Optimal scheduling of a microgrid using AI techniques

With the emergence of the microgrid, the penetration of renewable energy resources into the power system, along with the existing conventional generation systems, has increased, thereby decreasing the cost of generating power, reducing dependency on the grid, and decreasing the environmental impact. To ensure high reliability and cost effectiveness, the microgrid requires optimization of the scheduling of power as per demand to satisfy all the constraints. The distributed generators (DGs) are expected to optimally cater to the demand with the help of optimal scheduling using artificial intelligence (AI) techniques, which will result in a minimized cost of operation. The various DGs considered for the realization of this microgrid are solar PV, wind turbines, fuel cells, diesel generators, etc. This chapter focuses on the microgrid working in different modes of operation. The unpredictable nature of the loads and nonlinearity of the components of the microgrid make the optimal scheduling of the microgrid more complex. This chapter incorporates MATLAB simulations, to realize the microgrid and schedule the power to be generated by various DGs throughout the day, to achieve the main aim of cost minimization. It considers the day to be divided into 24 intervals of 1 h each, in which the power is to be scheduled. In this chapter, depending on the microgrid interaction and dynamic behavior, different scenarios consisting of various cases are considered and compared with the latest AI techniques.