Sarmad Ibrahim - Academia.edu (original) (raw)
Papers by Sarmad Ibrahim
Electric Power Systems Research, 2019
High penetration of distributed generation (DG) can cause fast voltage changes in distribution sy... more High penetration of distributed generation (DG) can cause fast voltage changes in distribution systems. Inverterbased DG can be a significant source of reactive power, which brings new opportunities to improve the performance of the distribution system. An integrated control strategy is formulated for the coordinated control of both distribution system equipment and inverter-based DG. The control strategy combines the use of inverter reactive power capability with the operation of voltage regulators in order to improve the expected value of a desired figure of merit (e.g., system losses) while maintaining appropriate system voltage magnitudes, by formulating chance constraints on the voltage magnitudes. The effectiveness of the proposed method is validated using the IEEE 123-node radial distribution system.
Electric Power Components and Systems (Taylor & Francis), 2020
The traditional service restoration methods are experiencing a significant challenge because the ... more The traditional service restoration methods are experiencing a significant challenge because the performance of such methods is often dominated by very large processing time. Therefore, it is important to develop a fast and an accurate method to solve a complex non-linear optimization problem representing the service restoration problem in a distribution system. In this paper, due to a binary nature of the service restoration problem, the Binary Water Cycle Algorithm (BWCA) is proposed to reduce out-of-service loads and system losses considering operational constraints, the radial topology of the distribution systems, and the influence of the presence of distributed generations (DGs) on the service restoration problem. The proposed method is a modified form of the Water Cycle Algorithm (WCA) that is mainly used for discrete and continuous optimization problems. The effectiveness of the proposed method is validated by comparing with other well-known meta-heuristic algorithms using a modified IEEE 33-node radial distribution system. The simulation results demonstrate the robustness of this method to provide a precise decision with short convergence time for solving service restoration problems.
International journal of electrical and computer engineering systems
Saetak Today&amp... more Saetak Today's visualization tools are equipped with highly interactive visual aids, which allow analysis and inspection of complex numerical data generated from high-bandwidth data sources such as simulation software, experimental rigs, satellites, scanners, etc. Such tools help ...
OF DISSERTATION DISTRIBUTION SYSTEM OPTIMIZATION WITH INTEGRATED DISTRIBUTED GENERATION In this d... more OF DISSERTATION DISTRIBUTION SYSTEM OPTIMIZATION WITH INTEGRATED DISTRIBUTED GENERATION In this dissertation, several volt-var optimization methods have been proposed to improve the expected performance of the distribution system using distributed renewable energy sources and conventional volt-var control equipment:photovoltaic inverter reactive power control for chance-constrained distribution system performance optimisation, integrated distribution system optimization using a chance-constrained formulation, integrated control of distribution system equipment and distributed generation inverters, and coordination of PV inverters and voltage regulators considering generation correlation and voltage quality constraints for loss minimization. Distributed generation sources (DGs) have important benefits, including the use of renewable resources, increased customer participation, and decreased losses. However, as the penetration level of DGs increases, the technical challenges of integr...
Integrated distribution system optimization using a chance-constrained formulation
2017 North American Power Symposium (NAPS), 2017
The rapidly rising penetration level of distributed generators (DGs) increases the risk of unacce... more The rapidly rising penetration level of distributed generators (DGs) increases the risk of unacceptable voltages in distribution systems. The conventional voltage regulation devices are limited by physical constraints in their ability to perform voltage/var control in response to photovoltaic (PV) output fluctuations. However, the reactive power capability of PV inverters alongside with conventional voltage regulation devices can be used to address this challenge. This paper proposes a integrated volt/var method based on a control action ahead of time to find both the optimal voltage regulation tap settings and PV reactive control parameters in which the maximum expected system performance with respect to a figure of merit of interest can be achieved while maintaining appropriate system voltage magnitudes and considering the uncertainty of PV power injections over the interval of interest. The effectiveness of the proposed method is validated using a modified IEEE 123-node radial di...
Electric Power Components and Systems, 2020
Electric Power Components and Systems, 2020
Distributed generation sources (DGs) are widely considered as important sources of power generati... more Distributed generation sources (DGs) are widely considered as important sources of power generation in distribution systems during the last few decades. Despite the substantial benefits of DGs, increasing the penetration level of the DGs can cause dramatic voltage magnitude fluctuations. Coordination of the use of dynamic reactive power sources such as photovoltaic (PV) inverters and voltage control equipment can mitigate rapid voltage magnitude fluctuations. A coordinated voltvar control method is proposed herein to achieve the optimal expected performance (e.g., system losses) while considering the spatial correlation among PV source powers and constraining the variability of voltage magnitudes throughout the distribution network within permissible ranges. The proposed strategy formulates chance constraints on the voltage magnitude and considers the uncertainty of PV power injections over the interval of interest to maintain voltage magnitudes within acceptable limits. The proposed method has been tested on the IEEE 123node radial distribution system for validation. Moreover, the simulation results demonstrate that the proposed method can effectively mitigate the fast voltage magnitude deviations with an acceptable reduction in system losses in the presence of intermittent renewable resources.
International Journal of Intelligent Engineering and Systems, 2020
This paper presents an Enhanced Water Cycle Algorithm (EWCA) to optimize the network reconfigurat... more This paper presents an Enhanced Water Cycle Algorithm (EWCA) to optimize the network reconfiguration and distributed generation (DG) integration simultaneously for minimizing system power losses and improving voltage stability index (VSI) in the distribution system while considering all operational constraints. For validation, the performance of the proposed method is compared with other methods, which utilized well-known meta-heuristic algorithms. Different cases for network reconfiguration and DG integration are carried out in order to evaluate the performance of the proposed method. The effectiveness of the proposed method is assessed using the IEEE 69-node radial distribution system. According to the simulation results obtained, the proposed method in which the simultaneous optimal network reconfiguration and the DG size and location are implemented can provide a remarkable solution in terms of power loss reduction and voltage profile improvement. The proposed method also proved its superiority compared with other existing methods in terms of power loss reduction (i.e., 84.2% loss reduction compared with the base case).
IET Generation, Transmission & Distribution, 2018
Distributed generation has many potential benefits including use of renewable resources, increase... more Distributed generation has many potential benefits including use of renewable resources, increased customer participation, and decreased losses. However, as the penetration of distributed renewable energy sources increases, the technical challenges of integrating these resources into the power system increase as well. One such challenge is the rapid variation of voltages along distribution feeders in response to photovoltaic (PV) output fluctuations, and the reactive power capability of PV inverters can be used to address this challenge. A method of achieving optimal expected performance with respect to a figure of merit of interest to the distribution system operator while maintaining appropriate system voltage magnitudes and considering the uncertainty of PV power injections is proposed. The method utilises reactive power injection both to improve system performance and to compensate for variations in active power injection. It requires infrequent communication between the distribution system operator and the PV inverters and bases its decisions on short-term forecasts, formulating voltage magnitude requirements as chance constraints. The proposed method is validated using the IEEE 123-node radial distribution test feeder and shown to improve the distribution system performance (with respect to existing methods) and maintain suitable voltages.
Energies
In this paper, the role of soft open point (SOP) is investigated with and without system re-confi... more In this paper, the role of soft open point (SOP) is investigated with and without system re-configuration (SR) in reducing overall system power losses and improving voltage profile, as well as the effect of increasing the number of SOPs connected to distribution systems under different scenarios using a proposed hybrid water cycle algorithm (HWCA). The HWCA is formulated to enhance the water cycle algorithm (WCA) search performance based on the genetic algorithm (GA) for a complex nonlinear problem with discrete and continuous variables represented in this paper by SOP installation and SR. The WCA is one of the most effective optimization algorithms, however, it may have difficulty striking a balance between exploration and exploitation due to the nature of the proposed nonlinear optimization problem, which mostly causes slow convergence and poor robustness. Consequently, the HWCA proposed in this paper is an efficient solution to improve the balance between exploration and exploita...
International Journal of Intelligent Engineering and Systems, 2020
Classification of a brain tumor is a critical step in the design of computer-aided diagnosis syst... more Classification of a brain tumor is a critical step in the design of computer-aided diagnosis systems for Magnetic Resonance Image (MRI) analysis. This work presents an efficient algorithm to classify a tumor in brain MRI images using statistical-based features and deep neural network. Data, within the region of interest, is transformed into two-dimensional discrete Gabor filter and wavelet transform. These filters are combined in this algorithm as directional transformation methods for utilizing all information in all orientations of the MRI input image. MRI Features are extracted based on the first and second order statistics from both domains. Two types of neural network classifiers are employed: Stacked Sparse Autoencoder (SSA) and Softmax Classifier (SMC). Two regularization functions are used in the training of the SA, sparsity regularization and L2-weight regularization. Sparsity regularization controls the firing of the neurons in the hidden layer, whereas L2-weight regularization reduces the effect of the overfitting and improves the performance of the SA. Two datasets are used to evaluate the proposed algorithm. The first dataset consists of 3,064 of T1-weighted MRI slices with three kinds of tumors: Pituitary, Glioma, and Meningioma. The second dataset consists of 200 MRI slices with low-grade and high-grade Glioma tumor collected from the BRATS dataset. The performance of the proposed algorithm is validated using the experimental results in terms of accuracy, specificity, and sensitivity compared to the existing algorithms. For the first dataset, the accuracy obtained is 94.0%, the sensitivity of Meningioma, Glioma, and Pituitary is 87.44%, 97.29%, and 94.27%, respectively, and the specificity of Meningioma, Glioma, and Pituitary is 98%, 96.89%, and 96.78%, respectively. For the BRATS dataset, the accuracy, the specificity, and the sensitivity achieved are 98.8%, 100%, and 100%, respectively.
Electric Power Systems Research, 2019
High penetration of distributed generation (DG) can cause fast voltage changes in distribution sy... more High penetration of distributed generation (DG) can cause fast voltage changes in distribution systems. Inverterbased DG can be a significant source of reactive power, which brings new opportunities to improve the performance of the distribution system. An integrated control strategy is formulated for the coordinated control of both distribution system equipment and inverter-based DG. The control strategy combines the use of inverter reactive power capability with the operation of voltage regulators in order to improve the expected value of a desired figure of merit (e.g., system losses) while maintaining appropriate system voltage magnitudes, by formulating chance constraints on the voltage magnitudes. The effectiveness of the proposed method is validated using the IEEE 123-node radial distribution system.
Electric Power Components and Systems (Taylor & Francis), 2020
The traditional service restoration methods are experiencing a significant challenge because the ... more The traditional service restoration methods are experiencing a significant challenge because the performance of such methods is often dominated by very large processing time. Therefore, it is important to develop a fast and an accurate method to solve a complex non-linear optimization problem representing the service restoration problem in a distribution system. In this paper, due to a binary nature of the service restoration problem, the Binary Water Cycle Algorithm (BWCA) is proposed to reduce out-of-service loads and system losses considering operational constraints, the radial topology of the distribution systems, and the influence of the presence of distributed generations (DGs) on the service restoration problem. The proposed method is a modified form of the Water Cycle Algorithm (WCA) that is mainly used for discrete and continuous optimization problems. The effectiveness of the proposed method is validated by comparing with other well-known meta-heuristic algorithms using a modified IEEE 33-node radial distribution system. The simulation results demonstrate the robustness of this method to provide a precise decision with short convergence time for solving service restoration problems.
International journal of electrical and computer engineering systems
Saetak Today&amp... more Saetak Today's visualization tools are equipped with highly interactive visual aids, which allow analysis and inspection of complex numerical data generated from high-bandwidth data sources such as simulation software, experimental rigs, satellites, scanners, etc. Such tools help ...
OF DISSERTATION DISTRIBUTION SYSTEM OPTIMIZATION WITH INTEGRATED DISTRIBUTED GENERATION In this d... more OF DISSERTATION DISTRIBUTION SYSTEM OPTIMIZATION WITH INTEGRATED DISTRIBUTED GENERATION In this dissertation, several volt-var optimization methods have been proposed to improve the expected performance of the distribution system using distributed renewable energy sources and conventional volt-var control equipment:photovoltaic inverter reactive power control for chance-constrained distribution system performance optimisation, integrated distribution system optimization using a chance-constrained formulation, integrated control of distribution system equipment and distributed generation inverters, and coordination of PV inverters and voltage regulators considering generation correlation and voltage quality constraints for loss minimization. Distributed generation sources (DGs) have important benefits, including the use of renewable resources, increased customer participation, and decreased losses. However, as the penetration level of DGs increases, the technical challenges of integr...
Integrated distribution system optimization using a chance-constrained formulation
2017 North American Power Symposium (NAPS), 2017
The rapidly rising penetration level of distributed generators (DGs) increases the risk of unacce... more The rapidly rising penetration level of distributed generators (DGs) increases the risk of unacceptable voltages in distribution systems. The conventional voltage regulation devices are limited by physical constraints in their ability to perform voltage/var control in response to photovoltaic (PV) output fluctuations. However, the reactive power capability of PV inverters alongside with conventional voltage regulation devices can be used to address this challenge. This paper proposes a integrated volt/var method based on a control action ahead of time to find both the optimal voltage regulation tap settings and PV reactive control parameters in which the maximum expected system performance with respect to a figure of merit of interest can be achieved while maintaining appropriate system voltage magnitudes and considering the uncertainty of PV power injections over the interval of interest. The effectiveness of the proposed method is validated using a modified IEEE 123-node radial di...
Electric Power Components and Systems, 2020
Electric Power Components and Systems, 2020
Distributed generation sources (DGs) are widely considered as important sources of power generati... more Distributed generation sources (DGs) are widely considered as important sources of power generation in distribution systems during the last few decades. Despite the substantial benefits of DGs, increasing the penetration level of the DGs can cause dramatic voltage magnitude fluctuations. Coordination of the use of dynamic reactive power sources such as photovoltaic (PV) inverters and voltage control equipment can mitigate rapid voltage magnitude fluctuations. A coordinated voltvar control method is proposed herein to achieve the optimal expected performance (e.g., system losses) while considering the spatial correlation among PV source powers and constraining the variability of voltage magnitudes throughout the distribution network within permissible ranges. The proposed strategy formulates chance constraints on the voltage magnitude and considers the uncertainty of PV power injections over the interval of interest to maintain voltage magnitudes within acceptable limits. The proposed method has been tested on the IEEE 123node radial distribution system for validation. Moreover, the simulation results demonstrate that the proposed method can effectively mitigate the fast voltage magnitude deviations with an acceptable reduction in system losses in the presence of intermittent renewable resources.
International Journal of Intelligent Engineering and Systems, 2020
This paper presents an Enhanced Water Cycle Algorithm (EWCA) to optimize the network reconfigurat... more This paper presents an Enhanced Water Cycle Algorithm (EWCA) to optimize the network reconfiguration and distributed generation (DG) integration simultaneously for minimizing system power losses and improving voltage stability index (VSI) in the distribution system while considering all operational constraints. For validation, the performance of the proposed method is compared with other methods, which utilized well-known meta-heuristic algorithms. Different cases for network reconfiguration and DG integration are carried out in order to evaluate the performance of the proposed method. The effectiveness of the proposed method is assessed using the IEEE 69-node radial distribution system. According to the simulation results obtained, the proposed method in which the simultaneous optimal network reconfiguration and the DG size and location are implemented can provide a remarkable solution in terms of power loss reduction and voltage profile improvement. The proposed method also proved its superiority compared with other existing methods in terms of power loss reduction (i.e., 84.2% loss reduction compared with the base case).
IET Generation, Transmission & Distribution, 2018
Distributed generation has many potential benefits including use of renewable resources, increase... more Distributed generation has many potential benefits including use of renewable resources, increased customer participation, and decreased losses. However, as the penetration of distributed renewable energy sources increases, the technical challenges of integrating these resources into the power system increase as well. One such challenge is the rapid variation of voltages along distribution feeders in response to photovoltaic (PV) output fluctuations, and the reactive power capability of PV inverters can be used to address this challenge. A method of achieving optimal expected performance with respect to a figure of merit of interest to the distribution system operator while maintaining appropriate system voltage magnitudes and considering the uncertainty of PV power injections is proposed. The method utilises reactive power injection both to improve system performance and to compensate for variations in active power injection. It requires infrequent communication between the distribution system operator and the PV inverters and bases its decisions on short-term forecasts, formulating voltage magnitude requirements as chance constraints. The proposed method is validated using the IEEE 123-node radial distribution test feeder and shown to improve the distribution system performance (with respect to existing methods) and maintain suitable voltages.
Energies
In this paper, the role of soft open point (SOP) is investigated with and without system re-confi... more In this paper, the role of soft open point (SOP) is investigated with and without system re-configuration (SR) in reducing overall system power losses and improving voltage profile, as well as the effect of increasing the number of SOPs connected to distribution systems under different scenarios using a proposed hybrid water cycle algorithm (HWCA). The HWCA is formulated to enhance the water cycle algorithm (WCA) search performance based on the genetic algorithm (GA) for a complex nonlinear problem with discrete and continuous variables represented in this paper by SOP installation and SR. The WCA is one of the most effective optimization algorithms, however, it may have difficulty striking a balance between exploration and exploitation due to the nature of the proposed nonlinear optimization problem, which mostly causes slow convergence and poor robustness. Consequently, the HWCA proposed in this paper is an efficient solution to improve the balance between exploration and exploita...
International Journal of Intelligent Engineering and Systems, 2020
Classification of a brain tumor is a critical step in the design of computer-aided diagnosis syst... more Classification of a brain tumor is a critical step in the design of computer-aided diagnosis systems for Magnetic Resonance Image (MRI) analysis. This work presents an efficient algorithm to classify a tumor in brain MRI images using statistical-based features and deep neural network. Data, within the region of interest, is transformed into two-dimensional discrete Gabor filter and wavelet transform. These filters are combined in this algorithm as directional transformation methods for utilizing all information in all orientations of the MRI input image. MRI Features are extracted based on the first and second order statistics from both domains. Two types of neural network classifiers are employed: Stacked Sparse Autoencoder (SSA) and Softmax Classifier (SMC). Two regularization functions are used in the training of the SA, sparsity regularization and L2-weight regularization. Sparsity regularization controls the firing of the neurons in the hidden layer, whereas L2-weight regularization reduces the effect of the overfitting and improves the performance of the SA. Two datasets are used to evaluate the proposed algorithm. The first dataset consists of 3,064 of T1-weighted MRI slices with three kinds of tumors: Pituitary, Glioma, and Meningioma. The second dataset consists of 200 MRI slices with low-grade and high-grade Glioma tumor collected from the BRATS dataset. The performance of the proposed algorithm is validated using the experimental results in terms of accuracy, specificity, and sensitivity compared to the existing algorithms. For the first dataset, the accuracy obtained is 94.0%, the sensitivity of Meningioma, Glioma, and Pituitary is 87.44%, 97.29%, and 94.27%, respectively, and the specificity of Meningioma, Glioma, and Pituitary is 98%, 96.89%, and 96.78%, respectively. For the BRATS dataset, the accuracy, the specificity, and the sensitivity achieved are 98.8%, 100%, and 100%, respectively.