Over the last two decades, researchers have developed techniques and models to establish the total capital costs (TCC) related to installation of electrical energy storage systems (ESSs). There are three major impediments to developing a reliable dataset for the LCC: (1) much of the data needed to properly construct the ESS LCC model depends on proprietary information; (2) newer energy storage technologies do not have a sufficient disposal cost profile; and (3) determination of disposal costs involve uncertainties related to the function, performance, system configuration, and stacking of ESSs. To overcome these three challenges, this study uses a Monte Carlo model to predict and validate life cycle disposal costs. Five battery technologies are considered: lead acid, lithium, sodium sulfur, vanadium redox, and zinc bromine. This study determined that disposal costs are more sensitive to battery lifetime and replacement costs than annual worth, operating costs, and adjusted interest rate.
Logistic regression models can serve as important tools in developing a framework to establish the value of electrical energy storage systems (ESSs). This study provides models that aggregate use-case scenarios of five battery types, as well as pumped hydro-electric storage systems. The grid applications include: bulk energy at generation, auxiliary services at transmission and distribution, and end-use customer services at distributed generation. The data is derived from 1, 261 real world systems. Five different models were developed for short, medium, and long-duration grid services. The models are designed to be technology agnostic and are not sensitive to either performance characteristics or operating conditions of the ESS. The results indicate the probability that an energy storage project will provide an individual service use case given that it may also yield another service, and how technology types and multiple selected applications influence those probabilities.
This report provides information about the DOE Office of Electricity Energy Storage Peer Review held in 2019 and includes posters reviewed in these categories: postdoctoral, validated reliability and safety performance, equitable regulatory environment and analytics, applied materials (Materials I), power electronics, industry acceptance, partnerships, and Materials I.