基于IGDT含电动汽车接入的能源系统输配协同双层优化调度

Bi-layer optimization scheduling of energy systemtransmission and distribution based on IGDT with electric vehicle access

电网中新能源与电动汽车渗透率的提升导致电力系统在局部时段灵活性严重不足。针对现有处理电力系统灵活性和供需不确定性过于保守或过于冒险的问题,提出一种基于信息间隙理论的双层优化调度模型。建立了包含输电与配电的能源调度系统,在此基础上提出电动汽车充放电双层优化调度策略。上层协调优化电动汽车、发电机组、风能和光伏发电,以实现供电成本的最小化。同时针对可再生能源发电的随机性问题,引入IGDT进行模拟分析。在配电网的下层优化,通过引入节点损耗灵敏度和节点电价,将电动汽车分配给充电节点,以实现电网损耗成本和充电成本的最小化。最后,通过ESS模型和IEEE33节点标准电网行仿真模拟分析,验证了所提策略的有效性及优越性。

The increase in the penetration of new energy and electric vehicles in the power grid has led to a serious lack of flexibility of the power system in local time periods.Aiming at the existing problems of dealing with power system flexibility and supply uncertainty that are too conservative or too risky,a two-layer optimal scheduling model based on information gap decision theory(IGDT)is proposed.An energy scheduling system(ESS)including transmission and distribution is established,and a two-layer optimal scheduling strategy for EV charging and discharging is proposed on this basis.The upper layer coordinates the optimization of EVs,gensets,wind and photovoltaic power generation to minimize the cost of power supply.Meanwhile,for the stochastic problem of renewable energy generation,IGDT is introduced for simulation and analysis.In the lower layer optimization of the distribution network,EVs are assigned to charging nodes by introducing node loss sensitivity(NLS)and node electricity price(NEP)to minimize the grid loss cost and charging cost.Finally,the effectiveness and superiority of the proposed strategy is verified by simulation and analyses through the ESS models and IEEE 33-node standard grid.