Higher order statistical moment application for solar PV potential analysis

Basri, Mohd Juhari Mat; Abdullah, Siti Zubaidah; Azrulhisham, E. A.; Harun, Khairulezuan

doi:10.1063/1.4966094

Cited by 1 publication

(3 citation statements)

References 6 publications

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“…The authors compared the results through plots with the computed values of WD and the actual value. The results ignored several seasonal variations but confirmed that WD maintained its efficiency, in comparison to Pearson parameter irradiance forecasting [79].…”

Section: Review Of Pv Power Forecasting Without Nnmentioning

confidence: 57%

“…The authors in [79] proposed a scheme, designed by using the Pearson system based on the calculation of probability distribution by matching theoretical moments with empirical moments. The authors developed a data processing system to perform distribution fitting and future potential analysis.…”

Section: Review Of Pv Power Forecasting Without Nnmentioning

confidence: 99%

“…Reference [80] proposed a model by combining different distribution schemes for different purposes understudy in their research. They also considered a clear-sky index for PV power production that was ignored in [79], and the mathematical formulas used for calculation of mean and variance of WD are mentioned in Equations (18) and (19), respectively.…”

Section: Review Of Pv Power Forecasting Without Nnmentioning

confidence: 99%

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Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review

et al. 2019

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Renewable energy sources (RESs) are the replacement of fast depleting, environment polluting, costly, and unsustainable fossil fuels. RESs themselves have various issues such as variable supply towards the load during different periods, and mostly they are available at distant locations from load centers. This paper inspects forecasting techniques, employed to predict the RESs availability during different periods and considers the dispatch mechanisms for the supply, extracted from these resources. Firstly, we analyze the application of stochastic distributions especially the Weibull distribution (WD), for forecasting both wind and PV power potential, with and without incorporating neural networks (NN). Secondly, a review of the optimal economic dispatch (OED) of RES using particle swarm optimization (PSO) is presented. The reviewed techniques will be of great significance for system operators that require to gauge and pre-plan flexibility competence for their power systems to ensure practical and economical operation under high penetration of RESs.

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Section: Review Of Pv Power Forecasting Without Nnmentioning

confidence: 57%

Section: Review Of Pv Power Forecasting Without Nnmentioning

confidence: 99%