A developed concentrated solar power model using artificial neural network technique

Moukhtar, Ibrahim; Elbaset, Adel A.; Dein, Adel Z. El; Qudaih, Yaser; Blagin, E.V.; Uglanov, D.A.; Mitani, Yasunori

doi:10.1109/mepcon.2017.8301357

Cited by 4 publications

(5 citation statements)

References 19 publications

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“…The voltage at node D 1 is higher than at node D 5, and the voltage drop percentage at nodes D 1 and D 5 are 1.2% and 1.53%, respectively. This voltage drop is lower than the drop using utility system only due to the excess power supply generated by the microgrids, [9,11,12] which is applied to loads at their nodes to overcome the voltage drop due to line impedances, as shown in Tab. 1, Fig.…”

Section: Scenario A: Voltage Analysis Of Microgrid and Utility System...mentioning

confidence: 96%

“…SRCI is the atmosphere clearness measure, which is the fraction of solar radiation that is transmitted through the atmosphere that reaches the surface of the earth. The New Assiut City region has an average irradiance level between 3.5 and 8.1 kWh/m²/day [9,11,12]. In summer months, solar irradiance is more than 8.1 kWh/m 2 /day, while during the winter months, irradiation is at its lowest level, 3.5 kWh/m 2 /day, as shown in Fig.…”

Section: Solar Profilementioning

confidence: 98%

“…Actual sunshine hours reach 11 hours per day. Thus, it is efficient to use solar energy as a renewable source in New Assiut City rather than using conventional energy sources [9][10][11][12][13].…”

Section: Solar Profilementioning

confidence: 99%

“…Figure 4: Average monthly irradiance (kW/m 2 /day) and clearness index (CI) values for New Assiut City, Egypt[9,11,12] …”

mentioning

confidence: 99%

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Improving the Power Quality of Smart Microgrid Based Solar Photovoltaic Systems

El-Zohri¹,

Rezk²,

Alamri³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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Microgrids are hybrid power systems that consist of several distributed generation resources and local loads that can supply electrical power to remote or specific areas. The integration of microgrids with the utility network is one of the most recent technologies developed in countries like Egypt. One area of study is how the integration of smart microgrids and utility systems can be used to solve power quality problems such as voltage sags, increased use of distributed generators, deep energy, and power loss. This paper is aimed at investigating a possible solution to some common and dangerous power quality issues associated with the integration of smart microgrids and utility systems such as voltage fluctuation and total harmonic distortion (THD) at different solar irradiance and load conditions. This study used a MATLAB and Simulink code developed to model and analyze smart microgrid and utility system integration and the power quality issue at different loads. This study focuses on five scenarios of voltage analysis and two scenarios of THD at different irradiance and load conditions. The results show that using an integrated smart microgrid and utility system will reduce the voltage drop percentage with high solar irradiance and will increase it with low solar irradiance at both high and low loads. Additionally, THD decreases with increasing solar irradiance and increases with decreasing solar irradiance at both high and low loads.

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Section: Scenario A: Voltage Analysis Of Microgrid and Utility System...mentioning

confidence: 96%

Section: Solar Profilementioning

confidence: 98%

Section: Solar Profilementioning

confidence: 99%

“…Figure 4: Average monthly irradiance (kW/m 2 /day) and clearness index (CI) values for New Assiut City, Egypt[9,11,12] …”

mentioning

confidence: 99%

See 2 more Smart Citations

Improving the Power Quality of Smart Microgrid Based Solar Photovoltaic Systems

El-Zohri¹,

Rezk²,

Alamri³

et al. 2021

Intelligent Automation &Amp; Soft Computing

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“…Lately, the use of Artificial Intelligence (AI) technology is synonymous in solving power system problems. AI techniques utilize the logic and knowledge representations of expert systems, artificial neural network (ANN) [11]- [12] and evolutionary computation (EC). The EC field includes PSO [13]- [17], Evolutionary Programming (EP) [8], [18]- [19], Artificial Immune Systems (AIS) [20]- [22] and Firefly Algorithm (FA) [23]- [24].…”

Section: Computational Intelligence Approachesmentioning

confidence: 99%

Oscillatory Stability Prediction Using PSO Based Synchronizing and Damping Torque Coefficients

Kamari¹,

Musirin²,

Hamid³

et al. 2018

Bulletin EEI

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This paper presents the assessment of stability domains for the angle stability condition of the power system using Particle Swarm Optimization (PSO) technique. An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to identify the angle stability condition on multi-machine system. In order to accelerate the determination of angle stability, PSO is proposed to be implemented in this study. The application of the proposed algorithm has been justified as the most accurate with lower computation time as compared to other optimization techniques such as Evolutionary Programming (EP) and Artificial Immune System (AIS). Validation with respect to eigenvalues determination, Least Square (LS) method and minimum damping ratio ξmin confirmed that the proposed technique is feasible to solve the angle stability problems.

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