计及电动汽车无功支撑能力的分布式电源与智能停车场联合规划方法

随着大量分布式电源(DG)及电动汽车(EV)接入配电网,为保证电网的高效、清洁、经济和安全运行,必须对二者进行合理的规划。为此,提出一种计及EV无功支撑能力的DG及智能停车场(IPL)联合规划方法。首先,基于有源配电网的基本物理结构,对EV动力电池的无功可调范围进行了推导。进一步考虑风电等间歇性DG出力、常规用电以及EV充电负荷时空分布的不确定性,通过构建发电—负荷场景以综合计及上述不确定性因素的影响。在此基础上,分别以系统投资和运行成本最小作为目标函数,构建了综合考虑DG和IPL选址定容的两阶段优化模型。根据模型特点,采用经典的遗传算法实现问题求解。以33节点配网系统为例,对所提模型的有效性进行验证。仿真结果表明,在配电网投资规划中充分考虑规模化入网EV的无功支撑能力,能够有效改善系统的电能质量,促进可再生能源高效利用,从而带来更好的经济效益。

A Combinatorial Planning Method for Distributed Generation and Intelligent Parking Lots Considering Reactive Supporting Capability of Electric Vehicles

With the growing penetration of distributed generations (DG) and electric vehicles (EV),the coordinated planning of the above two is necessary to ensure efficient,clean,economical and safe operation of distribution grids.Thus,this paper proposes a joint planning method for DG and intelligent parking lots which takes account of the reactive power capacity of EVs.Firstly,based on the fundamental structure of active distribution network,the adjustable range of reactive power of EV power battery is derived.Then,to represent the temporal and spatial uncertainties that associated with stochastic generation,traditional demand and EV charging loads,a series of generation-demand scenarios are built.On this basis,a two-stage planning model for optimal siting and sizing DG and intelligent parking lots (IPL) is developed,which takes the minimization of system construction and operation cost as the goal.According to the feature of the model,genetic algorithm is used to solve the problem.Effectiveness of the proposed model is tested on the 33-node distribution system,and the results show that considering reactive supporting capability of EV in distribution system planning can improve power quality and promote the efficiency for renewable energy utilization,thus bringing better economic benefits.