Paper
31 May 2023 Study on the stability of power market regulation under the multi-user coupling demand response
Yufang Liu, Ping Huang, Zeyang Liu, Lin Yang, Di Huang
Author Affiliations +
Proceedings Volume 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023); 127041E (2023) https://doi.org/10.1117/12.2680213
Event: 8th International Symposium on Advances in Electrical, Electronics and Computer Engineering (ISAEECE 2023), 2023, Hangzhou, China
Abstract
In order to guide the demand-side electricity consumption behaviour of users, after investigating the whole social electricity consumption load of a county in southern China, according to the demand response, time-of-use electricity price and the reality of China's electricity market, this paper adopts the fast non-dominated sorting genetic algorithm with elite strategy to conduct a more in-depth optimization study on the demand-side management measures of three different users, and the conclusions are as follows: Combined with the practical problems in the electricity market transaction, a mathematical model with the minimum peak-valley difference of the load curve and the maximum power consumption comfort as the objective function is built, and the bundle of variables is established. The optimization results show that the multi-objective optimization on the demand side is slightly insufficient in smoothing the load curve, but considering the comfort of users' electricity consumption, the multi-objective optimization will improve its comprehensive performance and have stronger practicability, which can play a guiding role in the demand response behaviour of users and power trading in the power market, and provide a theoretical basis for actual trading.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yufang Liu, Ping Huang, Zeyang Liu, Lin Yang, and Di Huang "Study on the stability of power market regulation under the multi-user coupling demand response", Proc. SPIE 12704, Eighth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2023), 127041E (31 May 2023); https://doi.org/10.1117/12.2680213
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KEYWORDS
Power consumption

Mathematical optimization

Genetic algorithms

Statistical analysis

Carbon

Data modeling

Mathematical modeling

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