Uncertainty compensation with coordinated control of EVs and DER systems in smart grids

Abstract

The exploitation of wind farms and solar cells have a special place due to their ability to produce more, more general acceptability, and more affordable. The only challenge facing the use of new energies is the uncertainty in their production due to the lack of sunlight and wind blowing continuously at different hours of the day and night. In this article, the problem of planning the flexibility of electric vehicle charging and discharging to coordinate with wind and solar production and to compensate for the uncertainty of these resources has been solved using the CPLEX solver. Also, in this article, the flexibility of charging and discharging of electric vehicles has been used to coordinate with wind and solar production and compensate for the uncertainty of these sources. In addition, the EVs (Electric Vehicles) are planned in such a way that the operating cost of the microgrid is minimized. To consider the uncertainty related to loading, wind, and solar production, different scenarios have been considered and programming in R language has been done. These scenarios have been considered using the time series method of data determination and correlation. Due to the high number of scenarios and the increase in the volume of calculations, the scenario reduction method is used, then several scenarios with the highest probability of occurrence are selected and optimization is done. The simulation is done using GAMS software. The optimization problem is solved by integer linear programming. The results indicate that the cost is reduced by considering the uncertainties, through optimal planning for the EVs, and it is also profitable for the operator.