考虑电动汽车参与韧性提升的配电网状态平滑切换控制策略

doi:10.12204/j.issn.1000-7229.2024.05.004

电力建设 ›› 2024, Vol. 45 ›› Issue (5): 29-36.doi: 10.12204/j.issn.1000-7229.2024.05.004

• 新型电力系统韧性基础理论与关键技术·栏目主持许寅教授、时珊珊高工、魏韡副教授· • 上一篇下一篇

考虑电动汽车参与韧性提升的配电网状态平滑切换控制策略

马继洋¹(), 蔡永翔²(), 唐巍¹, 张璐¹, 张志刚¹

1.中国农业大学信息与电气工程学院, 北京市 100083
2.贵州电网有限责任公司电力科学研究院, 贵阳市 550002

收稿日期:2023-05-24 出版日期:2024-05-01 发布日期:2024-04-29
通讯作者: 蔡永翔(1991),男,博士,工程师,主要研究方向为中低压配电网运行控制、直流配电网改造,E-mail:lpscaiyx@163.com。
作者简介:马继洋(1998),男,硕士研究生,主要研究方向为电动汽车充放电预测,E-mail:645909656@qq.com;
唐巍(1971),女,博士,教授,博士生导师,主要研究方向为智能配电网规划与运行控制、柔性配电技术与综合能源系统;
张璐(1990),男,博士,副教授,主要研究方向为配电网规划与优化运行;
张志刚(1998),男,硕士研究生,主要研究方向为配电网规划与运行控制。
基金资助:
国家自然科学基金面上项目(51977211)

Enhancing Distribution Network Resilience: Electric Vehicle Integration in Seamless State Switching Strategy

MA Jiyang¹(), CAI Yongxiang²(), TANG Wei¹, ZHANG Lu¹, ZHANG Zhigang¹

1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
2. Electric Power Research Institute of Guizhou Power Grid Co., Ltd., Guiyang 550002, China

Received:2023-05-24 Published:2024-05-01 Online:2024-04-29
Supported by:
National Natural Science Foundation of China(51977211)

摘要/Abstract

摘要：

在极端灾害发生后电动汽车(electric vehicle,EV)可作为移动电源给负荷供电,从而支撑配电网韧性提升。针对配电网故障发生不可预见、正常态和故障态调度模型切换导致调度指令不稳定问题,文章研究了运行状态平滑切换的EV参与配电网韧性提升策略。基于EV状态和连接方式的二进制变量建立线性化EV时空动态模型,能适应EV灵活调度算力大的需求。考虑EV和交通网不确定性因素,建立基于交通网和配电网信息实时滚动更新的正常态和故障态统一调度模型,正常态以经济性和韧性最优为目标,故障态以韧性最优为目标,通过引入状态表征参数实现两种状态间平滑切换。算例仿真表明,该策略在不影响精度的情况下显著降低了计算量,有助于实现配电网最优韧性恢复和状态平稳过渡。

关键词: 配电网, 电动汽车, 韧性, 平滑切换, 运行控制

Abstract:

In the aftermath of extreme disasters, electric vehicles (EV) can serve as mobile power sources, bolstering the resilience of distribution networks by supplying power to critical loads. To address the challenge of dispatching instruction instability stemming from unforeseeable faults, alongside the need for seamless switching between normal and fault state scheduling models in distribution networks, this study explores the integration of EVs into resilience enhancement strategies, with smooth switching of the running state. Based on the normalization of binary variables representing the EV state and connection mode, a linearized EV spatiotemporal dynamic model is developed, meeting the power requirements for large flexible EV scheduling computations. Considering the uncertainty factors inherent in EVs and transportation networks, a unified scheduling model encompassing both normal and fault states is formulated. This model relies on real-time rolling updates of information from both the transportation and distribution networks. In the normal state, the objective is to optimize economy and resilience, while the fault state aims at solely optimizing resilience. The seamless switching between these two states is realized through the introduction of state characterization parameters. The simulation results demonstrate that the proposed strategy significantly reduces computational overhead without compromising accuracy, thereby facilitating optimal resilience recovery and smooth transitions within the distribution network.

Key words: distribution network, electric vehicle, toughness, smooth switching, operation control

中图分类号:

TM712

马继洋, 蔡永翔, 唐巍, 张璐, 张志刚. 考虑电动汽车参与韧性提升的配电网状态平滑切换控制策略[J]. 电力建设, 2024, 45(5): 29-36.

MA Jiyang, CAI Yongxiang, TANG Wei, ZHANG Lu, ZHANG Zhigang. Enhancing Distribution Network Resilience: Electric Vehicle Integration in Seamless State Switching Strategy[J]. ELECTRIC POWER CONSTRUCTION, 2024, 45(5): 29-36.

图/表 13

图1 最佳充放电停车点示意图

Fig.1 Schematic diagram of the optimal charging and discharging parking point

图2 正常态和故障态切换流程

Fig.2 Scheduling process of normal state and fault state

图3 IEEE 33节点辐射状配电系统

Fig.3 IEEE 33-node radiant distribution system

图4 负荷功率预测值

Fig.4 The predicted power of the load

图5 风机功率预测值

Fig.5 The predicted power of the wind turbine

图6 光伏功率预测值

Fig.6 The predicted power of the photovoltaic

图7 正常态网损

Fig.7 Normal state network loss

图8 配电网解列

Fig.8 Distribution network decomposition

图9 灾中网损

Fig.9 Extreme disaster network loss

图10 有无EV参与调度的风光发电功率

Fig.10 The wind and PV power with or without EV

图11 灾后网损

Fig.11 The network loss after a disaster

表1 正常态和故障态下不同EV模型耗时

Table 1 Calculation time of different EV models in normal and fault states

表2 两种状态切换前后总时长对比

Table 2 Comparison of total duration before and after switching between two states

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考虑电动汽车参与韧性提升的配电网状态平滑切换控制策略

Enhancing Distribution Network Resilience: Electric Vehicle Integration in Seamless State Switching Strategy

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