Photovoltaic Power Forecasting Methods

Ismail Kaaya and Julian Ascencio-Vasquez

A chapter in Solar Radiation - Measurement, Modeling and Forecasting Techniques for Photovoltaic Solar Energy Applications from IntechOpen

Abstract: The rapid growth in grid penetration of photovoltaic (PV) calls for more accurate methods to forecast the performance and reliability of PV. Several methods have been proposed to forecast the PV power generation at different temporal horizons. In this chapter the different methods used in PV power forecasting are described with an example on their applications and related uncertainty. The methods discussed include physical, heuristic, statistical and machine learning methods. When benchmarked, it is shown that physical method showed the highest uncertainties compared to other methods. In the chapter, the effect of degradation on lifetime PV power and energy forecast is also assessed using linear and non-linear degradation scenarios. It is shown that the relative difference in lifetime yield prediction is over 5% between linear and non-linear scenarios.

Keywords: Degradation; Lifetime; Photovoltaic; Power; Forecasting (search for similar items in EconPapers)
JEL-codes: Q20 Q40 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:223117

DOI: 10.5772/intechopen.97049

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