A novel forecasting method based on the economic and demand response for FC/WT/PV unit and a 3 in 1 TES energy storage

Abstract

Due to the lack of distribution resources and increasing demand in the daily market, the use of renewable resources is increasing. But renewable sources and market prices are uncertain behavior and cause economic problems. This paper introduces a novel market participation model include wind turbine, photovoltaic, fuel cell integrated with a novel hybrid TES energy storage system (3 in 1 concept) to minimize cost and improve load demand reliability. Also, to solve he mentioned problem a novel forecasting method are proposed. This model is a new multi artificial neural network based on the complete ensemble empirical mode decomposition which is coupled with Tanh function and using RMSE, MAPE and NMAE method the error rate of the proposed method is calculated. By using this method, the forecasting accuracy is improved and also with a novel energy storage the economic issue and market reliability are improved. Also, using the stochastic model the uncertainty system's behavior are modeled to obtain an accurate results of market participation and increase demand supply. Finally, a testing system includes wind turbine/photovoltaic/fuel cell/storage system and demand response are used to prove the superiority of the proposed model in comparison to other models.