Integrated energy multi-objective optimization based on PARETO-GWO considering demand response

2022 4th International Conference on Electrical Engineering and Control Technologies (CEECT) Pub Date : 2022-12-01 DOI:10.1109/CEECT55960.2022.10030723

Tengfei Wu, D. Peng, Chunmei Xu, Danhao Wang

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Abstract

Under the background of “double carbon”, in order to effectively improve the energy utilization of regional integrated energy system (RIES), reduce carbon emissions, and improve the flexibility of system operation, this paper proposes a multi-objective optimization model based on PARETO-GWO and considering demand response RIES. Firstly, the modeling is carried out for RIES containing cooling, heating and electricity. Then a demand response model containing transferable, curtailable and replaceable thermal and electric loads is established. Finally, by intro-ducing external population Archive library and Pareto-based non-dominated solution GWO algorithm to obtain mul-ti-scenario operation strategies, the impact of demand response on RIES multi-objective optimization and power bias of units with different operation strategies are analyzed and demonstrated, and it is verified that multi-objective opti-mization can achieve more effective unification of system operation cost and carbon emission than single-objective scheduling.

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考虑需求响应的PARETO-GWO能源多目标综合优化

在“双碳”背景下，为了有效提高区域综合能源系统(RIES)的能源利用率，减少碳排放，提高系统运行的灵活性，本文提出了一种基于PARETO-GWO并考虑需求响应的RIES多目标优化模型。首先，对含冷、热、电的RIES系统进行建模。在此基础上，建立了包含可转移、可缩减和可替换的热、电负荷的需求响应模型。最后，通过引入外部人口档案库和基于pareto的非支配解GWO算法获得多场景运行策略，分析论证了需求响应对不同运行策略下机组的RIES多目标优化和功率偏差的影响，验证了多目标优化比单目标调度能更有效地实现系统运行成本和碳排放的统一。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 4th International Conference on Electrical Engineering and Control Technologies (CEECT)

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