Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community
In order to encourage energy saving and the adoption of renewable sources, this study provides a comprehensive experimental framework that integrates socioeconomic and behavioral objectives for the local energy community. The experiment aims to find out how successfully using behavioral intervention...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/10/2367 |
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| author | Pratik Mochi Kartik Pandya Joao Soares Zita Vale |
| author_facet | Pratik Mochi Kartik Pandya Joao Soares Zita Vale |
| author_sort | Pratik Mochi |
| collection | DOAJ |
| description | In order to encourage energy saving and the adoption of renewable sources, this study provides a comprehensive experimental framework that integrates socioeconomic and behavioral objectives for the local energy community. The experiment aims to find out how successfully using behavioral interventions might encourage customers to save electrical energy and encourage them to adopt renewable energy, e.g., solar photovoltaic energy, in the present case. Using this method, we can calculate the causal impact of the intervention on consumer participation in the local electricity sector. The study uses consumer data on the import and export of electrical power from retailer electricity utilities at a predetermined power exchange price and a midmarket price for local energy community power transactions. The local energy community model simulates the consumption, storage, and export of 20 residential customers who, in different scenarios, are the test subjects of an empirical experiment and embrace electricity conservation and renewable energy. We address the optimization issue of calculating the power exchange cost and revenue in various scenarios and comparing them with the base case cost. The cases are built on the customers’ behavioral interventions’ empirical response. The findings demonstrate that the interaction of socioeconomic and behavioral objectives leads to impressive cost savings of up to 19.26% for energy utility customers. The policy implication is suggested for local energy utilities. |
| first_indexed | 2024-03-11T03:31:46Z |
| format | Article |
| id | doaj.art-e357263f4b7a40339fa68f9003730be3 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T03:31:46Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-e357263f4b7a40339fa68f9003730be32023-11-18T02:19:58ZengMDPI AGMathematics2227-73902023-05-011110236710.3390/math11102367Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy CommunityPratik Mochi0Kartik Pandya1Joao Soares2Zita Vale3Department of Electrical Engineering, Chandubhai S Patel Institute of Technology (CSPIT), Charotar University of Science and Technology, CHARUSAT Campus, Changa 388421, IndiaIndependent Researcher, Anand 388001, IndiaGECAD—Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development, LASI—Intelligent Systems Associate Laboratory, School of Engineering (ISEP)—Polytechnic of Porto, 4200-072 Porto, PortugalSchool of Engineering, Polytechnic of Porto, 4249-015 Porto, PortugalIn order to encourage energy saving and the adoption of renewable sources, this study provides a comprehensive experimental framework that integrates socioeconomic and behavioral objectives for the local energy community. The experiment aims to find out how successfully using behavioral interventions might encourage customers to save electrical energy and encourage them to adopt renewable energy, e.g., solar photovoltaic energy, in the present case. Using this method, we can calculate the causal impact of the intervention on consumer participation in the local electricity sector. The study uses consumer data on the import and export of electrical power from retailer electricity utilities at a predetermined power exchange price and a midmarket price for local energy community power transactions. The local energy community model simulates the consumption, storage, and export of 20 residential customers who, in different scenarios, are the test subjects of an empirical experiment and embrace electricity conservation and renewable energy. We address the optimization issue of calculating the power exchange cost and revenue in various scenarios and comparing them with the base case cost. The cases are built on the customers’ behavioral interventions’ empirical response. The findings demonstrate that the interaction of socioeconomic and behavioral objectives leads to impressive cost savings of up to 19.26% for energy utility customers. The policy implication is suggested for local energy utilities.https://www.mdpi.com/2227-7390/11/10/2367behavioral economicscost optimizationenergy communityenergy conservationenergy economicsenergy policy |
| spellingShingle | Pratik Mochi Kartik Pandya Joao Soares Zita Vale Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community Mathematics behavioral economics cost optimization energy community energy conservation energy economics energy policy |
| title | Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community |
| title_full | Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community |
| title_fullStr | Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community |
| title_full_unstemmed | Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community |
| title_short | Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community |
| title_sort | optimizing power exchange cost considering behavioral intervention in local energy community |
| topic | behavioral economics cost optimization energy community energy conservation energy economics energy policy |
| url | https://www.mdpi.com/2227-7390/11/10/2367 |
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