a simulation-optimization model for solar pv panel selection under solar irradiance and load uncertainty

In this research, a multi-objective model is presented considering simulated behavior of high-efficiency rooftop solar pv panels in a factory, which are among the largest producers of greenhouse gases. the paper proposes a simulation-optimization approach that is used to maximize the net present value (npv) of economic benefits along with minimizing the payback period (pbp) of the investment and maximizing solar energy consumption rate (secr). in addition, the solar pv panels degradation and maintenance cost, as well as the uncertainty in solar irradiance and demand load, are also considered. the study consists of two scenarios, in the first of which both electricity tariffs and feed-in-tariffs (fit) are fixed by a long-term contract. the second scenario investigates the situation in which subsidies on electricity tariff are removed. the best types of panels are found in each scenario considering the trade-offs between objective functions. the preferred trade-off solution in the first scenario, with a 2% increase in pbp, achieves more than 10% growth in npv which is about $15000 in a year. in the second scenario, with only about a 0.2% decrease in npv and a 3% increase in pbp, the preferred solution attains a 9% increase in secr.