Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems
This study presents a novel method for optimal energy trading within microgrids considering renewable energy (RE) integration. The proposed approach uses the hybridization of particle swarm optimization and gravitational search algorithms (PSO-GSA) with Nash Bargaining to optimize power flow and ene...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-01-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016823010414 |
| _version_ | 1797347804371222528 |
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| author | Zia Ullah Hasan Saeed Qazi Ahmad Alferidi Mohammed Alsolami Badr Lami Hany M. Hasanien |
| author_facet | Zia Ullah Hasan Saeed Qazi Ahmad Alferidi Mohammed Alsolami Badr Lami Hany M. Hasanien |
| author_sort | Zia Ullah |
| collection | DOAJ |
| description | This study presents a novel method for optimal energy trading within microgrids considering renewable energy (RE) integration. The proposed approach uses the hybridization of particle swarm optimization and gravitational search algorithms (PSO-GSA) with Nash Bargaining to optimize power flow and energy trading between interconnected MGs and the main utility grid. Unlike existing solutions, the proposed model promotes cooperative energy trading among MGs and the main grid, considering network constraints and RE's inherent uncertainty; consequently, it addresses key challenges related to model design, pricing fairness, power flow optimization, and network constraints. The proposed method is implemented in MATLAB® considering the interconnection of four different MGs, called cooperative MGs, which optimally enable energy trading within the cooperative MGs and main utility. Simulation results, case studies and comparisons demonstrate the relevance of the proposed hybrid PSO-GSA in terms of maximizing the RE utilization, reducing load burden on the main grid and substantial cost reductions, with monthly energy costs decreased by $60,720 compared to the base case of $94,551. Also, the robustness and efficiency of the proposed PSOGSA algorithm are evaluated by comparing it with other well-established metaheuristic optimization methods under the same system data, control variables, and constraints. This research significantly contributes to MG energy trading by proactively optimizing economic operations and increasing RE utilization while adapting cooperation among interconnected MGs. |
| first_indexed | 2024-03-08T11:54:10Z |
| format | Article |
| id | doaj.art-33ab5e5a7d9047c4a33c88d3cbf8affe |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-03-08T11:54:10Z |
| publishDate | 2024-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-33ab5e5a7d9047c4a33c88d3cbf8affe2024-01-24T05:17:06ZengElsevierAlexandria Engineering Journal1110-01682024-01-01862333Optimal energy trading in cooperative microgrids considering hybrid renewable energy systemsZia Ullah0Hasan Saeed Qazi1Ahmad Alferidi2Mohammed Alsolami3Badr Lami4Hany M. Hasanien5School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, ChinaElectrical Engineering Department, COMSATS University Islamabad, Attock Campus, PakistanDepartment of Electrical Engineering, Faculty of Engineering, Taibah University, Medinah, Saudi Arabia; Corresponding author.Department of Electrical Engineering, Faculty of Engineering, Taibah University, Medinah, Saudi ArabiaDepartment of Electrical Engineering, Faculty of Engineering, Taibah University, Medinah, Saudi ArabiaElectrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo 11517, Egypt; Faculty of Engineering and Technology, Future University in Egypt, Cairo 11835, EgyptThis study presents a novel method for optimal energy trading within microgrids considering renewable energy (RE) integration. The proposed approach uses the hybridization of particle swarm optimization and gravitational search algorithms (PSO-GSA) with Nash Bargaining to optimize power flow and energy trading between interconnected MGs and the main utility grid. Unlike existing solutions, the proposed model promotes cooperative energy trading among MGs and the main grid, considering network constraints and RE's inherent uncertainty; consequently, it addresses key challenges related to model design, pricing fairness, power flow optimization, and network constraints. The proposed method is implemented in MATLAB® considering the interconnection of four different MGs, called cooperative MGs, which optimally enable energy trading within the cooperative MGs and main utility. Simulation results, case studies and comparisons demonstrate the relevance of the proposed hybrid PSO-GSA in terms of maximizing the RE utilization, reducing load burden on the main grid and substantial cost reductions, with monthly energy costs decreased by $60,720 compared to the base case of $94,551. Also, the robustness and efficiency of the proposed PSOGSA algorithm are evaluated by comparing it with other well-established metaheuristic optimization methods under the same system data, control variables, and constraints. This research significantly contributes to MG energy trading by proactively optimizing economic operations and increasing RE utilization while adapting cooperation among interconnected MGs.http://www.sciencedirect.com/science/article/pii/S1110016823010414Cooperative microgridOptimal energy tradingRenewable energyEnergy cost reduction |
| spellingShingle | Zia Ullah Hasan Saeed Qazi Ahmad Alferidi Mohammed Alsolami Badr Lami Hany M. Hasanien Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems Alexandria Engineering Journal Cooperative microgrid Optimal energy trading Renewable energy Energy cost reduction |
| title | Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| title_full | Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| title_fullStr | Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| title_full_unstemmed | Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| title_short | Optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| title_sort | optimal energy trading in cooperative microgrids considering hybrid renewable energy systems |
| topic | Cooperative microgrid Optimal energy trading Renewable energy Energy cost reduction |
| url | http://www.sciencedirect.com/science/article/pii/S1110016823010414 |
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