Three-Party Energy Management With Distributed Energy Resources in Smart Grid (1406.5794v1)

Abstract: In this paper, the benefits of distributed energy resources (DERs) are considered in an energy management scheme for a smart community consisting of a large number of residential units (RUs) and a shared facility controller (SFC). A non-cooperative Stackelberg game between RUs and the SFC is proposed in order to explore how both entities can benefit, in terms of achieved utility and minimizing total cost respectively, from their energy trading with each other and the grid. From the properties of the game, it is shown that the maximum benefit to the SFC in terms of reduction in total cost is obtained at the unique and strategy proof Stackelberg equilibrium (SE). It is further shown that the SE is guaranteed to be reached by the SFC and RUs by executing the proposed algorithm in a distributed fashion, where participating RUs comply with their best strategies in response to the action chosen by the SFC. In addition, a charging-discharging scheme is introduced for the SFC's storage device (SD) that can further lower the SFC's total cost if the proposed game is implemented. Numerical experiments confirm the effectiveness of the proposed scheme.

• The paper introduces a Stackelberg game-theoretic model that optimally prices energy trading between residential DERs and a shared facility controller.
• The study develops a decentralized algorithm that drives the system toward equilibrium while ensuring truthful energy reporting from all participants.
• Numerical experiments demonstrate up to 74.9% cost savings in energy procurement, underscoring the practical benefits of the proposed strategy.

A Game-Theoretic Approach to Energy Management in Smart Grids with Distributed Energy Resources

This paper, titled "Three-Party Energy Management With Distributed Energy Resources in Smart Grid," proposes an energy management scheme focusing on the deployment of distributed energy resources (DERs) within a smart grid context. The paper tackles a distributed energy market design involving residential units (RUs) and a shared facility controller (SFC) through the lens of non-cooperative Stackelberg game theory. The integration of game-theoretic principles is a strategic approach to efficiently manage energy distribution and trading between RUs, the SFC, and the main electricity grid.

Core Contributions

This research makes several significant contributions to the current understanding and methodologies in smart grid energy management:

1. System and Model Design: The authors propose a new system framework involving a smart grid that includes multiple RUs equipped with DERs and an SFC. The model accounts for energy trading properties between these entities without relying on centralized storage.
2. Stackelberg Game Theoretic Framework: The paper innovatively employs a Stackelberg game framework to model interactions between the SFC and RUs. The SFC, functioning as the leader, determines the optimal buying price per unit of energy from RUs to minimize its total energy cost incurred when purchasing from both the RUs and the main grid. Meanwhile, RUs, as followers, adjust their energy consumption to maximize utility.
3. Decentralized Algorithm: The paper presents a distributed algorithm that guides the players in the game — the SFC and RUs — towards the Stackelberg equilibrium (SE). This equilibrium ensures optimal pricing strategies for the SFC while enabling each RU to achieve maximal utility from its energy resources.
4. Strategy-Proof Mechanism: The game design ensures that RUs are motivated to report truthfully regarding their energy availability and consumption, avoiding untruthful strategies that could deviate from Nash equilibrium outcomes.
5. Inclusion of Storage Capabilities: The research is further extended to incorporate storage units at the SFC, regulated by a charging-discharging scheme dependent on fluctuating grid prices, intended to optimize the cost-effectiveness further.

Numerical Achievements and Implications

The paper conducts numerical experiments affirming the game's practicality and effectiveness in various scenarios concerning the number of RUs and their energy generation capabilities. Key numerical results demonstrate a substantial reduction in the SFC's energy procurement costs. For instance, average cost savings up to 74.9% are observed when comparing the communication among RUs and the SFC facilitated by the proposed Stackelberg game to a centralized solution without DERs.

Practical and Theoretical Considerations

The theoretical foundations of utilizing Stackelberg game dynamics in this grid set a precedent for future research in similar multi-agent energy environments, particularly those leveraging DERs. Practically, the authors outline a viable path toward enabling more decentralized, flexible energy markets within smart grids. This decentralized approach not only optimizes cost but inherently aligns with the dynamic nature of renewable energy sources characterized by variability and intermittency.

Future Directions

The authors suggest several avenues for potential exploration:

• The introduction of diverse pricing strategies and incentive mechanisms to enhance and broaden player participation in the energy market.
• Investigation into the influence of the grid's price fluctuations on the decision-making of RUs and SFC, potentially incorporating predictive analytics for price volatility management.
• Expansion of modeling frameworks to encapsulate more sophisticated load management techniques involving machine learning tools for demand forecasting and optimization.

In conclusion, the paper lays the groundwork for advanced energy management strategies in smart grids, notably by leveraging game-theoretic constructs to orchestrate decentralized energy trading. This research highlights the advantages of utilizing cooperative paradigms coupled with strategic pricing to foster more resilient and efficient energy consumer environments. The results provide a critical foundation upon which future research and practical deployments can build, seeking to enhance the flexibility and sustainability of smart grid systems.