Transforming Energy Networks via Peer to Peer Energy Trading: Potential of Game Theoretic Approaches (1804.00962v1)

Abstract: Peer-to-peer (P2P) energy trading has emerged as a next-generation energy management mechanism for the smart grid that enables each prosumer of the network to participate in energy trading with one another and the grid. This poses a significant challenge in terms of modeling the decision-making process of each participant with conflicting interest and motivating prosumers to participate in energy trading and to cooperate, if necessary, for achieving different energy management goals. Therefore, such decision-making process needs to be built on solid mathematical and signal processing tools that can ensure an efficient operation of the smart grid. This paper provides an overview of the use of game theoretic approaches for P2P energy trading as a feasible and effective means of energy management. As such, we discuss various games and auction theoretic approaches by following a systematic classification to provide information on the importance of game theory for smart energy research. Then, the paper focuses on the P2P energy trading describing its key features and giving an introduction to an existing P2P testbed. Further, the paper zooms into the detail of some specific game and auction theoretic models that have recently been used in P2P energy trading and discusses some important finding of these schemes.

• The paper demonstrates that game theoretic approaches significantly enhance P2P energy trading by optimizing strategic interactions among prosumers.
• It employs methodologies like Nash equilibria, coalition, and Stackelberg games to balance supply and demand across EVs, DER, and storage domains.
• Results show reduced energy loss, lower electricity costs, and improved network performance, validating the potential of decentralized energy systems.

Game Theoretic Approaches in Peer-to-Peer Energy Trading for Smart Grids

This paper explores an innovative approach for transforming energy networks through peer-to-peer (P2P) energy trading, a concept gaining traction within the smart grid paradigm. The researchers present a comprehensive analysis of employing game theoretic methodologies for managing P2P energy trading, underscoring the pivotal role of game theory in optimizing smart energy networks.

Overview of Game Theory in Smart Energy

Game theory has been extensively applied in various domains of smart energy management, including electric vehicles (EVs), distributed energy resources (DERs), and energy services. The integration of EVs into the grid necessitates sophisticated coordination strategies to optimize energy consumption and support grid services. Techniques such as Nash equilibria, coalition games, and Stackelberg games are employed to design decision-making frameworks that enhance energy trading, particularly in EVs via vehicle-to-grid interactions. In the DER and storage domain, game theory facilitates efficient energy trading, resource management, and incentive structures, highlighting its versatility and adaptability.

P2P Energy Trading: A Novel Paradigm

The paper delineates P2P energy trading as a decentralized model enabling direct energy transactions among prosumers. In this setup, traditional grid dependencies are minimized, and local energy production and consumption are emphasized, fostering a sustainable community-based approach. The Brooklyn Microgrid is presented as a real-world pilot illustrating the feasibility and benefits of this model.

Application of Game Theory in P2P Energy Trading

In P2P networks, game theoretic frameworks are adapted to address strategic interactions among participants. The authors categorize energy trading applications into three domains: EVs, DER and storage, and services. Each domain employs distinct game theoretic models:

1. EV Domain: An auction-based approach is utilized for P2P energy trading among EVs, integrated with consortium blockchains to ensure transaction security and user privacy. The auction process strategically balances supply and demand while maximizing social welfare.
2. DER and Storage Domain: Coalition games are deployed to manage energy trading between small-scale producers and end-users. By leveraging a canonical coalitional game model, revenue distribution among participants is optimized, ensuring stable and equitable P2P trading.
3. Service Domain: The integration of auction games with Stackelberg models facilitates service provision in P2P networks, emphasizing energy storage sharing. This hybrid approach yields robust demand response services, optimizing both residential and shared facility energy storage needs.

Results and Implications

The numerical analysis presented demonstrates the efficacy of the game-theoretic approaches in enhancing energy trading outcomes. In the EV domain, localized trading leads to reduced energy loss and increased system efficiency compared to hybrid models. In DER and storage, P2P trading significantly decreases electricity costs for end-users, while optimizing the blend of renewable sources enhances overall network performance. In service domains, residential participants benefit from increased utility through strategic storage sharing, outperforming traditional schemes.

Future Directions

The paper identifies several research avenues for advancing P2P energy trading. Key areas include consumer-centric models, regulatory integration, security enhancements using blockchain, and addressing challenges of incomplete information. Moreover, incorporating physical constraints such as Kirchhoff’s laws into game-theoretic frameworks presents an intriguing yet complex challenge.

In essence, the paper underscores the transformative potential of game-theoretic approaches in reimagining energy networks. By fostering efficient and secure P2P energy trading, these methodologies present a pathway towards decentralized, sustainable, and consumer-focused energy systems.