Coalitional Game Theory based Value Sharing in Energy Communities

This paper presents a coalitional game for value sharing in energy communities (ECs). It is proved that the game is super-additive, and the grand coalition effectively increases the global payoff. It is also proved that the model is balanced and thus, it has a nonempty core. This means there always exists at least one value sharing mechanism that makes the grand coalition stable. Therefore, prosumers will always achieve lower bills if they join to form larger ECs. A counterexample is presented to demonstrate that the game is not convex and value sharing based on Shapley values does not necessarily ensure the stability of the coalition. To find a stabilizing value sharing mechanism that belongs to the core of the game, the worst-case excess minimization concept is applied. In this concept, however, size of the optimization problem increases exponentially with respect to the number of members in EC. To make the problem computationally tractable, the idea of clustering members based on their generation/load profiles and considering the same profile and share for members in the same cluster is proposed here. K-means algorithm is used for clustering prosumers’ profiles. This way, the problem would have several redundant constraints that can be removed. The redundant constraints are identified and removed via the generalized Llewellyn’s rules. Finally, value sharing in an apartment building in the southern part of Finland in the metropolitan area is studied to demonstrate effectiveness of the method

State-Of-The-Art and Prospects for Peer-To-Peer Transaction-Based Energy System

Transaction-based energy (TE) management and control has become an increasingly relevant topic, attracting considerable attention from industry and the research community alike. As a result, new techniques are emerging for its development and actualization. This paper presents a comprehensive review of TE involving peer-to-peer (P2P) energy trading and also covering the concept, enabling technologies, frameworks, active research efforts and the prospects of TE. The formulation of a common approach for TE management modelling is challenging given the diversity of circumstances of prosumers in terms of capacity, profiles and objectives. This has resulted in divergent opinions in the literature. The idea of this paper is therefore to explore these viewpoints and provide some perspectives on this burgeoning topic on P2P TE systems. This study identified that most of the techniques in the literature exclusively formulate energy trade problems as a game, an optimization problem or a variational inequality problem. It was also observed that none of the existing works has considered a unified messaging framework. This is a potential area for further investigation

Realizing the potential of distributed energy resources and peer-to-peer trading through consensus-based coordination and cooperative game theory

Driven by environmental and energy security concerns, a large number of small-scale distributed energy resources (DERs) are increasingly being connected to the distribution network. This helps to support a cost-effective transition to a lower-carbon energy system, however, brings coordination challenges caused by variability and uncertainty of renewable energy resources (RES). In this setting, local flexible demand (FD) and energy storage (ES) technologies have attracted great interests due to their potential flexibility in mitigating the generation and demand variability and improving the cost efficiency of low-carbon electricity systems. The combined effect of deregulation and digitalization inspired new ways of exchanging electricity and providing management/services on the paradigm of peer-to-peer (P2P) and transparent transactions. P2P energy trading enables direct energy trading between prosumers, which incentivizes active participation of prosumer in the trading of electricity in the distribution network, in the meantime, the efficient usage of FD and ES owned by the prosumers also facilitates better local power and energy balance. Though the promising P2P energy trading brings numerous advancements, the existing P2P mechanisms either fail to coordinate energy in a fully distributed way or are unable to adequately incentivize prosumers to participate, preventing prosumers from accessing the highest achievable monetary benefits and/or suffering severely from the curse of dimensionality. Therefore, this thesis aims at proposing three P2P energy trading enabling mechanisms in the aspect of fully distributed efficient balanced energy coordination through consensus-based algorithm and two incentivizing pricing and benefit distribution mechanisms through cooperative game theory. Distributed, consensus-based algorithms have emerged as a promising approach for the coordination of DER due to their communication, computation, privacy and reliability advantages over centralized approaches. However, state-of-the-art consensus-based algorithms address the DER coordination problem in independent time periods and therefore are inherently unable to capture the time-coupling operating characteristics of FD and ES resources. This thesis demonstrates that state-of-the-art algorithms fail to converge when these time-coupling characteristics are considered. In order to address this fundamental limitation, a novel consensus-based algorithm is proposed which includes additional consensus variables. These variables express relative maximum power limits imposed on the FD and ES resources which effectively mitigate the concentration of the FD and ES responses at the same time periods and steer the consensual outcome to a feasible and optimal solution. The convergence and optimality of the proposed algorithm are theoretically proven while case studies numerically demonstrate its convergence, optimality, robustness to initialization and information loss, and plug-and-play adaptability. Moreover, this thesis proposes two computationally efficient pricing and benefit distribution mechanisms to construct a stable grand coalition of prosumers participating in P2P trading, founded on cooperative game-theoretic principles. The first one involves a benefit distribution scheme inspired by the core tatonnement process while the second involves a novel pricing mechanism based on the solution of single linear programming. The performance of the proposed mechanisms is validated against state-of-the-art mechanisms through numerous case studies using real-world data. The results demonstrate that the proposed mechanisms exhibit superior computational performance than the nucleolus and are superior to the rest of the examined mechanisms in incentivizing prosumers to remain in the grand coalition.Open Acces

Comparing Value Sharing Methods for Different Types of Energy Communities

Energy communities combine assets of different community members and can create financial value from energy trade and from providing flexibility. Sharing this value among the community members can be done in various ways depending on the main objectives of the energy community and selecting the most suitable value sharing method for a particular energy community is not always straightforward. There are several, partly contradictory, requirements to be fulfilled that include fairness, stability, understandability, computational feasibility and ability to incentivize individual members to act in a way that benefits the whole energy community. In this paper, alternative energy community value sharing methods are compared from different viewpoints. The most suitable value sharing method for a particular energy community can be selected by first defining what are the main requirements for value sharing and then proceeding to a more detailed analysis of the value sharing method options that fulfill those requirements.acceptedVersionPeer reviewe

Self-organizing Coordination of Multi-Agent Microgrid Networks

abstract: This work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.Dissertation/ThesisDoctoral Dissertation Systems Engineering 201