Abstract
Peer-to-peer (P2P) energy trading is referred to as flexible energy trades between peers, where the excessive energy from many small-scale Distributed Energy Resources (DERs) including those in dwellings, offices, factories, etc., is traded among local customers. To assess the feasibility of P2P energy trading, where local electricity demand and supply balancing is desired, a so-called P2P index was developed. By clustering the historical smart metering data using the k-means method, customers were categorized by their electricity consumption patterns and representative demand profiles of low voltage electrical distribution networks were produced. A linear programming optimization was carried out to find the optimal capacity of different DERs to maximize the local demand and supply balancing. PV systems and combined heat and power units were considered as the renewable resources. This work provides network planners with guidelines of appropriate shares of DERs for better constructing their future networks, and facilitates a P2P energy trading market paradigm.
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