Lagrange Multiplier-Based Optimization for Hybrid Energy Management System with Renewable Energy Sources and Electric Vehicles

Author:

Tran Huy Gia1,Ton-That Long1,Thao Nguyen Gia Minh2ORCID

Affiliation:

1. School of Electrical Engineering, International University, Vietnam National University, Ho Chi Minh City 700000, Vietnam

2. Department of Mechanical, Electrical and Electronic Engineering, Interdisciplinary Faculty of Science and Engineering, Shimane University, Matsue City 690-8504, Japan

Abstract

The issues of energy scarcity and environmental harm have become major priorities for both business and human progress. Hence, it is important and useful to focus on renewable energy research and efficient utilization of distributed energy sources (DERs). A microgrid (MG) is a self-managed system that encompasses these energy resources as well as interconnected consumers. It has the flexibility to function in both isolated and grid-connected configurations. This study aims to design an effective method of power management for a MG in the two operating modes. The proposed optimization model seeks to strike a balance between energy usage, protecting the life of batteries, and maximizing economic benefits for users in the MG, with consideration of the real-time electricity price and constraints of the power grid. Furthermore, in order to accurately account for the dynamic nature of not only the stationary battery banks used as the energy storage systems (ESS) but also the built-in batteries of electric vehicles (EVs), the model is presented as a multi-objective, multiparametric and constrained problem. The solution is proposed to be found using the Lagrange multiplier theory, which helps to achieve good performance with less computational burden. Lastly, simulation results from both the isolated and grid-connected modes also demonstrate the effectiveness of the designed method.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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