Uncertainty and simulation-based cost analyses for energy storage systems used in green buildings

Energy storage systems (ESS) provide buildings with the ability to store electricity generated from renewable energy sources (eg, solar photovoltaics), increasing building operational flexibility and reliability. Previous studies on ESS in buildings often make assumptions about key input parameters (eg, installation factor, roundtrip efficiency, etc.) being fixed, overlooking potential performance risks due to uncertainty or variations in these parameters. The goal of this paper is to quantify the impact of uncertainty in technical and financial parameters on the economic performance of Li-ion batteries (LIB), proton-exchange membranes reversible fuel cells (PEM RFC), and reversible solid oxide cells (RSOC). The analysis is conducted on three medium-sized office buildings located in three different climate zones of the United States: 2B (Phoenix, AZ), 3B-Coast (Los Angeles, CA), and 4C (Seattle, WA). Two metrics are used to evaluate the economic viability of the selected technologies, namely the levelized cost of electricity (LCOE) and the levelized cost of energy storage (LCOS). While the results of the LCOE and LCOS differed in value between those cities, the cost breakdown for LCOS in all locations shows that capital cost is the biggest cost contributor, followed by electricity cost. A Monte-Carlo simulation was also conducted to assess the impact of uncertainty in input parameters on the LCOS model. The simulation results allowed us to generate probable ranges and probability tables for the LCOS.