Estimating clear-sky PV electricity production without exogenous data
Stefani Peratikou, Alexandros G. Charalambides
Abstract
The global shift towards the utilization of renewable energy sources has driven the development of photovoltaics (PVs) and the need for their mass integration in energy markets. Although the penetration of PVs is dramatically increasing during the last decades, the ‘problem’ of PV power output fluctuations due to uncertain environmental parameters still remains an issue. A key challenge is to provide accurate predictions of PV power output since this will assist grid operators for efficient capacity management and scheduling. In this paper, a data-driven method was developed, using time-series of PV power output from a PV station in Limassol, Cyprus to estimate the clear-sky PV electricity production without any exogenous data. The time-series was divided into monthly intervals and analysed by using the mean value, the maximum value and the standard deviation. The predicted clear-sky PV signals calculated were compared to the best visibly smooth signal in terms of Root Mean Square Error, Mean Absolute Deviation, and Mean Absolute Percent Error. Results indicate that the proposed method can provide a good approximation of the true clear-sky signal and thus it can be argued that PV data alone can be used for clear-sky PV output calculation without any information from the manufacturer or location specific data.