METHOD FOR ONLINE COORDINATED OPTIMIZATION SCHEDULING OF TRUCK MOBILE CHARGING STATIONS

Related to the field of charging infrastructure optimization, a method for online coordinated optimization scheduling of truck mobile charging stations. A two-stage framework is proposed: (1) offline training stage, where a multi-period optimization decision model for TMCSs is constructed, and a look-ahead rolling horizon-value function approximation (LRH-VFA) algorithm is then developed to iteratively learn from historical EV charging data, considering the impact of current-period decisions on future profit; and (2) online scheduling stage, where TMCS scheduling decisions are dynamically updated based on the approximate value function obtained from offline training, along with short-term forecasts and real-time information. The method effectively accounts for the impact of uncertain EV charging demand on TMCS scheduling, dynamically adjusting decisions based on real-time updates. It enables better coordination of TMCS online scheduling between EV charging services and energy arbitrage, improving operator profitability while ensuring the quality of charging services.