Rolling horizon optimisation based peer-to-peer energy trading under real-time variations in demand and generation

Abstract

This paper has developed an approach to optimise energy sell and price bids at the sellers along with optimising energy purchase decisions at the buyers in a peer-to-peer (P2P) energy trading market. The optimum price and energy sell bids are designed to maximise the profit at the sellers, while buyers make energy purchase decisions to minimise their energy deficit. The proposed approach relies on a day-ahead optimisation mechanism that can utilise the daily generation and demand patterns as well as a rolling horizon based real-time update strategy when there are variations in generation or demand forecasts. The aforementioned approach is evaluated for a real-life generation and demand dataset under different scenarios. The numerical results demonstrate that when the forecasting error is not very high, the proposed optimisation approach can allow sellers to obtain some profit in most of the time intervals during the day.