research-article
Authors: Chunsheng Chen, Guang Tian, Lei Yang, Yang Yang
PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
Pages 208 - 212
Published: 31 July 2024 Publication History
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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.
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Index Terms
Optimization Method for Power Grid Resource Allocation Based on Multiple User Needs and Game Model
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Published In
PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
January 2024
969 pages
ISBN:9798400716638
DOI:10.1145/3674225
Copyright © 2024 ACM.
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 [emailprotected].
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 31 July 2024
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PEAI 2024
PEAI 2024: 2024 International Conference on Power Electronics and Artificial Intelligence
January 19 - 21, 2024
Xiamen, China
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