The layout methods and optical efficiency calculation theory of the heliostat field in the solar power tower plant were investigated. A new optimization and design method based on no-blocking radial stagger layout was proposed. An optical model of heliostat field was established and validated. The heliostat field of the Gemasolar power plant in Spain was redesigned by usingthe new optimization method The optical performance of the heliostat field was analyzed.Comparing to the original heliostat field, the annual average optical efficiency of the new heliostat field is increased from 61.62% to 63.14%, and the annual maximum optical efficiency is increased from 66.87% to 68.45%. Furthermore, the heliostat field density is improved from 20.42% to 27.36%. The optical performance of the heliostat field is enhanced. The feasibility of the new optimization and design method is validated.

This study presents a simple approach for fabricating polydimethylsiloxane （PDMS） films featuring textured surfaces. And the textured surface was chemically modified and optimized, which makes it with ideal spectral selectivity and a superhydrophobic surface. Testing results show that the superhydrophobic PDMS （SH-PDMS） film displays an average emissivity of approximately 97.0% within the "atmospheric window" band （8-13 μm）, along with an average solar transmittance of up to 94.8% in the range of 300-1100 nm. Consequently, the SH-PDMS film holds potential as an effective radiative cooling layer for photovoltaic （PV） panels. Application of this film to commercial photovoltaic panels demonstrates superhydrophobicity and self-cleaning properties on the panel surface. Furthermore, outdoor daytime testing results indicate a temperature reduction of 1.0-1.5 ℃ for PV panels featuring the SH-PDMS film compared to those with original glass surfaces. Additionally, the PV panels with SH-PDMS film exhibits reduced light reflection and improves photoelectric output relative to smooth photovoltaic surfaces.

In order to improve the efficiency of the proton exchange membrane fuel cell system, the existing Nernst electromotive force model was improved according to the actual stack performance and the working principle of PEMFC. By combining mechanism modeling and identification modeling methods, a new PEMFC system model with higher efficiency and better stability was established. The model was simulated, verified and analyzed based on Matlab platform. The results show that the new PEMFC system model can visually reflect the changing trends of the stack output voltage, output power, and battery efficiency affected by parameters such as temperature, hydrogen-oxygen ratio, and pressure difference. Compared with the traditional PEMFC system model, it has significant improvements in battery efficiency, endurance, and stability.

Aiming at the problem of insufficient quantitative comparative study on the wideband dynamic characteristics of the grid-following/grid-forming converters, this study initially constructs a small-signal model to represent the wideband dynamics of grid-following/grid-forming converters under virtual synchronous control, followed by comprehensive validation in both time and frequency domains. Building upon this foundation, the research employs eigenmode and participation factor analysis to quantitatively assess and compare the wideband dynamic characteristics and stability of the converters, identifying weakly damped eigenmodes and pinpointing critical control parameters. Moreover, utilizing the root locus method, the study quantitatively examines how active support parameters—such as virtual inertia and primary frequency modulation—along with grid strength, influence the dynamic characteristics of the converters and delineates their patterns of variation. Conclusively, the accuracy and validity of the findings are substantiated through the development of a detailed time-domain simulation model of the grid-following and grid-forming converters in Matlab/Simulink.

The paper proposes a rapid microfluidic fabrication method for encapsulated phase change materials （EPCMs）. C₁₅/TMPTA EPCMs are prepared using an immersed co-flowing capillary microfluidic device with UV-curing, supplemented by thermally conductive modification of the shell material with silicon carbide. Characterization techniques including high-speed cameras, SEM, OM, FT-IR, XRD, DSC, TGA and LFA are utilized to investigate the generation of compound droplets and the properties of EPCMs. The results show that within the selected range of flow rate parameters, the generation process of compound droplets exhibits three phenomena： dripping, core leakage and jetting. Under dripping and jetting phenomena, stable compound droplets are formed. However, when the flow rate ratio （Q_i/Q_o） is larger than 1.5 and the total flow rate （Q_total） is less than 160 µL/min, the core droplet will leak, resulting in the inability to generate the composite droplet normally. The sizes of core and compound droplets decrease with an increase in the outer phase capillary number （Ca_o）, while the frequency of compound droplet generation increases with Ca_o. Moreover, EPCMs prepared at Q_i/Q_o of 0.5, 1 and 1.5, with a Q_total of 150 µL/min, exhibit a multi-core structure, high monodispersity （with a coefficient of variation （C_v） <4%） and controllable size, ranging from 1.32 to 1.55 mm in diameter. The addition of 2wt% nano silicon carbide for modification enhances the encapsulation efficiency of EPCMs （increased by 16.17%） and thermal cycling stability, with only a 1.19% decrease in enthalpy value after 25 thermal cycles.

In response to the challenges associated with complex dynamic responses and inaccurate description of nonlinear relationships in proton exchange membrane fuel cell （PEMFC） modeling, this paper proposes a novel method for PEMFC modeling and parameter identification based on a multi-input single-output Hammerstein structure. Initially, an extreme learning machine （ELM） network is employed to capture the input nonlinearity within the Hammerstein model, thereby constructing a framework that precisely reflects both the dynamic and static characteristics of the PEMFC system. Subsequently, the key term separation technique is utilized to construct the identification model, from which the auxiliary model recursive least squares （AM-RLS） algorithm and the auxiliary model forgetting gradient （AM-FG） algorithm are derived for parameter identification by integrating the auxiliary model idea. Finally, by combining ElasticNet with mutual information analysis （MIA）, controllable variables strongly correlated with the output power quality are screened, thereby reducing modeling complexity and improving computational efficiency. Through simulation verification using the measured data under dynamic and steady current conditions, the results indicate that the established model can accurately predict the variation trend of output voltage and exactly reflect the quality fluctuation of output power.

The traditional photovoltaic storage charger widely used in the photovoltaic storage DC microgrid, the core part-bidirectional DC/DC is difficult to do at the same time to isolate and storage batteries need a wide range of voltage output. In this paper, a two-phase parallel asymmetric CLLC circuit topology and the associated control strategy are proposed, which adopts the control method of interleaved parallel and topology multiplexing to generate three modes of half-bridge, full-bridge, and full-bridge interleaved parallel to provide a wide voltage gain range, so that the converter operates near the above-resonant frequency point, and the three modes of operation achieve the zero-voltage turn-on of the primary-side switching tube. Aiming at the output power imbalance problem caused by the difference of actual resonance parameters in the full-bridge interleaved parallel mode, a method of compensating for the smaller gain phases, the phase-shift control method of increasing the secondary-side switching tubes is proposed. Through theoretical analysis and derivation of the corresponding gain formula, it is verified that the method can adjust the output gain and thus equalize the power. Finally, it is verified on the constructed 3.3 kW experimental platform that the converter can provide the voltage and power ranges required to satisfy the multi-stage charging of energy storage batteries, maintains the soft-switching in all the three modes, and achieves the power equalization in the full-bridge interleaved parallel mode.

The research progress of solid-state hydrogen storage technology is reviewed, including hydrogen storage materials, hydrogen storage devices and application status. Some hydrogen storage alloys have been successfully used in solid-state hydrogen storage devices. The high-capacity reversible hydrogen storage materials under mild hydrogen absorption and desorption conditions is the focus of current research and development. The optimized design of the hydrogen storage device effectively improves the rapid heat transfer characteristics and the safety performance. Hydrogen storage devices have been applied in the fields of distributed energy supply and motor vehicles. However, it is still necessary to further realize the coordination of rapid response, safety, reliability, and high hydrogen storage density of the hydrogen storage system.

Based on the performance differences and advantages and disadvantages of four kinds of water electrolysis hydrogen production technologies, the research status of membrane electrode, porous transport layer and bipolar plate in PEM electrolytic cell is summarized and prospected. Finally, combining with the advantages of PEM electrolytic water hydrogen production technology, the cost trend of this technology is analyzed and the application scenarios and development direction of this technology are predicted.

Accurate and reliable anomaly detection is of great significance to ensure the safe and efficient operation of wind turbines. However, due to the complex structure and variable operation conditions of wind turbines, the measure SCADA data usually present complex nonlinear and strongly correlated and coupling characteristics. To better capture spatial correlations among different sensor variables, a new wind turbine anomaly detection approach based on dilated causal convolution network is proposed. Specifically, Focal Loss is introduced to improve the traditional loss function to address the data imbalance issue. The proposed approach can extract effective multiscale spatially correlated features with different receptive field sizes and effectively model the hidden spatial causality among different sensor variables. Furthermore, it can provide an end-to-end anomaly detection solution for wind turbines, which can directly learn useful spatial features from raw SCADA data and build the nonlinear mapping relationship between original data space and condition label space, thus finally outputting the corresponding detection results. A real case study with SCADA data from a wind farm is used to verify the feasibility and effectiveness of the proposed approach.