Optimizing size of variable renewable energy sources by incorporating energy storage and demand response

Abstract

The electricity sector contributes to most of the global warming emissions generated from fossil fuel resources which are becoming rare and expensive due to geological extinction and climate change. It urges the need for less carbon-intensive, inexhaustible Renewable Energy Sources (RES) that are economically sound, easy to access and improve public health. The carbon-free salient feature is the driving motive that propels widespread utilization of wind and solar RES in comparisons to rest of RES. However, stochastic nature makes these sources, variable renewable energy sources (VRES) because it brings uncertainty and variability that disrupt power system stability. This problem is mitigated by adding energy storage (ES) or introducing the demand response (DR) in the system. In this paper, an electricity generation network of China by the year 2017 is modeled using EnergyPLAN software to determine annual costs, primary energy supply (PES) and CO2 emissions. The VRES size is optimized by adding ES and DR (daily, weekly, or monthly) while maintaining critical excess electricity production (CEEP) to zero. The results substantiate that ES and DR increase wind and solar share up to 1000 and 874 GW. In addition, it also reduces annual costs and emissions up to 4.36 % and 45.17 %.