Dynamic allocation of peer-to-peer clusters in virtual local electricity markets: A marketplace for EV flexibility

Abstract Local Electricity Markets (LEM) and peer-to-peer trading are new mechanisms to encourage the uptake of solar PV and to support the emergence of consumer-centric electricity markets. However, the coordination to trade between consumers and prosumers has different definitions depending on the context and features of the energy system. This paper introduces a new vision: creating virtual LEMs by cooperatively mixing (optimal matching) different load and renewable profiles that complement each other. Since consumer and prosumer profiles change every day (weather conditions or demand behaviors), the dynamic formation of virtual LEMs changes daily. To reward flexibility, Electric Vehicles (EV) are also pooled into forming a virtual LEM. That is, we investigate: What is the value of creating virtual local markets (via clustering)?, and what is the impact of EV flexibility on the creation of virtual LEMs? Through implementing a LEM optimization model with a clustering approach, we analyze the formation of LEMs for a set of end-users in London. Results indicate that a single large LEM (no clustering) is comparatively similar to multiple LEMs (clustering). EV flexibility obtains more revenue in this new marketplace. Findings are encouraging as dynamic virtual LEMs can enable, accelerate and bring scalability for a ubiquitous deployment of LEMs.