Electric power grids distribution generation system for optimal location and sizing — a case study investigation by various optimization algorithms
- Ali, Ahmed, Padmanaban, Sanjeevikumar, Twala, Bhekisipho, Marwala, Tshilidzi
- Authors: Ali, Ahmed , Padmanaban, Sanjeevikumar , Twala, Bhekisipho , Marwala, Tshilidzi
- Date: 2017
- Subjects: Optimization , Simulated annealing , Genetic algorithm
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278669 , uj:29908 , Citation: Ali, A., Padmanaban, S., Twala, B. & Marwala, T. 2017. Electric power grids distribution generation system for optimal location and sizing — a case study investigation by various optimization algorithms. Energies 2017, 10, 960; doi:10.3390/en10070960
- Description: Abstract: Abstract: In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the voltage profile for the power system under investigation. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple Distribution Generation DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA), and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of a longer processing time.
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- Authors: Ali, Ahmed , Padmanaban, Sanjeevikumar , Twala, Bhekisipho , Marwala, Tshilidzi
- Date: 2017
- Subjects: Optimization , Simulated annealing , Genetic algorithm
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/278669 , uj:29908 , Citation: Ali, A., Padmanaban, S., Twala, B. & Marwala, T. 2017. Electric power grids distribution generation system for optimal location and sizing — a case study investigation by various optimization algorithms. Energies 2017, 10, 960; doi:10.3390/en10070960
- Description: Abstract: Abstract: In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the voltage profile for the power system under investigation. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple Distribution Generation DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA), and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of a longer processing time.
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Monitoring the performance of photovoltaic system DC-DC converter
- Authors: Ali, Ahmed
- Date: 2019
- Subjects: Photovoltaic effects , DC‐DC power converters , Frequency shift keying
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/403645 , uj:33833 , Citation: Ali, A. 2019. Monitoring the performance of photovoltaic system DC-DC converter.
- Description: Abstract: This paper presents a mathematical form for a stand-alone photovoltaic (PV) system that was implemented and tested at three different temperatures (15°C, 20°C and 30°C). Proteus software was used to test the PV system under the different temperatures. This system consists of an array of solar cells, which are the source of the voltage and current, these values will be transmitted to PC in order to show the received values of currents and voltages. The system has been tested under three cases; no sun and load off, sun and all load on and finally sun and load on (Vin=Vout) (Iin=Iout). In three cases studied, the system was able to effectively transmit the voltage and current by using frequency shift keying (FSK). Some negligible losses occurred apparently due to the load effect. This work was undertaken in order to study the influence of temperature as a means of optimizing, the performance of PV systems by determining the highest stand-alone PV maximum power point tracking (MPPT). Implementation results and the generated voltage show that the system achieves the highest MPPT when exposed to a 30°C temperature, while an exposure of 15°C resulted in the lowest MPPT.
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- Authors: Ali, Ahmed
- Date: 2019
- Subjects: Photovoltaic effects , DC‐DC power converters , Frequency shift keying
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/403645 , uj:33833 , Citation: Ali, A. 2019. Monitoring the performance of photovoltaic system DC-DC converter.
- Description: Abstract: This paper presents a mathematical form for a stand-alone photovoltaic (PV) system that was implemented and tested at three different temperatures (15°C, 20°C and 30°C). Proteus software was used to test the PV system under the different temperatures. This system consists of an array of solar cells, which are the source of the voltage and current, these values will be transmitted to PC in order to show the received values of currents and voltages. The system has been tested under three cases; no sun and load off, sun and all load on and finally sun and load on (Vin=Vout) (Iin=Iout). In three cases studied, the system was able to effectively transmit the voltage and current by using frequency shift keying (FSK). Some negligible losses occurred apparently due to the load effect. This work was undertaken in order to study the influence of temperature as a means of optimizing, the performance of PV systems by determining the highest stand-alone PV maximum power point tracking (MPPT). Implementation results and the generated voltage show that the system achieves the highest MPPT when exposed to a 30°C temperature, while an exposure of 15°C resulted in the lowest MPPT.
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Optimization of PV Model using Fuzzy- Neural Network for DC-DC converter systems
- Authors: Ali, Ahmed , Hasan, Ali N.
- Date: 2018
- Subjects: Fuzzy Neural Network , Maximum power point tracking , Photo- voltaic
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/274566 , uj:29300 , Citation: Ali, A. & Hasan, A.N. 2018. Optimization of PV Model using Fuzzy- Neural Network for DC-DC converter systems.
- Description: Abstract: Due to the large demand on energy, energy sources, as well as the problems of the environment such as the dynamic weather conditions. Hence the world researchers nowadays are moving toward using solar energy because it gives different advantages over the traditional energy sources such as low maintenance costs, eternal sun energy, and the lack of revival of the gases of green houses. As a result, the photo- voltaic (PV) systems' power will be reduced. Under different weather conditions, maximizing the power point tracking (MPPT) is an important part to improve the solar systems power. In this paper, we introduce the neural network approaches for the PV systems. This paper also presents a novel application of Fuzzy Neural Network (FNN) in modeling a PV. The photovoltaic system model is designed with the use of MATLAB/SIMULINK software program with the connection of a DC-DC boost converter, a Maximum Power Point Tracking (MPPT) controller, a one-phase Voltage Source Converter (VSC) and a three-level bridge. The MPPT controller is used to cover the need for advanced controller that can detect the maximum power point in solar cell systems that have unstable current and voltage and keep the resultant power per cost low.
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- Authors: Ali, Ahmed , Hasan, Ali N.
- Date: 2018
- Subjects: Fuzzy Neural Network , Maximum power point tracking , Photo- voltaic
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/274566 , uj:29300 , Citation: Ali, A. & Hasan, A.N. 2018. Optimization of PV Model using Fuzzy- Neural Network for DC-DC converter systems.
- Description: Abstract: Due to the large demand on energy, energy sources, as well as the problems of the environment such as the dynamic weather conditions. Hence the world researchers nowadays are moving toward using solar energy because it gives different advantages over the traditional energy sources such as low maintenance costs, eternal sun energy, and the lack of revival of the gases of green houses. As a result, the photo- voltaic (PV) systems' power will be reduced. Under different weather conditions, maximizing the power point tracking (MPPT) is an important part to improve the solar systems power. In this paper, we introduce the neural network approaches for the PV systems. This paper also presents a novel application of Fuzzy Neural Network (FNN) in modeling a PV. The photovoltaic system model is designed with the use of MATLAB/SIMULINK software program with the connection of a DC-DC boost converter, a Maximum Power Point Tracking (MPPT) controller, a one-phase Voltage Source Converter (VSC) and a three-level bridge. The MPPT controller is used to cover the need for advanced controller that can detect the maximum power point in solar cell systems that have unstable current and voltage and keep the resultant power per cost low.
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Optimization of PV systems using ANN-PSO configuration technique under different weather conditions
- Farayola, Adedayo M., Sun, Yanxia, Ali, Ahmed
- Authors: Farayola, Adedayo M. , Sun, Yanxia , Ali, Ahmed
- Date: 2018
- Subjects: MPPT , GMPPT , P&O
- Language: English
- Type: Conference proceeding
- Identifier: http://hdl.handle.net/10210/290080 , uj:31485 , Citation: Farayola, A.M., Sun, Y. & Ali, A. 2018. Optimization of PV systems using ANN-PSO configuration technique under different weather conditions.
- Description: Abstract: Conventional MPPT techniques like Perturb&observe perform ineffective under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) technique is a recent meta-heuristic MPPT technique commonly used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel use of hybrid ANNPSO technique implemented using series-connected distributive MPPT configuration approach. The results of ANN-PSO distributive MPPT, PSO, and Perturb&observe (P&O) technique were compared with theoretical power values under different weather conditions. This work was done to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO DMPPT configuration exhibited the best performance.
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- Authors: Farayola, Adedayo M. , Sun, Yanxia , Ali, Ahmed
- Date: 2018
- Subjects: MPPT , GMPPT , P&O
- Language: English
- Type: Conference proceeding
- Identifier: http://hdl.handle.net/10210/290080 , uj:31485 , Citation: Farayola, A.M., Sun, Y. & Ali, A. 2018. Optimization of PV systems using ANN-PSO configuration technique under different weather conditions.
- Description: Abstract: Conventional MPPT techniques like Perturb&observe perform ineffective under partial shading condition due to its inability to effectively track the global maximum power point (GMPP). Particle swarm optimization (PSO) technique is a recent meta-heuristic MPPT technique commonly used to extract maximum power from PV systems but takes time to iteratively locate the GMPP. This paper presents a novel use of hybrid ANNPSO technique implemented using series-connected distributive MPPT configuration approach. The results of ANN-PSO distributive MPPT, PSO, and Perturb&observe (P&O) technique were compared with theoretical power values under different weather conditions. This work was done to determine the most efficient MPPT method that can be considered for MPPT task in PV systems under uniform irradiance and partial shading conditions. Obtained results show that ANN-PSO DMPPT configuration exhibited the best performance.
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Proportional study of perturb & observe and fuzzy logic control MPPT algorithm for a PV system under different weather conditions
- Nkambule, Mpho, Hasan, Ali N, Ali, Ahmed
- Authors: Nkambule, Mpho , Hasan, Ali N , Ali, Ahmed
- Date: 2019
- Subjects: Maximum power point tracking (MPPT) , Partial shading conditions (PSC) , Perturb and Observe
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/403635 , uj:33832 , Citation: Nkambule, M., Hasan, A.N. & Ali, A. 2019. Proportional study of perturb & observe and fuzzy logic control MPPT algorithm for a PV system under different weather conditions.
- Description: Abstract: Abstract—Photovoltaic (PV) system are highly affected by varying of insolation and temperature condition. Since a PV cell characteristic is a non-linear, P-V curve of a PV system shows multiple power peaks under partial shading conditions (PSC). Therefore, it is necessary to track the global maximum power to avoid the PV system operating in local peak power that result in a power loss. This paper presents the comparative study and evaluation of two maximum power point tracking (MPPT) algorithms, namely Perturb & Observe (P&O) and Fuzzy Logic Control (FLC). The MATLAB SIMULINK software is used to validate and prove the performance of the two MPPT techniques.
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- Authors: Nkambule, Mpho , Hasan, Ali N , Ali, Ahmed
- Date: 2019
- Subjects: Maximum power point tracking (MPPT) , Partial shading conditions (PSC) , Perturb and Observe
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/403635 , uj:33832 , Citation: Nkambule, M., Hasan, A.N. & Ali, A. 2019. Proportional study of perturb & observe and fuzzy logic control MPPT algorithm for a PV system under different weather conditions.
- Description: Abstract: Abstract—Photovoltaic (PV) system are highly affected by varying of insolation and temperature condition. Since a PV cell characteristic is a non-linear, P-V curve of a PV system shows multiple power peaks under partial shading conditions (PSC). Therefore, it is necessary to track the global maximum power to avoid the PV system operating in local peak power that result in a power loss. This paper presents the comparative study and evaluation of two maximum power point tracking (MPPT) algorithms, namely Perturb & Observe (P&O) and Fuzzy Logic Control (FLC). The MATLAB SIMULINK software is used to validate and prove the performance of the two MPPT techniques.
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Total harmonic distortion Performance in PV systems using Fuzzy Logic Controller
- Ali, Ahmed, Twala, Bhekisipho, Marwala, Tshilidzi, Boulkaibet, Ilyes
- Authors: Ali, Ahmed , Twala, Bhekisipho , Marwala, Tshilidzi , Boulkaibet, Ilyes
- Date: 2018
- Subjects: Fuzzy Logic Controller (FLC) , Variable Frequency drivers (VFDs) , Active power filters (APF)
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/278807 , uj:29926 , Citation: Ali, A. et al. 2018. Total harmonic distortion Performance in PV systems using Fuzzy Logic Controller.
- Description: Abstract: Solar photovoltaic (PV) and wind farm systems of renewable energy installations have been considered as the promising generating source that would cover the continuous energy demand. With the high incoming penetration of distribution generators (DG), both the end users of the electric power as well as the electric utilities have become more concerned on the issue of the electric network quality. A particular issue falling under the umbrella concept is capacitive coupling with the grounding systems that have become essential as a result of the high-frequency current that is imposed by the converters of power. Total harmonic distortion (THD) is limited by the quality standards of power (IEEE-519) within the range that is acceptable caused by power electronic equipment rapid usage. Thus, the primary aim of the work is to broaden the investigation of the power systems quality problems.
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- Authors: Ali, Ahmed , Twala, Bhekisipho , Marwala, Tshilidzi , Boulkaibet, Ilyes
- Date: 2018
- Subjects: Fuzzy Logic Controller (FLC) , Variable Frequency drivers (VFDs) , Active power filters (APF)
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/278807 , uj:29926 , Citation: Ali, A. et al. 2018. Total harmonic distortion Performance in PV systems using Fuzzy Logic Controller.
- Description: Abstract: Solar photovoltaic (PV) and wind farm systems of renewable energy installations have been considered as the promising generating source that would cover the continuous energy demand. With the high incoming penetration of distribution generators (DG), both the end users of the electric power as well as the electric utilities have become more concerned on the issue of the electric network quality. A particular issue falling under the umbrella concept is capacitive coupling with the grounding systems that have become essential as a result of the high-frequency current that is imposed by the converters of power. Total harmonic distortion (THD) is limited by the quality standards of power (IEEE-519) within the range that is acceptable caused by power electronic equipment rapid usage. Thus, the primary aim of the work is to broaden the investigation of the power systems quality problems.
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Use of MPPT techniques to reduce the energy pay-back time in PV systems
- Farayola, Adedayo M., Hasan, Ali N., Ali, Ahmed
- Authors: Farayola, Adedayo M. , Hasan, Ali N. , Ali, Ahmed
- Date: 2018
- Subjects: Artificial Intelligence (AI) , ANFIS , ANN
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/274581 , uj:29302 , Citation: Farayola, A.M., Hasan, A.N. & Ali, A. 2018. Use of MPPT techniques to reduce the energy pay-back time in PV systems.
- Description: Abstract: Photovoltaic (PV) energy is a free-energy that is used as an alternative to fossil fuel energy. However, PV system without maximum power point tracking (MPPT) produces a low, unstable power and with a long energy pay-back time. This paper presents an innovative artificial neuro-fuzzy inference system (ANFIS) MPPT technique that could extract maximum power from a complete PV system and with a lessened EPBT. To confirm the effectiveness of the ANFIS algorithm, its result was compared with the results of PV system using Perturb&Observe (P&O) technique, non-MPPT technique, combination of artificial neural network and support vector machine as ANN-SVM technique and using Pretoria city weather data as case studies. Results show that ANFIS-MPPT yielded the best result and with the lowest EPBT.
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- Authors: Farayola, Adedayo M. , Hasan, Ali N. , Ali, Ahmed
- Date: 2018
- Subjects: Artificial Intelligence (AI) , ANFIS , ANN
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/274581 , uj:29302 , Citation: Farayola, A.M., Hasan, A.N. & Ali, A. 2018. Use of MPPT techniques to reduce the energy pay-back time in PV systems.
- Description: Abstract: Photovoltaic (PV) energy is a free-energy that is used as an alternative to fossil fuel energy. However, PV system without maximum power point tracking (MPPT) produces a low, unstable power and with a long energy pay-back time. This paper presents an innovative artificial neuro-fuzzy inference system (ANFIS) MPPT technique that could extract maximum power from a complete PV system and with a lessened EPBT. To confirm the effectiveness of the ANFIS algorithm, its result was compared with the results of PV system using Perturb&Observe (P&O) technique, non-MPPT technique, combination of artificial neural network and support vector machine as ANN-SVM technique and using Pretoria city weather data as case studies. Results show that ANFIS-MPPT yielded the best result and with the lowest EPBT.
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