Performance analysis of the global maximum power point tracking based on spider monkey optimization for PV system

Husain, Mohammed Aslam; Pingale, Suresh B.; Bakar Khan, Aboo; Faiz Minai, Ahmad; Pandey, Yudhishthir; Shyam Dwivedi, Radhe

doi:10.1016/j.ref.2023.100503

Cited by 10 publications

(2 citation statements)

References 63 publications

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“…Five quality evaluations were chosen to quantify the impact of the suggested forecasting approach 8 , 69 , 73 – 75 expressed in Table 2 as:…”

Section: Performance Metricsmentioning

confidence: 99%

“…Solving the PV power forecasting issue using hybrid models has shown excellent performance compared with stand-alone models. Hybrid methods for time series forecasting have recently developed as a dynamic and active research area 8 using different techniques such as metaheuristic algorithms 9 , sparse representation theory 10 – 12 and decomposition ensemble learning approaches 13 . A review of various forecasting techniques for solar irradiation and PV power is provided in 13 , 14 .…”

Section: Introductionmentioning

confidence: 99%

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An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

Guermoui,

Fezzani,

Mohamed

et al. 2024

Sci Rep

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Integration renewable energy sources into current power generation systems necessitates accurate forecasting to optimize and preserve supply–demand restrictions in the electrical grids. Due to the highly random nature of environmental conditions, accurate prediction of PV power has limitations, particularly on long and short periods. Thus, this research provides a new hybrid model for forecasting short PV power based on the fusing of multi-frequency information of different decomposition techniques that will allow a forecaster to provide reliable forecasts. We evaluate and provide insights into the performance of five multi-scale decomposition algorithms combined with a deep convolution neural network (CNN). Additionally, we compare the suggested combination approach's performance to that of existing forecast models. An exhaustive assessment is carried out using three grid-connected PV power plants in Algeria with a total installed capacity of 73.1 MW. The developed fusing strategy displayed an outstanding forecasting performance. The comparative analysis of the proposed combination method with the stand-alone forecast model and other hybridization techniques proves its superiority in terms of forecasting precision, with an RMSE varying in the range of [0.454–1.54] for the three studied PV stations.

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“…Five quality evaluations were chosen to quantify the impact of the suggested forecasting approach 8 , 69 , 73 – 75 expressed in Table 2 as:…”

Section: Performance Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

Guermoui,

Fezzani,

Mohamed

et al. 2024

Sci Rep

View full text Add to dashboard Cite

show abstract

An optimization approach control of EV solar charging system with step-up DC–DC converter

Venkatesh,

Priya,

Hemachandu

et al. 2024

Analog Integr Circ Sig Process

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A novel Beluga Whale Optimization for maximum power tracking in photovoltaic systems under shading and non-shading conditions

N.B.,

2024

Energy Reports

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Performance analysis of the global maximum power point tracking based on spider monkey optimization for PV system

Cited by 10 publications

References 63 publications

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

An analysis of case studies for advancing photovoltaic power forecasting through multi-scale fusion techniques

An optimization approach control of EV solar charging system with step-up DC–DC converter

A novel Beluga Whale Optimization for maximum power tracking in photovoltaic systems under shading and non-shading conditions

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