Isbn: 9786209371073 - impact of phevs on renewable integrated power distribution systems: renewable integrated active distribution networks (11 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Taschenbuch. Condición: Neu. Impact of PHEVs on Renewable Integrated Power Distribution Systems | Renewable Integrated Active Distribution Networks | Satish Kumar Injeti (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209371073 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 128 pp. Englisch.

Paperback. Condición: new. Paperback. This dissertation addresses the challenges of traditional centralized power generation, fossil fuel depletion, high emissions, growing demand, and transmission losses by focusing on optimal planning of Distributed Generation (DG) in distribution networks. Advanced metaheuristic algorithms are created to make systems work better, keep voltage stable, handle more load, and make more money. A Butterfly Optimization Algorithm (BOA) with an -constraint approach is proposed to minimize losses and improve loadability. Further, a Pareto-based Multi-Objective Chaotic Velocity Butterfly Optimization Algorithm (MOCVBOA) is introduced for planning non-dispatchable (PV, WT) and dispatchable (PV-BESS, WT-Biomass) DGs under renewable and load uncertainties. The dissertation also examines DG planning under Plug-In Electric Vehicle (PHEV) charging scenarios using TOPSIS-based optimal solution selection. Finally, the planning of PV and PV-BESS units, considering both conventional and PHEV loads under private and public charging scenarios, is analyzed. Results show that optimal DG integration significantly reduces energy losses, improves voltage profiles, and mitigates PHEV-induced stress. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

Condición: New. Print on Demand.

Condición: New. Print on Demand.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This dissertation addresses the challenges of traditional centralized power generation, fossil fuel depletion, high emissions, growing demand, and transmission losses by focusing on optimal planning of Distributed Generation (DG) in distribution networks. Advanced metaheuristic algorithms are created to make systems work better, keep voltage stable, handle more load, and make more money. A Butterfly Optimization Algorithm (BOA) with an ¿-constraint approach is proposed to minimize losses and improve loadability. Further, a Pareto-based Multi-Objective Chaotic Velocity Butterfly Optimization Algorithm (MOCVBOA) is introduced for planning non-dispatchable (PV, WT) and dispatchable (PV-BESS, WT-Biomass) DGs under renewable and load uncertainties. The dissertation also examines DG planning under Plug-In Electric Vehicle (PHEV) charging scenarios using TOPSIS-based optimal solution selection. Finally, the planning of PV and PV-BESS units, considering both conventional and PHEV loads under private and public charging scenarios, is analyzed. Results show that optimal DG integration significantly reduces energy losses, improves voltage profiles, and mitigates PHEV-induced stress.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch.…

Condición: New. PRINT ON DEMAND.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This dissertation addresses the challenges of traditional centralized power generation, fossil fuel depletion, high emissions, growing demand, and transmission losses by focusing on optimal planning of Distributed Generation (DG) in distribution networks. Advanced metaheuristic algorithms are created to make systems work better, keep voltage stable, handle more load, and make more money. A Butterfly Optimization Algorithm (BOA) with an -constraint approach is proposed to minimize losses and improve loadability. Further, a Pareto-based Multi-Objective Chaotic Velocity Butterfly Optimization Algorithm (MOCVBOA) is introduced for planning non-dispatchable (PV, WT) and dispatchable (PV-BESS, WT-Biomass) DGs under renewable and load uncertainties. The dissertation also examines DG planning under Plug-In Electric Vehicle (PHEV) charging scenarios using TOPSIS-based optimal solution selection. Finally, the planning of PV and PV-BESS units, considering both conventional and PHEV loads under private and public charging scenarios, is analyzed. Results show that optimal DG integration significantly reduces energy losses, improves voltage profiles, and mitigates PHEV-induced stress.…