Sadiq Ahmad - Academia.edu (original) (raw)

Papers by Sadiq Ahmad

Research paper thumbnail of Configuration Detection of Grounding Grid: Static Electric Field Based Nondestructive Technique

IEEE Access

Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the ... more Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the extension in a substation. Furthermore, older substations grounding grid configurations are unknown. Existing literature regarding configuration detection mainly accounts for the magnetic field that required a gradient to locate the grounding conductor.The gradient of raw measurement in the substation vicinity enhances electromagnetic noise and distorts the results. Therefore, in this paper, we have developed a new algorithm, Configuration Detection of Grounding Grid (CDGG) based on the static electric field and the concept of ordered pairs to draw the configuration of the unknown grounding grid. Unlike, the practiced magnetic field, the electric field does not require a gradient. The maximum electric field value indicates the location of a grounding conductor. The connection between nodes is verified by measuring the electric field on the circle. Furthermore, the proposed algorithm also locates any diagonal conductor in the configuration. Mathematical reasoning and simulation results illustrate that our proposed algorithm is feasible to draw the configuration of the unknown grounding grid.

Research paper thumbnail of Towards Optimization Approaches in Smart Grid A Review*

2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)

Research paper thumbnail of Efficient Energy Management in a Microgrid

2018 International Conference on Power Generation Systems and Renewable Energy Technologies (PGSRET)

Research paper thumbnail of Joint Energy Management and Energy Trading in Residential Microgrid System

IEEE Access

The sustainability of the power systems assures consumers to have efficient and cost-effective en... more The sustainability of the power systems assures consumers to have efficient and cost-effective energy consumption. Consumers' energy management is one of the solutions that in fact boosts the power system stability via efficiently scheduling the appliances. In addition to energy management, consumers fulfill their low-cost energy consumption using decentralized energy generation (such as solar, wind, plug-in hybrid electric vehicles, and small diesel generator). This decentralized energy generation and its trading among the prosumers and consumers help in the distribution grid stability and continuous supply. In this paper, the joint energy management and energy trading model is presented, which provides low-cost electricity consumption to the distribution system. The proposed framework is a twofold system. In the first fold, the distribution system is divided into a number of microgrids, where each microgrid electricity demand is managed using a unified energy management approach. While the local energy produced is traded among the microgrids in the second fold, through energy trading concepts that fulfill the consumers' demand without stressing the utility company. The results indicate that the proposed model reduced the electricity cost of the microgrids with maximum share of self-generation. Moreover, the results also indicate that each microgrid either fulfills its electricity demand from self-generation or purchases it from the nearby microgrid.

Research paper thumbnail of AI and Blockchain Integrated Billing Architecture for Charging the Roaming Electric Vehicles

IoT

Due to the proliferation of extended travel range electric vehicles (EVs), these will travel thro... more Due to the proliferation of extended travel range electric vehicles (EVs), these will travel through different networks that might be served by different utility companies. Therefore, we propose an architecture capable of offering a charging service to roaming vehicles. Furthermore, although the energy internet supports both the flow of energy and information, it does not support seamless EV roaming service, because it is based on a centralized architecture. The blockchain technology that is based on a decentralized system has the potential to support a secure billing platform for charging the EVs roaming through different electrical jurisdictions. Furthermore, the integration of artificial intelligence (AI) ensures that the participating players get a fair portion of the revenue. Thus, the objective of this paper is to develop an AI and blockchain integrated billing architecture that would offer a charging service to the “roaming” EVs and present a fair and unified billing solution.

Research paper thumbnail of Unified optimization model for energy management in sustainable smart power systems

International Transactions on Electrical Energy Systems

Research paper thumbnail of Low complexity approach for energy management in residential buildings

International Transactions on Electrical Energy Systems

Research paper thumbnail of A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid

Energies

The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch betwee... more The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch between generation and utilization in power systems is a challenging task and also a very hot topic in the current research era. Researchers of the conventional power grid in the traditional power setup are confronting difficulties to figure out the above problem. Smart grid technology can handle these issues efficiently. In the smart grid, consumer demand can be efficiently managed and handled by employing demand-side management (DSM) algorithms. In general, DSM is an important element of smart grid technology. It can shape the consumers’ electricity demand curve according to the given load curve provided by the utilities/supplier. In this survey, we focused on DSM and potential applications of DSM in the smart grid. The review in this paper focuses on the research done over the last decade, to discuss the key concepts of DSM schemes employed for consumers’ demand management. We review DSM sc...

Research paper thumbnail of Optimized Energy Consumption and Demand Side Management in Smart Grid

Smart Grid as a Solution for Renewable and Efficient Energy, 2000

This chapter reviews prevailing methodologies and future techniques to optimize energy consumptio... more This chapter reviews prevailing methodologies and future techniques to optimize energy consumption. It discerns that smart grid provides better tools and equipment to control and monitor the consumer load, and optimize the energy consumption. Smart grid is essentially composed of smart energy equipment, advance metering infrastructure and Phasor Measurement Units (Synchrophaors) that helps to achieve optimized energy consumption. The chapter also places focus on demand side management and optimized energy consumption scheduling; and establishes that both, the utilities, as well as the users can play a vital role in intelligent energy consumption and optimization. The literature review also reveals smart protection, self-healing systems and off-peak operation result in minimizing transmission and distribution losses, as well as optimizing the energy consumption.

Research paper thumbnail of Smart energy-consumption management system considering consumers' spending goals (SEMS-CCSG)

International Transactions on Electrical Energy Systems, 2015

Research paper thumbnail of Applications of ICA in Cognitive Radio Sensor Networks," Book chapter in Cognitive Radio Sensor Networks

Research paper thumbnail of Applications of Independent Component Analysis in Endmember Extraction and Abundance Quantification for Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2000

Independent component analysis (ICA) has shown success in many applications. This paper investiga... more Independent component analysis (ICA) has shown success in many applications. This paper investigates a new application of the ICA in endmember extraction and abundance quantification for hyperspectral imagery. An endmember is generally referred to as an idealized pure signature for a class whose presence is considered to be rare. When it occurs, it may not appear in large population. In this case, the commonly used principal components analysis may not be effective since endmembers usually contribute very little in statistics to data variance. In order to substantiate the author's findings, an ICA-based approach, called ICA-based abundance quantification algorithm (ICA-AQA) is developed. Three novelties result from the author's proposed ICA-AQA. First, unlike the commonly used least squares abundance-constrained linear spectral mixture analysis (ACLSMA) which is a second-order statistics-based method, the ICA-AQA is a high-order statistics-based technique. Second, due to the use of statistical independency, it is generally thought that the ICA cannot be implemented as a constrained method. The ICA-AQA shows otherwise. Third, in order for the ACLSMA to perform the abundance quantification, it requires an algorithm to find image endmembers first then followed by an abundance-constrained algorithm for quantification. As opposed to such a two-stage process, the ICA-AQA can accomplish endmember extraction and abundance quantification simultaneously in one-shot operation. Experimental results demonstrate that the ICA-AQA performs at least comparably to abundance-constrained methods. Index Terms-Abundance-constrained linear spectral mixture analysis (ACLSMA), abundance quantification, endmember extraction, FastICA, high-order statistics-based independent component (IC) prioritization algorithm (HOS-ICPA), IC prioritization, ICA-based endmember extraction algorithm (ICA-EEA), independent component analysis (ICA)-based abundance quantification algorithm (ICA-AQA), initialization driven-based IC prioritization algorithm (ID-ICPA), virtual dimensionality (VD).

Research paper thumbnail of A Survey on Radio Resource Allocation in Cognitive Radio Sensor Networks

ABSTRACT Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical (... more ABSTRACT Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical (ISM) band for transmissions. However, with the increasing usage and demand of these networks, the currently available ISM band does not suffice for their transmissions. This spectrum insufficiency problem has been overcome by incorporating the opportunistic spectrum access capability of cognitive radio (CR) into the existing WSN, thus giving birth to CR sensor networks (CRSNs). The sensor nodes in CRSNs depend on power sources that have limited power supply capabilities. Therefore, advanced and intelligent radio resource allocation schemes are very essential to perform dynamic and efficient spectrum allocation among sensor nodes and to optimize the energy consumption of each individual node in the network. Radio resource allocation schemes aim to ensure QoS guarantee, maximize the network lifetime, reduce the internode and internetwork interferences, etc. In this paper, we present a survey of the recent advances in radio resource allocation in CRSNs. Radio resource allocation schemes in CRSNs are classified into three major categories, i.e., centralized, cluster-based, and distributed. The schemes are further divided into several classes on the basis of performance optimization criteria that include energy efficiency, throughput maximization, QoS assurance, interference avoidance, fairness and priority consideration, and hand-off reduction. An insight into the related issues and challenges is provided, and future research directions are clearly identified.

Research paper thumbnail of Radio Resource Management in Cognitive Radio Sensor Networks

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band... more Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs' research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted.

Research paper thumbnail of Configuration Detection of Grounding Grid: Static Electric Field Based Nondestructive Technique

IEEE Access

Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the ... more Grounding grid configuration which, is key to its fault diagnosis, changes continuously with the extension in a substation. Furthermore, older substations grounding grid configurations are unknown. Existing literature regarding configuration detection mainly accounts for the magnetic field that required a gradient to locate the grounding conductor.The gradient of raw measurement in the substation vicinity enhances electromagnetic noise and distorts the results. Therefore, in this paper, we have developed a new algorithm, Configuration Detection of Grounding Grid (CDGG) based on the static electric field and the concept of ordered pairs to draw the configuration of the unknown grounding grid. Unlike, the practiced magnetic field, the electric field does not require a gradient. The maximum electric field value indicates the location of a grounding conductor. The connection between nodes is verified by measuring the electric field on the circle. Furthermore, the proposed algorithm also locates any diagonal conductor in the configuration. Mathematical reasoning and simulation results illustrate that our proposed algorithm is feasible to draw the configuration of the unknown grounding grid.

Research paper thumbnail of Towards Optimization Approaches in Smart Grid A Review*

2019 2nd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET)

Research paper thumbnail of Efficient Energy Management in a Microgrid

2018 International Conference on Power Generation Systems and Renewable Energy Technologies (PGSRET)

Research paper thumbnail of Joint Energy Management and Energy Trading in Residential Microgrid System

IEEE Access

The sustainability of the power systems assures consumers to have efficient and cost-effective en... more The sustainability of the power systems assures consumers to have efficient and cost-effective energy consumption. Consumers' energy management is one of the solutions that in fact boosts the power system stability via efficiently scheduling the appliances. In addition to energy management, consumers fulfill their low-cost energy consumption using decentralized energy generation (such as solar, wind, plug-in hybrid electric vehicles, and small diesel generator). This decentralized energy generation and its trading among the prosumers and consumers help in the distribution grid stability and continuous supply. In this paper, the joint energy management and energy trading model is presented, which provides low-cost electricity consumption to the distribution system. The proposed framework is a twofold system. In the first fold, the distribution system is divided into a number of microgrids, where each microgrid electricity demand is managed using a unified energy management approach. While the local energy produced is traded among the microgrids in the second fold, through energy trading concepts that fulfill the consumers' demand without stressing the utility company. The results indicate that the proposed model reduced the electricity cost of the microgrids with maximum share of self-generation. Moreover, the results also indicate that each microgrid either fulfills its electricity demand from self-generation or purchases it from the nearby microgrid.

Research paper thumbnail of AI and Blockchain Integrated Billing Architecture for Charging the Roaming Electric Vehicles

IoT

Due to the proliferation of extended travel range electric vehicles (EVs), these will travel thro... more Due to the proliferation of extended travel range electric vehicles (EVs), these will travel through different networks that might be served by different utility companies. Therefore, we propose an architecture capable of offering a charging service to roaming vehicles. Furthermore, although the energy internet supports both the flow of energy and information, it does not support seamless EV roaming service, because it is based on a centralized architecture. The blockchain technology that is based on a decentralized system has the potential to support a secure billing platform for charging the EVs roaming through different electrical jurisdictions. Furthermore, the integration of artificial intelligence (AI) ensures that the participating players get a fair portion of the revenue. Thus, the objective of this paper is to develop an AI and blockchain integrated billing architecture that would offer a charging service to the “roaming” EVs and present a fair and unified billing solution.

Research paper thumbnail of Unified optimization model for energy management in sustainable smart power systems

International Transactions on Electrical Energy Systems

Research paper thumbnail of Low complexity approach for energy management in residential buildings

International Transactions on Electrical Energy Systems

Research paper thumbnail of A Compendium of Performance Metrics, Pricing Schemes, Optimization Objectives, and Solution Methodologies of Demand Side Management for the Smart Grid

Energies

The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch betwee... more The curtailing of consumers’ peak hours demands and filling the gap caused by the mismatch between generation and utilization in power systems is a challenging task and also a very hot topic in the current research era. Researchers of the conventional power grid in the traditional power setup are confronting difficulties to figure out the above problem. Smart grid technology can handle these issues efficiently. In the smart grid, consumer demand can be efficiently managed and handled by employing demand-side management (DSM) algorithms. In general, DSM is an important element of smart grid technology. It can shape the consumers’ electricity demand curve according to the given load curve provided by the utilities/supplier. In this survey, we focused on DSM and potential applications of DSM in the smart grid. The review in this paper focuses on the research done over the last decade, to discuss the key concepts of DSM schemes employed for consumers’ demand management. We review DSM sc...

Research paper thumbnail of Optimized Energy Consumption and Demand Side Management in Smart Grid

Smart Grid as a Solution for Renewable and Efficient Energy, 2000

This chapter reviews prevailing methodologies and future techniques to optimize energy consumptio... more This chapter reviews prevailing methodologies and future techniques to optimize energy consumption. It discerns that smart grid provides better tools and equipment to control and monitor the consumer load, and optimize the energy consumption. Smart grid is essentially composed of smart energy equipment, advance metering infrastructure and Phasor Measurement Units (Synchrophaors) that helps to achieve optimized energy consumption. The chapter also places focus on demand side management and optimized energy consumption scheduling; and establishes that both, the utilities, as well as the users can play a vital role in intelligent energy consumption and optimization. The literature review also reveals smart protection, self-healing systems and off-peak operation result in minimizing transmission and distribution losses, as well as optimizing the energy consumption.

Research paper thumbnail of Smart energy-consumption management system considering consumers' spending goals (SEMS-CCSG)

International Transactions on Electrical Energy Systems, 2015

Research paper thumbnail of Applications of ICA in Cognitive Radio Sensor Networks," Book chapter in Cognitive Radio Sensor Networks

Research paper thumbnail of Applications of Independent Component Analysis in Endmember Extraction and Abundance Quantification for Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2000

Independent component analysis (ICA) has shown success in many applications. This paper investiga... more Independent component analysis (ICA) has shown success in many applications. This paper investigates a new application of the ICA in endmember extraction and abundance quantification for hyperspectral imagery. An endmember is generally referred to as an idealized pure signature for a class whose presence is considered to be rare. When it occurs, it may not appear in large population. In this case, the commonly used principal components analysis may not be effective since endmembers usually contribute very little in statistics to data variance. In order to substantiate the author's findings, an ICA-based approach, called ICA-based abundance quantification algorithm (ICA-AQA) is developed. Three novelties result from the author's proposed ICA-AQA. First, unlike the commonly used least squares abundance-constrained linear spectral mixture analysis (ACLSMA) which is a second-order statistics-based method, the ICA-AQA is a high-order statistics-based technique. Second, due to the use of statistical independency, it is generally thought that the ICA cannot be implemented as a constrained method. The ICA-AQA shows otherwise. Third, in order for the ACLSMA to perform the abundance quantification, it requires an algorithm to find image endmembers first then followed by an abundance-constrained algorithm for quantification. As opposed to such a two-stage process, the ICA-AQA can accomplish endmember extraction and abundance quantification simultaneously in one-shot operation. Experimental results demonstrate that the ICA-AQA performs at least comparably to abundance-constrained methods. Index Terms-Abundance-constrained linear spectral mixture analysis (ACLSMA), abundance quantification, endmember extraction, FastICA, high-order statistics-based independent component (IC) prioritization algorithm (HOS-ICPA), IC prioritization, ICA-based endmember extraction algorithm (ICA-EEA), independent component analysis (ICA)-based abundance quantification algorithm (ICA-AQA), initialization driven-based IC prioritization algorithm (ID-ICPA), virtual dimensionality (VD).

Research paper thumbnail of A Survey on Radio Resource Allocation in Cognitive Radio Sensor Networks

ABSTRACT Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical (... more ABSTRACT Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical (ISM) band for transmissions. However, with the increasing usage and demand of these networks, the currently available ISM band does not suffice for their transmissions. This spectrum insufficiency problem has been overcome by incorporating the opportunistic spectrum access capability of cognitive radio (CR) into the existing WSN, thus giving birth to CR sensor networks (CRSNs). The sensor nodes in CRSNs depend on power sources that have limited power supply capabilities. Therefore, advanced and intelligent radio resource allocation schemes are very essential to perform dynamic and efficient spectrum allocation among sensor nodes and to optimize the energy consumption of each individual node in the network. Radio resource allocation schemes aim to ensure QoS guarantee, maximize the network lifetime, reduce the internode and internetwork interferences, etc. In this paper, we present a survey of the recent advances in radio resource allocation in CRSNs. Radio resource allocation schemes in CRSNs are classified into three major categories, i.e., centralized, cluster-based, and distributed. The schemes are further divided into several classes on the basis of performance optimization criteria that include energy efficiency, throughput maximization, QoS assurance, interference avoidance, fairness and priority consideration, and hand-off reduction. An insight into the related issues and challenges is provided, and future research directions are clearly identified.

Research paper thumbnail of Radio Resource Management in Cognitive Radio Sensor Networks

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band... more Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs' research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted.