Implementation of an Energy Management System for Real-Time Power Flow Control in AC Microgrid

TL;DR

This paper presents an EMS for AC microgrids that optimizes power flow using predictive data to minimize costs, verified through simulations and real-time testing.

Contribution

It introduces a novel EMS that integrates solar prediction, tariff, and load data for cost-effective power management in AC microgrids.

Findings

Effective power flow regulation with predictive control.

Cost reduction demonstrated through simulations and real-time tests.

Validation of EMS performance in a 10kW PV system.

Abstract

Microgrid (MG) system, which is composed of renewable resources with the utility grid, energy storage unit, electric vehicles, and loads, acts as a single controllable entity. To get efficient and low-cost energy, need to manage power flow within MG depending on renewable resources and load demand. This paper proposes an energy management system (EMS) for grid-connected photovoltaic (PV) and energy storage system (ESS) based on AC MG. The proposed EMS regulates power flow through the AC bus considering next-day solar irradiance prediction, tariff profile, and day-ahead load demand to minimize the cost of electricity. The recommended EMS for the MG system has been verified using MATLAB/Simulink. Also, the algorithm has been tasted with real time data of a 10kW PV system.