A Review of probabilistic methods for defining reserve requirements

Abstract

In this paper we examine potential improvements in how load and generation forecast uncertainty is captured when setting reserve levels in power systems with significant renewable generation penetration and discuss the merit of proposed new methods in this area. One important difference between methods is whether reserves are defined based on the marginal distribution of forecast errors, as calculated from historic data, or whether the conditional distribution, specific to the time at which reserves are being scheduled, is used. This paper is a review of published current practice in markets which are at the leading edge of this problem, summarizing their experiences, and aligning it with academic modeling work. We conclude that the ultimate goal for all markets expected to manage high levels of renewable generation should be a reserve setting mechanism which utilizes the best understanding of meteorological uncertainties combined with traditional models of uncertainty arising from forced outages.