Dynamic electricity pricing for electric vehicles using stochastic programming

摘要: Abstract Electric Vehicles (EVs) are an important source of uncertainty, due to their variable demand, departure time and location. In smart grids, the electricity demand can be controlled via Demand Response (DR) programs. Smart charging vehicle-to-grid seem highly promising methods for EVs control. However, high capital costs remain a barrier implementation. Meanwhile, incentive price-based schemes that do not require level control implemented influence EVs' demand. Having effective tools deal with increasing uncertainty is increasingly players, such as energy aggregators. This paper formulates stochastic model day-ahead resource scheduling, integrated dynamic pricing EVs, address challenges brought by renewable sources uncertainty. The two-stage programming approach used obtain optimal EVs. A realistic case study projected 2030 presented based on Zaragoza network. results demonstrate it more than deterministic preferable. indicates adequate DR like proposed one increase customers' satisfaction in addition improve profitability aggregation business.