Virtual Power Plants (VPPs) are fast emerging as a viable means of integrating small and distributed energy resources (DERs), like wind and solar, into the electricity supply network (Grid). VPPs are formed via the aggregation of a large number of DERs, so that they exhibit the characteristics of a traditional generator in terms of predictability and robustness. In this work, we promote the formation of such “cooperative” VPPs (CVPPs) using techniques from the field of distributed Artificial Intelligence and game theory. In particular, we design a payment mechanism that encourages DERs to join CVPPs with increased size and visibility to the network operator. Our method is based on strictly proper scoring rules and incentivises the provision of accurate predictions of expected electricity generation from member DERs, which aids in the planning of the supply schedule at the Grid. We empirically evaluate our approach using the real-world setting of 16 commercial wind farms in the UK, and we show that it incentivises real DERs to form CVPPs, and outperforms the current state of the art payment mechanism developed for this problem.

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Virtual Power Plants (VPPs) are fast emerging as a suitable means of integrating small and distributed energy resources (DERs), like wind and solar, into the electricity supply network (Grid). VPPs are formed via the aggregation of a large number of such DERs, so that they exhibit the characteristics of a traditional generator in terms of predictability and robustness. In this work, we promote the formation of such "cooperative" VPPs (CVPPs) using multi-agent technology. In particular, we design a payment mechanism that encourages DERs to join CVPPs with large overall production. Our method is based on strictly proper scoring rules and incentivises the provision of accurate predictions from the CVPPs - and in turn, the member DERs - which aids in the planning of the supply schedule at the Grid. We empirically evaluate our approach using the real-world setting of 16 commercial wind farms in the UK. We show that our mechanism incentivises real DERs to form CVPPs, and outperforms the current state of the art payment mechanism developed for this problem.@en

We propose a new scheme for efficient demand side management for the Smart Grid. Specifically, we envisage and promote the formation of cooperatives of medium-large consumers and equip them (via our proposed mechanisms) with the capability of regularly participating in the existing electricity markets by providing electricity demand reduction services to the Grid. Based on mechanism design principles, we develop a model for such cooperatives by designing methods for estimating suitable reduction amounts, placing bids in the market and redistributing the obtained revenue amongst the member agents. Our mechanism is such that the member agents have no incentive to show artificial reductions with the aim of increasing their revenues.@en

The creation of Virtual Power Plants (VPPs) has been suggested in recent years as the means for achieving the cost-efficient integration of the many distributed energy resources (DERs) that are starting to emerge in the electricity network. In this work, we contribute to the development of VPPs by offering a game-theoretic perspective to the problem. Specifically, we design cooperatives (or "cooperative VPPs"-CVPPs) of rational autonomous DER-agents representing small-to-medium size renewable electricity producers, which coalesce to profitably sell their energy to the electricity grid. By so doing, we help to counter the fact that individual DERs are often excluded from the wholesale energy market due to their perceived inefficiency and unreliability. We discuss the issues surrounding the emergence of such cooperatives, and propose a pricing mechanism with certain desirable properties. Specifically, our mechanism guarantees that CVPPs have the incentive to truthfully report to the grid accurate estimates of their electricity production, and that larger rather than smaller CVPPs form; this promotes CVPP efficiency and reliability. In addition, we propose a scheme to allocate payments within the cooperative, and show that, given this scheme and the pricing mechanism, the allocation is in the core and, as such, no subset of members has a financial incentive to break away from the CVPP. Moreover, we develop an analytical tool for quantifying the uncertainty about DER production estimates, and distinguishing among different types of errors regarding such estimates. We then utilize this tool to devise protocols to manage CVPP membership. Finally, we demonstrate these ideas through a simulation that uses real-world data.@en