Stochastic Analysis of Dependable Hydropower Capacity

Abstract

Indexed sequential modeling (ISM) has been proposed by the Western Area Power Administration as an alternative approach to developing firm marketable capacity, i.e., project‐dependable hydropower capacity (PDC), in contrast with the usual approach of basing PDC on the most adverse period of record. ISM allows a probabilistic analysis of hydropower capacity by extracting a series of overlapping short‐term (say, 10 year) inflow sequences directly from the historical record, which includes the most adverse period, and then simulating reservoir operations over this interval for each sequence. As a means of evaluating ISM, the New Melones Reservoir system in the federal Central Valley Project of California was selected as a case study for comparing hydropower output generated from ISM input with use of a multivariate stochastic inflow generation model. A comparison of monthly power and energy output at 95% confidence limits, 10% risk level, and most adverse, showed reasonably good correspondence between the two methods, except for a few months of energy production in the final year of simulation.