Results 151 to 160 of about 1,108 (256)

Predicting Solar Photovoltaic Power Output in Saudi Arabia's Jazan Region: Performance Comparison of Machine Learning Models

Energy Science &Engineering, EarlyView.
Workflow of the PV power estimation and ML forecasting methodology. ABSTRACT Accurate prediction of solar panel energy output is vital for managing power systems effectively and maintaining a stable electrical grid. This is especially important in regions that rely heavily on renewable sources. This research provides a direct comparison of five machine
Abdoalateef Alzhrani, Abdullahi Abubakar Mas'ud, Mohd Khairul Amri Kamarudin, Firdaus Muhammad‐Sukki, Abdullahi Mohammad   +4 more
wiley   +1 more source

GRNN-DP-MPC Co-optimization for predictive energy management in hybrid UAVs. [PDF]

Sci Rep
Kan W, Chen S, Lei W, Ma C, Pan J.
europepmc   +1 more source

Improved Power Tracking and Performance Evaluation Using a Tri‐Meta Hybrid DOA–CSA–WOA‐Based MPPT Controller for Standalone PV System

Energy Science &Engineering, EarlyView.
A Tri‐Meta Hybrid DOA–CSA–WOA Maximum Power Point Tracking controller is developed to enhance photovoltaic system performance. The proposed approach achieves higher tracking efficiency, faster convergence, and robust operation under dynamic irradiance and partial shading conditions.
Ali Abbas, Muhammad Farhan, Nouman Safdar, Muhammad Junaid Rabbani, Mohammad Rashed M. Altimania, Waleed Mohammed Abdelfattah, Hafiz Mudassir Munir   +6 more
wiley   +1 more source

Accurate forecasting of photovoltaic optimal points and efficiency using advanced hybrid machine learning models. [PDF]

Sci Rep
Kumar A, Asif M, Naji M, Spoorthi B, Sahu BN, Radhika S, Al-Hedrewy M, Khudaynazarov E, Nurmatovich HA.   +8 more
europepmc   +1 more source

Comparative Analysis of Al2O3/Water–TiO2/Chlorophyll Hybrid Nanofluids in a Photovoltaic–Thermal Solar Water Heating System

Energy Science &Engineering, EarlyView.
TiO2/chlorophyll bio‐hybrid nanofluid achieved the highest PVT performance, increasing thermal efficiency to 38.74% and overall efficiency to 51.35%, compared with 35.96% and 48.45% for Al2O3/water and 27.77% and 40.18% for water. The results demonstrate the potential of bio‐hybrid nanofluids for high‐efficiency solar thermal energy conversion ...
Oluwaseyi Omotayo Alabi, Oluwatoyin Joseph Gbadeyan, Oludolapo Akanni Olanrewaju   +2 more
wiley   +1 more source

Solar potential assessment using machine learning and climate change projections for long-term energy planning. [PDF]

Sci Rep
Reddy BNS, Gautam K, Pachauri N.
europepmc   +1 more source

Pulsed Light Technology in Food Safety and Preservation: Principles, Applications, and Future Directions

Food Chemistry International, EarlyView.
Pulsed light technology uses short high‐intensity broad‐spectrum flashes (200–1100 nm) to inactivate microbes via DNA damage. It preserves food quality, extends shelf life, and works on liquids, meats, and produce, often combined with other hurdles for enhanced efficacy.
Abdul Mueez Ahmad, Laiba Younas, Fatima Javed, Rimsha Amjad, Muhammad Tayyab Raza   +4 more
wiley   +1 more source

Climate-aware hybrid Kolmogorov-Arnold networks for interpretable solar radiation forecasting. [PDF]

Sci Rep
Rahmath M, Alameen A, Sayed Abdellatif M.   +2 more
europepmc   +1 more source

Non‐fullerene acceptor aggregation regulation via additives dipole moment leads to 19.9% power conversion efficiency in bilayer organic solar cells

FlexMat, EarlyView.
Additives interact with non‐fullerene acceptors to modulate their aggregation behavior and molecular orientation via optimizing crystallization kinetics. The optimized morphology effectively suppresses charge carrier recombination and enhances charge transport. Notably, 2‐chloro‐1,3‐dibromobenzene with the dipole moments of 2.56 D enables the PM6/L8‐BO
Jingjing Zhao, Jiancheng Zhong, Yuanyuan Qin, Chenxi Cao, Lanlan Zhang, Xin Li, Min Zhang, Hongxiang Li, Zhipeng Kan   +8 more
wiley   +1 more source

Optimized energy management of PV-Powered lighting system for smart cities using perfumer optimization algorithm and graph ensemble neural network. [PDF]

Sci Rep
Hussain Z, Selvam P, Sivaramkrishnan M, Ramkumar MS, Paramasivam S, Ghouse M, Khan TMY, Khan MA, Zewdie A.   +8 more
europepmc   +1 more source