Multi-energy dispatching for uncertainty EV demand: A simulation approach - Shengxuan Ye; Shengxuan Ye; Yuxuan Dai; Fenglin Zhang; Zhiqi Qin; Shuwen Jin; Qiyao Yan; Qiyao Yan; Yangbing Xu (Frontiers in Energy Research, 2022)
Uncertainty and randomness in demand and supply bring significant challenges to the stable operation of the grid and the scheduling planning of multi-energy sources. To solve these challenges, we propose and analyze a multi-energy dispatching model which minimizes the total cost and enhances the efficiency of supplying power. Specifically, we design matching algorithms that simulate an appropriately scaled sequence of stochastic EV demand. We also analyze four different energy dispatching scenarios proving that the scheduling model and the multi-energy synergistic microgrid structure can bring higher efficiency and lower costs. Our main contribution is using a simulation approach to take EVs into account for demand-side uncertainty, which significantly improves the efficiency of grid dispatch.