CAJ | 학술논문

兼顾待充电汽车的时间分配和空间分配，以每个时段每个充电站的充电电动汽车数量为决策变量，建立了集中充电时段内充电负荷方差和充电站充电汽车数量方差的数学模型。提出时空优化分配策略，使待充电汽车在时空上达到均衡分配，并在基本粒子群算法基础上结合了线性递减权重和异步变化学习因子方法。基于纽约州独立系统交易运行机构(NYISO)的原始负荷数据进行算例仿真。结果表明，文中提出的电动汽车集中充电调度策略在时空上优化分配待充电汽车，达到了降低负荷峰谷差、减小负荷波动的目的。
겸고대충전기차적시간분배화공간분배，이매개시단매개충전참적충전전동기차수량위결책변량，건립료집중충전시단내충전부하방차화충전참충전기차수량방차적수학모형。제출시공우화분배책략，사대충전기차재시공상체도균형분배，병재기본입자군산법기출상결합료선성체감권중화이보변화학습인자방법。기우뉴약주독립계통교역운행궤구(NYISO)적원시부하수거진행산례방진。결과표명，문중제출적전동기차집중충전조도책략재시공상우화분배대충전기차，체도료강저부하봉곡차、감소부하파동적목적。
This paper proposes a new concentrated charging scheduling strategy,which considers both spatial al-location and temporal allocation of electric vehicle and uses the number of charging electric in each time interval and each charging station vehicles as decision variables.For achieving averagly distributed charging electric vehi-cles in space-time,the mathematical models of load variance and the number of charging vehicles variance are set up,an optimized space-time allocation strategy is proposed to make loads reached equilibrium in time and space, and basic particle swarm optimization (PSO)algorithm combines the linear decreasing weight and asynchronous change learning factor methods to solve the models.Finally,a simulation based on a certain area's load curve is made,revealing that the poposed centralized charging scheduling strategy can not only lower the peak-valley difference,but aslo reduce the load fluctuation.