Fuzzy logic controller and game theory based distributed energy resources allocation
Energy management and demand control through conventional energy generation sources are challenging for energy providers. Distributed energy resources (DERs) allocation near load centers may provide a suitable solution. The main contribution of the paper improves the voltage profile and reduce the a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2020-08-01
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| Series: | AIMS Energy |
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| Online Access: | https://www.aimspress.com/article/10.3934/energy.2020.3.474/fulltext.html |
| _version_ | 1818000642962096128 |
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| author | Akash Talwariya Pushpendra Singh Mohan Lal Kolhe Jalpa H. Jobanputra |
| author_facet | Akash Talwariya Pushpendra Singh Mohan Lal Kolhe Jalpa H. Jobanputra |
| author_sort | Akash Talwariya |
| collection | DOAJ |
| description | Energy management and demand control through conventional energy generation sources are challenging for energy providers. Distributed energy resources (DERs) allocation near load centers may provide a suitable solution. The main contribution of the paper improves the voltage profile and reduce the active and reactive power losses in the distribution network. DERs are integrated with IEEE 33 bus system using fuzzy logic controller (FLC) and game theory for two different cases with unity and 0.9 power factor (PF) and compares with conventional methods of integration (i.e., modified novel method, power loss sensitivity method, voltage sensitivity analysis method). The capacity of DERs is optimized by FLC with the help of three triangular input functions voltage profile, active power loss, and reactive power loss. The location of integration of DERs in the radial distribution network is identified by game theory. Game theory is a mathematical algorithm, the results of multiple runs of DERs integration with the desired capacity calculated by FLC, identify the location for integration. The results comparison of DERs integration with the proposed methodology and conventional method shows the effectiveness of the proposed methodology. The voltage profile of the IEEE 33 bus system is increased by 6.70% with unity PF and 7.10% with 0.9 PF most among the applied methodologies and reduce the active and reactive power losses for both unity and 0.9 PF cases. |
| first_indexed | 2024-04-14T03:24:13Z |
| format | Article |
| id | doaj.art-19fabb25049045cdb877b2708a6827f4 |
| institution | Directory Open Access Journal |
| issn | 2333-8334 |
| language | English |
| last_indexed | 2024-04-14T03:24:13Z |
| publishDate | 2020-08-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Energy |
| spelling | doaj.art-19fabb25049045cdb877b2708a6827f42022-12-22T02:15:13ZengAIMS PressAIMS Energy2333-83342020-08-018347449210.3934/energy.2020.3.474Fuzzy logic controller and game theory based distributed energy resources allocationAkash Talwariya0Pushpendra Singh1Mohan Lal Kolhe2Jalpa H. Jobanputra31 Department of Electrical Engineering, JK Lakshmipat University, Jaipur (Rajasthan), 302026, India1 Department of Electrical Engineering, JK Lakshmipat University, Jaipur (Rajasthan), 302026, India2 Faculty of Engineering and Science, University of Agder, Grimstad (Agder), NO 4879, Norway3 Department of Electrical Engineering, Shroff SR Rotary Institute of Chemical Technology, Bharuch (Gujrat), 393135, IndiaEnergy management and demand control through conventional energy generation sources are challenging for energy providers. Distributed energy resources (DERs) allocation near load centers may provide a suitable solution. The main contribution of the paper improves the voltage profile and reduce the active and reactive power losses in the distribution network. DERs are integrated with IEEE 33 bus system using fuzzy logic controller (FLC) and game theory for two different cases with unity and 0.9 power factor (PF) and compares with conventional methods of integration (i.e., modified novel method, power loss sensitivity method, voltage sensitivity analysis method). The capacity of DERs is optimized by FLC with the help of three triangular input functions voltage profile, active power loss, and reactive power loss. The location of integration of DERs in the radial distribution network is identified by game theory. Game theory is a mathematical algorithm, the results of multiple runs of DERs integration with the desired capacity calculated by FLC, identify the location for integration. The results comparison of DERs integration with the proposed methodology and conventional method shows the effectiveness of the proposed methodology. The voltage profile of the IEEE 33 bus system is increased by 6.70% with unity PF and 7.10% with 0.9 PF most among the applied methodologies and reduce the active and reactive power losses for both unity and 0.9 PF cases.https://www.aimspress.com/article/10.3934/energy.2020.3.474/fulltext.htmldistributed energy resourcesfuzzy logic controllergame theorycooperative game theoryintelligent distribution network |
| spellingShingle | Akash Talwariya Pushpendra Singh Mohan Lal Kolhe Jalpa H. Jobanputra Fuzzy logic controller and game theory based distributed energy resources allocation AIMS Energy distributed energy resources fuzzy logic controller game theory cooperative game theory intelligent distribution network |
| title | Fuzzy logic controller and game theory based distributed energy resources allocation |
| title_full | Fuzzy logic controller and game theory based distributed energy resources allocation |
| title_fullStr | Fuzzy logic controller and game theory based distributed energy resources allocation |
| title_full_unstemmed | Fuzzy logic controller and game theory based distributed energy resources allocation |
| title_short | Fuzzy logic controller and game theory based distributed energy resources allocation |
| title_sort | fuzzy logic controller and game theory based distributed energy resources allocation |
| topic | distributed energy resources fuzzy logic controller game theory cooperative game theory intelligent distribution network |
| url | https://www.aimspress.com/article/10.3934/energy.2020.3.474/fulltext.html |
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