OPTIMAL CONFIGURATION OF WIND-PHOTOVOLTAIC-ESS COMPLEMENTARY POWER GENERATION SYSTEM BASED ON BI-LEVEL OPTIMIZATION MODEL

Wang Lei; Wang Zhao; Feng Bin; Yang Panfeng

doi:10.19912/j.0254-0096.tynxb.2020-0430

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Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (5) : 98-104. DOI: 10.19912/j.0254-0096.tynxb.2020-0430

OPTIMAL CONFIGURATION OF WIND-PHOTOVOLTAIC-ESS COMPLEMENTARY POWER GENERATION SYSTEM BASED ON BI-LEVEL OPTIMIZATION MODEL

Wang Lei, Wang Zhao, Feng Bin, Yang Panfeng

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Abstract

An optimal configuration of wind-photovoltaic-ESS complementary power generation system based on bi-level optimization model is proposed, the outer layer is optimized to maximize the annual net income of the complementary power generation system by quantum particle swarm optimization （QPSO）, the inner layer is optimized to minimize the sunrise force volatility and peak-valley difference of complementary generation system, and optimizes the charge-discharge power of ESS through 8760 hours production simulation. The simulation results show that the proposed algorithm can effectively solve the capacity optimization allocation problem of wind-photovoltaic-ESS complementary power generation system in the planning stage.

Key words

wind-photovoltaic-ESS / capacity configuration / bi-level optimization model / quantum particle swarm optimization / 8760 hours production simulation

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Wang Lei, Wang Zhao, Feng Bin, Yang Panfeng. OPTIMAL CONFIGURATION OF WIND-PHOTOVOLTAIC-ESS COMPLEMENTARY POWER GENERATION SYSTEM BASED ON BI-LEVEL OPTIMIZATION MODEL[J]. Acta Energiae Solaris Sinica. 2022, 43(5): 98-104 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0430

References

[1] 田世明, 栾文鹏, 张东霞, 等. 能源互联网技术形态与关键技术[J]. 中国电机工程学报, 2015, 35(14): 3482-3494.
TIAN S M, LUAN W P, ZHANG D X, et al.Technical forms and key technologies on energy internet[J]. Proceedings of the CSEE, 2015, 35(14): 3482-3494.
[2] 叶季蕾, 薛金花, 王伟, 等. 储能技术在电力系统中的应用现状与前景[J]. 中国电力, 2014, 47(3): 1-5.
YE J L, XUE J H, WANG W, et al.Application of energy storage technology and its prospect in power system[J]. Electric power, 2014, 47(3): 1-5.
[3] 曹阳, 黄越辉, 袁越, 等. 基于时序仿真的风光容量配比分层优化算法[J]. 中国电机工程学报, 2015, 35(5):1072-1078.
CAO Y, HUANG Y H, YUAN Y, et al.Stratified optimization algorithm for optimal proportion of wind and solar capacity based on time sequence simulation[J]. Proceedings of the CSEE, 2015, 35(5): 1072-1078.
[4] 唐浩, 杨国华, 王鹏珍, 等. 基于CO₂排放量的风光互补发电系统容量优化配置[J]. 电力建设, 2017, 38(3):108-114.
TANG H, YANG G H, WANG P Z, et al.Capacity optimal configuration of wind/PV hybrid power system based on carbon dioxide emission[J]. Electric power construction, 2017, 38(3): 108-114.
[5] 胡林献, 顾雅云, 姚友素. 并网型风光互补系统容量优化配置方法[J]. 电网与清洁能源,2016, 32(3): 120-126.
HU L X, GU Y Y, YAO Y S.Optimal capacity configuration method for grid-connected wind-solar complementary power system[J]. Power system and clean energy, 2016, 32(3): 120-126.
[6] 李建林, 牛萌, 田立亭, 等. 光伏扶贫电站光-储协同配置方法研究[J]. 太阳能学报, 2019, 40(1): 79-86.
LI J L,NIU M, TIAN L T, et al.Research on PV-storage coordinated capacity configuration for photovoltaic poverty alleviation station[J]. Acta energiae solaris sinica, 2019,40(1): 79-86.
[7] 刘艳平, 贾春娟. 基于遗传算法的独立型风光互补发电容量优化[J]. 电力系统及其自动化学报, 2015, 27(10): 69-74.
LIU Y P, JIA C J.Capacity optimization of independent wind/PV hybrid power generation system based on GA[J]. Proceedings of the CSU-EPSA, 2015, 27(10): 69-74.
[8] 吴克河, 周欢, 刘吉臻. 大规模并网型风光储发电单元容量优化配置方法[J]. 太阳能学报, 2015, 36(12):2946-2953.
WU K H, ZHOU H, LIU J Z.Capacity allocation optimization method of large scale grid connected wind-PV-battery generation unit[J]. Acta energiae solaris sinica,2015, 36(12): 2946-2953.
[9] 齐志远, 郭佳伟, 李晓炀. 基于联合概率分布的风光互补发电系统优化配置[J]. 太阳能学报, 2018, 39(1):203-209.
QI Z Y, GUO J W, LI X Y.Optimal configuration for wind power and solar power hybrid systems based on joint probability distribution of wind speed with solar irradiance[J]. Acta energiae solaris sinica, 2018, 39(1): 203-209.
[10] 于东霞, 张建华, 王晓燕, 等. 并网型风光储互补发电系统容量优化配置[J]. 电力系统及其自动化学报,2019, 31(10): 59-65.
YU D X,ZHANG J H, WANG X Y, et al.Optimal capacity configuration of grid-connected wind-PV-storage hybrid power generation system[J]. Proceedings of the CSU-EPSA, 2019,31(10):59-65.
[11] 贾彦, 李文雄, 赵萌, 等. 罚函数改进粒子群算法的风光储系统优化配置[J]. 太阳能学报,2019, 40(7): 2071-2077.
JIA Y, LI W X, ZHAO M, et al.Optimal configeration for solar-wind-battery hybrid power system based on penalty function improved particle swarm optimization[J]. Acta energiae solaris sinica, 2019, 40(7): 2071-2077.
[12] 陈天, 蔡泽祥, 谢鹏, 等. 基于改进微分进化算法的风光互补系统发电容量优化配置[J]. 电力科学与技术学报, 2017, 32(3): 22-28.
CHEN T, CAI Z X,XIE P, et al.Capacity optimization of wind/solar hybrid power generation system based on improved differential evolution algorithm[J]. Journal of electric power science and technology, 2017, 32(3): 22-28.
[13] 葛维春, 滕健伊, 潘超,等. 含风光储能源-储-荷规划与运行调控策略[J]. 电力系统保护与控制, 2019, 47(13): 46-53.
GE W C, TENG J Y, PAN C, et al.Operation regulation strategy of source-storage-load with wind energy storage energy[J]. Power system protection and control, 2019, 47(13): 46-53.
[14] 李建林, 郭斌琪, 牛萌, 等. 风光储系统储能容量优化配置策略[J]. 电工技术学报, 2018, 33(6): 1189-1196.
LI J L,GUO B Q, NIU M, et al.Optimal configuration strategy of energy storage capacity in wind/PV/storage hybrid system[J]. Transactions of China Electrotechnical Society, 2018, 33(6): 1189-1196.
[15] 郑乐, 胡伟, 陆秋瑜, 等. 储能系统用于提高风电接入的规划和运行综合优化模型[J]. 中国电机工程学报,2014, 34(16): 2533-2543.
ZHENG L, HU W, LU Q Y,et al.Research on planning and operation model for energy storage system to optimize wind power integration[J]. Proceedings of the CSEE,2014, 34(16): 2533-2543.
[16] 韩晓娟, 程成, 籍天明, 等. 计及电池使用寿命的混合储能系统容量优化模型[J]. 中国电机工程学报, 2013,33(34): 83-89.
HAN X J, CHEN C, JI T M, et al.Capacity optimal modeling of hybrid energy storage systems considering battery life[J]. Proceedings of the CSEE, 2013, 33(34):83-89.
[17] 谭兴国, 王辉, 张黎, 等. 微电网复合储能多目标优化配置方法及评价指标[J]. 电力系统自动化, 2014, 38(8): 7-14.
TAN X G,WANG H,ZHANG L,et al.Multi-objective optimization of hybrid energy storage and assessment indices in microgrid[J]. Automation of electric power systems, 2014, 38(8): 7-14.
[18] 孙俊. 量子行为粒子群优化算法研究[D]. 无锡: 江南大学, 2009.
SUN J.Particle swarm optimization with particles having quantum behavior[D]. Wuxi: Jiangnan University, 2009.
[19] 孙郁闻天. 基于量子行为的多目标粒子群优化算法的研究及其应用[D]. 镇江: 江苏大学, 2019.
SUN Y W T. A study of multi-objective particle swarm optimization based on quantum behavior and its application[D]. Zhenjiang: Jiangsu University,2019.
[20] 王智冬, 刘连光, 刘自发, 等. 基于量子粒子群算法的风火打捆容量及直流落点优化配置[J]. 中国电机工程学报, 2014, 34(13): 2055-2062.
WANG Z D, LIU L G, LIU Z F, et al.Optimal configuration of wind & coal power capacity and DC placement based on quantum PSO algorithm[J]. Proceedings of the CSEE, 2014, 34(13): 2055-2062.