TWO-LAYER OPTIMIZATION METHOD FOR SYSTEM OPERATION BASED ON HYBRID TIME SCALES

Liu Zhijian; Hu Yubin; Meng Xiangrui; Li Hanyu; Wu Di; Zhang Shicong

doi:10.19912/j.0254-0096.tynxb.2024-2175

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Acta Energiae Solaris Sinica ›› 2025, Vol. 46 ›› Issue (7) : 37-50. DOI: 10.19912/j.0254-0096.tynxb.2024-2175

Special Topics of Academic Papers at the 31th Annual Meeting of the China Association for Science and Technology

TWO-LAYER OPTIMIZATION METHOD FOR SYSTEM OPERATION BASED ON HYBRID TIME SCALES

Liu Zhijian^1,2, Hu Yubin¹, Meng Xiangrui¹, Li Hanyu¹, Wu Di^1,2, Zhang Shicong³

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Abstract

Aiming at the operation of distributed energy system （ DES ）, this paper proposes a bi-level optimization operation method based on mixed time scale regulation. This method aims to minimize the daily operating cost of the system and the power adjustment of the electrical related equipment, and constructs the optimal scheduling model of the upper minute level and the lower second level. The upper-level scheduling covers cooling, heating and power generation equipment with different response speeds, and regulates them through different time intervals to achieve mixed-time scale scheduling optimization. The lower layer mainly schedules power-related fast response equipment to improve the reliability of power supply in a short time scale. The results show that the proposed method can describe the response characteristics of cooling and heating equipment more accurately. Compared with single-layer scheduling, the daily operating costs of typical days in winter and summer are reduced by 5.2% and 24.3%, respectively. The utilization rate of renewable energy increased by 6.9% and 3.0%; the primary energy utilization rate increased by 4.0% and 26.6%; the primary energy saving rate reached 4.2% and 22.3%, which significantly improved the economic performance and energic performance utilization efficiency of the system and effectively guaranteed the efficient and stable operation of the system.

Key words

distributed energy / scheduling / renewable energy / regulating time / response characteristic / mixing time scale

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Liu Zhijian, Hu Yubin, Meng Xiangrui, Li Hanyu, Wu Di, Zhang Shicong. TWO-LAYER OPTIMIZATION METHOD FOR SYSTEM OPERATION BASED ON HYBRID TIME SCALES[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 37-50 https://doi.org/10.19912/j.0254-0096.tynxb.2024-2175

References

[1] 柳思贤, 丁坤, 董海鹰. 考虑碳捕集和电转气的零碳园区综合能源系统经济调度[J]. 太阳能学报, 2024, 45(9): 188-196.
LIU S X, DING K, DONG H Y.Zero-carbon economic dispatch of park integrated energy system considering carbon capture and power to gas[J]. Acta energiae solaris sinica, 2024, 45(9): 188-196.
[2] 薛东, 段立强, 高统彤, 等. 考虑多重特征与不确定性度量的综合能源系统负荷预测研究[J]. 太阳能学报, 2024, 45(7): 379-388.
XUE D, DUAN L Q, GAO T T, et al.Study of integrated energy system load forecasting considering multiple characteristics and uncertainty measures[J]. Acta energiae solaris sinica, 2024, 45(7): 379-388.
[3] DENG Y, LIU Y C, ZHANG Y, et al.Optimization and performance analysis of CCHP-GSHP-SE system under different start factors[J]. Energy conversion and management, 2022, 266: 115827.
[4] 郭凯杰, 耿光超, 江全元, 等. 计及超短期预测误差的风储系统跟踪计划出力控制策略[J]. 太阳能学报, 2023, 44(2): 326-333.
GUO K J, GENG G C, JIANG Q Y, et al.Output control strategy of wind storage system tracking plan considering ultra short term prediction error[J]. Acta energiae solaris sinica, 2023, 44(2): 326-333.
[5] 董燕, 陈乙瑞, 朱永胜, 等. 多时间尺度下智能楼宇异构负荷协同调度研究[J]. 太阳能学报, 2024, 45(8): 210-217.
DONG Y, CHEN Y R, ZHU Y S, et al.Research on coordinated scheduling of heterogeneous loads in smart buildings under multi-time scales[J]. Acta energiae solaris sinica, 2024, 45(8): 210-217.
[6] 罗政杰, 任惠, 辛国雨, 等. 基于模型预测控制的高比例可再生能源电力系统多时间尺度动态可靠优化调度[J]. 太阳能学报, 2024, 45(6): 150-160.
LUO Z J, REN H, XIN G Y, et al.Multi-time scale dynamic reliable optimal scheduling of power system with high propottion renewable energy based on model predictive control[J]. Acta energiae solaris sinica, 2024, 45(6): 150-160.
[7] 李杨, 孙斌, 吴峰, 等. 考虑动态频率约束的多能源电力系统日前-日内优化调度[J]. 太阳能学报, 2024, 45(2): 406-415.
LI Y, SUN B, WU F, et al.Day-ahead and intra-day optimal scheduling of multi-energy power systems considering dynamic frequency constraints[J]. Acta energiae solaris sinica, 2024, 45(2): 406-415.
[8] ZHANG Z W, WANG C F, CHEN S, et al.Multitime scale co-optimized dispatch for integrated electricity and natural gas system considering bidirectional interactions and renewable uncertainties[J]. IEEE transactions on industry applications, 2022, 58(4): 5317-5327.
[9] 王智, 陶鸿俊, 蔡文奎, 等. 多时间尺度滚动优化在冷热电联供系统中的优化调度研究[J]. 太阳能学报, 2023, 44(2): 298-308.
WANG Z, TAO H J, CAI W K, et al.Optimal scheduling research of multi-time-scale rolling optimization in CCHP system[J]. Acta energiae solaris sinica, 2023, 44(2): 298-308.
[10] 张大海, 贠韫韵, 王小君, 等. 计及风光不确定性的新能源虚拟电厂多时间尺度优化调度[J]. 太阳能学报, 2022, 43(11): 529-537.
ZHANG D H, YUN Y Y, WANG X J, et al.Multi-time scale of new energy scheduling optimization for virtual power plant considering uncertainty of wind power and photovoltaic power[J]. Acta energiae solaris sinica, 2022, 43(11): 529-537.
[11] 王季康, 李华, 张海龙, 等. 计及储能响应特性的风氢混合并网控制[J]. 太阳能学报, 2024, 45(5): 400-411.
WANG J K, LI H, ZHANG H L, et al.Hybrid wind-hydrogen grid-connected control considering energy storage response[J]. Acta energiae solaris sinica, 2024, 45(5): 400-411.
[12] QIN Y X, LIU P, LI Z.Multi-timescale hierarchical scheduling of an integrated energy system considering system inertia[J]. Renewable and sustainable energy reviews, 2022, 169: 112911.
[13] WU M, XU J Z, ZENG L J, et al.Two-stage robust optimization model for park integrated energy system based on dynamic programming[J]. Applied energy, 2022, 308: 118249.
[14] ZHOU Y Z, GE J Y, LI X, et al.Bi-level distributionally robust optimization model for low-carbon planning of integrated electricity and heat systems[J]. Energy, 2024, 302: 131777.
[15] WU D, HAN Z H, LIU Z J, et al.Comparative study of optimization method and optimal operation strategy for multi-scenario integrated energy system[J]. Energy, 2021, 217: 119311.
[16] HAN Z H, MA F F, WU D, et al.Collaborative optimization method and operation performances for a novel integrated energy system containing adiabatic compressed air energy storage and organic Rankine cycle[J]. Journal of energy storage, 2021, 41: 102942.
[17] ZHANG H, HAN Z H, WU D, et al.Energy optimization and performance analysis of a novel integrated energy system coupled with solar thermal unit and preheated organic cycle under extended following electric load strategy[J]. Energy, 2023, 272: 127094.
[18] LIU Z J, LI Y, FAN G Y, et al.Co-optimization of a novel distributed energy system integrated with hybrid energy storage in different nearly zero energy community scenarios[J]. Energy, 2022, 247: 123553.
[19] SADEGHI D, AHMADI S E, AMIRI N, et al.Designing, optimizing and comparing distributed generation technologies as a substitute system for reducing life cycle costs, CO₂ emissions, and power losses in residential buildings[J]. Energy, 2022, 253: 123947.
[20] WANG Y W, SONG M H, JIA M Y, et al.Multi-objective distributionally robust optimization for hydrogen-involved total renewable energy CCHP planning under source-load uncertainties[J]. Applied energy, 2023, 342: 121212.
[21] 席昌远, 吴迪, 李桂强, 等. 计及需求侧柔性负荷调控的综合能源系统优化运行方法研究[J]. 暖通空调, 2024, 54(8): 81-89.
XI C Y, WU D, LI G Q, et al.Optimal operation method of integrated energy systems considering flexible load regulation of demand side[J]. Heating ventilating & air conditioning, 2024, 54(8): 81-89.
[22] GUO J C, LIU Z J, WU X, et al.Two-layer co-optimization method for a distributed energy system combining multiple energy storages[J]. Applied energy, 2022, 322: 119486.
[23] CHONG Z X, YANG L J, JIANG Y N, et al.Hybrid-timescale optimal dispatch strategy for electricity and heat integrated energy system considering integrated demand response[J]. Renewable energy, 2024, 232: 121123.
[24] WANG X J, HAN L, WANG C, et al.A time-scale adaptive dispatching strategy considering the matching of time characteristics and dispatching periods of the integrated energy system[J]. Energy, 2023, 267: 126584.
[25] LI P, WANG Z X, WANG J H, et al.A multi-time-space scale optimal operation strategy for a distributed integrated energy system[J]. Applied energy, 2021, 289: 116698.
[26] 王智, 陶鸿俊, 张玲. 冷热电联供系统多时间尺度滚动优化运行方法研究[J]. 动力工程学报, 2022, 42(3): 276-285.
WANG Z, TAO H J, ZHANG L.Research on multi-time scale rolling optimal operation method of combined cooling, heating and power system[J]. Journal of Chinese Society of Power Engineering, 2022, 42(3): 276-285.
[27] LIU Z J, FAN G Y, MENG X R, et al.Multi-time scale operation optimization for a near-zero energy community energy system combined with electricity-heat-hydrogen storage[J]. Energy, 2024, 291: 130397.
[28] 贺庆, 常大伟, 张俊礼, 等. 天然气冷热电联产系统区间负荷调度策略优化[J]. 动力工程学报, 2022, 42(4): 365-371.
HE Q, CHANG D W, ZHANG J L, et al.Optimization of interval load scheduling strategy for a CCHP system using natural gas[J]. Journal of Chinese Society of Power Engineering, 2022, 42(4): 365-371.
[29] JIANG R H, YANG X P.Performance analysis and application of a novel combined cooling, heating and power system integrated with multi-energy storage system[J]. Journal of energy storage, 2024, 86: 111276.
[30] FANG X L, DONG W, WANG Y B, et al.Multiple time-scale energy management strategy for a hydrogen-based multi-energy microgrid[J]. Applied energy, 2022, 328: 120195.