| 引用本文: | 王彬,郭文鑫,李世明,等.基于短期预测信息和长期值函数近似的大规模电动汽车实时随机优化调度算法[J].电力系统保护与控制,2019,47(24):47-56.[点击复制] |
| WANG Bin,GUO Wenxin,LI Shiming,et al.Real-time charging optimization for large-scale electric vehicles based on short term forecast information and long term value function approximation[J].Power System Protection and Control,2019,47(24):47-56[点击复制] |
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| 摘要: |
| 针对大规模电动汽车(Electric Vehicle, EV)和可再生能源接入背景下主动配电网的实时随机调度问题，提出了一种结合短期预测信息和长期值函数近似的双层实时调度模型。为应对大量EV接入后的维数灾问题，首先提出双层调度框架，上层建立EV集群模型，下层根据EV特性提出功率分配算法对每辆EV制定充电计划，实现上层集群指令的完全消纳并满足各EV充电的需求。同时，为应对EV行为、实时电价及可再生能源出力不确定性的问题，实时优化时采用预测算法预测短期内未来接入的EV行为、可再生能源最大出力与实时电价，并通过值函数近似评估短期决策后系统的值函数，从而实现EV集群充电计划、可再生能源调度计划与购电计划的实时分阶段决策。仿真算例表明，所提模型可以实现大规模EV接入下主动配电网的实时随机调度，同时具备良好的鲁棒性。 |
| 关键词: 电动汽车 实时优化 随机优化 |
| DOI：10.19783/j.cnki.pspc.190158 |
| 投稿时间：2019-02-12修订日期：2019-06-10 |
| 基金项目:中国南方电网有限责任公司科技项目资助(GDKJXM20172831) |
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| Real-time charging optimization for large-scale electric vehicles based on short term forecast information and long term value function approximation |
| WANG Bin,GUO Wenxin,LI Shiming,ZHAO Ruifeng,LI Bo,LU Jiangang,PAN Zhenning |
| (Electric Dispatch and Control Center, Guangdong Power Grid Co., Ltd., Guangzhou 510060, China;College of Electric Power, South China University of Technology, Guangzhou 510640, China) |
| Abstract: |
| This paper proposes a hierarchical framework for the real-time dispatch of Active Distribution Networks (ADN) with high penetration of Electric Vehicles (EVs) and renewable energy, based on near term forecast information and long term value function approximation. To solve the curse of dimensionality after large-scale EVs access, in the upper layer, an equivalent EV cluster model is developed; while in the lower layer, the power allocation algorithm considering the diverse characteristics of EVs is proposed to make specific strategies for each EV while tracking the upper layer instruction. To handle the stochastic EV charging behaviors, maximum output of renewable energy and real-time price, the near term forecast information of those stochastic factors are considered in the proposed method. Further, value function approximations are adopted to evaluate the value function of the system after the near term decision, by which way the real-time dispatches of EV clusters, renewable energy, and electricity purchase can be given stage by stage. Simulation cases verify the effectiveness and the robustness of the proposed model in the real-time coordinated dispatch of ADN with high penetration of EVs. This work is supported by Science and Technology Project of China Southern Power Grid Co., Ltd. (No. GDKJXM20172831). |
| Key words: large-scale EVs real-time optimization stochastic optimization |
