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RISS 인기검색어
- 검색키워드
- 저자 : Saad A. Mohamed Abdelwahab (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Saleh B.,Yousef Ali M.,Ebeed Mohamed,Abo-Elyousr Farag K.,Elnozahy Ahmed,Mohamed Moayed,Abdelwahab Saad A. Mohamed 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.6
The main target of this paper is to allow renewable energy resources (RES) to participate eff ectively within hybrid micro grids via an optimal proportional integral- derivative (PID) controller. This paper proposes two techniques of optimal PID controllers in a hybrid renewable generation energy system. These techniques are particle swarm optimization (PSO) and lightning attachment procedure optimization (LAPO). The hybrid renewable generation energy system in this study includes a photovoltaic source, wind turbine, and battery storage, which are connected to a point of common coupling via DC/DC boost converters. The controller at the inverter consists of a current controller and voltage source controller, which results in three PID gains at each controller. In order to obtain the PID gains, a time domain objective function is formulated in terms of the voltage, and current errors. The obtained results with the individual advanced optimization LAPO and PSO algorithm are compared. The results display that the developed LAPO algorithms give better results compared to the conventional PSO at the input and output current, voltage, and power. All the results have been taken under several operating conditions of wind turbine (wind speed) and solar sun (changing irradiance and temperature).
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Elnozahy, Ahmed,Yousef, Ali M.,Abo‑Elyousr, Farag K.,Mohamed, Moayed,Abdelwahab, Saad A. Mohamed The Korean Institute of Power Electronics 2021 JOURNAL OF POWER ELECTRONICS Vol.21 No.8
The main purpose of this paper to compare and analyze three types of controllers in the three phases DC-AC inverters in hybrid renewable energy source (HRES) systems. To achieve this, two modern controllers are developed and compared based on sliding mode control (SMC) and artificial neural network techniques. The HRESs comprise photovoltaic (PV), wind turbines, battery storage systems, and transmission lines connected to infinite bus bars via a step-up transformer. The developed controllers at the inverter side utilize both voltage control and current regulation. A DC-DC boost converter is employed to set up a voltage demand at the point of common coupling (PCC). Then, the formulation of an HRES with the developed controllers is presented. The developed controllers are considered to operate under various solar radiations, temperatures, and wind speed loading conditions. The HRESs with the developed controllers are simulated via MATLAB/Simulink to verify the effectiveness of the developed controllers. The obtained results demonstrate that adaptive SMC and artificial ANN control techniques give better results in terms of input power, output power, current, and voltage when compared to classic PI control.
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Optimal Economic and Environmental Indices for Hybrid PV/ Wind-Based Battery Storage System
Elnozahy Ahmed,Yousef Ali M.,Ghoneim Sherif S. M.,Abdelwahab Saad A. Mohamed,Mohamed Moayed,Abo-Elyousr Farag K. 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.6
This paper shows an application of hybrid PV/wind energy and battery storage in the islanded area. This work’s main target allows the distributed energy resources to contribute effi ciently in the economic feasibility and enhance the environmental impact of the hybrid renewable energy source. Several factors such as levelized cost of energy (COE), greenhouse gas (GHG) emissions, and loss of power supply probability are studied. A combined solution is to compromise the economic and environmental aspects via the Utopia point approach is investigated. The optimal confi guration of the hybrid PV/wind along with battery-storage and diesel engine as secondary source is obtained via meta-heuristic optimizers: Genetic Algorithm (GA) and Particle-Swarm Optimization (PSO) and impartial comparison of the results with HOMER software. The results of Utopia point solution show that the PV (about 46%) and wind turbine (about 13%) are shared signifi cantly as primary renewable sources and battery storage (about 39%) as storage options. Meanwhile, the diesel engine (about 3%) has insignifi cant sharing in feeding the demand load. The optimal COE and GHG, which are achieved via GA and PSO optimization techniques are 0.182$/kWh and 12076 kg/year, agansit 0.343$/kWh and 17618 kg/year that are obtained via HOMER software, respectively. This corssponing to 47% and 31% reduction in COE and GHG, respectively. Sensitivity studies demonstrate that the variation of the wind energy sharing from 50 to 150% shows that the wind energy has a slight eff ect considering the GHG emissions. Contrarily, lower PV sharing ratios undesirably raises the levelized COE, however, reduces the GHG emissions.
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