A Python Application Developed Based on Economic End-of-Life Models to Assess PV-BESS Systems

<jats:p>This chapter proposes an application developed in Python that can assist in the decision of acquiring a photovoltaic (PV) system with an integrated battery energy storage system (BESS). Based on the data provided by the user, the application determines the levelized cost of energy (LCOE), for the PV system, and the levelized cost of storage (LCOS), for the BESS. Then, it returns the total levelized cost (TLC) and indicates if the investment is profitable, by comparing TLC with the cost of electricity acquired from the grid. To validate the proposed application, a large household consumer located in Bucharest, Romania, is analyzed. The proposed PV-BESS system is designed in PV*SOL Premium software, based on the consumption profile and location coordinates of the consumer. The proposed PV system has an installed power of 10 kW, while BESS has a capacity of 15 kWh. Based on the data input by the user, regarding the PV and BESS parameters, received government incentives and discount rate, the proposed Python application determines LCOE, LCOS and TLC. The results returned indicate that TLC has a lower value, of 0.1925 €/kWh, compared to the unit price of electricity purchased from the grid, of 0.25 €/kWh, demonstrating the efficiency of the technical solution. The developed Python application can be a useful tool for investors, industrial and residential consumers, and other interested stakeholders, used to determine the feasibility of a PV-EESS system and the economic impact of implementing the analyzed solution.</jats:p>