An algorithm for simulating end-user behaviour in a real time pricing market

Abstract

The energy market has changed radically over the last decade, mainly due to an increased penetration of renewable energies. Now the end users have directly access to the energy market and can actively take part to the electricity market. Electricity customers can indeed modify their behavior through Demand Response, namely by means of pricing strategies that support a change in the end-users habits. This can be accomplished through a 'loads aggregator', a third party that collects the requests and signals for Active Demand-based services coming from the markets and the different actors of energy market. This paper describes a simulation framework to generate the simulated optimal behavior of the electrical users. Based on a given real-time pricing curves the simulator evaluates the power consumption hour by hour if the user behaves according to what the price curve and thus the loads aggregator suggests. A case study shows the advantages/disadvantages of the proposed pricing approach and the limits of the simulator

Case Study of Residential PV Power and Battery Storage with the Danish Flexible Pricing Scheme

“…From the consumers' perspective, the electricity market is mostly a supply of energy, traded for monetary value. This has been coupled with real-time pricing (RTP), to prioritize RES [11][12][13]. In turn, technical advancements in consumer technology and systems have been made to utilize RTP schemes, including behind-the-meter storage (BTMS) systems, where energy storage is installed locally to minimize the electricity bill of the consumers [14][15][16][17][18].…”