A5009617303- Metaheuristic Optimization Algorithms Research
- Microgrid Control and Optimization
- Smart Grid Energy Management
- Hybrid Renewable Energy Systems
- Advanced Multi-Objective Optimization Algorithms
- Vehicle Routing Optimization Methods
- Energy and Environment Impacts
- Process Optimization and Integration
- Optimal Power Flow Distribution
- Fuel Cells and Related Materials
- Fluid Dynamics and Mixing
- Robotic Path Planning Algorithms
- Machine Learning and ELM
- Energy Load and Power Forecasting
- Religion and Sociopolitical Dynamics in Nigeria
- Frequency Control in Power Systems
- Solar Thermal and Photovoltaic Systems
- Photovoltaic System Optimization Techniques
- Aerospace Engineering and Control Systems
- Electric Vehicles and Infrastructure
- Advanced Optimization Algorithms Research
- Solar Radiation and Photovoltaics
- Teaching and Learning Programming
- Physics of Superconductivity and Magnetism
- Distributed and Parallel Computing Systems
University of Hassan II Casablanca
2023-2024
Université Hassan II Mohammedia
2024
The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by Henry's law, which describes the solubility of gas in liquid under specific pressure conditions. Since its introduction Hashim et al. 2019, HGSO has gained significant attention for unique features, including minimal adaptive parameters and balanced exploration-exploitation trade-off, leading to favorable convergence. This study provides an up-to-date survey HGSO, covering walk through historical...
As a result of advancements in technology and population growth, there has been significant rise global electrical demand. Consequently, the integration renewable sources such as photovoltaic (PV) systems into distribution gained popularity an effective solution to meet increasing load requirements. This research paper introduces optimized approach for allocating PV at various penetration levels, utilizing powerful optimization algorithm known modified Reptile Search Algorithm (MRSA). MRSA...
In this paper, an enhanced version of the Exponential Distribution Optimizer (EDO) called mEDO is introduced to tackle global optimization and multi-level image segmentation problems. EDO a math-inspired optimizer that has many limitations in handling complex multi-modal tries solve these drawbacks using 2 operators: phasor operator for diversity enhancement adaptive p-best mutation strategy preventing it converging local optima. To validate effectiveness suggested optimizer, comprehensive...
Abstract A recently developed algorithm inspired by natural processes, known as the Artificial Gorilla Troops Optimizer (GTO), boasts a straightforward structure, unique stabilizing features, and notably high effectiveness. Its primary objective is to efficiently find solutions for wide array of challenges, whether they involve constraints or not. The GTO takes its inspiration from behavior in world. To emulate impact gorillas at each stage search process, employs flexible weighting...
Gradient‐Based Optimizer (GBO) is a highly mathematics‐based metaheuristic algorithm that has garnered significant attention since its introduction. It offers several inherent advantages, such as low computational complexity, rapid convergence, and easy implementation. However, GBO some drawbacks, including lack of population diversity tendency to get trapped in local optima. To address these shortcomings, this research introduces an improved version (iGBO). In iGBO, introducing the Sobol...
This study conducts a comparative assessment to optimize the design of Hybrid Renewable Energy System (HRES) consisting PV panels, wind turbines (WTs), and hydrogen storage (PV/WT/FC). The focuses on Dakhla City, leveraging its favorable weather conditions evaluate potential renewable energy sources. A novel approach, Selective Ensemble Marine Predators (SEMPA), is introduced. SEMPA utilizes selective ensemble learning strategy enhance performance Algorithm (MPA) determine optimal system...
The purpose of this paper is to present an optimization model designed identify the ideal size for a standalone hybrid renewable energy system (HRES) that can effectively meet requirements rural community located in Southwest Morocco while maximizing profitability. HRES, which composed Photovoltaic (PV) panels, Wind Turbines (WTs), Hydrogen Tanks (HTs), Electrolyzer units, and Fuel Cell (FC) system, will be maximize efficiency DO assessed study compared commonly used methods such as Genetic...
The evaluation of photovoltaic (PV) model parameters has gained importance considering emerging new energy power systems. Because weather patterns are unpredictable, variations in PV output nonlinear and periodic. It is impractical to rely on a time series because traditional forecast techniques based linearity. As result, meta-heuristic algorithms have drawn significant attention for their exceptional performance extracting characteristics from solar cell models. This study analyzes...