The dependence of quantile power prices on supply from renewables

Understanding power prices dynamics is crucial for valuing flexibility assets such as storage or flexible consumption facilities that accommodate fluctuations in supply from variable renewables. Owners of need to know how extreme can become order optimally manage (dis)charging adjusting volumes. We examine predict those high and low prices, being the different quantiles price probability distribution function, question renewable sources affect quantile prices. The first contribution our paper we apply regressions a panel data framework. This methodology acknowledges day-ahead markets’ structured cross-sectional and, opposed previous regression techniques introduced markets, allows simultaneous predictions all hours during delivery day. Day-ahead 24 h next day are determined at same moment, one before delivery. hourly therefore not time-series, but cross section. second interaction between demand sources, instead linear dependencies only. find lower higher more heavily affected by variations than centre enables owners better their anticipation excess scarce sources. By doing so, they increase systems face increasing installed capacity energy