Renewable Energy Integration through Coalition Formation for P2P Energy Trading

Abstract

Renewable energy sources are highly unreliable; hence prosumers connected to renewable energy sources find unreliable energy surplus and demands which should be managed frequently within neighbourhoods. Peer-to-peer(P2P) energy trading has emerged as the next-generation energy management mechanism to manage unreliability concerns within local communities. This process needs a prosumer with energy demand to join with a set of prosumers with energy surpluses to fulfil the energy need. Finding the optimal set of prosumers with energy surpluses is a challenge that is not yet duly addressed in literature considering the unreliability of energy sources and constraints in local communities. This paper presents a game-theoretic approach, applies coalition formation game theory supported by a clustering-based approach and solves an optimisation problem to find optimal coalitions. The optimal coalitions are the winning coalitions found from our coalition formation game. This game considers frequent change of energy surpluses and demands, distance to prosumers, the quantity of energy sale, and dynamic clustering on potential coalitions. The payoff will calculate the quantity of energy sale. We used a multi-threading and parallel computing approach to find the optimal size of the cluster that gives winning coalitions. We implemented our clusteringbased coalition formation algorithm in Java. We tested for the efficiency and success rate using a residential PV energy production and consumption data set from California state in the USA. We compared the number of successful coalitions resulted from our algorithm with the hierarchical coalition formation algorithm(HCF) in literature. Our experimental results showed that both the sizes of the neighbourhood and sizes of the cluster have a significant impact on the number of successful coalitions and the proposed algorithm has a higher success rate compared to the HCF algorithm.

Social Factors in P2P Energy Trading Using Hedonic Games

“…To form coalitions, a prosumer first must meet its demand from its solar panels, then calculate its surplus or deficit, and then, based on price thresholds of coalitions and available energy prices will be engaged in P2P trading. Coalitional game theory is used in [26] to find the winning coalitions that will play the game of optimizing the energy transfer within a community of prosumers that aim to operate independently from the main grid. Frequent changes in energy demand and generation are considered as well as a utility function that computes the coalition energy availability when all prosumers act together.…”

Optimal Battery Energy Storage System Scheduling within Renewable Energy Communities

“…BESS scheduling optimization using MILP techniques with the objective of increasing RES self-consumption is explored in [50], while the multi-objective optimization carried out by [51] had cost and emissions reductions as main goals. Collaborative approaches are also investigated, involving demand response management of residential loads and optimal scheduling of BESS [52,53] with the objective of establishing P2P energy trading [54,55]. Multi-time-scale models such as in [56] and [57] try to deal with load and generation forecast errors, adjusting in real time the day-ahead scheduling previously prepared.…”

Coalition Formation among the Cooperative Agents for Efficient Energy Consumption

“…Clustering is one effective method in WSN [34][35][36][37][38] to save energy and maximize network life. In the cluster system, WSN nodes are divided into clusters and the cluster header (CH) acts as a node to coordinate other members of each cluster.…”