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The short-term variability of photovoltaic (PV) system-generated power due to ambient conditions, such as passing clouds, represents a key challenge for network planners and operators. Such variability can be reduced using a geographical smoothing technique based on installing multiple PV systems over certain locations at distances of meters to kilometers. To accurately estimate the PV system’s generated power during cloud events, a variability reduction index (VRI), which is a function of several parameters, should be calculated precisely. In this paper, the Wavelet Transform Technique (WTT) along with Adaptive Neuro Fuzzy Inference System (ANFIS) are used to develop new models to estimate the PV system’s power output during cloud events. In this context, irradiance data collected from one PV system along with other parameters, including ambient conditions, were used to develop the proposed models. Ultimately, the models were validated through their application on a 0.7 km2 PV plant with 16 rooftop PV systems in Brisbane, Australia.

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The penetration of photovoltaic systems (PVs) to existing power grids is increasing as they are considered attractive options for electricity generation in distribution networks. This paper focuses on estimating the total power generated by a group of neighbouring PVs, spread over a distribution network using a single pyranometer for measuring the solar irradiance. A new empirical‐based model that employs the Gene Expression Programming (GEP) technique is proposed to correlate the distribution of the PVs and the irradiance measured by the pyranometer and estimate the total power generated by the PVs. The geographic variability reduction index has been considered in developing the proposed model that also employs a Wavelet Transform technique to enhance its accuracy. The effective performance of the proposed model is validated using real data collected by the Solar Project at the University of Queensland, Brisbane, Australia. Results reveal that the proposed technique yields more accurate results when compared with other existing approaches in the literature.

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