مشخصات پژوهش

This paper investigates distributed stochastic optimal energy management of an active distribution network with multi-microgrids in which both the distribution system operator (DSO) and microgrids (MGs) strive to minimize operational costs. The primary obstacles include the preservation of privacy and the management of uncertainties in a decentralized environment. Renewable energy sources, a demand response program, and a parking lot for electric vehicles (EVs) are all features that are associated with MGs. EVs can offer flexibility by adjusting the charging and discharging power according to the needs and advantages of the MGs, using the gridto- vehicle and vehicle-to-grid mechanism. Scenarios were generated using probability density function which were reduced by mixed integer linear programming-based scenario reduction approach to overcome the computation complexity. The alternating direction method of multipliers is utilized to manage the DSO and MG optimization problems in a distributed manner that ensures privacy and scalability. The model is tested on a modified IEEE 33-bus system with four microgrids. Based on the findings, it is evident that the bidirectional charging of EVs plays a crucial role in enabling MGs to shift their energy consumption from peak hours to offpeak hours and the proposed approach improves flexibility and enables more realistic scheduling under uncertainty.