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.which is defined as the aggregation of DGs, electrical loads and generation interconnected among themselves and with the distribution network as well [1]. On the other side, lower cost, cleaner power generation mechanism, more reliability, better power quality and high flexibility are some of the main advantages of using RESs [2]. Recently, several researches have been used to investigate the MG problem under different loading and distinctive targets. The developing solution methods are experiencing continuous replacements in order to keep these net-works at the optimal operating point and control with different targets in the MG operation management domain.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.