A novel modification approach based on MTLBO algorithm for optimal management of renewable micro-grids in power systems

The consumer's demand of more reliable and economic sources has made an impact on the new competitive electricity markets. In this regard, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach. This paper presents a novel solution methodology based on Teacher-Learning-Based Optimization (TLBO) algorithm to solve the optimal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), photovoltaic (PV) and Micro Turbine (MT). Moreover, storage devices have been considered to meet the energy mismatch. The solution of this nonlinear constraint optimization problem minimizes the total cost of the grid and RESs, concurrently. Nevertheless, in finding the optimal solution, the interactive effects of MG and utility in a 24 hour time interval are taken into consideration which would increase the complexity of the problem intensely. In order to explore the total search space globally, a modification method is proposed which is compromised of two modification methods based on TLBO. In the end, the suggested algorithm is tested through a typical renewable MG as the test system to demonstrate the superiority of the proposed method over the other well-known algorithms.