Optimizing Power Exchange Cost Considering Behavioral Intervention in Local Energy Community

Pratik Mochi, Kartik Pandya, Joao Soares () and Zita Vale
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Pratik Mochi: Department of Electrical Engineering, Chandubhai S Patel Institute of Technology (CSPIT), Charotar University of Science and Technology, CHARUSAT Campus, Changa 388421, India
Kartik Pandya: Independent Researcher, Anand 388001, India
Joao Soares: GECAD—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, Portugal
Zita Vale: School of Engineering, Polytechnic of Porto, 4249-015 Porto, Portugal

Mathematics, 2023, vol. 11, issue 10, 1-15

Abstract: 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.

Keywords: behavioral economics; cost optimization; energy community; energy conservation; energy economics; energy policy; local electricity market; renewable energy; social nudge (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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