Dual Layer Optimization Model For Capacity Configuration Of Rural Multi Microgrid System With Biogas Energy Generation

ZHANG Jinliang; CHENG Jia

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Electric Power Construction ›› 2025

Dual Layer Optimization Model For Capacity Configuration Of Rural Multi Microgrid System With Biogas Energy Generation

ZHANG Jinliang, CHENG Jia

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Abstract

[Objective] In order to solve the problem of new energy system capacity allocation in rural areas, respond to the requirements of rural revitalization and low carbon, and improve the rate of renewable energy consumption, a microgrid system capacity allocation method based on the interaction between sub-microgrids and considering biogas energy generation is proposed. [Methods] Firstly, the structure of rural multi-microgrids is analyzed and a multi-microgrid system model for biogas energy generation containing inter-microgrid energy scheduling strategy is established; secondly, a two-layer model for capacity allocation and operation co-optimization of multi-microgrid system containing biogas energy generation is established, with the upper objective of the minimization of the annual integrated cost of multi-microgrids and the maximization of the utilization rate of renewable energy sources and the lower objective of the minimization of the operating cost of multi-microgrid system, which is solved by using the Particle swarm algorithm combined with Cplex solver; for the cost of the microgrid system, the Shapley value method is used to share the microgrids equitably. [Results] Matlab simulation results and example analyses show that the proposed introduction of biogas energy as a power generation unit can increase the penetration rate of new energy; the proposed rural inter-microgrid power interaction, the overall capacity allocation of new energy and energy storage have been reduced, which reduces the annual investment cost, making the cost of purchasing power from the outside of the multi-microgrid reduced by 9%, and the power sales are also on a downward trend; the microgrid cost is apportioned by using the Shapley value method, and the actual cost of each microgrid is reduced by 6.3%, 2%, and 4% respectively compared to the scenario of independent operation. Using the Shapley value method to apportion the costs of microgrids, the actual costs of each microgrid are reduced by 6.3%, 2%, and 4.4%, respectively, compared with the scenarios in which the microgrids are operated independently. [Conclusions] The proposed two-layer optimization model for capacity allocation of rural multi-microgrid system containing biogas energy generation results in lower annual integrated cost, reduced carbon emissions, increased internal consumption of new energy sources, and reduced dependence on the grid at the rural load side, which can achieve both economy and environmental friendliness.

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rural multi microgrid / biogas energy / double-layer optimization / particle swarm algorithm / cost-sharing

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ZHANG Jinliang, CHENG Jia. Dual Layer Optimization Model For Capacity Configuration Of Rural Multi Microgrid System With Biogas Energy Generation[J]. Electric Power Construction. 2025

References

[1] 郑云平,焦春雷,亚夏尔·吐尔洪,等.基于新能源发电的构网型协调储能控制策略研究[J]. 高压电器,2023,59(07): 65-74.
ZHENG Yunping, JIAO Chunlei, YASHAR TURHONG, et al.Research on coordinated energy storage control strategy based on new energy generation with structured network type[J]. High Voltage Apparatus, 2023, 59(07): 65-74.
[2] 王大兴,宁妍,汪敬培,等.构建新型电力系统背景下的微电网鲁棒简化建模[J] .中国电力,2024,57(01): 148-157.
WANG Daxing, NING Yan, WANG Jingpei, et al.Robust Simplified Modeling of Microgrids in the Context of Building a New Power System[J] .China Electric Power,2024, 57(01): 148-157.
[3] 陈心宜,胡秦然,石庆鑫,等.新型电力系统居民分布式资源管理综述[J].电力系统自动化,2024,48(05): 157-175.
CHEN Xinyi, HU Qinran, SHI Qingxin, et al.Overview of Residential Distributed Resource Management in New Power Systems[J]. Power System Automation, 2024, 48(05): 157-175.
[4] 李翔宇,黎东阳,张正江,等.孤岛微电网系统的混合控制策略及动态滤波技术研究[J].全球能源互联网,2024,7(03): 336-347.
LI Xiangyu, LI Dongyang, ZHANG Zhengjiang, et al.Research on hybrid control strategy and dynamic filtering technology for islanded microgrid system[J]. Global Energy Internet, 2024,7(03): 336-347.
[5] 田健. 微电网绿色低碳发展的关键技术与应用[J].计量科学与技术,2023,67(07): 25-33.
TIAN Jian.Key Technologies and Applications for Green and Low Carbon Development of Microgrids[J]. Metrology Science and Technology, 2023, 67(07): 25-33.
[6] 许中阳,宋晓通.含高比例清洁能源的微电网多目标优化调度策略[J].分布式能源,2023,8(02): 19-25.
XU Zhongyang, Song Xiaotong.Multi-objective optimal scheduling strategy for microgrids containing a high proportion of clean energy[J]. Distributed Energy, 2023, 8(02): 19-25.
[7] 邱益林. 智能电网可再生能源微电网系统设计分析[J].太阳能学报,2023,44(08): 568.
QIU Yilin.Design and Analysis of Renewable Energy Microgrid System for Smart Grid[J]. Journal of Solar Energy, 2023, 44(08): 568.
[8] 艾平,彭宇志,金柯达,等.面向低碳村镇的可再生能源热电联供系统仿真与优化[J].农业机械学报,2023,54(S2):350-358+399.
AI Ping, Peng Yuzhi, Jin Koda, et al. Simulation and optimization of renewable energy cogeneration system for low-carbon villages and towns[J]. Journal of Agricultural Machinery, 2023, 54(S2): 350-358+399.
[9] 刘金华,陈璐,刘凡骞,等.风-光-抽水蓄能互补系统经济容量配置研究[J].供用电,2025,42(04): 99-107.
LIU Jinhua, CHEN Lu, LIU Fanqian, et al.Research on economic capacity allocation of wind-photovoltaic-pumped storage complementary system[J]. Power Supply,2025,42(04): 99-107.
[10] 杨跃,安然然,梁晓兵,等.计及灵活性约束的配电网-微电网灵活性资源协同规划模型[J].广东电力,2023,36(08): 54-69.
YANG Yue, AN Ranran, LIANG Xiaobing, et al.A cooperative planning model of distribution-microgrid flexibility resources taking flexibility constraints into account[J]. Guangdong Electric Power,2023,36(08): 54-69.
[11] 赵安军,李旺,于军琪,等.基于户间调度的青海农村家庭光储容量配置优化[J].电力系统及其自动化学报,2023,35(07):45-56.
ZHAO Anjun, LI Wang, YU Junqi, et al.Optimization of household photovoltaic storage capacity configuration in rural households in Qinghai based on inter household scheduling[J]. Journal of Electric Power Systems and Automation, 2023, 35(07): 45-56.
[12] 端木陈睿,史林军,蹇德平,等.计及多时间尺度的梯级水-风-光互补基地储能容量优化配置[J].电力自动化设备,2024,44(07): 173-179.
DUANMU Chenrui, SHI Linjun, JIAN Deping, et al.Energy Storage Capacity Optimization Configuration of Cascade Water Wind Photovoltaic Complementary Bases Considering Multiple Time Scales[J]. Electric Power Automation Equipment,2024,44(07): 173-179.
[13] YUAN H, YE H, CHEN Y, et al.Research on the optimal configuration of photovoltaic and energy storage in rural microgrid[J].Energy Reports, 2022, 8: 1285-1293.
[14] 金家桢,易承东,冯震.偏远农村的风光储微网容量配置优化[J].电工材料,2024,(05):92-96.
JIN Jiazhen, YI Chengdong, FENG Zhen.Optimisation of capacity allocation for wind-solar storage microgrids in remote rural areas[J]. Electrical Materials, 2024, (05): 92-96.
[15] 侯永全,徐敦彬,袁晓冬,等.基于博弈论的含氢微网多主体能源系统优化配置[J].高压电器,2024,60(07): 48-59.
HOU Yongquan, XU Dunbin, YUAN Xiaodong, et al.Optimized allocation of hydrogen-containing microgrid multi-subject energy system based on game theory[J]. High Voltage Electrical Apparatus, 2024, 60(07): 48-59.
[16] 张冲标,钱辰雯,俞红燕,等.基于ADMM的多场景县域多微电网交互运行策略[J].中国电力,2024,57(02):9-18.
ZHANG Chongbiao, QIAN Chenwen, YU Hongyan, et al.Interactive Operation Strategy of Multi scenario County Multi microgrid Based on ADMM[J]. China Electric Power, 2024, 57(02):9-18.
[17] 黄冬梅,陈柯翔,孙锦中,等.含电解制氢装置及光热电站的海岛微网优化调度[J].电力系统及其自动化学报,2022,34(11): 24-31.
HUANG Dongmei, CHEN Kexiang, SUN Jinzhong, et al.Optimization and scheduling of island microgrids with electrolytic hydrogen production units and solar thermal power plants[J]. Journal of Power Systems and Automation, 2022, 34(11): 24-31.
[18] 朱祖祥,朱革兰,秦飞翔.基于博弈的多综合能源微网系统优化运行策略[J]. 广东电力,2023,36(02): 52-65.
ZU Zuxiang, ZHU Gelan, QIN Feixiang.Game-based optimal operation strategy for multi-integrated energy microgrid system[J]. Guangdong Electric Power,2023,36(02): 52-65.
[19] 吕荣胜,黄正伟,魏业文,等.基于主从博弈的多微网共享储能优化调度研究[J].现代电子技术,2024,47(20): 46-50.
LV Rongsheng, Huang Zhengwei, Wei Yewen, et al.Research on optimal scheduling of shared energy storage in multiple microgrids based on master-slave game[J]. Modern Electronic Technology, 2024, 47(20): 46-50.
[20] 王永利,姜斯冲,郭璐,等.基于共享氢容量备用的多微网双层优化方法[J].电力建设,2024,45(11): 65-78.
WANG Yongli, JIANG Sichong, GUO Lu, et al.A double-layer optimisation method for multiple microgrids based on shared hydrogen capacity backup[J]. Electric Power Construction, 2024,45(11): 65-78.
[21] 王俊翔,李华强,邓靖微,等.考虑需求侧灵活性资源的商业园区微网多目标优化调度[J].电力建设,2021,42(03): 35-44.
WANNG Junxiang, Li Huaqiang, Deng Jingwei, et al.Multi-objective optimal scheduling of business park microgrid considering demand-side flexibility resources[J]. Electric Power Construction, 2021, 42(03): 35-44.
[22] 寇凌峰,季宇,曲雪原,等.含海洋能发电的海岛微网源荷储容量优化配置研究[J].电测与仪表,2024, 61(05): 135-145.
KOU Lingfeng, JI Yu, QU Xueyuan, et al.Research on Optimal Configuration of Source Load Storage Capacity for Island Microgrids with Ocean Energy Generation[J]. Electrical Measurement and Instrumentation, 2024, 61(05): 135-145.
[23] 檀勤良,单子婧,丁毅宏,等.考虑蓄电池与电制氢的多能源微网灵活性资源配置双层优化模型[J].电力建设,2023,44(02): 38-49.
TAN Qinliang, DAN Dajing, DING Yihong, et al.A Dual layer Optimization Model for Flexible Resource Allocation in Multi Energy Microgrids Considering Batteries and Hydrogen Production[J]. Electric Power Construction, 2023, 44(02): 38-49.
[24] 安源,郑申印,苏瑞,等.风光水储多能互补发电系统双层优化研究[J].太阳能学报,2023,44(12): 510-517.
AN Yuan, ZHENG Shenyin, SU Rui, et al.Double layer optimization research on wind solar water storage multi energy complementary power generation system[J]. Journal of Solar Energy, 2023, 44(12): 510-517.
[25] WANG W, LI C, HE Y, et al.Enhancement of household photovoltaic consumption potential in village microgrid considering electric vehicles scheduling and energy storage system configuration[J]. Energy, 2024, 311: 133330.
[26] 杨昆,刘通,柏林,等.基于谈判博弈的微电网群多主体共享储能容量优化配置策略[J].电测与仪表,2024,61(03): 33-41.
YANG Kun, LIU Tong, BERLIN, et al. Optimal allocation strategy of shared energy storage capacity for multiple subjects in microgrid cluster based on negotiation game[J]. Electrical Measurement and Instrumentation, 2024, 61(03): 33-41.
[27] 赵杰,王聪,李冠冠,等.考虑需求响应的多微网P2P能源交易低碳运行策略[J].电力建设,2023,44(12):54-65.
ZHAO Jie,WANG Cong,LI Guanguan,et al.Low carbon operation strategy for multi microgrid P2P energy trading considering demand response[J].Electric Power Construction,2023,44(12):54-65.
[28] 贝斌斌,乐程毅,基于供需博弈的园区综合能源微网系统优化[J] .自动化仪表,2023,44(02):91-96.
BEIBin bin,LE Chengyi,Optimization of Integrated Energy Microgrid System in Industrial Parks Based on Supply and Demand Game[J].Automation Instrumentation,2023,44(02):91-96.
[29] 徐艳春,刘海权,孙思涵,等.计及需求响应和共享储能的多微网系统双层优化调度[J].电力自动化设备,2023,43(06):18-26.
XU Yanchun, LIU Haiquan, SUN Sihan, et al.Double layer optimization scheduling of multi microgrid systems considering demand response and shared energy storage[J].Power Automation Equipment, 2023, 43(06): 18-26.
[30] 胡俊杰,曲佳桐,王文浩,基于模型预测控制的高速公路综合能源微网群分布式能量优化调度方法[J].广东电力,2024,37(12): 87-96.
HU Junjie,Qu Jiatong,Wang Wenhao.Distributed energy optimization scheduling method for integrated energy microgrid cluster on highway based on model predictive control[J]. Guangdong Electric Power,2024,37(12):87-96.
[31] 吴睿行,刘丽军,林锟,等.考虑虚拟储能参与的多微网混合博弈运行策略[J].电网技术,1-15.
WU Ruixing, Liu Lijun, Lin Kun, et al.Multi-microgrid hybrid game operation strategy considering virtual energy storage participation[J]. Grid Technology, 1-15.
[32] 杨磊,周凯旋,贺凯,等.温度修正对光伏发电系统性能比影响分析[J].可再生能源,2024,42(01):16-21.
YANG Lei, ZHOU Kaixuan, HE Kai, et al.Analysis of the Impact of Temperature Correction on the Performance Ratio of Photovoltaic Power Generation Systems[J]. Renewable Energy, 2024, 42(01): 16-21.
[33] 张雷,刘思彤,李勇,分布式光伏发电系统并网技术分析[J].电子技术,2024,53(02):372-374.
ZHANG Lei, LIU Sitong, LI Yong, Analysis of Grid Connection Technology for Distributed Photovoltaic Power Generation System[J]. Electronic Technology, 2024, 53(02): 372-374.
[34] 卢颖辉. 计及微网储能系统多尺度不确定性容量协调优化[J].储能科学与技术,2021,10(06):2235-2243.
LUU, Yinghui.Counting and coordinated optimization of energy storage system for microgrid with multi-scale uncertainty capacity[J]. Energy Storage Science and Technology, 2021, 10(06): 2235-2243.
[35] 王尚斌,苑丽伟,方莹,等.计及新能源波动的分布式储能分层控制策略[J].山东电力技术,2024,51(09): 74-84.
WANG Shangbin, YUAN Liwei, FANG Ying, et al.Hierarchical control strategy of distributed energy storage taking into account new energy fluctuation[J]. Shandong Power Technology,2024,51(09): 74-84.