考虑光伏消耗和通信灵活性的 5G 基站虚拟电站多目标区间规划

IF 2.4 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Smart Grid Pub Date : 2024-07-23 DOI:10.1049/stg2.12178
Dawei Zhang, Xudong Cui, Changbao Xu, Shigao Lv, Lianhe Zhao
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引用次数: 0

摘要

5G基站的大规模部署给配电网的经济运行带来了严峻的挑战,此外,作为一种新型的可调负荷,其运行的灵活性也为促进光伏的消纳和利用提供了潜在的途径。本文提出了一种虚拟电站与配电网的多目标区间协同规划方法。首先,在深入分析基站运行特性和通信负荷传输特性的基础上,构建了参与蜂窝式呼吸需求响应模型的5G虚拟电站基站。针对系统经济性与环境性能之间的内在矛盾,以系统投资和运行成本最低、碳排放最少为优化目标,建立了虚拟电站与配电网协同规划的多目标区间优化模型。将建立的模型转化为确定性优化问题,并采用 NSGA-II 算法进行求解。修改后的 IEEE-33 节点系统被用于案例分析,以分析不同规划方案和响应特性对系统经济性的影响。计算结果验证了所提方法的有效性。
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Multi‐objective interval planning for 5G base station virtual power plants considering the consumption of photovoltaic and communication flexibility
Large‐scale deployment of 5G base stations has brought severe challenges to the economic operation of the distribution network, furthermore, as a new type of adjustable load, its operational flexibility has provided a potential way to promote the consumption and utilization of photovoltaic. In this paper, a multi‐objective interval collaborative planning method for virtual power plants and distribution networks is proposed. First, on the basis of in‐depth analysis of the operating characteristics and communication load transmission characteristics of the base station, a 5G base station of virtual power plants participating in the cellular respiratory demand response model is constructed. In view of the inherent contradiction between system economy and environmental performance, a multi‐objective interval optimization model for collaborative planning of virtual power plants and distribution networks is established with the lowest system investment and operating costs and the lowest carbon emissions as the optimization goals. The established model is transformed into a deterministic optimization problem, which is solved by NSGA‐II algorithm. The modified IEEE‐33 node system is used in the case analysis to analyse the impact of different planning schemes and response characteristics on the system economy. The calculation results verify the effectiveness of the proposed method.
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来源期刊
IET Smart Grid
IET Smart Grid Computer Science-Computer Networks and Communications
CiteScore
6.70
自引率
4.30%
发文量
41
审稿时长
29 weeks
期刊最新文献
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