HIERARCHICAL COORDINATION OPTIMIZATION METHOD OF REGIONAL MICRO-ENERGY-GRID GROUP BASED ON SCENARIO CONSTRUCTION TECHNOLOGY

Chen Zhiyong, Ding Xiaohua, Han Jinglin, Han Tao, Feng Xichun, Hou Ruosong, Li Hongtao

Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (5) : 289-296.

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Acta Energiae Solaris Sinica ›› 2024, Vol. 45 ›› Issue (5) : 289-296. DOI: 10.19912/j.0254-0096.tynxb.2023-0159

HIERARCHICAL COORDINATION OPTIMIZATION METHOD OF REGIONAL MICRO-ENERGY-GRID GROUP BASED ON SCENARIO CONSTRUCTION TECHNOLOGY

  • Chen Zhiyong1, Ding Xiaohua2, Han Jinglin3, Han Tao2, Feng Xichun1, Hou Ruosong1, Li Hongtao3
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Abstract

Considering the uncertainty of wind stroke, light output, and load power in regional micro energy networks, a hierarchical coordination optimization method for new energy consumption in regional micro energy networks is proposed. Introduce a normal Copula function to establish joint distribution relationships between time and conditional correlations of various random variables, thereby establishing typical scenarios of uncertainty. After considering the losses and prediction error costs of wind and light abandonment, a hierarchical coordinated optimization model is established with the goal of minimizing the operating cost of the micro energy network. The upper layer of this model is the coordination and consumption optimization of flexible resources in the micro energy network group, while the lower layer is the internal consumption optimization of the micro energy network. Using a hierarchical optimization method based on objective cascading analysis to iteratively solve, a hierarchical coordination optimization strategy for regional micro energy networks is obtained. Finally, an example of a micro energy grid group was used for validation, indicating that the proposed method improves the new energy consumption rate of the regional power grid.

Key words

micro-energy-network / new energy / consumption / hierarchical coordination optimization

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Chen Zhiyong, Ding Xiaohua, Han Jinglin, Han Tao, Feng Xichun, Hou Ruosong, Li Hongtao. HIERARCHICAL COORDINATION OPTIMIZATION METHOD OF REGIONAL MICRO-ENERGY-GRID GROUP BASED ON SCENARIO CONSTRUCTION TECHNOLOGY[J]. Acta Energiae Solaris Sinica. 2024, 45(5): 289-296 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0159

References

[1] 周京华, 孟祥飞, 陈亚爱, 等. 基于新能源发电的电解水制氢直流电源研究[J]. 太阳能学报, 2022, 43(6): 389-397.
ZHOU J H, MENG X F, CHEN Y A, et al.Research on DC power supply for hydrogen production from electrolytic water based on new energy generation[J]. Acta energiae solaris sinica, 2022, 43(6): 389-397.
[2] 王永真, 康利改, 张靖, 等. 综合能源系统的发展历程、典型形态及未来趋势[J]. 太阳能学报, 2021, 42(8): 84-95.
WANG Y Z, KANG L G, ZHANG J, et al.Development history, typical form and future trend of integrated energy system[J]. Acta energiae solaris sinica, 2021, 42(8): 84-95.
[3] WU Y, LAU V K N, TSANG D H K, et al. Optimal energy scheduling for residential smart grid with centralized renewable energy source[J]. IEEE systems journal, 2014, 8(2): 562-576.
[4] WU H Y, SHAHIDEHPOUR M, ALABDULWAHAB A, et al.Demand response exchange in the stochastic day-ahead scheduling with variable renewable generation[J]. IEEE transactions on sustainable energy, 2015, 6(2): 516-525.
[5] 马志侠, 张林鍹, 郑兴, 等. 基于PEMFC-P2G与风光不确定的综合能源系统优化调度[J]. 太阳能学报, 2022, 43(6): 441-447.
MA Z X, ZHANG L X, ZHENG X, et al.Optimal scheduling of integrated energy system based on PEMFC-P2G and inpact of wind power and photovoltaic uncertainty[J]. Acta energiae solaris sinica, 2022, 43(6): 441-447.
[6] MURTY V V S N, KUMAR A. Retraction note: multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems[J]. Protection and control of modern power systems, 2022, 7: 11.
[7] 凌梓, 杨秀, 李莉华, 等. 含电转气多能系统的协调控制与优化调度[J]. 太阳能学报, 2020, 41(12): 9-17.
LING Z, YANG X, LI L H, et al.Coordinated control and optimal scheduling of multi energy systems with power-to-gas devices[J]. Acta energiae solaris sinica, 2020, 41(12): 9-17.
[8] 舒印彪, 张智刚, 郭剑波, 等. 新能源消纳关键因素分析及解决措施研究[J]. 中国电机工程学报, 2017, 37(1): 1-9.
SHU Y B, ZHANG Z G, GUO J B, et al.Study on key factors and solution of renewable energy accommodation[J]. Proceedings of the CSEE, 2017, 37(1): 1-9.
[9] 杨经纬, 张宁, 王毅, 等. 面向可再生能源消纳的多能源系统: 述评与展望[J]. 电力系统自动化, 2018, 42(4): 11-24.
YANG J W, ZHANG N, WANG Y, et al.Multi-energy system towards renewable energy accommodation: review and prospect[J]. Automation of electric power systems, 2018, 42(4): 11-24.
[10] 马腾飞, 吴俊勇, 郝亮亮, 等. 基于能源集线器的微能源网能量流建模及优化运行分析[J]. 电网技术, 2018, 42(1): 179-186.
MA T F, WU J Y, HAO L L, et al.Energy flow modeling and optimal operation analysis of micro energy grid based on energy hub[J]. Power system technology, 2018, 42(1): 179-186.
[11] 徐青山, 李淋, 蔡霁霖, 等. 考虑电能交互的冷热电多微网系统日前优化经济调度[J]. 电力系统自动化, 2018, 42(21): 36-44.
XU Q S, LI L, CAI J L, et al.Day-ahead optimized economic dispatch of CCHP multi-microgrid system considering power interaction among microgrids[J]. Automation of electric power systems, 2018, 42(21): 36-44.
[12] 董帅, 王成福, 徐士杰, 等. 计及网络动态特性的电-气-热综合能源系统日前优化调度[J]. 电力系统自动化, 2018, 42(13): 12-19.
DONG S, WANG C F, XU S J, et al.Day-ahead optimal scheduling of electricity-gas-heat integrated energy system considering dynamic characteristics of networks[J]. Automation of electric power systems, 2018, 42(13): 12-19.
[13] 王博, 詹红霞, 张勇, 等. 考虑风电不确定性的风蓄火联合优化经济调度研究[J]. 电力工程技术, 2022, 41(1): 93-100.
WANG B, ZHAN H X, ZHANG Y, et al.Combined optimal economic dispatch of wind-storage-fire considering wind power uncertainty[J]. Electric power engineering technology, 2022, 41(1): 93-100.
[14] LI G Z, WANG R, ZHANG T, et al.Multi-objective optimal design of renewable energy integrated CCHP system using PICEA-G[J]. Energies, 2018, 11(4): 743.
[15] KIPTOO M K, ADEWUYI O B, LOTFY M E, et al.Multi-objective optimal capacity planning for 100% renewable energy-based microgrid incorporating cost of demand-side flexibility management[J]. Applied sciences, 2019, 9(18): 3855.
[16] 韩中合, 马帆帆, 吴迪, 等. 基于AA-CAES的综合能源系统协同优化与性能分析[J]. 太阳能学报, 2022, 43(12): 550-558.
HAN Z H, MA F F, WU D, et al.Collaborative optimization and performance analysis of integrated energy system based on AA-CAES[J]. Acta energiae solaris sinica, 2022, 43(12): 550-558.
[17] DOLATABADI A, MOHAMMADI-IVATLOO B, ABAPOUR M, et al.Optimal stochastic design of wind integrated energy hub[J]. IEEE transactions on industrial informatics, 2017, 13(5): 2379-2388.
[18] 徐健玮, 马刚, 高丛, 等. 基于风光场景生成的综合能源系统日前-日内优化调度[J]. 分布式能源, 2022, 7(4): 18-27.
XU J W, MA G, GAO C, et al.Day-ahead and intra-day optimal scheduling of integrated energy systems based on scenario generation[J]. Distributed energy, 2022, 7(4): 18-27.
[19] LI C Z, SHI Y M, LIU S, et al.Uncertain programming of building cooling heating and power (BCHP) system based on Monte-Carlo method[J]. Energy and buildings, 2010, 42(9): 1369-1375.
[20] 宋宇, 李涵. 基于核密度估计和Copula函数的风、光出力场景生成[J]. 电气技术, 2022, 23(1): 56-63.
SONG Y, LI H.Typical scene generation of wind and photovoltaic power output based on kernel density estimation and Copula function[J]. Electrical engineering, 2022, 23(1): 56-63.
[21] 朱兰, 牛培源, 唐陇军, 等. 考虑直接负荷控制不确定性的微能源网鲁棒优化运行[J]. 电网技术, 2020, 44(4): 1400-1413.
ZHU L, NIU P Y, TANG L J, et al.Robust optimal operation for micro-energy grid considering uncertainties of direct load control[J]. Power system technology, 2020, 44(4): 1400-1413.
[22] 武梦景, 万灿, 宋永华, 等. 含多能微网群的区域电热综合能源系统分层自治优化调度[J]. 电力系统自动化, 2021, 45(12): 20-29.
WU M J, WAN C, SONG Y H, et al.Hierarchical autonomous optimal dispatching of district integrated heating and power system with multi-energy microgrids[J]. Automation of electric power systems, 2021, 45(12): 20-29.
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