Peer-to-peer energy trading in microgrids: A game-theoretic approach
Malik, Sweta
Malik, Sweta
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Publication Date
2024-03-20
Type
Thesis
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Abstract
As the world transitions from the traditional centralized power system towards a decentralized model with the widespread integration of distributed energy resources (DERs), the struggle for demand-supply flexibility becomes increasingly apparent. Despite the significant strides in net metering initiatives and integration of DERs into wholesale markets, these methods do not effectively reward users. An effective approach to optimizing the performance of DERs involves implementing a local energy trading framework based on the Peer-to-Peer (P2P) concept. P2P energy trading strives to enhance the economic advantages for consumers and prosumers (consumers who also generate electricity) by providing them the opportunity to actively engage in energy transactions with neighbouring peers within the distribution network. The key contribution of this dissertation is to develop a P2P energy trading algorithm employing game-theoretical and auction mechanisms approaches. The thesis focuses on two main types of game theory: a) Cooperative game theory and b) Non-Cooperative game theory. Within the realm of cooperative game theory, a novel priority-based Approach is proposed to manage energy interactions and transactions within a Local Energy Community (LEC), facilitating the formation of a stable and optimized grand coalition. The resultant coalition effectively maximizes the economic benefits for both prosumers (by increasing their revenue) and consumers (by offering savings on electricity bills). Non-cooperative game theory-based trading algorithm is also developed in this work, with the objective of optimizing the outcomes of individual participants through bipartite directed graphs and strategic decision-making. The developed trading algorithm utilizes Fractional Hedonic Games (FHG) and preference parameters to form stable and efficient coalitions that maximize individual gains. A valuation function matrix is generated to calculate the payoff between pairs of participants, facilitating the selection of the most advantageous trading pairs. Finally, a comparative analysis between the cooperative and non-cooperative game theory approaches is deployed in a microgrid, and economic analysis is evaluated. Furthermore, this dissertation introduces a comparative framework for the double action mechanism. It compares four double-action mechanisms namely (Average, McAfee, Trade Reduction, and Vickrey-Clarke-Groves) for P2P energy trading. The proposed algorithm is adaptive, catering to diverse user preferences and bidding strategies over various time intervals. Additionally, a novel P2P energy trading algorithm that integrates all four auction mechanisms, various bidding strategies, preference parameters, and time-of-use tariffs is presented. Simulation results are presented on various types of microgrids, extending also to microgrid-to-microgrid energy trading scenarios, thus providing insights into scalability and performance. Towards the end of this research, a blockchain-based decentralized Home Energy Management System (HEMS) to optimize demand response within the microgrid is implemented. In conclusion, this dissertation advances the P2P energy trading framework through the application of game theory and double auction mechanisms. By simulating diverse microgrid and LEC scenarios, it provides novel insights into energy management, market dynamics, and decentralized system scalability, demonstrating the potential of P2P trading for a more sustainable, efficient, and economically viable energy future.
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NUI Galway