Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research
The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-01-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/1/186 |
| _version_ | 1811306959234662400 |
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| author | Pavlos S. Georgilakis |
| author_facet | Pavlos S. Georgilakis |
| author_sort | Pavlos S. Georgilakis |
| collection | DOAJ |
| description | The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area. |
| first_indexed | 2024-04-13T08:56:04Z |
| format | Article |
| id | doaj.art-eb48149624954bd4ba31e6c6b217703d |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T08:56:04Z |
| publishDate | 2020-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-eb48149624954bd4ba31e6c6b217703d2022-12-22T02:53:19ZengMDPI AGEnergies1996-10732020-01-0113118610.3390/en13010186en13010186Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future ResearchPavlos S. Georgilakis0School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), 15780 Athens, GreeceThe massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area.https://www.mdpi.com/1996-1073/13/1/186aggregatorartificial intelligencecomputational intelligencedistributed energy resourcesdistributed generationdistribution systems operationlocal energy marketssmart distribution systemtransactive energy |
| spellingShingle | Pavlos S. Georgilakis Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research Energies aggregator artificial intelligence computational intelligence distributed energy resources distributed generation distribution systems operation local energy markets smart distribution system transactive energy |
| title | Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research |
| title_full | Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research |
| title_fullStr | Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research |
| title_full_unstemmed | Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research |
| title_short | Review of Computational Intelligence Methods for Local Energy Markets at the Power Distribution Level to Facilitate the Integration of Distributed Energy Resources: State-of-the-art and Future Research |
| title_sort | review of computational intelligence methods for local energy markets at the power distribution level to facilitate the integration of distributed energy resources state of the art and future research |
| topic | aggregator artificial intelligence computational intelligence distributed energy resources distributed generation distribution systems operation local energy markets smart distribution system transactive energy |
| url | https://www.mdpi.com/1996-1073/13/1/186 |
| work_keys_str_mv | AT pavlossgeorgilakis reviewofcomputationalintelligencemethodsforlocalenergymarketsatthepowerdistributionleveltofacilitatetheintegrationofdistributedenergyresourcesstateoftheartandfutureresearch |