An algorithm for the optimal sizing of the PV system for prosumers based on economic indicators and the input data time step

• Published in: Solar energy Vol. 262; p. 111882
• Main Authors: Mišljenović, Nemanja, Šimić, Zvonimir, Topić, Danijel, Knežević, Goran
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.09.2023
• Subjects: LCOE; NPV; Optimal size; Prosumer; PV system; ROI; PV system; Prosumer; NPV; ROI; Optimal size; LCOE
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2023.111882

This paper elaborates on an algorithm for finding the optimal size of a photovoltaic (PV) system of a prosumer based on economic factors. The proposed algorithm was developed in the MATLAB programming language and is applied to the Croatian case study considering the Croatian legislation regarding prosumers. The proposed algorithm uses load profile, solar radiation, external temperature and PV module technical characteristics as input data. The algorithm considers the impact of electricity generated from the prosumer’s PV system on the price that the prosumer will receive for the energy exported to the grid as well as achieved savings to calculate the economic indicators — Levelized Cost of Electricity (LCOE), Return on Investment (ROI) and Net Present Value (NPV). Based on the calculated economic indicators LCOE, ROI, and NPV, the optimal size of the PV system is selected. The proposed algorithm was applied to two profiles of prosumers (household and industrial) to demonstrate its usefulness. Furthermore, the impact of the time step of input data on the results has been also investigated. Finally, the proposed algorithm is applied to the input data with 15- and 60-minute time steps for the household prosumer and for the industrial prosumer to obtain the optimal size of the PV system considering the calculated economic indicators. •Optimal sizing of PV systems based on economic indicators.•The resolution of the input data does not over-affect the economic indicators.•Applications of the proposed algorithm to households and industry.•Industrial consumers have a shorter return on investment.•Estimates of PV power production concerning technical and external influences.