Photovoltaic cleaning frequency optimization under different degradation rate patterns.

Dust accumulation significantly affects the performance of photovoltaic modules and its impact can be mitigated by various cleaning methods. Optimizing the cleaning frequency is essential to minimize the soiling losses and, at the same time, the costs. However, the effectiveness of cleaning lowers with time because of the reduced energy yield due to degradation. Additionally, economic factors such as the escalation in electricity price and inflation can compound or counterbalance the effect of degradation on the soiling mitigation profits. The present study analyzes the impact of degradation, escalation in electricity price and inflation on the revenues and costs of cleanings and proposes a methodology to maximize the profits of soiling mitigation of any system. The energy performance and soiling losses of a 1 MW system installed in southern Spain were analyzed and integrated with theoretical linear and nonlinear degradation rate patterns. The Levelized Cost of Energy and Net Present Value were used as criteria to identify the optimum cleaning strategies. The results showed that the two metrics convey distinct cleaning recommendations, as they are influenced by different factors. For the given site, despite the degradation effects, the optimum cleaning frequency is found to increase with time of operation. Image 1 • The optimum cleaning schedule varies depending on time of operation and health state. • Different cleaning schedules can be recommended based on the LCOE and NPV. • PV degradation does not affect the LCOE based cleaning decision algorithm. • Inflation influences the profitability of cleaning schedule over time. • Nonlinear degradation affects the cleaning frequency and its profitability. [ABSTRACT FROM AUTHOR]