Optimal Operation and Management of Energy Resources in Microgrids in the Presence of Renewable Resources and Energy Storage by Modified Grey Wolf Optimization Algorithm

Nikoukar, Javad; Mohammadi, Shokoofeh; Hanif, Hamid Reza; Aminpour Gogani, Reza; Ghafari, Masoumeh; Behvandi, AbdolReza

doi:10.61186/jgeri.2.1.1

Optimal Operation and Management of Energy Resources in Microgrids in the Presence of Renewable Resources and Energy Storage by Modified Grey Wolf Optimization Algorithm

Document Type : Research article

Authors

Javad Nikoukar ¹

Shokoofeh Mohammadi ¹

Hamid Reza Hanif ²

Reza Aminpour Gogani ³

Masoumeh Ghafari ⁴

AbdolReza Behvandi ⁵

¹ Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran.

² Iran University of Science and Technology (IUST), Tehran, Iran.

³ Resilient Smart Grid Research Lab, Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran.

⁴ Electrical and Computer Engineering Department, Babol Noshirvani University of Technology, Babol, Iran.

⁵ Department of Electrical Engineering, Ramhormoz Branch, Islamic Azad University, Ramhormoz, Iran.

https://doi.org/10.61186/jgeri.2.1.1

Abstract

This paper delves into the meticulous optimization of distributed energy resources and their storage within a conventional microgrid framework. The optimization endeavor leverages an array of cutting-edge technologies including photovoltaic, wind, fuel cells, micro-turbines, and batteries, with the dual objectives of curtailing operational expenses and fortifying system reliability. To attain these objectives, the article employs a refined algorithm derived from the Grey Wolf Optimization technique. Furthermore, simulations are executed under two distinct scenarios. In the first scenario, the presumption is that all distributed energy resources within the microgrid are exploitable, whereas in the second scenario, spatial constraints necessitate the exclusion of photovoltaic and wind turbine resources. Simulation outcomes evince that post-implementation of energy management via metaheuristic algorithms, there is a discernible reduction in the operational costs of the microgrid alongside an enhancement in system reliability. Additionally, the elimination of photovoltaic and wind resources results in escalated costs and grid blackout within the microgrid. In summary, the simulation findings affirm the superior efficacy of the proposed modified Grey Wolf algorithm in addressing energy management quandaries in comparison to the Particle Swarm Optimization algorithm.

Graphical Abstract

Optimal Operation and Management of Energy Resources in Microgrids in the Presence of Renewable Resources and Energy Storage by Modified Grey Wolf Optimization Algorithm

Highlights

❖Modified Grey Wolf Optimization (MGWO) algorithm optimizes microgrid energy management.
❖ MGWO beats Particle Swarm Optimization (PSO) in two scenarios, reducing costs and improving efficiency.
❖ Negative energy costs indicate economic gains from electricity sales, especially with renewables.

Keywords

Microgrid Energy Management

Distributed Generation Resources

Reliability

Gray Wolf Algorithm

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The ethical issues, including plagiarism, informed consent, misconduct, data fabrication and/or falsification, double publication and/or submission, redundancy, have been completely observed by the authors.

Credit Authorship Contribution Statement

Javad Nikoukar: Conceptualization, Project administration, Visualization, Methodology. Shokoofeh Mohammadi: Data curation, Formal analysis, Investigation, Resources, Writing-review & editing. Hamid Reza Hanif: Data curation, Funding acquisition, Visualization, Writing-review & editing. Reza Aminpour Gogani: Methodology, Resources, Validation, Roles/Writing-original draft. Masoumeh Ghafari: Software, Resources, Software, Roles/Writing-original draft, Writing-review & editing. Abdolreza Behvandi: Data curation, Formal analysis, Investigation, Resources, Validation.

Bibliography

Javad Nikoukar was born in Mashhad, Iran, in 1983. He received the B.S. degree in electrical power engineering from Ferdowsi University, Mashhad, Iran, in 2006 and the M.S. degree in electrical power engineering from the University of Tehran, Tehran, Iran, in 2008. He earned his Ph.D. degree in electrical power engineering from Sharif University of Technology, Tehran, Iran in 2013. Since 2015 he has been an assistant professor in Mashhad branch, Islamic Azad University, Mashhad, Iran. His primary research interests are electric machine analysis, modelling, and simulation, innovative electrical drive control approaches, and renewable energy systems.

Shokoofeh Mohammadi was born in Saveh, Iran, in 1988. She received the B.Sc., M.Sc., degrees in 2015, 2018, respectively, in Chemist and Energy systems engineering, energy systems modeling engineering, respectively. She is currently an, TA with the Department of mechanical engineering, Islamic Azad University, Saveh, Iran. And Ph.D. student at Science and Research Branch, Islamic Azad University, Tehran, Iran. Her main research interests are energy system analysis and reliability, Exergy Analysis, Modeling and Simulation. She has Active as a researcher/ QA manager in different Industrial Companies.

Hamid Reza Hanif received his B.Sc. and M.Sc. in Mathematics and PHD degrees in Electrical Power Engineering from Iran University of Science and Technology, Iran Tehran in 2014 and 2019 and 2023 respectively. He has authored and co-authored more than 75 papers in international journals and conferences. He has also published a book and co-authored some book chapters. His main research interests include renewable energy, technologies, Microgrids, Power System Planning, Power Systems, Smart grids, Electric vehicles, and fault location. Since 2018 he has been a reviewer and Editorial Board Member of several high-quality journals.

Reza Aminpour Gogani received his B.Sc. and M.Sc. and Ph.D. in Electrical Power Engineering from Azarbaijan Shahid Madani University. He has authored and co-authored more than 10 papers in international journals and conferences. He has also published a book and co-authored some book chapters. His main research interests include renewable energy, technologies, Microgrids, Power system Planning, Power Systems, Smart grids, Electric vehicles, and fault location. Since 2018 he has been a reviewer of several high-quality journals.

Masoumeh Ghafari was born in 2000 in Ilam, Iran. She received the bachelor's degree in Electrical Engineering from Malayer University, Malayer, Iran, in 2023. With a keen interest in advancing the field of Electrical Engineering, she is currently pursuing the master's degree at Babol Noshirvani University of Technology, Babol, Iran, Specializing in Electrical Engineering with a focus on Control Systems. her research interests include Smart Grids, Energy Optimization, and Application of Neural Networks in Renewable Energy Systems.

Abdolreza Behvandi was born in 1987 in Iran. He received his B.Sc., M.Sc., and Ph.D. degrees all in Electrical Engineering (Power Systems) in 2010, 2012, and 2019 from Isfahan University of Technology, Isfahan University, and Shahid Chamran University of Ahvaz, respectively. Currently, he is an Assistant Professor at Department of Electrical Engineering, Ramhormoz Branch, Islamic Azad University, Ramhormoz, Iran. His special interests are power system studies, power system protection, renewable energy, and microgrids.

Citation
Nikoukar, S. Mohammadi, et al.," Optimal Operation and Management of Energy Resources in Microgrids in the Presence of Renewable Resources and Energy Storage by Modified Grey Wolf Optimization Algorithm," Journal of Green Energy Research and Innovation, vol. 2, no. 1, pp. 1-13, 2025.