Energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading

Abstract

With the penetration of large amounts of renewable energy resources into energy system, the interaction between energy supply and demand has become more complex and diverse. The complexity and diversity make it more difficult to achieve real-time, efficient, accurate and dynamic matching of energy supply and demand. Therefore, the study proposes an efficient energy supply-demand interaction model integrating uncertainty forecasting and peer-to-peer energy trading. First, to reduce the impact of supply and demand uncertainty on the energy supply and demand matching, gate recurrent unit and long short-term memory models are used to forecast power generation and consumption. Then, based on the results of forecasting, an energy supply-demand interaction model is proposed to assist the energy system in achieving dynamic energy supply-demand matching. Finally, the effectiveness of the proposed energy supply-demand interaction model has been verified through experiments. The proposed energy supply-demand interaction model that considers supply and demand uncertainty and economic benefits helps to better achieve transparent, efficient, stable, and sustainable matching of supply and demand. This study can reduce the impact of supply and demand uncertainty by forecasting power generation and consumption. In addition, this study considers the preferences of prosumers in their trading, reduces the cost of electricity for prosumers, and realizes the profitability of multiple subjects involved in the trading.