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AI-Driven Optimization for Solar Energy Systems (Paperback)
Edité par
LAP Lambert Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Paperback
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. The rising global demand for sustainable energy has accelerated solar PV adoption, yet efficiency is limited by challenges such as variable irradiance, partial shading, storage, and grid integration. This study explores 15 nature-inspired AI optimization algorithms-ABC, PSO, PIO, DIO, PDO, SMO, RIOA, ACO, TIOA, OIOA, EIO, CIO, OOA, PIOA, and MLO-that mimic biological behaviors to solve nonlinear, multi-objective problems in solar systems. Using theoretical models and case studies, the research shows how these methods improve MPPT, tilt/orientation, storage scheduling, microgrid dispatch, and reliability. Results highlight ABC, ACO, TIOA, CIO, RIOA, and OOA as top performers, achieving 98-99% MPPT efficiency, 6-9% annual yield gains, and major reductions in storage losses and diesel reliance. Lightweight approaches like PDO and simplified ABC excel in embedded MPPT, while CIO, OIOA, and EIO deliver high-accuracy offline tilt and layout optimization. Specialized roles include MLO for power quality and PIOA/OOA for resource scheduling. Collectively, these algorithms provide adaptive, scalable solutions that boost efficiency, cut costs, and enhance sustainability in solar energy. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9786202452588
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EUR 86,29
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Expédition nationale : Etats-Unis
Expédition nationale : Etats-Unis
Quantité disponible : 1 disponible(s)
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AI-Driven Optimization for Solar Energy Systems
Edité par
LAP Lambert Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Couverture souple
Vendeur : California Books, Miami, FL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur I-9786202452588
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EUR 86,29
Livraison gratuite
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Expédition nationale : Etats-Unis
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AI-Driven Optimization for Solar Energy Systems
Edité par
LAP LAMBERT Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
PAP
Vendeur : PBShop.store US, Wood Dale, IL, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9786202452588
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EUR 94,14
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Expédition nationale : Etats-Unis
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AI-Driven Optimization for Solar Energy Systems
Edité par
LAP LAMBERT Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
PAP
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
PAP. Etat : New. New Book. Shipped from UK. Established seller since 2000. N° de réf. du vendeur L2-9786202452588
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EUR 90,48
Expédition à EUR 3,75
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
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AI-Driven Optimization for Solar Energy Systems
Edité par
Omniscriptum, LAP Lambert Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The rising global demand for sustainable energy has accelerated solar PV adoption, yet efficiency is limited by challenges such as variable irradiance, partial shading, storage, and grid integration. This study explores 15 nature-inspired AI optimization algorithms-ABC, PSO, PIO, DIO, PDO, SMO, RIOA, ACO, TIOA, OIOA, EIO, CIO, OOA, PIOA, and MLO-that mimic biological behaviors to solve nonlinear, multi-objective problems in solar systems. Using theoretical models and case studies, the research shows how these methods improve MPPT, tilt/orientation, storage scheduling, microgrid dispatch, and reliability. Results highlight ABC, ACO, TIOA, CIO, RIOA, and OOA as top performers, achieving 98-99% MPPT efficiency, 6-9% annual yield gains, and major reductions in storage losses and diesel reliance. Lightweight approaches like PDO and simplified ABC excel in embedded MPPT, while CIO, OIOA, and EIO deliver high-accuracy offline tilt and layout optimization. Specialized roles include MLO for power quality and PIOA/OOA for resource scheduling. Collectively, these algorithms provide adaptive, scalable solutions that boost efficiency, cut costs, and enhance sustainability in solar energy. 176 pp. Englisch. N° de réf. du vendeur 9786202452588
Acheter neuf
EUR 79,90
Expédition à EUR 23
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)
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AI-Driven Optimization for Solar Energy Systems (Paperback)
Edité par
LAP Lambert Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Paperback
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : new. Paperback. The rising global demand for sustainable energy has accelerated solar PV adoption, yet efficiency is limited by challenges such as variable irradiance, partial shading, storage, and grid integration. This study explores 15 nature-inspired AI optimization algorithms-ABC, PSO, PIO, DIO, PDO, SMO, RIOA, ACO, TIOA, OIOA, EIO, CIO, OOA, PIOA, and MLO-that mimic biological behaviors to solve nonlinear, multi-objective problems in solar systems. Using theoretical models and case studies, the research shows how these methods improve MPPT, tilt/orientation, storage scheduling, microgrid dispatch, and reliability. Results highlight ABC, ACO, TIOA, CIO, RIOA, and OOA as top performers, achieving 98-99% MPPT efficiency, 6-9% annual yield gains, and major reductions in storage losses and diesel reliance. Lightweight approaches like PDO and simplified ABC excel in embedded MPPT, while CIO, OIOA, and EIO deliver high-accuracy offline tilt and layout optimization. Specialized roles include MLO for power quality and PIOA/OOA for resource scheduling. Collectively, these algorithms provide adaptive, scalable solutions that boost efficiency, cut costs, and enhance sustainability in solar energy. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786202452588
Acheter neuf
EUR 96,92
Expédition à EUR 42,21
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 1 disponible(s)
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AI-Driven Optimization for Solar Energy Systems
Edité par
LAP LAMBERT Academic Publishing Okt 2025, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware Books on Demand GmbH, Überseering 33, 22297 Hamburg 176 pp. Englisch. N° de réf. du vendeur 9786202452588
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EUR 79,90
Expédition à EUR 60
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
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AI-Driven Optimization for Solar Energy Systems : AI-Driven Optimization for Solar Energy Systems: Nature-Inspired Algorithms for Solar Energy System. DE
Edité par
Omniscriptum, LAP Lambert Academic Publishing, 2025
ISBN 10 : 6202452587
ISBN 13 : 9786202452588
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware - The rising global demand for sustainable energy has accelerated solar PV adoption, yet efficiency is limited by challenges such as variable irradiance, partial shading, storage, and grid integration. This study explores 15 nature-inspired AI optimization algorithms-ABC, PSO, PIO, DIO, PDO, SMO, RIOA, ACO, TIOA, OIOA, EIO, CIO, OOA, PIOA, and MLO-that mimic biological behaviors to solve nonlinear, multi-objective problems in solar systems. Using theoretical models and case studies, the research shows how these methods improve MPPT, tilt/orientation, storage scheduling, microgrid dispatch, and reliability. Results highlight ABC, ACO, TIOA, CIO, RIOA, and OOA as top performers, achieving 98-99% MPPT efficiency, 6-9% annual yield gains, and major reductions in storage losses and diesel reliance. Lightweight approaches like PDO and simplified ABC excel in embedded MPPT, while CIO, OIOA, and EIO deliver high-accuracy offline tilt and layout optimization. Specialized roles include MLO for power quality and PIOA/OOA for resource scheduling. Collectively, these algorithms provide adaptive, scalable solutions that boost efficiency, cut costs, and enhance sustainability in solar energy. N° de réf. du vendeur 9786202452588
Acheter neuf
EUR 80,86
Expédition à EUR 65
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)