My peer-reviewed paper, A Financial Algorithm for Computing the Levelized Cost of Storing PV Electricity (LCOS),was presented at Solar Power International 2017 (SPI-17), 10-13 Sept., Las Vegas.
Abstract— This paper discusses the financial and technical principles underlying the levelized cost method of computing the cost of storing solar (PV) electricity (LCOS). The paper presents a levelized cost (LC) algorithm. The algorithm uses nine recognized energy storage system (EES) specifications to compute the levelized cost of the stored electricity. The algorithm equations are presented. Published ESS specifications are cited. For rapid computation, a worksheet is provided. The goal of this paper is to present a standard computational algorithm for financial analysts to use. A financial analyst can do a levelized cost computation based on paper’s LC algorithm and on the algorithm’s nine ESS specifications. The paper’s algorithm gives the analyst who has an ESS specifications, a quick “back of the envelope” verification of a developer’s (utility-scale), manufacturer’s (C & I; residential), or researcher’s (prototype) value for the cost (US$/MWh; €/MWh) of energy storage.
This paper also has a case study that demonstrates how to obtain/develop the nine ESS specs. Published specs for the Eos Aurora® (a utility-scale [1 MW│ 4 MWh] DC battery ESS manufactured by Eos Energy Storage) and Cabin Creek (a utility-scale [300 MW │ 1,450 MWh] Pumped Hydro ESS in Clear Creek County, CO owned by Xcel Energy) are used in the case study. Because the ESS CapEx is a required spec, the LC algorithm can also be the basis for an ESS financial (valuation. A second paper will compute the LC of using an ESS to provide ancillary services (frequency and voltage stabilization plus VARS). The paper has now been revised (Version 2.00) to take into account the suggestions of the SPI-17 attendees