基于改进粒子群算法的电动汽车停车场V2G策略研究

计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 92-96.

基于改进粒子群算法的电动汽车停车场V2G策略研究

邵炜晖¹, 许维胜¹, 徐志宇¹, 王宁¹, 农静²

同济大学电子与信息工程学院上海201804¹
贵州电网有限责任公司电网规划研究中心贵阳550003²

出版日期:2019-02-26 发布日期:2019-02-26
作者简介:邵炜晖(1988-),男,博士生,主要研究方向为能源互联网下需求侧响应、虚拟电厂等,E-mail:shaoweihui@126.com;许维胜(1966-),男,教授,主要研究方向为应急管理、智能电网、大数据应用等;徐志宇(1982-),男,高级工程师,主要研究方向为先进控制策略在电力市场中的应用、信息融合理论等;王宁(1992-),男,博士生,主要研究方向为能源互联网架构、超网络理论等;农静(1973-),女,高级工程师,主要研究方向为电力系统新技术和电网规划等。
基金资助:
本文受国家自然科学基金项目(71401125,71540022,61773292),高等学校博士学科点专项科研基金资助项目(20130072110045),中国南方电网有限责任公司科技项目(GZKJXM20160635)资助。

Research of V2G Strategies for EV Parking Lot Based on Improved PSO

SHAO Wei-hui¹, XU Wei-sheng¹, XU Zhi-yu¹, WANG Ning¹, NONG Jing²

College of Electronic and Information Engineering,Tongji University,Shanghai 201804,China¹
Power Grid Planning and Research Center of Guizhou Power Grid Co.,Ltd.,Guiyang 550003,China²

Online:2019-02-26 Published:2019-02-26

摘要/Abstract

摘要： 为解决电动汽车大规模并网带来的一系列问题,国内外逐步在城市商业停车场内提供电动汽车充电服务。在此背景下,提出一种基于电动汽车并网技术的电动汽车充放电停车场模型。该模型响应实时电价,对电动汽车的充电并网行为进行动态调度,继而与电网进行能量交互。在求解电动汽车最优调度策略时采用粒子群优化算法,从可行性编码、自适应搜索半径、边界变异修正等方面进行改进,以提高算法的效率及收敛精度。仿真实验采用美国PJM公司的实时电价数据及主流电动汽车的型号参数,对比分析了3种不同情景下电动汽车停车场的运营过程及结果,验证了所提模型的合理性以及改进算法的有效性。

关键词: V2G, 充放电策略, 电动汽车停车场, 粒子群算法, 实时电价

Abstract: Electric vehicle parking lot is built nearby commercial office buildings for electric vehicles charging and par-king to solve a series of problems broughtby large-scale grid-connected electric vehicles.A V2G based electric vehicle parking lot model (V2G_EVPL) was proposed to describe charging and discharging behaviors of electric vehicles in the parking lot based on vehicle to grid (V2G) technology.Under the conditions of the real-time pricing (RTP),V2G_EVPL dynamically schedules the electric vehicle charging or discharging,and then interacts with the grid for energy.Improved particle swarm optimization (IPSO) algorithm is applied to solve the optimal scheduling for electric vehicles.Improvements,such as feasibility coding,adaptive search radius and boundary variability correction,are made to improve the efficiency and the convergence accuracy of PSO.Real-time price data of PJM and the parameters of mainstream electric vehicles are used in simulation.The operation process and results of V2G_EVPL under three different scenarios are compared and analyzed.Results of the simulations show that the proposed model is reasonable and the improved PSO algorithm is both efficient and effective.

Key words: Charge and discharge strategy, Electric vehicle parking lot, PSO, Real-time pricing, V2G

中图分类号:

TP734

邵炜晖, 许维胜, 徐志宇, 王宁, 农静. 基于改进粒子群算法的电动汽车停车场V2G策略研究[J]. 计算机科学, 2018, 45(11A): 92-96. https://doi.org/

SHAO Wei-hui, XU Wei-sheng, XU Zhi-yu, WANG Ning, NONG Jing. Research of V2G Strategies for EV Parking Lot Based on Improved PSO[J]. Computer Science, 2018, 45(11A): 92-96. https://doi.org/

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