A multi-objective optimization for energy management in a renewable micro-grid system: A data mining approach

To make renewable Micro-Grid (MG) systems work as a sustainable set, one confronts a multi-objective, multi-constraint problem. To optimally operate these hybrid energy systems, one should consider the problems due to huge amount of raw data achieved through several measuring systems in different sections in a MG. In this paper, a new Smart Energy Management System (SEMS) is proposed and tested via simulation studies. The proposed SEMS performs some critical tasks such as data acquisition, data processing, and determining control signals for the MG. Two objective functions are defined for the SEMS to minimize the total operating cost and the net emission of the fossil fueled Distributed Generators with respect to some technical and reliability (Expected Energy Not Supplied index) constraints for the MG. The simulation results show a promising performance of the proposed SEMS for smart micro-grids. (C) 2014 AIP Publishing LLC.