| 引用本文: | 赵玉,徐天奇,李琰,等.基于分时电价的电动汽车调度策略研究[J].电力系统保护与控制,2020,48(11):92-101.[点击复制] |
| ZHAO Yu,XU Tianqi,LI Yan,et al.Research on electric vehicle scheduling strategy based on time-shared electricity price 2. Anhui Jinzhai Pumped Storage Power Company Limited, Lu’an 237333, China)[J].Power System Protection and Control,2020,48(11):92-101[点击复制] |
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| 摘要: |
| 电动汽车作为一种新兴负荷，大量接入配电网会对电能质量、频率稳定、电压稳定等产生一系列影响。通过对现有的分时电价制度进行分析，在配电网方面以系统负荷均方差最小化和系统负荷峰谷差最小化为目标函数。在用户侧方面以电动汽车用户充放电成本和电池损耗成本最低作为目标函数，建立电动汽车多目标优化调度模型。通过云自适应粒子群算法进行寻优。仿真结果表明:该调度策略适合于分时电价，与固定电价相比优化了系统负荷同时降低了用户成本。价差更大、均值更高的分时电价2与分时电价1相比略微增加了用户成本，但它对电网的调峰能力明显增强。 |
| 关键词: 云自适应粒子群算法 峰谷分时电价 多目标经济调度 电动汽车 影响分析 |
| DOI：10.19783/j.cnki.pspc.190770 |
| 投稿时间：2019-07-03修订日期：2019-08-30 |
| 基金项目:国家自然科学基金项目资助(61761049);云南省教育厅科学研究基金项目资助(2019Y0168);云南省应用基础研究青年项目资助(2018FD052) |
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| Research on electric vehicle scheduling strategy based on time-shared electricity price 2. Anhui Jinzhai Pumped Storage Power Company Limited, Lu’an 237333, China) |
| ZHAO Yu,XU Tianqi,LI Yan,CUI Lin,CHEN Xiaoya |
| (School of Electrical and Information Technology, Yunnan Minzu University, Kunming 650500, China;Anhui Jinzhai Pumped Storage Power Company Limited, Lu’an 237333, China)) |
| Abstract: |
| As an emerging load, there will be a series of impacts from electric vehicles connected largely to the power grid, such as power quality, frequency stability and voltage stability. Through analysis of the existing time-sharing electricity price system, this paper establishes a multi-objective optimization scheduling model by adopting the minimization of mean square error and peak and off-peak difference system load as the objective function in terms of power distribution network. It also uses the minimum of battery charging and discharging cost of electric car users and the minimum of battery loss as the objective function from the aspect of users. A cloud adaptive particle swarm optimization algorithm is applied in this paper. The simulation results show that the dispatching strategy is suitable for a time-sharing tariff, and compared with the fixed electricity price, the time-sharing electricity price optimizes the system load and reduces the user cost at the same time. The time-sharing electricity price 2, where the peak-valley price difference is larger and the mean value is higher, increases slightly the user cost compared with the time-sharing electricity price 1, but the peak-regulating capacity of the power grid is evidently enhanced. This work is supported by National Natural Science Foundation Project of China (No. 61761049) and Scientific Research Foundation Project of Yunnan Education Department (No. 2019Y0168) and Yunnan Applied Basic Research Youth Project (No. 2018FD052). |
| Key words: cloud adaptive particle swarm optimization peak-valley time pricing multi-objective economic dispatching electric vehicle impact analysis |
