The role of risk-based demand response in resource management of a grid-connected renewable-based large-scale microgrid with stationary and mobile energy storage systems and emission tax

Abstract

Integration of energy storage systems with local electricity systems, like microgrids, is emerging due to their economical, reliability, and environmental benefits. These advantages can be achieved by load management subject to the related condition, such as the hour of the day, electricity price, etc. From an economic point of view, energy storage systems can reduce the share of costly power generators in supplying the peak demand. In other words, they can be charged in low-demand hours and discharged in peak-demand hours, when the electricity price is high. In this work, the impact of stationary battery storage and electric vehicles on the resource management of a large-scale microgrid is assessed through a stochastic model. The understudy microgrid includes also renewable energy sources (namely solar photovoltaic systems and wind turbines) as well as diesel generators. This study considers the uncertainty in the electricity price, where a scenario-based risk management approach is employed to control the risk associated with price uncertainty. The resulting model is implemented in the GAMS software package to be solved by a suitable solver. Numerical simulation of a large-scale microgrid is accomplished to validate the effectiveness of energy storage systems in the economic improvement of the understudy microgrid.