A novel framework for photovoltaic energy optimization based on supply–demand constraints
Introduction: Distributed power supply has increasingly taken over as the energy industry’s primary development direction as a result of the advancement of new energy technology and energy connectivity technology. In order to build isolated island microgrids, such as villages, islands, and remote mo...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-12-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1267579/full |
| _version_ | 1797372988385918976 |
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| author | Yaoqiang Sun Nan Liu Imran Khan Imran Khan Youn-Cheol Park Yung-Cheol Byun Dag Øivind Madsen |
| author_facet | Yaoqiang Sun Nan Liu Imran Khan Imran Khan Youn-Cheol Park Yung-Cheol Byun Dag Øivind Madsen |
| author_sort | Yaoqiang Sun |
| collection | DOAJ |
| description | Introduction: Distributed power supply has increasingly taken over as the energy industry’s primary development direction as a result of the advancement of new energy technology and energy connectivity technology. In order to build isolated island microgrids, such as villages, islands, and remote mountainous places, the distributed power supply design is frequently employed. Due to government subsidies and declining capital costs, the configured capacity of new energy resources like solar and wind energy has been substantially rising in recent years. However, the new energy sources might lead to a number of significant operational problems, including over-voltage and ongoing swings in the price of power. Additionally, the economic advantages availed by electricity consumers may be impacted by the change in electricity costs and the unpredictability of the output power of renewable energy sources.Methods: This paper proposes a novel framework for enhancing renewable energy management and reducing the investment constraint of energy storage. First, the energy storage incentive is determined through a bi-level game method. Then, the net incentive of each element is maximized by deploying a master–slave approach. Finally, a reward and punishment strategy is employed to optimize the energy storage in the cluster.Results: Simulation results show that the proposed framework has better performance under different operating conditions.Discussion: The energy storage operators and numerous energy storage users can implement master–slave game-based energy storage pricing and capacity optimization techniques to help each party make the best choices possible and realize the multi-subject interests of energy storage leasing supply and demand win–win conditions. |
| first_indexed | 2024-03-08T18:42:42Z |
| format | Article |
| id | doaj.art-3816f817e5a14cb8b3aa651dd4b8449a |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-03-08T18:42:42Z |
| publishDate | 2023-12-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-3816f817e5a14cb8b3aa651dd4b8449a2023-12-29T04:16:21ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2023-12-011110.3389/fenrg.2023.12675791267579A novel framework for photovoltaic energy optimization based on supply–demand constraintsYaoqiang Sun0Nan Liu1Imran Khan2Imran Khan3Youn-Cheol Park4Yung-Cheol Byun5Dag Øivind Madsen6Department of Basic Education and Research, Changchun Sci-Tech University, Changchun, ChinaBasic Department, Jilin College of Technical Education, Changchun, ChinaDepartment of Electrical Engineering, University of Engineering and Technology, Peshawar, PakistanIslamic University Centre for Scientific Research, The Islamic University, Najaf, IraqDepartment of Mechanical Systems Engineering, Jeju National University, Jeju-si, Republic of KoreaDepartment of Computer Engineering, Major of Electronic Engineering, Jeju, Republic of KoreaSchool of Business, University of South-Eastern Norway, Kongsberg, NorwayIntroduction: Distributed power supply has increasingly taken over as the energy industry’s primary development direction as a result of the advancement of new energy technology and energy connectivity technology. In order to build isolated island microgrids, such as villages, islands, and remote mountainous places, the distributed power supply design is frequently employed. Due to government subsidies and declining capital costs, the configured capacity of new energy resources like solar and wind energy has been substantially rising in recent years. However, the new energy sources might lead to a number of significant operational problems, including over-voltage and ongoing swings in the price of power. Additionally, the economic advantages availed by electricity consumers may be impacted by the change in electricity costs and the unpredictability of the output power of renewable energy sources.Methods: This paper proposes a novel framework for enhancing renewable energy management and reducing the investment constraint of energy storage. First, the energy storage incentive is determined through a bi-level game method. Then, the net incentive of each element is maximized by deploying a master–slave approach. Finally, a reward and punishment strategy is employed to optimize the energy storage in the cluster.Results: Simulation results show that the proposed framework has better performance under different operating conditions.Discussion: The energy storage operators and numerous energy storage users can implement master–slave game-based energy storage pricing and capacity optimization techniques to help each party make the best choices possible and realize the multi-subject interests of energy storage leasing supply and demand win–win conditions.https://www.frontiersin.org/articles/10.3389/fenrg.2023.1267579/fullrenewable energyphotovoltaicgrid station clustergame theoryparticle swarm optimization |
| spellingShingle | Yaoqiang Sun Nan Liu Imran Khan Imran Khan Youn-Cheol Park Yung-Cheol Byun Dag Øivind Madsen A novel framework for photovoltaic energy optimization based on supply–demand constraints Frontiers in Energy Research renewable energy photovoltaic grid station cluster game theory particle swarm optimization |
| title | A novel framework for photovoltaic energy optimization based on supply–demand constraints |
| title_full | A novel framework for photovoltaic energy optimization based on supply–demand constraints |
| title_fullStr | A novel framework for photovoltaic energy optimization based on supply–demand constraints |
| title_full_unstemmed | A novel framework for photovoltaic energy optimization based on supply–demand constraints |
| title_short | A novel framework for photovoltaic energy optimization based on supply–demand constraints |
| title_sort | novel framework for photovoltaic energy optimization based on supply demand constraints |
| topic | renewable energy photovoltaic grid station cluster game theory particle swarm optimization |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1267579/full |
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