Optimizing Distributed Generation and Energy Storage in Microgrids through Intelligent Energy Administration Strategies

¹ Department of Applied Sciences, New Horizon College of Engineering, Bangalore, India
² Department of CSE-AI&ML, MLR Institute of Technology, Hyderabad, Telangana, India
³ Lovely Professional University, Phagwara, India
⁴ Lloyd Law College, Greater Noida, Uttar Pradesh, India
⁵ Department of Medical Laboratory Technology, College of Medical Technologies, The Islamic University, Najaf, Iraq
⁶ Department of Electrical & Electronics Engineering, IILM University, Greater Noida, India

^* Corresponding Author: Priyanka.agrawal.ei@gmail.com

Abstract

An intelligent energy management strategy (IEAS), used for performing peak performance of microgrid, is proposed. SEMS mainly contains three modules -- energy retention system administration module, optimisation component, and power prediction module. From research done on the characteristics of solar PV production under various metrological scenarios, a module for power prediction one day ahead of time has been proposed. The mechanism of energy retention is its two most important characteristics: the retention must be improved across many time steps; energy pricing structures should be considered. Thus, the optimal way to operate are determined by using the ESS module. The storage device and the ESS financial performance can be evaluated by simultaneously considering ESSs of multiple-time limiting defined ESS. Thus, based on IEMS, the operations of DG, smart managing ESS and economical load dispatch is converted into a single-object optimisation problem. Finally, to get a workable approach of load management, an efficiency component for VE-GA is presented. This module generates control diagram of the dispersed generators and ESS, and give three different operation strategies.