research-article

Energy Management in Microgrids with Renewable Energy Sources and Demand Response

Authors:

Pushpendra Singh,

Praveen Bansal,

Yashwant SawleAuthors Info & Claims

Volume 110, Issue C

https://doi.org/10.1016/j.compeleceng.2023.108848

Published: 01 September 2023 Publication History

Highlights

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To reduce peak load demands and energy costs, MG uses DGs for a 24-hour period.

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Minimize operational l.,costs as well as environmental emissions.

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Equality and inequality constraints are considered.

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The DE algorithm is simple and performs better than GA & PSO technique.

Abstract

This manuscript presents a unique method for stochastic management of renewable energy sources using Micro Grid (MG). This method is based on the demand reduction function to provide a demand side reserve to supply electricity to consumers. To reduce peak demand and energy costs, a typical MG for distributed generation (DG) is used to schedule 24-hour power. The optimal generation scheduling problem is solved as both single-objective and multi-objective optimization problems. Differential Evolution and Multi-Objective Differential Evolution are used to minimize operating costs and environmental emissions, which consider equality and inequality constraints to find the best way to allocate power among the many units connected to MG. Power allocation using DE is shown to be more cost effective and environmentally friendly compared to Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) based technique.

Graphical abstract

Fig. A.1: Schematic configuration of micro grid with connecting all DG and feeders

Fig. A.1 shows a schematic diagram of the micro grid with connecting all DGs and feeders. The considered system contains several technical power components such as micro turbine, wind turbine, photo-voltaic, phosphoric acid fuel cell and battery for reliable operation of the system.

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Cited By

Zuluaga-Ríos CGuarnizo-Lemus C(2024)Data-driven approaches for generating probabilistic short-term renewable energy scenariosComputers and Electrical Engineering10.1016/j.compeleceng.2024.109817120:PCOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.compeleceng.2024.109817
Chakraborty ARay S(2024)Optimal allocation of distribution generation sources with sustainable energy management in radial distribution networks using metaheuristic algorithmComputers and Electrical Engineering10.1016/j.compeleceng.2024.109142116:COnline publication date: 1-May-2024
https://dl.acm.org/doi/10.1016/j.compeleceng.2024.109142

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Published In

cover image Computers and Electrical Engineering

Computers and Electrical Engineering Volume 110, Issue C

Sep 2023

1432 pages

ISSN:0045-7906

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Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 September 2023

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Cited By

Zuluaga-Ríos CGuarnizo-Lemus C(2024)Data-driven approaches for generating probabilistic short-term renewable energy scenariosComputers and Electrical Engineering10.1016/j.compeleceng.2024.109817120:PCOnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.compeleceng.2024.109817
Chakraborty ARay S(2024)Optimal allocation of distribution generation sources with sustainable energy management in radial distribution networks using metaheuristic algorithmComputers and Electrical Engineering10.1016/j.compeleceng.2024.109142116:COnline publication date: 1-May-2024
https://dl.acm.org/doi/10.1016/j.compeleceng.2024.109142

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