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Optimization Method for Power Grid Resource Allocation Based on Multiple User Needs and Game Model

Published: 31 July 2024 Publication History

Abstract

With the expansion of the power system scale and the diversification of user needs, the optimization of power grid resource allocation has become a key issue in improving the efficiency of the power system and meeting user needs. Therefore, a power grid resource allocation optimization method based on multiple user needs and game models is proposed. Obtain user electricity consumption and user type information through ARIMA model and decision tree algorithm to determine user needs. Introduce a game model to describe the competition and cooperation relationships between different participants, construct a resource allocation model, and introduce chaotic particle swarm optimization algorithm to obtain the optimal solution during the model solving process, achieving optimization of power grid resource allocation. The experimental results show that this method can achieve efficient allocation of power grid resources, improve energy utilization efficiency and renewable energy consumption capacity.

References

[1]
LIN Lingxue;LIAO Biying;GUAN Lin. Optimal Generation Configuration Methods for Standalone Microgrids Based on Wind and Solar Resources Characteristics[J]. Journal of South China University of Technology(Natural Science Edition), 2021, 49(07):103-115.
[2]
ZHU Hanchao;MA Rui. Optimal configuration method of CCHP microgrid considering demand side management[J]. Power System Protection and Control, 2019, 47(02):139-146.
[3]
GAO Xueping;FU Lijun;JI Feng;ZHANG Yan;HUANG Meixian. Research on optimal configuration of energy storage in integrated power system with pulse load[J]. Journal of National University of Defense Technology, 2022, 44(06):81-88.
[4]
SHE Wei;YANG Xiaoyu;TIAN Zhao;MA Jianhong;LI Zhengze;LIU Wei. Decentralization Configuration Method of Power Resources Based on User Preference[J]. Automation of Electric Power Systems, 2019, 43(13):98-104+138.
[5]
ZHAO Nan;WANG Beibei. Optimal Allocation of Distributed Generation in Distribution System Considering Multi-type Demand Response Resources[J]. Electric Power, 2019, 52(11):51-59+67.
[6]
NIU Huanna;QIAN Li;YANG Lu;WANG Kun. Optimal allocation of flexible resources in distribution network considering cost of flexible auxiliary services[J]. Electric Power Automation Equipment, 2021, 41(10):52-59.
[7]
XIAO Wei;YIN Zhixiang;YE Zi;YANG Jing. On Multiple Constraint and Multiple Objective Household Energy Management Method Based on Game Theory[J]. Journal of Hunan University of Science And Technology:Natural Science Edition, 2022, 37(03):68-76.
[8]
Wang Jidong;Song Qiming;Li Jifang. Optimal operation of microgrid based on multi-agent chaotic particle swarm optimization[J]. Renewable Energy Resources, 2022, 40(04):513-519.
[9]
ZHANG Guobin;ZHANG Jiahui;GUO Ruijun;GAO Zhengping;NIU Yuguang. An Adaptive Chaotic Particle Swarm Optimization Based Scheduling Strategy for Combined Cooling,Heating and Power System[J]. Modern Electric Power, 2020, 37(06):551-558.
[10]
ZUO Shuai;CUI Shuang-xi;ZHENG Hao;MENG Guang-ming. Integrated Energy Optimal Dispatch Considering Wind Power Consumption and Cascade Utilization[J]. Computer Simulation, 2022, 39(09):125-129+455.

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  1. Optimization Method for Power Grid Resource Allocation Based on Multiple User Needs and Game Model

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

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    Published: 31 July 2024

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