| 引用本文: | 沈国辉,陈 光,赵 宇,等.基于双目标分层优化和TOPSIS排序的电动汽车有序充电策略[J].电力系统保护与控制,2021,49(11):115-123.[点击复制] |
| SHEN Guohui,CHEN Guang,ZHAO Yu,et al.Orderly charging optimization strategy of an electric vehicle based on double objective hierarchical optimization and TOPSIS ranking[J].Power System Protection and Control,2021,49(11):115-123[点击复制] |
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| 基于双目标分层优化和TOPSIS排序的电动汽车有序充电策略 |
| 沈国辉1,2,陈光1,2,赵宇1,2,李晓光1,2,耿爱国1,2,袁浩1,2,刘方1,2 |
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| (1.南瑞集团有限公司(国网电力科学研究院有限公司)，江苏 南京 211106;
2.北京科东电力控制系统有限责任公司，北京 100192) |
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| 摘要: |
| 针对当前有序充电策略控制目标相对单一无法满足用户多方面需求的现状，提出了基于双目标分层优化的有序充电控制策略。首先，建立了主站与能源控制器分层协同控制的整体架构。其次，将控制用户充电成本作为第一层优化目标，将减小电网负荷波动作为第二层优化目标，完成双目标分层优化算法模型的设计。最后，设计了台区负荷越限时刻电动汽车充电功率动态调整的实时控制策略。从用户充电行为特征出发，采用TOPSIS排序方法确定用户的充电需求优先级，为有序充电策略的充电计划调度提供依据。电动汽车有序充电策略已投入运行于郑州等地小区，设计成果既节约用户充电成本，又实现电力负荷削峰填谷的目标，验证有序充电策略的实用性和有效性。 |
| 关键词: 电动汽车 有序充电 分层优化 实时控制策略 TOPSIS排序 |
| DOI：DOI: 10.19783/j.cnki.pspc.200955 |
| 投稿时间：2020-10-11修订日期：2020-11-20 |
| 基金项目:国家电网公司科技项目资助“电动汽车集群优化虚拟储能与负荷控制关键技术研究及示范应用”(5418- 202018247A-0-0-00) |
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| Orderly charging optimization strategy of an electric vehicle based on double objective hierarchical optimization and TOPSIS ranking |
| SHEN Guohui1,2,CHEN Guang1,2,ZHAO Yu1,2,LI Xiaoguang1,2,GENG Aiguo1,2,YUAN Hao1,2,LIU Fang1,2 |
| (1. NARI Group Corporation (State Grid Electric Power Research Institute Co., Ltd., Nanjing 211106, China;
2. Beijing Kedong Electric Power Control System Corporation Limited, Beijing 100192, China) |
| Abstract: |
| The control target of the current orderly charging strategy is relatively single, and cannot meet the needs of users in many aspects. Thus this paper proposes an orderly charging control strategy based on double objective hierarchical optimization. First, it establishes the overall architecture of hierarchical collaborative control between master station and energy controller. Secondly, the control of user charging cost is taken as the first level optimization objective, and the reduction of grid load fluctuation is taken as the second level objective to complete the design of double objective hierarchical optimization strategy. Last, it designs a real time control strategy to adjust the charging power of the charging pile when the load exceeds the limit. At the same time, based on the characteristics of user charging behavior, it uses the TOPSIS ranking method to determine the priority of user charging demand. This provides the basis for charging planning and scheduling of an orderly charging strategy. In this paper, the optimization strategy for orderly charging of electric vehicles has been put into operation in Zhengzhou and other districts. The design shows that the goal of cost savings and peak load shifting can be achieved, verifying the practicability and effectiveness of the charging strategy.
This work is supported by the Science and Technology Project of State Grid Corporation of China “Key Techniques Research and Demonstration Application of Virtual Energy Storage and Load Control of EV Clusters Optimization” (No. 5418-202018247A-0-0-00). |
| Key words: electric vehicle orderly charging hierarchical optimization real time control strategy TOPSIS ranking |
