Economic battery sizing and power dispatch in a grid-connected charging station using convex method

Optimal utilization of storage devices consists of Battery Energy Storage System (BESS), Electric Vehicles (EVs) alongside applying Demand Side Management (DSM) strategies, created many opportunities consist of reducing cost and increasing penetration rate of renewable energy sources (RESs) in a distribution network. This paper presents, mixed-integer linear programming (MILP) framework-based model to evaluate operating and trading costs of a charging station integrated with PV, BESS, and building considering: (i) a K-means clustering-based algorithm for estimating the PV generation power, (ii) Holt-Winter method for predicting the building demand for a day, (iii) V2G (vehicle to grid) and V2B (vehicle to building) capabilities of EVs, (iv) the effects of power trading between the charging station with the MGs and utility grid in different price rates based on the future market, (v) the impacts of the using the BESS in optimal capacity, (vi) utilization of a DSM strategy for building demand by shifting the non-important demand to the optimal time. Bilateral power flow between the electrical line caused to make the problem formulation as a non-convex. To deal with this challenge, the convex relaxation method is used to transform the problem from MILP to a linear programming (LP) model. To assess the effects of the proposed scheduling scheme on the total costs of the charging station, seven different scenarios are discussed and solved by the convex method. The results have verified that the use of the proposed scheme improves the reliability of the system and decreases the daily operational and trading cost of the charging station and also causes to reduce the total power injected by the utility grid to the model.