Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach
In this study, the effects of agent-based modeling on deregulated electricity markets using AMES (Artificial Market Environment Simulator) have been investigated. It is shown how the Independent System Operator (ISO) intervenes to control market dynamics and maintain supply-demand balance through lo...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10781381/ |
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| author | Feyyaz Aydin Canan Karatekin |
| author_facet | Feyyaz Aydin Canan Karatekin |
| author_sort | Feyyaz Aydin |
| collection | DOAJ |
| description | In this study, the effects of agent-based modeling on deregulated electricity markets using AMES (Artificial Market Environment Simulator) have been investigated. It is shown how the Independent System Operator (ISO) intervenes to control market dynamics and maintain supply-demand balance through locational marginal pricing (LMP). This study uses a model called Agent-Based Model (ABM) to simulate generation companies (GenCo’s) and load-serving entities (LSEs) in order to enhance market efficiency and stability. The methodology encompasses both static and dynamic testing of GenCo’s, integrating learning algorithms to optimize bidding strategies. The results showed that allowing generators to learn from previous experiences enabled them to make better offers in real-time, thus leading to higher profits. Furthermore, it shows that where DG units are located in the power system as well as their size can significantly raise generator earnings. Finally, when generators have the ability for learning, their profits increased considerably under various scenarios compared with those examples where learning cannot be applied, which demonstrates how helpful strategic learning could be for market participants. Moreover, it looks into the consequences of power system faults such as line faults; it demonstrates that distributed generation can mitigate the impacts of power system interruptions and uphold load flow in order to enhance overall market resilience. It draws attention to the fact that agent-based models are a powerful analytical technique for assessing and enhancing deregulated electricity markets. Additionally, political and operational choices obtained from dynamic and strategic modeling approaches like these will be good for electrical power systems. |
| format | Article |
| id | doaj-art-225af55e9c444419a0e307a560d3d3a3 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Access |
| spelling | doaj-art-225af55e9c444419a0e307a560d3d3a32024-12-14T00:01:39ZengIEEEIEEE Access2169-35362024-01-011218475518477510.1109/ACCESS.2024.351278110781381Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based ApproachFeyyaz Aydin0https://orcid.org/0009-0007-9052-0024Canan Karatekin1Department of Electrical Engineering, Istanbul Technical University, Sariyer, Istanbul, TürkiyeDepartment of Electrical Engineering, Istanbul Technical University, Sariyer, Istanbul, TürkiyeIn this study, the effects of agent-based modeling on deregulated electricity markets using AMES (Artificial Market Environment Simulator) have been investigated. It is shown how the Independent System Operator (ISO) intervenes to control market dynamics and maintain supply-demand balance through locational marginal pricing (LMP). This study uses a model called Agent-Based Model (ABM) to simulate generation companies (GenCo’s) and load-serving entities (LSEs) in order to enhance market efficiency and stability. The methodology encompasses both static and dynamic testing of GenCo’s, integrating learning algorithms to optimize bidding strategies. The results showed that allowing generators to learn from previous experiences enabled them to make better offers in real-time, thus leading to higher profits. Furthermore, it shows that where DG units are located in the power system as well as their size can significantly raise generator earnings. Finally, when generators have the ability for learning, their profits increased considerably under various scenarios compared with those examples where learning cannot be applied, which demonstrates how helpful strategic learning could be for market participants. Moreover, it looks into the consequences of power system faults such as line faults; it demonstrates that distributed generation can mitigate the impacts of power system interruptions and uphold load flow in order to enhance overall market resilience. It draws attention to the fact that agent-based models are a powerful analytical technique for assessing and enhancing deregulated electricity markets. Additionally, political and operational choices obtained from dynamic and strategic modeling approaches like these will be good for electrical power systems.https://ieeexplore.ieee.org/document/10781381/Agent-based modeling (ABM)locational marginal pricing (LMP)distributed generation (DG)load serving entities (LSE)deregulated electricity marketsoptimal power flow (OPF) |
| spellingShingle | Feyyaz Aydin Canan Karatekin Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach IEEE Access Agent-based modeling (ABM) locational marginal pricing (LMP) distributed generation (DG) load serving entities (LSE) deregulated electricity markets optimal power flow (OPF) |
| title | Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach |
| title_full | Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach |
| title_fullStr | Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach |
| title_full_unstemmed | Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach |
| title_short | Strategic Integration of Distributed Generation in a Deregulated Power Market: An Agent-Based Approach |
| title_sort | strategic integration of distributed generation in a deregulated power market an agent based approach |
| topic | Agent-based modeling (ABM) locational marginal pricing (LMP) distributed generation (DG) load serving entities (LSE) deregulated electricity markets optimal power flow (OPF) |
| url | https://ieeexplore.ieee.org/document/10781381/ |
| work_keys_str_mv | AT feyyazaydin strategicintegrationofdistributedgenerationinaderegulatedpowermarketanagentbasedapproach AT canankaratekin strategicintegrationofdistributedgenerationinaderegulatedpowermarketanagentbasedapproach |