| 引用本文: | 张聪,许晓慧,孙海顺,等.基于自适应遗传算法的规模化电动汽车智能充电策略研究[J].电力系统保护与控制,2014,42(14):19-24.[点击复制] |
| ZHANG Cong,XU Xiao-hui,SUN Hai-shun,et al.Smart charging strategy of large-scale electric vehicles based on adaptive genetic algorithm[J].Power System Protection and Control,2014,42(14):19-24[点击复制] |
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| 摘要: |
| 电动汽车充电负荷在时空上具有不确定性，大规模电动汽车无序充电会导致配电网峰值负荷超过设备允许极限，给电网运行带来严重影响。以平滑配电网日负荷曲线为优化目标，建立了考虑各电动汽车用户充电需求约束的规模化电动汽车智能充电控制策略求解模型，并采用自适应遗传算法求解。以IEEE33节点配电网系统为例，基于蒙特卡洛随机模拟规模化电动汽车并网场景，对比研究了无序充电和智能充电两种控制模式下电动汽车负荷对配电网的影响，验证了利用所提方法对实现平滑负荷的有效性。 |
| 关键词: 蒙特卡洛模拟 自适应遗传算法 智能充电 电动汽车 配电系统 |
| DOI：10.7667/j.issn.1674-3415.2014.14.004 |
| 投稿时间：2014-04-29修订日期：2014-07-08 |
| 基金项目:国家电网公司基础性前瞻性科技项目资助（NY71-13-014） |
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| Smart charging strategy of large-scale electric vehicles based on adaptive genetic algorithm |
| ZHANG Cong,XU Xiao-hui,SUN Hai-shun,ZHOU Xin |
| (State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;China Electric Power Research Institute, Beijing 100000, China) |
| Abstract: |
| Electric vehicles connected to the grid exhibits strong uncertainty in time and space. Dumb charging of large-scale electric vehicles might have adverse impacts on distribution system by causing much high peak load exceeding the supply limits of devices. This paper proposes a model for smart charging control of electric vehicles, which takes smoothing the daily load profile as the objective function and fully accounts the EV owner’s requirement. An adaptive genetic algorithm is applied for solving the model. Using the IEEE 33-bus case as the test systems, scenarios of EVs integration are simulated by Monte Carlo stochastic methods. Smart charging strategy is obtained using the proposed model and method. By comparing with the load profile under dumb charging, the validity of the proposed model is proved. |
| Key words: Monte Carlo simulation adaptive genetic algorithm smart charging electric vehicles distribution networks |
