Imagen de Portada

Techno-Economic Design of a Hybrid Photovoltaic–Wind System for a Residential Microgrid Considering Uncertainties Using Dynamic Parameters Bald Eagle Algorithm

Guardado en:
Publicado en:International Journal of Energy Research vol. 2025 (2025)
Autor principal: Mehrdad Ahmadi Kamarposhti
Otros Autores: Shokouhandeh, Hassan, Outbib, Rachid, Colak, Ilhami, El Manaa Barhoumi
Publicado:
John Wiley & Sons, Inc.
Materias:
Fuel cells
Load shedding
Particle swarm optimization
Marine mammals
Electrical loads
System reliability
Distributed generation
Random variables
Algorithms
Wind
Systems design
Fines & penalties
Probability density functions
Energy resources
Statistical analysis
Uncertainty
Radiation
Photovoltaic cells
Efficiency
Design optimization
Monte Carlo simulation
Photovoltaics
Cost reduction
Renewable resources
Objective function
Cost analysis
Hybrid systems
Alternative energy sources
Cost control
Parameters
Operating costs
Economic
Acceso en línea:Citation/Abstract
Full Text
Full Text - PDF
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Resumen:This paper presents a probabilistic cost-based model for grid-connected photovoltaic (PV)–wind hybrid system design, employing probability density functions (PDFs) and Monte Carlo simulation (MCS) to address renewable generation and load demand uncertainties. The proposed scenario-based approach features an innovative objective function incorporating weighted scenario costs, allowing controlled load shedding through energy not supplied (ENS) penalties while enforcing system reliability via a loss of power supply probability (LPSP) constraint. For optimization, we develop a dynamic parameter bald eagle search (DP-BES) algorithm, demonstrating through MATLAB simulations its superior performance over Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) methods, with the hybrid PV–wind configuration achieving maximum cost reduction (41%) compared to standalone PV (33%) or wind (25%) systems.
ISSN:0363-907X
1099-114X
DOI:10.1155/er/5413946
Fuente:Advanced Technologies & Aerospace Database