Key points are not available for this paper at this time.
This paper presents a methodology for estimating the optimal amount of automatic frequency restoration reserve provided by an aggregation of renewable power plants. The increasing penetration of distributed weather-dependent renewable generation presents a challenge to grid operators. Wind and photovoltaic power plants are technically able to provide ancillary services, but their stochastic behavior currently hinders their integration into reserve mechanisms. In the methodology developed a quantile regression forest model is used to forecast the aggregated production and a copula-based approach integrates the dependence between prices and renewable production. We then propose and compare three strategies to derive an optimal quantile of the combined production forecasts that can be used as basis to provide a reliable ancillary service to the System Operator. The methodology is evaluated using historical prices for energy and automatic frequency restoration reserve along with production measurements from the several renewable power plants.
Camal et al. (Thu,) studied this question.