Economic Optimization Operation Strategy Of Microgrid Based On Behavioral Economics Theory

TAO Changhe; LU Ling; ZHANG Yu; WANG Can; LIU Yuzheng; HE Jintao; YANG Daiqiang; WANG Mingchao; CHENG Bentao

PDF(1162 KB)

Electric Power Construction ›› 2025

Economic Optimization Operation Strategy Of Microgrid Based On Behavioral Economics Theory

TAO Changhe¹, LU Ling¹, ZHANG Yu², WANG Can¹, LIU Yuzheng¹, HE Jintao¹, YANG Daiqiang¹, WANG Mingchao¹, CHENG Bentao¹

Author information +

History +

Abstract

[Objective] With the continuous increase in the proportion of renewable energy in the overall energy mix, the inherent uncertainty and variability in power generation pose challenges to the stable operation and economic efficiency of microgrid systems. Demand response strategies emerge as crucial measures to enhance the integration capacity of renewable energy in microgrids. [Methods] Firstly, to optimize the fitting ability of the demand response model to user behavior, this paper constructs a demand response model based on the endowment effect by deeply analyzing the psychological factors of users in the process of participating in demand response. Then, based on this demand response model, an economic optimization operation strategy for microgrids is proposed. Considering the comprehensive satisfaction of users and the operation cost, a microgrid economic operation model is established. The Pareto optimization technology combining -constraint and relaxation factor is adopted to solve the operation model, and the economic optimization operation of the microgrid is achieved under the constraints of equipment operation power and grid interaction. [Results] The simulation analysis verifies the effectiveness of the demand response model proposed in this paper in improving the economic benefits of microgrids and its superiority over traditional demand response models, while also enhancing user satisfaction. [Conclusions] The demand response model based on behavioral economics theory proposed in this paper can more accurately describe user demand response behavior. The introduction of the endowment effect theory provides a new perspective for understanding and predicting consumers' responses to energy price changes, enabling microgrid operators to more accurately adjust power supply strategies to cope with demand fluctuations and market changes. The demand response model proposed in this paper can effectively promote user participation in peak shaving and valley filling, and reduce the operation cost of the system.

Key words

microgrid / demand response / behavioral economics / economic optimization operation

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

TAO Changhe, LU Ling, ZHANG Yu, WANG Can, LIU Yuzheng, HE Jintao, YANG Daiqiang, WANG Mingchao, CHENG Bentao. Economic Optimization Operation Strategy Of Microgrid Based On Behavioral Economics Theory[J]. Electric Power Construction. 2025

References

[1] 樊晓伟,王瑞妙,杨海峰,等.计及源荷不确定的综合能源微电网集群优化运行[J].电力建设,2024,45(08):128-139.
FAN Xiaowei,WANG Ruimiao,YANG Haifeng,et al.Optimization Operation of Integrated Energy Microgrid Cluster Considering Source-Load Uncertainty[J]. Electric Power Construction,2024,45(08):128-139.
[2] 王灿,张雪菲,凌凯,等.基于区间概率不确定集的微电网两阶段自适应鲁棒优化调度[J].中国电机工程学报,2024,44(05):1750-1764.
Wang Can, Zhang Xuefei, Ling Kai, et al.Two-stage Adaptive Robust Optimal Scheduling Based on the Interval Probability Uncertainty Set for Microgrids[J]. Proceedings of the CSEE,2024,44(05):1750-1764.
[3] 张晓佳,王灿,张佳恒,等.基于多能需求响应与改进BiLSTM的综合能源系统负荷预测[J].电力建设,2025,46(04):113-125.
ZHANG Xiaojia, WANG Can, ZHANG Jiaheng, et al.Integrated Energy System Load Forecasting Based on Multi-energy Demand Response and Improved BiLSTM[J]. Electric Power Construction, 2025,46(04):113-125.
[4] 程江洲,胡敏,刘闯.考虑需求响应和用户满意度的主动配电网优化调度[J].全球能源互联网,2024,7(04):443-453.
CHENG Jiangzhou, HU Min, LIU Chuang.Optimal Dispatching of Active Distribution Network Considering Demand Response and Customer Satisfaction[J]. Journal of Global Energy Interconnection, 2024,7(04):443-453.
[5] 左超文,王樊云,陈洁.考虑需求响应的光热电站热电联供型微网分层优化调度[J].分布式能源,2024,9(02):63-73.
ZUO Chaowen, WANG Fanyun, CHEN Jie.Hierarchical Optimization Scheduling of Combined Heat and Power Microgrid for Photothermal Power Station Considering Demand Response[J]. Distributed Energy, 2024,9(02):63-73.
[6] 王雅雯. 基于需求侧响应的风光储微电网经济优化研究[J].广东电力,2023,36(09):10-16.
WANG Yawen.Research on Economic Optimization of Wind and Solar Energy Storage Microgrid Based on Demand Response[J]. Guangdong Electric Power, 2023,36(09):10-16.
[7] 李怡晨,李强,李宏伟,等.融合阶梯式碳交易与需求响应的源荷协同优化[J].广东电力,2024,37(04):71-79.
LI Yichen, LI Qiang, LI Hongwei, et al.Source-load Collaborative Optimization Combining Stepwise Carbon Trading and Demand response[J]. Guangdong Electric Power, ,2024,37(04):71-79.
[8] 郭国栋,徐倩雯,龚雁峰.考虑需求响应的互联交直流混合微电网的分布式经济调度模型[J].电测与仪表,2023,60(05):116-125+153.
GUO Guodong, XU Qianwen, GONG Yanfeng. A distributed economic dispatching model for networked hybrid AC/DC microgrids considering demand response[J]. Electrical Measurement & Instrumentation, 2023,60(05):116-125+153.
[9] 李逸超,刘伟峰,施泉生.块调度模式下的智慧小区自动需求响应模型[J].电测与仪表,2024,61(03):50-57.
LI Yichao, LIU Werifeng, SHI Quansheng.Automatic demand response model of intelligent community in block scheduling model[J]. Electrical Measurement & Instrumentation,2024,61(03):50-57.
[10] 樊伟,李旭东,王尧,等.新型电力系统灵活性资源聚合两阶段调度优化模型[J].电力建设,2023,44(02):25-37.
FAN Wei,LI Xudong,WANG Yao, et al.Two-Stage Scheduling Optimization Model of Flexible Resource Aggregation in New Power System[J]. Electric Power Construction,2023,44(02):25-37.
[11] Gamil M, Senjyu T, Takahashi H, et al.Optimal multi-objective sizing of a residential microgrid in Egypt with different ToU demand response percentages[J]. Sustainable Cities and Society, 2021, 75: 103293.
[12] 赵洪山, 赵航宇, 侯杰群等. 需求响应对配电网供电可靠性影响分析[J]. 电力自动化设备, 2017, 37(01): 8-14.
ZHAO Hongshan, ZHAO Hangyu, HOU Jiequn, et al.Effect of demand response on supply reliability of distribution network[J]. Electric Power Automation Equipment, 2017, 37(01): 8-14.
[13] 张媛媛. 考虑需求响应的热电联供型微网优化调度研究[D]. 青岛:青岛大学, 2021.
ZHANG Yuanyuan.Research on Optimal Scheduling of Combined Heat and Power MicroGrids Considering Demand Response[D]. Qingdao:Qingdao University,2021
[14] Nikzad M, Mozafari B.Reliability assessment of incentive-and priced-based demand response programs in restructured power systems[J]. International Journal of Electrical Power & Energy Systems, 2014, 56:83-96.
[15] Chai Y, Xiang Y, Liu J, et al.Incentive-based demand response model for maximizing benefits of electricity retailers[J]. Journal of Modern Power Systems and Clean Energy, 2019, 7(06): 1644-1650.
[16] 马瑞真,张新燕,章攀钊,等.计及需求响应与主从博弈的微电网低碳优化调度[J].现代电子技术,2023,46(07):121-127.
MA Ruizhen, ZHANG Xinyan, ZHANG Panzhao,et al.Low-carbon optimal dispatch of micro-grid considering demand response and Stackelberg game[J]. Modern Electronics Technique,2023,46(07):121-127.
[17] 周孟然,王旭,邵帅,等.考虑需求响应和碳排放额度的微电网分层优化调度[J].中国电力,2022,55(10):45-53.
ZHOU Mengran, WANG Xu, SHAO Shuai, et al.Hierarchical Optimal Scheduling of Microgrid Considering Demand Response and Carbon Emission Quota[J]. Electric Power, 2022,55(10):45-53.
[18] 牟颖,薛万磊,汲国强,等.基于对数平均迪氏指数分解的居民生活用电增长特征分析[J].山东电力技术,2024,51(10):44-54.
MUYing,XUE Wanlei,JI Guoqiang, et al.Analysis on the Growth Characteristics of Residential Electricity Consumption Based on Logarithmic Mean Divisa Index Decomposition[J]. Shandong Electric Power, 2024,51(10):44-54.
[19] 王坤,李树旭,李俊杰,等.促进用户负荷特性优化的分时电价机制设计方法[J].山东电力技术,2024,51(04):36-46.
WANG Kun,LI Shuxu,LI Junjie, et al.Design Method for Time-of-use Tariff Mechanism to Promote User Load Characteristics Optimization[J]. Shandong Electric Power, 2024,51(04):36-46.
[20] 沙广林,刘璐,马春艳,等.考虑车网互动的电动汽车有序充电策略[J].供用电,2023,40(10):46-54.
SHA Guanglin, LIU Lu, MA Chunyan, et al.Orderly charging strategy for electric vehicles considering the vehicle-network interaction[J]. Distribution & Utilization,2023,40(10):46-54.
[21] 黄彦璐,胡旭东,林振福,等.考虑峰荷特性的电力系统负荷侧碳排放责任核算方法[J].电力建设,2025,46(02):88-98.
HUANG Yanlu, HU Xudong, LIN Zhenfu, et al.Accounting Method for Carbon Emission Obligation on Load Side of Power System Based on Peak Load Characteristics[J]. Electric Power Construction,2025,46(02):88-98.
[22] 张美霞, 王晓晴, 杨秀, 等. 考虑路网和用户满意度的集群电动汽车主从博弈优化调度策略[J]. 电力系统保护与控制, 2024, 52(03): 1-11.
ZHANG Meixia, WANG Xiaoqing, YANG Xiu, et al.Stackelberg game optimization scheduling strategy for aggregated electric vehicles considering customer satisfaction and the road network[J]. Power System Protection and Control, 2024, 52(03): 1-11.
[23] 陈景文,单茜,王金锋,等.考虑分时电价下需求响应的用户侧储能优化配置[J].陕西科技大学学报,2024,42(04):167-176.
CHENG Jingwen, SHAN Xi, WANG Jinfeng, et al.Optimal configuration of user-side energy storage considering demand response under time of use price[J]. Journal of Shaanxi University of Science & Technology2024,42(04):167-176.
[24] 郭晓利, 赵莹, 曲楠, 等. 基于满意度的户用型微电网多属性需求响应策略[J]. 太阳能学报, 2021, 42(07): 21-27.
GUO Xiaoli, ZHAO Ying, QU Nan, et al.Multi-Attribute Demand Response Strategy Of Household Microgrid Based On Satisfaction[J]. Acta Energiae Solaris Sinica, 2021, 42(07): 21-27.
[25] 唐巍, 高峰. 考虑用户满意度的户用型微电网日前优化调度[J]. 高电压技术, 2017, 43(01): 140-148.
TANG Wei, GAO Feng.Optimal Operation of Household Microgrid Day-ahead Energy Considering User Satisfaction[J]. High Voltage Engineering, 2017, 43(01): 140-148.
[26] 何文华,丁贵立,韩威,等.综合考虑电网碳效益和用户满意度的需求响应激励策略优化模型研究[J].供用电,2023,40(10):95-105.
HE Wenhua, DING Guili, HAN Wei, et al.Optimization model research of demand response incentive strategy considering carbon benefits of power grid and user satisfaction[J]. Distribution & Utilization,2023,40(10):95-105.
[27] 谢郑溶钊,林顺富,沈运帷,等.考虑用户心理的居民社区负荷聚合商优化调度[J].上海电力大学学报,2024,40(02):161-168.
XIE Zhengrongzhao, LIN Shunfu, SHEN Yunwei,et al.Optimal Scheduling of Residential Community Load Aggregator Considering User Psychology[J]. Journal of Shanghai University of Electric Powe,2024,40(02):161-168.
[28] Morewedge C, Giblin C.Explanations of the endowment effect: An integrative review[J]. Trends in Cognitive Sciences, 2015, 19(06): 339-348.
[29] DUPONTYD,LEE SG.The Endowment Effect, Status Quo Bias and Loss Aversion: Rational Alternative Explanation[J].Journal of Risk and Uncertainty,2002,25(1):87-101.
[30] 熊小萍, 杨辉, 蔡义明. 考虑用户禀赋效应和环保意识不确定性的微电网鲁棒优化调度方法[J]. 中国电机工程学报, 2023, 43(21): 8260-8270.
XIONG Xiaoping, YANG Hui, CAI Yiming.Robust Optimal Dispatch Method of Microgrid Considering User Endowment Effect and Environmental Awareness Uncertainty[J]. Proceedings of the CSEE, 2023, 43(21): 8260-8270.
[31] 林瑾. 计及禀赋效应的负荷聚合商需求响应激励策略研究[D]. 北京:华北电力大学, 2023.
LIN Jin.Research on Demand response incentive strategy to the load aggregators considering the customers' endowment effect[D].Beijing: North China Electric Power University,2023.
[32] 彭一海, 刘继春, 刘俊勇. 两级电力市场环境下考虑多类型零售套餐的售电公司购售电策略[J]. 电网技术, 2022, 46(03): 944-957.
PENG Yihai, LIU Jichun, LIU Junyong.Electricity Purchasing and Selling Strategies for Electricity Retailers Considering Multiple Types of Retail Packages in Two Level Electricity Market[J]. Power System Technology, 2022, 46(03): 944-957.
[33] 郭小龙,亢朋朋,田晨,等.考虑碱性电解槽状态转换的风电制-储氢系统优化调度[J].高压电器,2024,60(07):60-68+77.
GUO Xiaolong, KANG Pengpeng, TIAN Chen,et al. Optimal Scheduling of Hydrogen Production-storage System from Wind Power Considering State Transition of Alkaline Electrolyzer[J]. High Voltage Apparatus, 2024,60(07):60-68+77.
[34] 葛磊蛟, 范延赫, 来金钢, 等.面向低碳经济的人工智能赋能微电网优化运行技术[J]. 高电压技术, 2023, 49(06): 2219-2238.
GE Leijiao, FAN Yanhe, LAI Jingang, et al.Artificial Intelligence Enabled Microgrid Optimization Technology for Low Carbon Economy[J]. High Voltage Apparatus, 2023, 49(06): 2219-2238.
[35] 陈将宏,王羲沐,李伟亮,等.采用改进北方苍鹰算法的微电网优化调度研究[J].重庆理工大学学报(自然科学),2024,38(01):281-289.
CHEN Jianghong, WANG Ximu, LI Weiliang, et al.Research on optimal scheduling of microgrid using improved Northern Goshawk algorithm[J] Journal of Chongqing University of Technology( Natural Science) ,2024,38(01):281-289.
[36] 李东东, 陈天旭, 沈运帷, 等. 基于联合虚拟储能系统的海岛微电网协同优化策略[J]. 中国电机工程学报, 2023, 43(20): 7842-7856.
LI Dongdong, CHEN Tianxu, SHEN Yunwei, et al.Collaborative Optimization of Island Microgrid Based on Joint Virtual Energy Storage System Strategy[J]. Proceedings of the CSEE, 2023, 43(20): 7842-7856.
[37] 李整,谭文,秦金磊.一种用于机组组合问题的改进双重粒子群算法[J].中国电机工程学报,2012,32(25):189-195+26.
LI Zheng, TAN Wen, QIN Jinlei. An Improved Dual Particle Swarm Optimization Algorithm for Unit Commitment Problem[J]. Proceedings of the CSEE, 2012,32(25):189-195+26.
[38] Yang Z, Ghadamyari M, Khorramdel H, et al.Robust multi-objective optimal design of islanded hybrid system with renewable and diesel sources/stationary and mobile energy storage systems[J]. Renewable and Sustainable Energy Reviews, 2021, 148: 111295.
[39] Mohseni-Bonab S, Rabiee A.Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: a stochastic approach. Renew Energy 2016, 85: 598-609.
[40] 李国荣. 基于用户需求响应的分时电价优化研究[D].南京:南京邮电大学,2022.
LI Guorong.Research on time-of-use price optimization based on user's demand response[D]. Nanjing:Nanjing University of Posts and Telecommunications,2022.