A5088638819- Microgrid Control and Optimization
- Power System Optimization and Stability
- Optimal Power Flow Distribution
- Power Systems Fault Detection
- Smart Grid Energy Management
- Electric Power System Optimization
- Islanding Detection in Power Systems
- HVDC Systems and Fault Protection
- Advanced DC-DC Converters
- Multilevel Inverters and Converters
- Frequency Control in Power Systems
- Photovoltaic System Optimization Techniques
- Advanced Battery Technologies Research
- Power System Reliability and Maintenance
- Solar Radiation and Photovoltaics
- High-Voltage Power Transmission Systems
- Sensorless Control of Electric Motors
- Electric Vehicles and Infrastructure
- Hybrid Renewable Energy Systems
- Wind Turbine Control Systems
- Power Quality and Harmonics
- Advanced Control Systems Design
- Machine Fault Diagnosis Techniques
- Power Systems and Renewable Energy
- Silicon Carbide Semiconductor Technologies
King Fahd University of Petroleum and Minerals
2016-2025
Sustainable Energy Systems (United Kingdom)
2024
University of Petroleum
2024
Dhahran Health Center
2019-2023
King Abdullah City for Atomic and Renewable Energy
2019-2023
Renewable Energy Systems (United States)
2021-2023
Arabian Gulf University
2022
Saudi Aramco (Saudi Arabia)
2019
Queen's University
2019
Royal Military College of Canada
2019
This paper presents a new multiobjective evolutionary algorithm for environmental/economic power dispatch (EED) problem. The EED problem is formulated as nonlinear constrained optimization A strength Pareto (SPEA) based approach proposed to handle the true with competing and noncommensurable objectives. employs diversity-preserving mechanism overcome premature convergence search bias problems. hierarchical clustering also imposed provide decision maker representative manageable...
The potential and effectiveness of the newly developed Pareto-based multiobjective evolutionary algorithms (MOEA) for solving a real-world power system nonlinear optimization problem are comprehensively discussed evaluated in this paper. Specifically, nondominated sorting genetic algorithm, niched Pareto strength algorithm (SPEA) have been successfully applied to an environmental/economic electric dispatch problem. A new procedure quality measure is proposed paper order evaluate different...
In this paper, a novel evolutionary algorithm-based approach to optimal design of multimachine power system stabilizers (PSSs) is proposed. The proposed employs the particle swarm optimization (PSO) technique search for settings PSS parameters. Two elgenvalue-based objective functions enhance damping electromechanical modes are considered. robustness initial guess demonstrated. performance PSO-based (PSOPSS) under different disturbances, loading conditions, and configurations tested examined...
This paper presents an efficient and reliable tabu search (TS)-based approach to solve the optimal power flow (OPF) problem. The proposed employs TS algorithm for settings of control variables OPF Incorporation as a derivative-free optimization technique in solving problem significantly reduces computational burden. One main advantages is its robustness own parameter well initial solution. In addition, characterized by ability avoid entrapment local solution prevent cycling using flexible...
The dynamic nature of the distribution network challenges stability and control effectiveness microgrids in both grid-connected autonomous modes. In this paper, linear nonlinear models operating different modes are presented. Optimal design LC filter, controller parameters, damping resistance is carried out case mode. On other hand, parameters power sharing coefficients optimized problem has been formulated as an optimization where particle swarm employed to search for optimal settings each...
The utilization of renewable energy sources (RESs) has become significant throughout the world especially over last two decades. Although high-level RESs penetration reduces negative environmental impact compared to conventional fossil fuel based generation, control issues more complex as well total inertia system is significantly decreased due removal synchronous generators. Some other technical issues, high uncertainties, low fault ride through capability, current, generation reserve, and...
Optimal multiobjective design of robust multimachine power system stabilizers (PSSs) using genetic algorithms is presented in this paper. A conventional speed-based lead-lag PSS used work. The operating at various loading conditions and configurations treated as a finite set plants. are tuned to simultaneously shift the lightly damped undamped electromechanical modes all plants prescribed zone s-plane. problem formulated optimize composite objective functions comprising damping factor, ratio...
Robust design of multimachine power system stabilizers (PSSs) using simulated annealing (SA) optimization technique is presented in this paper. The proposed approach employs SA to search for optimal parameter settings a widely used conventional fixed-structure lead-lag PSS (CPSS). parameters the based stabilizer (SAPSS) are optimized order shift electromechanical modes at different loading conditions and configurations simultaneously left s-plane. Incorporation as derivative-free...
This paper demonstrates the use of genetic algorithms for simultaneous stabilization multimachine power systems over a wide range operating conditions via single-setting system stabilizers. The at various is treated as finite set plants. problem selecting parameters stabilizers which simultaneously stabilize this plants converted to simple optimization solved by algorithm with an eigenvalue-based objective function. Two functions are presented, allowing selection stabilizer shift some...