of multi-energy storage in the deep sea wind power clusters under the proposed strategy can effectively improve the economy of the system, alleviate the pressure of deep sea power delivery to a certain extent, and verify the feasibility of the strategy.
  • Zhao Qiaohong, Wu Lianghong, Guo Bizhang, Yang Jingwei, Zhou Wuxi, Cao Junwei
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    When the primary frequency control modulation applies the traditional control algorithm to control the existing wind groups, there are problems such as over-supporting of energy during sudden changes in wind speed leading to wind turbines power drop or even off-grid, poor anti-disturbance performance, and large control errors, making it difficult to meet the grid ultra-fast and strong complementary inertia support of the high standard requirements. In order to solve the above problems, based on the analysis of a large number of wind groups of historical data, this article proposes an anti-energy over-support high-precision and high-reliability optimization control algorithm. Firstly, a spike identification algorithm is proposed to identify and prevent the energy over-support problem in advance. Secondly, an asymptotic variable-length stepping algorithm is given to improve the perturbation resistance. Then an adaptive dynamic compensation algorithm is adopted to improve the control accuracy of the system. Finally, the algorithm is applied to control a representative wind groups in a mountainous area of Hunan province. The actual application results show that after using the algorithm in this article, the system does not appear power fall and off-grid problems, the anti-disturbance performance has been significantly improved, and the control accuracy is within 0.5%, which is much higher than the test standard requirements. The optimized control algorithm of wind groups electric primary frequency regulation proposed in this article significantly improves the grid stability, safety and disturbance rejection of wind groups.
  • Li Yao, Hu Jun, Wu Xiaolong, Deng Yue, Zhang Shuan, Zhu Caichao
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    Due to the fatigue reliability issues of sliding-bearing gearboxes in large-megawatt wind turbines, the 6.2 MW WTG is taken as the research object. Internal and external excitations of gears, random loads, electromagnetic characteristics, and sliding bearings are comprehensively considered. The electromechanical coupling dynamics model of the WTG is built under random wind speed. The dynamic characteristics of the transmission components are studied. The strength degradation process of the transmission components throughout their life cycle is characterized using fracture mechanics theory. Based on reliability design theory and fuzzy reliability theory, a time-varying reliability model of a sliding-bearing WTG considering the fuzziness of allowable wear is established. The influences of strength degradation and sliding bearings on WTG's time-varying reliability are explored. Through experimental comparison and verification, the accuracy of the theoretical model meets engineering requirements.
  • Liu Jiayi, Yang Dejian, Mu Jia’nan, Chen Ning, Qian Minhui, Yan Gangui
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    In order to address the difficulty of parameter setting of fast frequency support strategy for high proportion wind power grid connected power system and the complex problem of stall caused by excessive release of rotor kinetic energy of low wind speed unit caused by power equivalent distribution, an adaptive frequency support control strategy for wind farm under the mode of “centralized response + autonomous execution” is proposed. For this purpose, a wind farm frequency support architecture of “centralized response + autonomous execution” mode is proposed by using the hierarchical idea. The upper layer considers the dynamic compensation of the system disturbance, and builds the frequency support strategy based on the auto-disturbance rejection controller model. Aiming at the difficulty of auto-disturbance rejection parameter tuning, the influence of different linear auto-disturbance rejection control parameters on the fast frequency support effect and the operating state of the wind turbine is explored, and a linear auto-disturbance rejection controller parameter tuning method based on particle swarm optimization algorithm is proposed. In the lower layer, considering the phenomenon of speed stall, for the problem of primary frequency regulation power distribution of wind turbines with different wind speeds in the wind farm, a setting method of adaptive dynamic correction of active power response coefficient by rotor speed is proposed. After receiving the active incremental signal of the station, the unit combines the active power response coefficient to respond independently to the fast frequency support, and realizes the control mode of “wind farm centralized response + unit autonomous execution”. A four-machine two-area system with wind farm is simulated and analyzed. The simulation results verify the effectiveness of the proposed control strategy to suppress the stall of the wind turbine speed and the feasibility of the frequency support effect.
  • Wei Dongze, Liu Zuhong, Qiao Mengna
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    In order to investigate the effect of spacing ratio on the vortex-induced motion of semi-submersible offshore wind turbine, this paper adopts the method of towed pool model test to carry out the research on the effect of spacing ratio on the key features of the response amplitude, frequency and trajectory of the vortex-induced motion of semi-submersible wind turbine at a 45° incidence. Three phases of more pronounced vortex-induced motion were observed, i.e. per-lock-in region, lock-in region, and post-lock-in region. It is shown that the spacing ratio is an important factor in determining the amplitude of the three-way motion response of a semi-submersible wind turbine, and that larger spacing ratios may lead to more intense motions, which may result in a greater risk of fatigue damage to the structure. The effect of spacing ratio on the structure three-way motion coupling relationship is not obvious, at the same time, while the structure motion trajectory of each spacing ratio is basically the same as the rule of change of reduced velocity.
  • Zhang Xun, Liu Jia, Xu Hongcheng, Yao Wenbo
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    In the field of wind turbine engineering, the accurate analysis of the cumulative deformation of pile foundations and structures under long-term stochastic wind loads has been hindered by the absence of an appropriate simulation loading apparatus. To fill this gap, a novel hydraulic-actuated device with automatic control capabilities for simulating stochastic wind loads is designed and developed. A 1g reduced scale model test is conducted to comprehensively verify the loading performance of the proposed device, and to deeply analyze the cumulative deformation response of the belled pile foundation and tower, as well as to explore the action mechanism of various influencing factors. The test results demonstrate that the designed simulated loading device can stably output long - term stochastic loads. The output load shows a high degree of consistency with the theoretical calculation curve. Regarding the loading error caused by the inertia of the actuator rod of the selected hydraulic actuator, it is significantly affected by low wind speeds, while the impact of the loading frequency on this error is negligible. For the belled pile foundation in loess, the lateral cumulative displacement and vertical cumulative settlement at the top increase rapidly in the initial stage of stochastic loading and then gradually reach a stable state. These deformation values increase dramatically with the rise in wind speed, whereas the changes in deformation due to variations in frequency are extremely small. Under different average wind speeds and loading frequencies, the variations in the lateral cumulative displacement at the top of the tower and the belled pile foundation are positively correlated. However, due to the influence of pile - soil interaction, as well as the changes in mean wind speed and loading frequency, the amplitude of the lateral cumulative displacement during the initial rising stage and the variation characteristics of the increase in lateral cumulative displacement during the stable stage are significantly different.
  • Zhao Zhong, Hui Zenghong, Zhang Yong, Sun Zhongguo, Luo Yuming
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    Focusing on the digital trarsformation of wind tunnel tests, in response to the demand for the integration of physical wind tunnel tests and computational fluid dynamics(CFD) numerical tests, this study designed and developed a digital wind tunnel system based on the NF-3 airfoil wind tunnel at Northwestern Polytechnical University(NWPU). The system replicates the experimental NF-3 wind tunnel model, simulates the control process of experimental wind speed, and enables automated execution of experiments in a virtual wind tunnel. To achieve automation and operational deployment, the digital wind tunnel system uses customized grid templates for the automatic generation of both background and model grids. These grids are assembled using overset grid technology, and low-speed precondition techniques are employed to accelerate the convergence of the compressible flow solver. This paper firstly introduces the basic component sections and the control strategy of the physical wind tunnel. Subsequently, it elaborates on the design of the digital wind tunnel system, including the automatic generation of airfoil grid, automated assembly of wind tunnel and airfoil grids, flow solver methodologies, and virtual control strategies for digital wind tunnel. Finally, this research conducts a virtual experiment in the digital wind tunnel utilizing the standard wind turbine air-foil DU91-W2-250, and compared with traditional CFD simulated results. The results demonstrate that the system can effectively support digital wind tunnel experiments, capturing spanwise separated flow region variations that are absent in conventional quasi-2D simulations and the results align better with physical experiments.
  • Liu Yang, Xie Jun’en, Chen Zhichao, Xiu Xinyan, Yu Haoming, Qin Jiang
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    The paper proposes a fuel cell power generation system based on biodiesel reforming. The effects of parameters such as water-carbon ratio, steam reforming temperature, and fuel cell fuel utilization rate on the system performance are investigated through modelling and simulation calculations. Afterwards, the optimal working point of the system is obtained based on an optimization algorithm. The results show that: lowering the steam-carbon ratio increases both H2 and CO concentrations in the reformed gas; increasing the fuel utilization rate of the fuel cell effectively improves the system efficiency, but excessively high a fuel utilization rate results in additional power loss for feed preheating; the maximum efficiency of the power generation system at rated power is 42.21%, and the power generation system has improved in terms of fuel consumption and carbon emission compared with the diesel engine.
  • Pan Yujin, Kou Wei, Sun Zhaonan, Zhou Yan, Yang Siyu
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    Based on the relevant accounting methods of life cycle assessment and the Intergovernmental Panel on Climate Change (IPCC) National Greenhouse Gas Inventory Guidelines, the carbon emission reduction benefits and potential of biomass gasification power generation with CO2 capture-soda production technology were evaluated. The results show that biomass gasification power generation with CO2 capture-soda production technology using corn stover as raw material has significant carbon reduction benefits, with a reduction of 3.88 t/(t-straw) or 6.45t/(MW·h). The contributions of CO2 capture-soda production and power generation to carbon reduction benefits are 84.27% and 15.69%, respectively. Collaborative optimization of transportation and power generation systems can achieve a maximum carbon reduction of 4.32 t/(t-straw), showing great carbon reduction potential. Compared with similar technologies from the perspective of product output or biomass waste reduction, biomass gasification power generation with CO2 capture-soda production technology has strong carbon reduction benefits.
  • Li Peng, Zhao Guanghui, Jia Yuzhe, Liu Tao, He Zhifeng
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    With the background of developing mid-deep geothermal energy, the current research of the conventional borehole heat exchanger(BHE) is reviewed firstly. Then, the measures to improve the heat extraction capacity of BHEs are discussed qualitatively and quantitatively from three aspects, including the modification of the wellbore, improvement of the BHE structure, and enhancement of groundwater seepage. It provides a reference for promoting the development and application of BHE technology.
  • Zhang Weibing, Lu Jie, Wu Kai, Yang Xingfu, Li Peng, Duan Xinsheng
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    Based on practical engineering, this paper conducts the thermal response test of horizontal and vertical borehole heat exchangers. Analyzed the thermal properties and heat transfer capacity differences of heat exchangers under different burial methods, as well as economics, are analyzed. The results indicate that the average thermal conductivity of the rock and soil mass within the vertical borehole heat exchanger range is 74.5% higher than that of the horizontal, the average thermal diffusion coefficient is 61.5% higher, and the thermal resistance is 18.9% lower. Under heating conditions, the heat transfer per linear meter of horizontal and vertical borehole heat exchanger is 9.20 and 42.36 W/m, respectively. The horizontal borehole heat exchanger is 78.3% lower than that of vertical. Under cooling conditions, the heat transfer per linear meter of horizontal and vertical borehole heat exchanger is 12.62 and 67.55 W/m, respectively. The horizontal borehole heat exchanger is 81.3% lower than that of vertical. The combination of horizontal and vertical borehole heat exchanger saves 448300 RMB in cost compared to using only vertical borehole heat exchanger.
  • Jia Chunchao, Wu Zhiquan, Hu Qingya, Han Zhonghe, Chen Yunyang
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    This article compares and summarizes the types and development status of Brayton pumped thermal energy storage (B-PTES) technology and other mainstream long-term energy storage technologies. B-PTES technology is sorted out and analyzed from six aspects: parameter optimization, system configuration, selection of circulating working fluid and thermal storage materials, thermal/cold storage units, operation mode, and economy. B-PTES is more competitive, but its efficiency still needs to be improved. In terms of system configuration, multi-objective optimization can be carried out by comprehensively considering factors such as economy and working fluid characteristics; In terms of core equipment, equipment efficiency can be further improved by addressing issues such as high-temperature creep of high-temperature compressors, low-temperature brittleness of low-temperature expanders, and enhanced heat transfer and flow drag reduction of heat exchangers; In addition, the coupling of application scenarios such as thermal power, nuclear power, and combined cooling, heating, and power generation highlights the advantages of flexible deployment of B-PTES technology, further enhancing its competitiveness in long-term energy storage technology.
  • Ge Pengjiang, Ke Xianbo, Li Haibo, Lyu Jinli, Zhang Dehai
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    Addressing the multi-time scale coupling issues in power and energy balance systems involving pumped storage and cascade hydropower stations, this study focuses on provincial power grids dominated by multi-basin cascade hydropower systems to explore supply-demand balance challenges across different temporal scales. Firstly, the characteristics of the provincial power grid mainly consisting of multi basin cascade hydropower stations with pumped storage and the bidirectional coupling relationship of different time scales were analyzed, and a robust optimization method based on confidence intervals was determined; Secondly, a power and electricity balance model was established at different time scales of year, week, and day; Finally, simulation calculations were conducted based on the planning and construction of a provincial power grid in 2030, and results under different scenarios were analyzed. The simulation results show that the power and electricity balance method proposed in this paper can balance various indicators of different time scale plans and ensure both weekly and daily peak shaving needs while formulating annual plans. Pumped storage power stations can play a role in various situations considering different water and load conditions. They can not only transfer electricity during wet years, but also use large storage capacity to operate in a conventional hydroelectric manner to absorb and replenish water, and provide high-quality rotating backup power for the system.
  • Zhang Xu, Li Yanghai, Cao Fuyi, Wang Tingju, Sun Li
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    This study aimed to investigate how the atmospheric humidity and environment temperature of air affect the performance of a 300 MW compressed air energy storage power plant. A comprehensive mathematical model accounting for high-precision air physical properties was developed. The results show that assuming air behave as an ideal gas results in a smaller design capacity than in reality, leading to insufficient heat and power supply, particularly at high pressure and temperature. Additionally, the influence of the atmospheric humidity and environment temperature on the operational characteristics of compressors were studied. An increase in atmospheric humidity and environment temperature reduces the output of the compression system, requiring a larger opening of the frequency converter and a longer charging time to maintain the design pressure of the air reservoir. Finally, water condensation is most intense at Stages 1 and 2 for both intermediate and high-temperature scenarios. As the atmospheric humidity and temperature increase, more water condenses for every stage and the position where condensation happens moves ahead. Operators must address this issue by monitoring the position of condensation and taking appropriate measures.
  • Zhang Xinghao, Xu Chuanbo
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    This study addresses the variability of wind and photovoltaic power generation by proposing a two-stage optimization model for a hybrid energy storage system that includes supercapacitors and alkaline/proton exchange membrane hydrogen production. Initially, the raw power signals of wind and solar power are decomposed using empirical mode decomposition and reconstructed into multi-frequency scale fluctuations based on grid-connected power limits. Subsequently, in the first stage, a multi-type electrolysis power allocation strategy is proposed to construct a multi-objective capacity planning model that includes the levelized cost of hydrogen production and the rate of wind and solar power curtailment, which is solved using an improved non-dominated sorting genetic algorithm. Then, in the second stage, an operational optimization model is constructed to minimize the comprehensive cost, which is solved using Gurobi. Actual case results demonstrate that, compared to standalone alkaline electrolyzer and standalone proton exchange membrane electrolyzer systems, the system proposed in this study reduces the exceedance of grid-connected fluctuating power by 35.15% and 20.15%, respectively, and lowers the fluctuation penalty cost by 9.7% and 1.04%, respectively. Additionally, its levelized cost of hydrogen is 39.89% lower than that of the standalone proton exchange membrane system, and the curtailment rate of wind and solar power is reduced by 20.15%.
  • Zou Yang, Yao Yujia, Shi Songhao, Huang Yu, Fang Menghong, Jin Tao
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    Microgrid and energy storage, as an effective way to promote new energy consumption, are becoming the current research hotspot. In order to explore effective approaches to power interaction between different subjects within the microgrid under the situation of green and low-carbon transformation of energy structure and the reform of the electricity market, and to fully utilize the regulatory potential of energy storage as an independent subject participating in power trading, this paper proposes a coordinative optimization strategy based on the hierarchical nested game of independent energy storage and supply-demand dual-response in microgrids. Firstly, based on the flexible adjustment of source-storage-load, a two-level nested game interaction framework is constructed for multiple subjects in the microgrid, in which the first-level game is the optimization of energy consumption strategy for photovoltaic users' demand response, and the second-level game is the optimization of microgrid's energy supply strategy through the coordination of independent energy storage, achieving dual-response of supply and demand through the interaction of decision variables at two-level. Secondly, according to the source-storage-load hierarchical nested framework, a distributed collaborative optimization model considering the interests of various market participants is established. Then, the heuristic algorithm combined with the mixed integer programming method is used to solve the interaction strategies of supply and demand multiple participants in pursuit of the optimal objective. Finally, the effectiveness of the proposed strategy was rerified through numerical examples, i.e., it can effectively balance the interests of multiple subjects, improve the utilization rate of energy storage resources, optimize the balance between supply and demand of microgrids, and achieve an improvement in overall economic benefits.
  • Jin Wei, Wu Yunya, Liu Aizhong, Kan Jiarong, Ding Hang, Zheng Yang
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    Aiming at the problems of long energy transfer path, low equalization efficiency and weak modularity of conventional battery equalizer in the process of equalizing multiple battery packs, this paper proposes a modular lithium battery equalizer based on half-bridge. The equalizer is modularized by combining a half-bridge equalization circuit and a multi-winding transformer, and the introduction of phase-shift control makes the voltage between each battery cell realize rapid equalization. Firstly, the working principle of the proposed equalizer is analyzed, and the key factors affecting the energy transfer of battery cells within and between equalizer modules are derived. Secondly, the effects of different shift ratios on the active power of the equalizer are revealed through theoretical analysis. Finally, a simulation model and an experimental platform are constructed, and the equalization experiments are conducted on two groups of eight series-connected lithium batteries. The simulation and experimental data verify the developed equalizer outperforms conventional methods in balancing speed, efficiency and scalability.
  • Liu Yu, Chang Xuelun, He Chengshuang, Qu Yaping, Wang Wenbo, Lin Yuebin
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    This article systematically describes the effects of modification through fiber, oxide and organic resin on the physical properties of PEEK materials. Specifically, the use of fiber materials enhances force uniformity and overall strength; the addition of oxides improves high temperature stability and service life; while the addition of resins reduces the coefficient of friction and wear rate. Additionally, the article also explores the effects of manufacturing techniques such as injection molding, 3D printing and hot press molding on the properties of PEEK. Finally, it highlights the promising prospects of PEEK materials in hydrogen production and underscores their broad application potential in medical, aerospace and automotive fields.
  • Zhang Yifan, Ye Fang, Guo Hang, Chen Hao, Zhang Weibo
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    Using computational fluid dynamics (CFD) tools, combined with the Toyota Mirai model, a representative product of hydrogen fuel cell vehicles, the leakage and diffusion of hydrogen in the chassis area and cab were numerically simulated by changing the operating conditions and environmental conditions, and the effects of leakage location, ambient temperature and ventilation conditions on hydrogen leakage and diffusion were studied. The results show that the diffusion of hydrogen is relatively stable when there are fewer obstacles, and hydrogen will accumulate when there are more obstacles. The increase of ambient temperature will intensify the movement of gas molecules, so that the diffusion range of hydrogen in the same time is larger, but the influence of ambient temperature on hydrogen leakage and diffusion is small. Enhanced ventilation promotes the fusion of hydrogen with air. With the increase of the number of vents, the hydrogen diffusion effect is more significant. After adding ventilation conditions, the volume fraction of hydrogen inside the vehicle reaches the lower limit of flammable concentration in a shorter time.
  • Zhang Shouhua, Wang Haixiang, Li Jiepu, Yang Hong, Han Wulin, Li Xiang
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    The failure mode and effects analysis (FMEA) method is used to identify and analyze the potential accident scenarios of the high-pressure hydrogen storage cylinder group of the liquid hydrogen refueling station, and the qualitative risk assessment of these accident scenarios is carried out in the form of a risk matrix. In addition, the risk matrix results for the high-pressure hydrogen storage cylinder group of the liquid hydrogen refueling station with and without safety measures are compared, and the results show that the proposed safety measures can reduce the risk level of the high-pressure hydrogen storage cylinder group to a tolerable level.
  • Shi Yong, Hu Zhilong, Xie Di, Wang Liangliang, Yao Jigang, Su Jianhui
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    This paper proposes a fuel cell aging trend prediction method based on the PatchTST model. By segmenting time series data into multiple local time windows and combining the Transformer architecture to capture long-and short-term dependencies, the method achieves precise prediction of fuel cell aging trends. In the experiments, the model was trained under steady-state and quasi-dynamic operating conditions using data with training set proportions of 50%, 60%, and 70%, respectively, to predict aging trends for future horizons of 50 h, 100 h, and 150 h. Analysis based on error evaluation metrics, such as URMSE and UMAE, indicates that the model achieves the lowest prediction error when the training set proportion is 60% for the FC1 dataset and 50% for the FC2 dataset. Although the error increases slightly as the prediction horizon extends, the overall performance remains relatively stable. Under the conditions where the FC1 dataset is divided by 50% and 60% ratios, the prediction errors of the PatchTST model are lower than those of the Informer, Transformer, GRU, and LSTM models.
  • Song Xu, Bao Zewei, Zong Wen’gang
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    This study employs numerical simulations to develop a model for an ethanol steam reforming reactor aimed at hydrogen production, featuring the direct electrical heating of a SiC foam catalyst carrier. The model investigates reactor performance under varying operating conditions, including inlet temperature, water-to-ethanol ratio, inlet flow rate, and electrical heating power, with ethanol conversionrate and reactant composition used as evaluation metrics. The results reveal that increasing inlet temperature and electrical heating power effectively raises the reaction temperature, thereby accelerating the reforming reaction. Specifically, ethanol conversionrate increases significantly from 95.5% to 98.2%, as the inlet temperature rises from 873.15 K to 1073.15 K. Similarly, boosting electrical heating power from 14 W to 24 W improves ethanol conversionrate from 94.6% to 98.9%. Furthermore, optimizing the water-to-ethanol ratio and reducing the inlet flow rate are also effective strategies for further enhancing ethanol conversion.
  • Fu Lirong, Tang Yiwen, Liu Jinyi, Wu Shengwei, Xiao Mingwei
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    This study develops an improved flow field design by incorporating micro-guide blocks into a traditional straight channel. The guide blocks are arranged in a staggered manner within the flow field to induce airflow disturbances, promoting convective mass transfer and enhancing the transport of reactant gases. A three-dimensional, steady-state, non-isothermal two-phase model of a PEMFC with the novel guide block flow field was developed using the CFD method. The study systematically investigated the output performance, oxygen mass fraction, and gas flow velocity of the fuel cell. The quantitative analysis was conducted to evaluate the impact of the number of guide blocks on fuel cell performance and compared the results with a traditional straight channel PEMFC.The results elucidate the mechanism by which the improved flow field enhances the output performance of the PEMFC. The flow channel with 8 flow-guide blocks, compared to the traditional straight flow channel, shows an 18.73% increase in maximum current density and an 8.46% improvement in the peak power density of the fuel cell, achieving a net power density of 0.6208 W/cm2.
  • Liu Jinwu, Ji Ruyi, Ye Jianjun, Dong Qiaoying, He Yao, Shao Kaibin
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    Taking a multi-layer insulation structure cryogenic liquid hydrogen tank as the research object, an equivalent heat transfer model of the insulation structure was constructed based on the Layer by Layer theory. The temperature distribution characteristics of each structure of the liquid hydrogen tank under different vacuum degrees were analyzed, revealing the mechanism of the influence of vacuum degree on the heat transfer characteristics of the liquid hydrogen tank. The correlation between vacuum failure conditions and temperature distribution laws was then established. The results show that the temperature of the head on both sides of the liquid hydrogen tank is higher than that of the central tank area. When the vacuum degree is 10-2~1 Pa, the multi-layer insulation structure in the liquid hydrogen tank mainly relies on thermal radiation for heat transfer. When the vacuum degree of the interlayer gradually fails from 1 Pa to 104 Pa, the heat conduction effect begins to manifest and gradually dominates the heat transfer, and the wall temperature of the outer tank will decrease from 291.34 K to 275.78 K. When the vacuum degree deteriorates from 104 Pa to 105 Pa, the number of gas molecules in the adiabatic structure increases, and the flow of high and low-temperature gas molecules in the vacuum layer intensifies, which significantly promotes the role of convection heat transfer in heat transfer, resulting in a temperature rise of about 4.01 K on the outer wall surface of the liquid hydrogen tank. The correlation between vacuum degree and temperature distribution will help to explore the impact of vacuum failure on the heat transfer mechanism and achieve vacuum monitoring for multi-layer insulated liquid hydrogen tanks.
  • Liang Guozhuang, Xie Lei, Liu Yida, Fan Junyu, Duan Xuxing, Tian Hanlei
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    To address the stringent power requirements of high-efficiency electrolysis-based hydrogen production systems, which demand low current ripple, high output current, and low output voltage, this paper presents a high step-down ratio interleaved DC/DC converter utilizing coupled inductors. The proposed converter incorporates a flyback capacitor structure, effectively limiting the maximum voltage stress on the power devices to half of the input voltage, thereby improving system safety and reliability. Through the implementation of time-division multiplexing with coupled inductors, the converter achieves soft-switching operation, which significantly reduces switching losses at high frequencies. Additionally, the interleaved design mitigates output current ripple, thereby enhancing dynamic performance and system stability. Simulation and experimental results corroborate that the proposed converter exhibits superior soft-switching characteristics, minimal current ripple, reduced output voltage, and satisfies the stringent power quality standards required for high-efficiency hydrogen production systems.
  • Dang Jing, Qi Meng, Zhu Taolin, Zhao Xuyang, Deng Zijian, Liu Yi
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    This study investigates the adaptability and efficiency variations of two hydrogen production technologies, direct photoelectrocatalytic hydrogen production and indirect photovoltaic electrolysis hydrogen production, across diverse geographical regions, utilizing solar radiation data from various provinces. By systematically assessing key factors including annual radiation intensity, daylight duration, wavelength distribution, and diurnal variations, the study elucidates the impact of differing radiation conditions on hydrogen production efficiency. The performance of photoelectrocatalysts is contingent upon their absorption wavelength range. Significant variations in absorption efficiency across the spectrum are observed among different catalysts. TiO2 stands out for its stable hydrogen production capabilities, attributed to its environmental friendliness, high stability, and low cost, positioning it as the current predominant catalyst. A comparative analysis with CdS catalysts reveals that TiO2 necessitates modifications to broaden its absorption wavelength range, enhance reaction efficiency, and improve the utilization of visible light. Seasonal fluctuations in solar radiation influence the hydrogen production capabilities of photoelectrocatalysts. Hydrogen production reaches its zenith in summer and is at its nadir in winter. Optimizing the catalysts can bolster hydrogen production efficiency year-round. Photovoltaic hydrogen production consistently outperforms photoelectrocatalysis across all seasons, particularly in summer. Integrating photovoltaic and photoelectrocatalytic technologies can optimize solar energy utilization and mitigate seasonal variations. Regions in the west and south, notably areas such as Tibet, exhibit the highest solar radiation and hydrogen production potential. Future research should concentrate on refining photoelectrocatalysts and synergizing photovoltaic power generation with hydrogen production to achieve more efficient and cost-effective hydrogen energy production.