Short-Term Prediction of the Solar Photovoltaic Power Output Using Nonlinear Autoregressive Exogenous Inputs and Artificial Neural Network Techniques Under Different Weather Conditions DOI Creative Commons
Abdulrahman Th. Mohammad, Wisam A. M. Al-Shohani

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6153 - 6153

Published: Dec. 6, 2024

The power generation by solar photovoltaic (PV) systems will become an important and reliable source in the future. Therefore, this aspect has received great attention from researchers, who have investigated accurate credible models to predict output of PV modules. This prediction is very planning short-term resources, management energy distribution, operation security for systems. paper aims explore sensitivity Nonlinear Autoregressive Exogenous Inputs (NARX) Artificial Neural Network (ANNs) as a result weather dynamics short term predicting goal was achieved based on experimental dataset module obtained during sunny days summer cloudy winter, using data algorithm NARX ANN. In addition, analysis results model were compared with those static ANN measure accuracy superiority nonlinear model. showed that offers good estimates efficient term. Thus, coefficient determination (R2) mean square error (MSE) 94.4–97.9% 0.08261–0.04613, respectively, days, R2 MSE 90.1–89.2% 0.281–0.249, winter days. Overall, it can be concluded more than when conditions are stable gradual change. Moreover, effectiveness specificity learn generalize effectively

Language: Английский

Integrating thermal phase-change material energy storage with solar collectors: A comprehensive review of techniques and applications DOI
Farooq H. Ali, Qusay Rasheed Al-Amir, Hameed K. Hamzah

et al.

International Communications in Heat and Mass Transfer, Journal Year: 2025, Volume and Issue: 162, P. 108606 - 108606

Published: Jan. 22, 2025

Language: Английский

Citations

6
Construction of a framework for real-time evaluation of regulation effect of distributed photovoltaic users based on multi-source data fusion DOI Open Access

Bo Feng,

Junpeng Zhao,

Yifeng Wang

et al.

Applied Mathematics and Nonlinear Sciences, Journal Year: 2025, Volume and Issue: 10(1)

Published: Jan. 1, 2025

Abstract Distributed photovoltaic (PV) power generation is one of the new quality productive forces to promote application green energy and realize high-quality development. In order improve regulation effect in process PV generation, multiple sources data such as economic factors, electricity consumption habits, indoor temperature are included calculation, a real-time evaluation framework users constructed, particle swarm algorithm used solve efficient energy. The case study shows that different habits behaviors have an impact on load dispatch situation. After using this paper’s scheme for regulation, in-situ increases by 77.2% 89.4% two scenarios, where adjustable consists electric water heaters washing machines (Scenario 1) cars, 2), respectively. This scenario able better cope with scheduling demand under weather conditions, returns during experimental cycle totaled 113.215 yuan, gains 8.180%, 10.186%, 12.593%, respectively, over remaining three alternative scenarios.

Language: Английский

Citations

0
A novel feature engineering-based hybrid approach for precise construction cost estimation using fuzzy-AHP and artificial neural networks DOI

Eman Abu-Mahfouz,

Sameer Al‐Dahidi, Emhaidy S. Gharaibeh

et al.

International Journal of Construction Management, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 11

Published: March 27, 2025

Language: Английский

Citations

0
Photovoltaic power forecasting based on VMD-SSA-Transformer: Multidimensional analysis of dataset length, weather mutation and forecast accuracy DOI
Chao Zhai,

Xinyi He,

Zhixiang Cao

et al.

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135971 - 135971

Published: April 1, 2025

Language: Английский

Citations

0
Short-Term Prediction of the Solar Photovoltaic Power Output Using Nonlinear Autoregressive Exogenous Inputs and Artificial Neural Network Techniques Under Different Weather Conditions DOI Creative Commons
Abdulrahman Th. Mohammad, Wisam A. M. Al-Shohani

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6153 - 6153

Published: Dec. 6, 2024

The power generation by solar photovoltaic (PV) systems will become an important and reliable source in the future. Therefore, this aspect has received great attention from researchers, who have investigated accurate credible models to predict output of PV modules. This prediction is very planning short-term resources, management energy distribution, operation security for systems. paper aims explore sensitivity Nonlinear Autoregressive Exogenous Inputs (NARX) Artificial Neural Network (ANNs) as a result weather dynamics short term predicting goal was achieved based on experimental dataset module obtained during sunny days summer cloudy winter, using data algorithm NARX ANN. In addition, analysis results model were compared with those static ANN measure accuracy superiority nonlinear model. showed that offers good estimates efficient term. Thus, coefficient determination (R2) mean square error (MSE) 94.4–97.9% 0.08261–0.04613, respectively, days, R2 MSE 90.1–89.2% 0.281–0.249, winter days. Overall, it can be concluded more than when conditions are stable gradual change. Moreover, effectiveness specificity learn generalize effectively

Language: Английский

Citations

1