Optimization of an Energy Distribution Management System for a Hybrid Microgrid (Battery–Wind–Photovoltaic) Using an Adaptive Autoregressive Algorithm

Abstract

The integration of energy storage technologies with renewable energy systems can significantly reduce the operational costs of microgrids within modern power networks. This paper presents a novel Energy Distribution Management System (EDMS) capable of minimizing the daily operational cost of a microgrid while simultaneously maximizing the self-consumption of renewable energy resources through the optimal scheduling of a centralized Battery Energy Storage System (BESS) based on a predefined cost function. The proposed renewable energy management framework adopts a two-layer architecture. In the upper layer, a convex optimization technique is employed to solve the optimization problem and determine the reference power values that should be exchanged between the microgrid and the utility grid using a sampling interval of 15 minutes. For system simulation and forecasting purposes, an Adaptive Autoregressive (AR) algorithm is implemented in MATLAB. Simulation results demonstrate that the proposed renewable energy management framework, with its hierarchical two-layer structure, successfully reduces the total daily operational cost of the microgrid while enhancing the self-consumption rate of renewable energy resources