Cost minimization in a MicroGrid connected with Wind and PV generations using a hybrid Cat Swarm optimization and micro Differential Evolution

This paper proposes a new hybrid methodology to solve the cost minimization of generation in a MicroGrid. This solution methodology is modeled using two powerful heuristic based methods such that the main optimizer is the Cat Swarm optimization and final solution tuning is done by a micro Differential Evolution. The MicroGrid is modeled with three different types of generating sources such that diesel generating plant and renewable sources like wind and solar. The diesel generating plant is modeled as a non-convex fuelcost function and wind and solar generating sources are formulated as non-linear cost function but will be formulated as inequality constraints. The objective function is the combination of diesel generator fuel-cost and the cost of power transferable between main grid and micro grid. A 150 bus Islanded MicroGrid system is adopted such that the system has various types of distributed generations such that wind, Solar and diesel power plants are connected. Simulation results are shown for the proposed hybrid algorithm and compared with the techniques applied individually before they were hybridized. Final results demonstrates the applicability of the proposed hybrid algorithm for solving the cost minimization problem in a MicroGrid.