Estimation of ESS and DR Requirements Based on Stocastic Reliability Analysis

Probabilistic models of renewable energy (RE) generation have been adopted to evaluate reliability indices using the Monte Carlo (MC) stochastic simulation method over the past years. However, with an increasing number of new energy sources injected into the future grid, the existing analysis methods are obsolete. This paper integrates the decision operating model of energy storage systems (ESS) and demand response (DR) behavior model into the existing probabilistic reliability analysis method. According to respective ESS owners, ESSs are divided into grid type and user type. Furthermore, the price-incentive DR load model is combined in the method to simulate consumer behaviors. The Taiwan Power system, which is an isolated grid with a 37 GW peak load and expected 20% RE penetration, is employed as a case study. According to the proposed method, the most suitable DR compensation price and ESS installed capacity are analyzed to decrease system investment and maintain system reliability in this paper.