| 引用本文: | 程 杉,钟仕凌,尚冬冬,魏康林,王 灿.考虑电动汽车时空负荷分布特性的主动配电网动态重构[J].电力系统保护与控制,2022,50(17):1-13.[点击复制] |
| CHENG Shan,ZHONG Shiling,SHANG Dongdong,WEI Kanglin,WANG Can.Dynamic reconfiguration of an active distribution network considering temporal and spatialload distribution characteristics of electric vehicles[J].Power System Protection and Control,2022,50(17):1-13[点击复制] |
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| 摘要: |
| 实现电动汽车(Electric Vehicle, EV)规模化发展并与电网双赢的关键问题之一是如何提高EV充电负荷的预测准确性，并保证含大规模EV充电负荷的配电网运行的安全性和经济性。考虑EV时空负荷分布特性，建立了主动配电网动态重构与有功、无功联合优化数学模型，并给出了其求解方法。首先，根据出行链技术和马尔可夫决策理论，考虑天、人、路对EV的影响因素，构建了EV单位能耗模型和充电负荷的时空分布预测模型。其次，提出考虑储能系统、有载分接开关、投切电容器组、静止无功补偿装置和动态重构多种主动管理措施，计及经济、技术指标和各设备、系统运行约束，建立了含EV的主动配电网动态重构与有功-无功联合优化数学模型。然后，为了提高所构建模型的求解效率，通过二阶锥松弛和变量乘积线性化方法将非凸等式约束和非线性不等式约束线性化后，将原始的混合整数非线性规划问题转化为易求解计算的混合整数二阶锥问题。最后，基于修改的IEEE33节点系统进行仿真实验和对比分析，结果验证了所提方法的有效性和优越性。 |
| 关键词: 电动汽车 时空分布 主动配电网 二阶锥松弛 动态重构 |
| DOI：DOI: 10.19783/j.cnki.pspc.211439 |
| 投稿时间：2021-10-26修订日期：2022-01-17 |
| 基金项目:国家自然科学基金项目资助(52107108)；电力系统智能运行与安全防御宜昌市重点实验研究项目资助(2020DLXY01)；智能终端四川省重点实验室开放基金项目资助(SCITLAB-1009) |
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| Dynamic reconfiguration of an active distribution network considering temporal and spatialload distribution characteristics of electric vehicles |
| CHENG Shan,ZHONG Shiling,SHANG Dongdong,WEI Kanglin,WANG Can |
| (1. Yichang Key Laboratory of Intelligent Operation and Security Defense of Power System (China Three Gorges University),
Yichang 443002, China; 2. China Intelligent Terminal Key Laboratory of Sichuan Province (Yibin University), Yibin 644000, China) |
| Abstract: |
| To improve the accurate prediction of electric vehicle (EV) charging load and ensure the stability and economy of the distribution network penetrated with a large scale of EV is one of the key issues in realizing a win-win situation for the EV and distribution network. In this paper, a combined optimization model of active and reactive power for active distribution network reconstruction and its solution method are established considering the characteristics of EV temporal and spatial load distribution. First, from travel chain technology and Markov decision theory, and considering the influence of weather, the EV owner and traffic, an EV unit energy consumption model and the spatial-temporal load model of charging load are constructed. Secondly, considering all of the energy storage system, on-load tap changer, capacitor banks, static var compensation, dynamic reconfiguration of various active management measures, economic indicators and operation constraints, a dynamic reconfiguration and active reactive-power optimization model of an EV active distribution network are established. Then, to improve solution efficiency, the original model is transformed into a mixed integer second order cone model using second-order cone relaxation and variable product linearization methods. Finally, an improved IEEE33 system is used for simulation analysis to verify the effectiveness and superiority of the proposed method.
This work is supported by the National Natural Science Foundation of China (No. 52107108). |
| Key words: electric vehicle spatial-temporal distribution active distribution network second-order cone relaxation dynamic restructuring |
