New results in forecasting of photovoltaic systems output based on solar radiation forecasting

Abstract

Accurate short term forecasting of photovoltaic (PV) systems output has a great significance for fast development of PV parks in South-East Europe, as well as in the case of Romania. Our approach on solar radiation forecast is based on two methods: autoregressive integrated moving average and artificial neural network. We have analyzed the daily solar irradiation variability and defined four synoptic situations to include the influence of cloudiness changes. Decadal variations of global solar radiation were also considered for long term forecast. The results were obtained using a database from Bucharest/Afumati Meteorological Station. We have developed an accurate forecasting model for a PV system's power output based on solar radiation forecasting results. By using complete datasets and including meteorological parameters such as cloudiness, relative humidity, air temperature, atmospheric pressure, and sunshine duration, as input for our model, we have managed to minimize forecasting errors and to obtain a more accurate forecast of the power output for the analyzed demo PV system.

Preface to Special Issue: Renewable Energy in South-Eastern Europe

“…22 The approach has great significance for fast development of PV parks in South-East Europe. The approach is based on two methods: ARIMA (Autoregressive Integrated Moving Average) and ANN (Artificial Neural Network).…”

Forecasting of Energy Production for Photovoltaic Systems Based on ARIMA and ANN Advanced Models

“…The error calculated between the measured and the predicted values of P ac using the ANN model is 8.89%. At the Bucharest-Afumatzi meteorological station, the global solar irradiance is automatically measured on a horizontal surface, with the pyranometer CM11 Kipp&Zonen- In the solar radiation forecast of the BIPV lab system from the Polytechnic University of Bucharest, both studied models were used, namely, ARIMA and ANN [9,11]. The error of the solar radiation forecast depends on its daily variation.…”

“…The four situations include changes in the amounts of cloudiness on the previous day and on the forecast day and are as follows (see Figure 8) [9]:…”

“…Reliable and accurate forecasts play a key role in improving PV solar power plants [1][2][3][9][10][11][12]. The main challenging problem in the production of solar energy is the intermittent electricity generation using PV systems, due to weather conditions.…”

“…The peculiarities of the model used in this forecast are highlighted by defining a backshift operator B of the time series [9]: B Zt = z t−1 , where z t and z t−1 are two consecutive observations of the time series. Then, B j can be defined as B j Zt = z t−j .…”