Model estimation of photovoltaic power generation using partial information

Abstract

In this paper we propose a method for the estimation of the parameters of the well-known PVUSA model of a photovoltaic plant, to be used for generation forecasting purposes. We address this problem in a scenario where measurements of meteorological variables (i.e. solar irradiance and temperature) at the plant site are not available. The proposed approach efficiently exploits only power generation measurements and theoretical clear-sky irradiance, and is characterized by very low computational effort. Experimental validation is also presented. The proposed procedure is currently being deployed at several DSO control centres in Italy

Estimation of photovoltaic generation forecasting models using limited information

“…The information contained in such portions is then exploited in a recursive parameter estimation algorithm in combination with theoretical clear-sky irradiance provided by a suitable model. The method proposed in this paper improves over [26,27,29], since it is able to adapt to parameter variations and requires the tuning of a single threshold coefficient whose physical role can be interpreted in terms of the cloud cover factor (CCF) [31].…”

“…Notice that clear-sky generation forecasts provide an upper bound on the power that can be generated by a plant, and as such they can be used by the DSO, for instance, when scheduling the maintenance of the portion of the grid where the plant is located. Despite its simplicity, very good forecasting accuracy is obtained from the PVUSA model when the parameter vector µ is estimated using measured irradiance and temperature data via, e.g., standard least squares fitting (see, e.g., [26]).…”

Computational methods for technical validation of demand response products

“…In both cases, the focus is often on obtaining as accurate forecasts of meteorological variables as possible, that are then plugged into the plant power curve. Estimation of the parameters of the power curve of a photovoltaic plant is addressed in [18] in a scenario where measurements of meteorological variables at the plant site are not available (particularly suited to DSO applications). To the best of the authors' knowledge, little or no attention is dedicated in the literature to the forecasting of other DG sources, such as micro combined heat and power systems.…”

Bidding strategies for renewable energy generation with non stationary statistics

“…Although model (4) is linear-inthe-parameters, parameter estimation is complicated by the fact that measurements of solar radiation and air temperature may not be available at the plant site. A heuristic approach to estimate such parameters in the partial information case is presented in [Bianchini et al, 2013], which relies on historical data of generated power, air temperature forecasts and clear-sky solar irradiance. The clear-sky generation profile can be computed from (4) by replacing I m with the clear-sky solar irradiance I cs,m and T m with commonly available temperature forecasts.…”