综合考虑充电需求和配电网接纳能力的电动汽车充电站规划

Planning of Electric Vehicle Charging Stations Considering Charging Demands and Acceptance Capacity of Distribution Network

综合考虑充电需求和配电网接纳能力的电动汽车充电站规划对电动汽车和配电网协同发展具有重要意义。对电动汽车出行大数据进行数理统计,获取出行和充电行为特征指标;以此为基础用马尔科夫原理和轮盘赌法模拟目标数量下电动汽车的出行链,预测充电需求时空分布,获得配电网各节点充电需求不可达率和不满足率;进而筛选候选站址和接入方案,采用熵权修正的层次分析法评估配电网对候选接入方案的接纳能力;以建设运营总成本最小为目标建立充电设施规划模型,采用遗传算法求解,通过配电网潮流计算检验规划结果的合理性。IEEE33节点系统案例验证了所提方法的有效性。

The planning of electric vehicle(EV) charging stations with a comprehensive consideration of the charging demands and the acceptance capacities of the distribution network is of great significance to the development of EVs and the transformation of the distribution network. The probability statistics on the big data of EV travels help digging out the travel and charging rules of the EVs. Then the Markov chain and the roulette method are used to simulate the travel chains of EVs under the target quantity based on the behavioral characteristic index, predicting the spatial and temporal distribution of the charging demands. According to the unreachable and unsatisfied rates of the charging demands, the candidate sites are screened and the access schemes are determined. The acceptance capacity of the distribution network to the candidate access schemes is evaluated with the analytic hierarchy process(ahp) modified by the entropy weight. A charging facility planning model with the goal of minimizing the total cost of construction and operation is established and solved by the genetic algorithm. According to the planning results, the charging stations are connected to the distribution network and the power flow is calculated so the eligibility of the planning results is verified. An example of IEEE33 node system is given to demonstrate the effectiveness of the proposed method.