BI-LEVEL OPTIMAL OPERATION STRATEGY OF DISTRIBUTION NETWORK WITH DISTRIBUTED ENERGY

Chen Qian; Wang Weiqing; Wang Haiyun

doi:10.19912/j.0254-0096.tynxb.2021-0326

PDF(6306 KB)

Acta Energiae Solaris Sinica ›› 2022, Vol. 43 ›› Issue (10) : 507-517. DOI: 10.19912/j.0254-0096.tynxb.2021-0326

BI-LEVEL OPTIMAL OPERATION STRATEGY OF DISTRIBUTION NETWORK WITH DISTRIBUTED ENERGY

Chen Qian, Wang Weiqing, Wang Haiyun

Author information +

History +

Abstract

In response to the call of "carbon peaking, carbon neutralization", considering the economy and environmental protection of distribution network operation with distributed generation（DG）, this paper constructs a bi-level optimization model of distribution network with DG. In this model, DG investment and operation cost and environmental benefits are taken as the upper objectives to optimize the configuration of DG, and network loss and voltage offset cost are taken as the lower objectives to optimize the reactive power of distribution network. According to the characteristics of the model, an improved sparrow search algorithm is proposed to solve the model, adding tent chaotic map to initialize the population, introducing firefly disturbance mechanism to improve the operator, and optimizing the cross-border processing mechanism to maintain the population diversity. The simulation results show that the model can effectively improve the economic and environmental protection of distribution network operation, and verify the advantages of the improved sparrow search algorithm in solving complex high-dimensional nonlinear non-convex combinatorial optimization problems with discrete variables.

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

Chen Qian, Wang Weiqing, Wang Haiyun. BI-LEVEL OPTIMAL OPERATION STRATEGY OF DISTRIBUTION NETWORK WITH DISTRIBUTED ENERGY[J]. Acta Energiae Solaris Sinica. 2022, 43(10): 507-517 https://doi.org/10.19912/j.0254-0096.tynxb.2021-0326

References

[1] 杨博文. 能源转型中未来主力能源发展方向探析[J]. 能源与节能, 2020(6): 49-50, 91
YANG B W.Analysis on the development direction of future main energy in energy transformation[J]. Energy and energy conservation, 2020(6): 49-50, 91
[2] 杨蕾, 吴琛, 黄伟, 等. 含高比例风光新能源电网的多目标无功优化算法[J]. 电力建设, 2020, 41(7): 100-109.
YANG L, WU C, HUANG W, et al.Multi objective reactive power optimization algorithm for power grid with high proportion of wind and solar energy[J]. Electric power construction, 2020, 41(7): 100-109.
[3] AJEIGBE O A, MUNDA J L, HAMAM Y.Optimal allocation of renewable energy hybrid distributed generations for small-signal stability enhancement[J]. Energies, 2019, 12(24): 4777.
[4] KAZMI S A A, AHMAD H W, SHIN D R. A new improved voltage stability assessment index-centered integrated planning approach for multiple asset placement in mesh distribution systems[J]. Energies, 2019, 12(16): 3163.
[5] 吴文传. 主动配电网网络分析与运行调控[M]. 北京: 科学出版社, 2016.
WU W C.Active distribution network analysis and operation regulation[M]. Beijing: Science Press, 2016.
[6] 陈光宇, 黄越辉, 张仰飞, 等. 基于博弈策略含风电和机组运行极限约束的多目标优化调度模型及求解[J]. 太阳能学报, 2020, 41(7): 372-384.
CHEN G Y, HUANG Y H, ZHANG Y F, et al.Multi objective optimal dispatch model with wind power and unit operation limit constraints based on game strategy and its solution[J]. Acta energiae solaris sinica, 2020, 41(7): 372-384.
[7] 董海鹰, 陈彦求, 汪宁渤, 等. 含前端调速式风电机组风电场的无功运行优化[J]. 太阳能学报, 2020, 41(11): 254-260.
DONG H Y, CHEN Y Q, WANG N B, et al.Reactive power operation optimization of wind farm with front end variable speed wind turbine[J]. Acta energiae solaris sinica, 2020, 41(11): 254-260.
[8] 寇凌峰, 吴鸣, 李洋, 等. 主动配电网分布式有功无功优化调控方法[J]. 中国电机工程学报, 2020, 40(6): 1856-1865.
KOU L F, WU M, LI Y, et al.Distributed active and reactive power optimal control method for active distribution network[J]. Proceedings of the CSEE, 2020,40(6): 1856-1865.
[9] 宋倩芸. 计及多种分布式能源运行的配电网双层优化规划方法[J]. 电力系统保护与控制, 2020, 48(11): 53-61.
SONG Q Y.Bilevel optimization planning method for distribution network considering multiple distributed energy operation[J]. Power system protection and control, 2020, 48(11): 53-61.
[10] 罗培, 孙吉浩. 有源配电网动态无功优化解耦方法研究[J]. 高电压技术, 2021, 47(4): 1323-1333.
LUO P, SUN J H.Decoupling method for dynamic reactive power optimization of active distribution network[J]. High voltage engineering, 2021, 47(4): 1323-1333.
[11] 张涛, 余利, 姚剑峰, 等. 基于改进多目标差分灰狼算法的配电网无功优化[J]. 信息与控制, 2020, 49(1): 78-86.
ZHANG T, YU L, YAO J F, et al.Reactive power optimization of distribution network based on improved multi-objective differential gray wolf algorithm[J]. Information and control, 2020, 49(1): 78-86.
[12] XUE J K, SHEN B.Novel swarm intelligence optimization approach: sparrow search algorithm[J]. Systems science & control engineering an open access journal, 2019, 8(1): 22-34.
[13] 吕鑫, 慕晓冬, 张钧, 等. 混沌麻雀搜索优化算法[J]. 北京航空航天学报, 2021, 47(8): 1712-1720.
LYU X, MU X D, ZHANG J, et al.Chaos sparrow search optimization algorithm[J]. Journal of Beijing University of Aeronautice and Astronautics, 2021, 47(8): 1712-1720.
[14] 毛清华, 张强. 融合柯西变异和反向学习的改进麻雀算[J]. 计算机科学与探索, 2021, 15(6): 1155-1164.
MAO Q H, ZHANG Q.Improved sparrow algorithm based on Cauchy mutation and reverse learning[J]. Journal of frontiers of couputer science and technology, 2021, 15(6): 1155-1164.
[15] LIU L F, SONG Z D,YU H Y, et al.A modified fuzzy C-means(FCM) clustering algorithm and its application on carbonate fluid identification[J]. Journal of applied geophysics, 2016, 129: 28-35.
[16] YU S H, ZUO X K, FAN X L, et al.An improved firefly algorithm based on personalized step strategy[J]. Computing, 2021(2): 1436-5057.
[17] BARAN M E, WU F F.Network reconfiguration in distribution systems for loss reduction and load balancing[J]. IEEE transactions on power delivery, 1989, 9(4): 101-102.