Energy Community Management Based on Artificial Intelligence for the Implementation of Renewable Energy Systems in Smart Homes

Author:

Khayyat Manal Mahmoud1ORCID,Sami Benslama2ORCID

Affiliation:

1. Department of Computer Science and Artificial Intelligence, College of Computers, Umm Al-Qura University, Makkah 24382, Saudi Arabia

2. Faculty of Applied Studies, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Abstract

The trade, control, and management of transactive energy have gained significant relevance and are receiving a lot of interest from academia and industry. New strategies for their progress and implementation are emerging. The prosumer concept involves the integration of household loads with solar PV and battery storage systems. It is suggested as a practical technique to include renewable energy sources and reduce strain on the distribution grid. This study indicates establishing a home-smart community connected to a power grid, explicitly emphasizing prosumers. The district employs cooperative game theory to enable the sharing, controlling, and coordinating of excess energy generated by distributed energy resources (DERs) with neighboring prosumers experiencing energy shortages. The energy community examined in this study comprises six identical prosumers, encompassing residential energy use, solar photovoltaic (PV) installations, and battery storage systems. Furthermore, the community consists of an energy community manager and an energy retailer, both tied to a distribution system. The intended market model assesses the economic advantages of incorporating renewable sources into a centralized transactive energy trading system This approach reduces transaction costs and power expenditures, offering cost savings to producers and consumers. The results show that the suggested intelligent method has successfully decreased consumer electricity costs in various circumstances. Indeed, the proposed approach seeks to oversee the exchange, organization, and control of the community’s household electricity consumption effectively. Furthermore, its objective is to diminish energy usage, enhance system effectiveness, and minimize operational strain and carbon emissions.

Funder

Deanship of Scientific Research at Umm Al-Qura University

Publisher

MDPI AG

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