The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform

K R Niazi - One of the best experts on this subject based on the ideXlab platform.

  • cross term decomposition method for loss allocation in Distribution systems considering load power factor
    Electric Power Components and Systems, 2018
    Co-Authors: Pankaj Kumar, Nikhil Gupta, K R Niazi, Anil Swarnkar
    Abstract:

    The customers of Distribution system are generally encouraged to maintain better power factor through suitable tariff structures. The feeder power loss allocation is a part of tariff. The feeder power losses also depend upon power factor of loads. Therefore, loss allocation method should incorporate suitable rewarding and penalizing strategy for better and poor factors loads. This paper proposes a new Distribution loss allocation method that considers load power factor to allocate losses in a more practical way. The proposed method employs bifurcation of cross terms of branch power loss among contributing nodes. The method provides loss allocation to system nodes in such a way that it provides rebates/penalties against variation in load power factor only to the concerned nodes. The proposed method is applied to 30-bus and 33-bus Test Distribution system and compared with other established methods. The analysis of the application results highlights the importance of the proposed method.

  • improved elephant herding optimization for multiobjective der accommodation in Distribution systems
    IEEE Transactions on Industrial Informatics, 2018
    Co-Authors: Nand K. Meena, Nikhil Gupta, Anil Swarnkar, Sonam Parashar, K R Niazi
    Abstract:

    This work introduces a new methodology to solve a multiobjective distributed energy resource (DER) accommodation problem of Distribution systems by combining a technique for order of preference by similarity to ideal solution and an improved elephant herding optimization technique. A complex real-life multiobjective DER planning problem is formulated and solved using the proposed method. The aim is to determine the optimal sites and sizes of DERs to maximize the overall benefits of utility and consumers. The proposed technique is productively implemented on three small to large-scale benchmark Test Distribution systems of 33-bus, 118-bus, and 880-bus. The optimal solutions obtained are compared with the methods available in the literature. The comparison shows that the proposed optimization method is promising.

  • simultaneous allocation of distributed energy resource using improved particle swarm optimization
    Applied Energy, 2017
    Co-Authors: Neeraj Kanwar, Nikhil Gupta, K R Niazi, Anil Swarnkar, R C Bansal
    Abstract:

    Abstract Smart grid initiatives require integrated solution for radial Distribution networks (RDNs) to achieve their optimum performance. The optimal allocation of distributed energy resources (DERs), such as shunt capacitors and distributed generation, when integrated with Distribution network reconfiguration (DNR), can achieve desired objectives of smart Distribution systems. This paper addresses a multi-objective formulation for simultaneous allocation of DERs in RDNs to maximize annual savings by reducing the charges for annual energy losses, peak power losses and substation capacity release against the annual charges incurred to purchase DERs while maintaining better node voltage profiles and feeder current profiles. An improved particle swarm optimization (IPSO) method is proposed to overcome against the inherent tendency of local trappings in PSO. A node sensitivity-based guided search algorithm (GSA) is also suggested to enhance the overall performance of the optimizing tool. GSA virtually squeezes the problem search space without loss of diversity. Distribution networks are optimally reconfigured after optimally placing DERs. The proposed method is investigated on the benchmark IEEE 33-bus and 69-bus Test Distribution systems. The application results show that the proposed integrated approach is very useful for electric utilities to enhance their profits and stagger their future expansion plans.

  • Distribution network reconfiguration for power quality and reliability improvement using genetic algorithms
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Nikhil Gupta, Anil Swarnkar, K R Niazi
    Abstract:

    Abstract This paper presents an efficient Genetic Algorithms (GAs) based method to improve the reliability and power quality of Distribution systems using network reconfiguration. Two new objective functions are formulated to address power quality and reliability issues for the reconfiguration problem. Various power quality and reliability objectives such as feeder power loss, system’s node voltage deviation, system’s average interruption frequency index, system’s average interruption unavailability index and energy not supplied are transformed into a single objective function. This single objective problem is then solved using the GA-based method. The effectiveness of the proposed objective functions has been investigated on two different standard Test Distribution systems. Application results are promising when compared with other existing method.

  • adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced Distribution systems for loss minimization
    Swarm and evolutionary computation, 2011
    Co-Authors: Anil Swarnkar, Nikhil Gupta, K R Niazi
    Abstract:

    Abstract This paper presents an efficient method for the reconfiguration of radial Distribution systems for minimization of real power loss using adapted ant colony optimization. The conventional ant colony optimization is adapted by the graph theory to always create feasible radial topologies during the whole evolutionary process. This avoids tedious mesh check and hence reduces the computational burden. The initial population is created randomly and a heuristic spark is introduced to enhance the pace of the search process. The effectiveness of the proposed method is demonstrated on balanced and unbalanced Test Distribution systems. The simulation results show that the proposed method is efficient and promising for reconfiguration problem of radial Distribution systems.

Nikhil Gupta - One of the best experts on this subject based on the ideXlab platform.

  • cross term decomposition method for loss allocation in Distribution systems considering load power factor
    Electric Power Components and Systems, 2018
    Co-Authors: Pankaj Kumar, Nikhil Gupta, K R Niazi, Anil Swarnkar
    Abstract:

    The customers of Distribution system are generally encouraged to maintain better power factor through suitable tariff structures. The feeder power loss allocation is a part of tariff. The feeder power losses also depend upon power factor of loads. Therefore, loss allocation method should incorporate suitable rewarding and penalizing strategy for better and poor factors loads. This paper proposes a new Distribution loss allocation method that considers load power factor to allocate losses in a more practical way. The proposed method employs bifurcation of cross terms of branch power loss among contributing nodes. The method provides loss allocation to system nodes in such a way that it provides rebates/penalties against variation in load power factor only to the concerned nodes. The proposed method is applied to 30-bus and 33-bus Test Distribution system and compared with other established methods. The analysis of the application results highlights the importance of the proposed method.

  • improved elephant herding optimization for multiobjective der accommodation in Distribution systems
    IEEE Transactions on Industrial Informatics, 2018
    Co-Authors: Nand K. Meena, Nikhil Gupta, Anil Swarnkar, Sonam Parashar, K R Niazi
    Abstract:

    This work introduces a new methodology to solve a multiobjective distributed energy resource (DER) accommodation problem of Distribution systems by combining a technique for order of preference by similarity to ideal solution and an improved elephant herding optimization technique. A complex real-life multiobjective DER planning problem is formulated and solved using the proposed method. The aim is to determine the optimal sites and sizes of DERs to maximize the overall benefits of utility and consumers. The proposed technique is productively implemented on three small to large-scale benchmark Test Distribution systems of 33-bus, 118-bus, and 880-bus. The optimal solutions obtained are compared with the methods available in the literature. The comparison shows that the proposed optimization method is promising.

  • simultaneous allocation of distributed energy resource using improved particle swarm optimization
    Applied Energy, 2017
    Co-Authors: Neeraj Kanwar, Nikhil Gupta, K R Niazi, Anil Swarnkar, R C Bansal
    Abstract:

    Abstract Smart grid initiatives require integrated solution for radial Distribution networks (RDNs) to achieve their optimum performance. The optimal allocation of distributed energy resources (DERs), such as shunt capacitors and distributed generation, when integrated with Distribution network reconfiguration (DNR), can achieve desired objectives of smart Distribution systems. This paper addresses a multi-objective formulation for simultaneous allocation of DERs in RDNs to maximize annual savings by reducing the charges for annual energy losses, peak power losses and substation capacity release against the annual charges incurred to purchase DERs while maintaining better node voltage profiles and feeder current profiles. An improved particle swarm optimization (IPSO) method is proposed to overcome against the inherent tendency of local trappings in PSO. A node sensitivity-based guided search algorithm (GSA) is also suggested to enhance the overall performance of the optimizing tool. GSA virtually squeezes the problem search space without loss of diversity. Distribution networks are optimally reconfigured after optimally placing DERs. The proposed method is investigated on the benchmark IEEE 33-bus and 69-bus Test Distribution systems. The application results show that the proposed integrated approach is very useful for electric utilities to enhance their profits and stagger their future expansion plans.

  • Distribution network reconfiguration for power quality and reliability improvement using genetic algorithms
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Nikhil Gupta, Anil Swarnkar, K R Niazi
    Abstract:

    Abstract This paper presents an efficient Genetic Algorithms (GAs) based method to improve the reliability and power quality of Distribution systems using network reconfiguration. Two new objective functions are formulated to address power quality and reliability issues for the reconfiguration problem. Various power quality and reliability objectives such as feeder power loss, system’s node voltage deviation, system’s average interruption frequency index, system’s average interruption unavailability index and energy not supplied are transformed into a single objective function. This single objective problem is then solved using the GA-based method. The effectiveness of the proposed objective functions has been investigated on two different standard Test Distribution systems. Application results are promising when compared with other existing method.

  • adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced Distribution systems for loss minimization
    Swarm and evolutionary computation, 2011
    Co-Authors: Anil Swarnkar, Nikhil Gupta, K R Niazi
    Abstract:

    Abstract This paper presents an efficient method for the reconfiguration of radial Distribution systems for minimization of real power loss using adapted ant colony optimization. The conventional ant colony optimization is adapted by the graph theory to always create feasible radial topologies during the whole evolutionary process. This avoids tedious mesh check and hence reduces the computational burden. The initial population is created randomly and a heuristic spark is introduced to enhance the pace of the search process. The effectiveness of the proposed method is demonstrated on balanced and unbalanced Test Distribution systems. The simulation results show that the proposed method is efficient and promising for reconfiguration problem of radial Distribution systems.

Anil Swarnkar - One of the best experts on this subject based on the ideXlab platform.

  • cross term decomposition method for loss allocation in Distribution systems considering load power factor
    Electric Power Components and Systems, 2018
    Co-Authors: Pankaj Kumar, Nikhil Gupta, K R Niazi, Anil Swarnkar
    Abstract:

    The customers of Distribution system are generally encouraged to maintain better power factor through suitable tariff structures. The feeder power loss allocation is a part of tariff. The feeder power losses also depend upon power factor of loads. Therefore, loss allocation method should incorporate suitable rewarding and penalizing strategy for better and poor factors loads. This paper proposes a new Distribution loss allocation method that considers load power factor to allocate losses in a more practical way. The proposed method employs bifurcation of cross terms of branch power loss among contributing nodes. The method provides loss allocation to system nodes in such a way that it provides rebates/penalties against variation in load power factor only to the concerned nodes. The proposed method is applied to 30-bus and 33-bus Test Distribution system and compared with other established methods. The analysis of the application results highlights the importance of the proposed method.

  • improved elephant herding optimization for multiobjective der accommodation in Distribution systems
    IEEE Transactions on Industrial Informatics, 2018
    Co-Authors: Nand K. Meena, Nikhil Gupta, Anil Swarnkar, Sonam Parashar, K R Niazi
    Abstract:

    This work introduces a new methodology to solve a multiobjective distributed energy resource (DER) accommodation problem of Distribution systems by combining a technique for order of preference by similarity to ideal solution and an improved elephant herding optimization technique. A complex real-life multiobjective DER planning problem is formulated and solved using the proposed method. The aim is to determine the optimal sites and sizes of DERs to maximize the overall benefits of utility and consumers. The proposed technique is productively implemented on three small to large-scale benchmark Test Distribution systems of 33-bus, 118-bus, and 880-bus. The optimal solutions obtained are compared with the methods available in the literature. The comparison shows that the proposed optimization method is promising.

  • simultaneous allocation of distributed energy resource using improved particle swarm optimization
    Applied Energy, 2017
    Co-Authors: Neeraj Kanwar, Nikhil Gupta, K R Niazi, Anil Swarnkar, R C Bansal
    Abstract:

    Abstract Smart grid initiatives require integrated solution for radial Distribution networks (RDNs) to achieve their optimum performance. The optimal allocation of distributed energy resources (DERs), such as shunt capacitors and distributed generation, when integrated with Distribution network reconfiguration (DNR), can achieve desired objectives of smart Distribution systems. This paper addresses a multi-objective formulation for simultaneous allocation of DERs in RDNs to maximize annual savings by reducing the charges for annual energy losses, peak power losses and substation capacity release against the annual charges incurred to purchase DERs while maintaining better node voltage profiles and feeder current profiles. An improved particle swarm optimization (IPSO) method is proposed to overcome against the inherent tendency of local trappings in PSO. A node sensitivity-based guided search algorithm (GSA) is also suggested to enhance the overall performance of the optimizing tool. GSA virtually squeezes the problem search space without loss of diversity. Distribution networks are optimally reconfigured after optimally placing DERs. The proposed method is investigated on the benchmark IEEE 33-bus and 69-bus Test Distribution systems. The application results show that the proposed integrated approach is very useful for electric utilities to enhance their profits and stagger their future expansion plans.

  • Distribution network reconfiguration for power quality and reliability improvement using genetic algorithms
    International Journal of Electrical Power & Energy Systems, 2014
    Co-Authors: Nikhil Gupta, Anil Swarnkar, K R Niazi
    Abstract:

    Abstract This paper presents an efficient Genetic Algorithms (GAs) based method to improve the reliability and power quality of Distribution systems using network reconfiguration. Two new objective functions are formulated to address power quality and reliability issues for the reconfiguration problem. Various power quality and reliability objectives such as feeder power loss, system’s node voltage deviation, system’s average interruption frequency index, system’s average interruption unavailability index and energy not supplied are transformed into a single objective function. This single objective problem is then solved using the GA-based method. The effectiveness of the proposed objective functions has been investigated on two different standard Test Distribution systems. Application results are promising when compared with other existing method.

  • adapted ant colony optimization for efficient reconfiguration of balanced and unbalanced Distribution systems for loss minimization
    Swarm and evolutionary computation, 2011
    Co-Authors: Anil Swarnkar, Nikhil Gupta, K R Niazi
    Abstract:

    Abstract This paper presents an efficient method for the reconfiguration of radial Distribution systems for minimization of real power loss using adapted ant colony optimization. The conventional ant colony optimization is adapted by the graph theory to always create feasible radial topologies during the whole evolutionary process. This avoids tedious mesh check and hence reduces the computational burden. The initial population is created randomly and a heuristic spark is introduced to enhance the pace of the search process. The effectiveness of the proposed method is demonstrated on balanced and unbalanced Test Distribution systems. The simulation results show that the proposed method is efficient and promising for reconfiguration problem of radial Distribution systems.

Andrew Keane - One of the best experts on this subject based on the ideXlab platform.

  • local versus centralized charging strategies for electric vehicles in low voltage Distribution systems
    Power and Energy Society General Meeting, 2013
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Summary form only given. Controlled charging of electric vehicles offers a potential solution to accommodating large numbers of such vehicles on existing Distribution networks without the need for widespread upgrading of network infrastructure. Here, a local control technique is proposed whereby individual electric vehicle charging units attempt to maximize their own charging rate for their vehicle while maintaining local network conditions within acceptable limits. Simulations are performed to demonstrate the benefits of the technique on a Test Distribution network. The results of the method are also compared to those from a centralized control method whereby electric vehicle charging is controlled by a central controller. The paper outlines the advantages and disadvantages of both strategies in terms of capacity utilization and total energy delivered to charging vehicles.

  • Local versus centralized charging strategies for electric vehicles in low voltage Distribution systems
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Controlled charging of electric vehicles offers a potential solution to accommodating large numbers of such vehicles on existing Distribution networks without the need for widespread upgrading of network infrastructure. Here, a local control technique is proposed whereby individual electric vehicle charging units attempt to maximise their own charging rate for their vehicle while maintaining local network conditions within acceptable limits. Simulations are performed to demonstrate the benefits of the technique on a Test Distribution network. The results of the method are also compared to those from a centralized control method whereby EV charging is controlled by a central controller. The paper outlines the advantages and disadvantages of both strategies in terms of capacity utilization and total energy delivered to charging EVs.

  • impact assessment of varying penetrations of electric vehicles on low voltage Distribution systems
    Power and Energy Society General Meeting, 2010
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Advances in the development of electric vehicles, along with policy incentives will see a wider uptake of this technology in the transport sector in future years. However, the widespread implementation of electric vehicles could lead to adverse effects on power system networks, especially existing Distribution networks. This work investigates some of the potential impacts from various levels of uncontrolled electric vehicle charging on a Test Distribution network. The network is examined under worst case scenario conditions for residential electricity demand in an effort to assess the full impact from electric vehicles. The results demonstrate that even for relatively modest levels of electric vehicle charging, both the voltage and thermal loading levels can exceed safe operating limits. The results also indicate the importance of assessing each phase on the network separately in order to capture the full effects of uncontrolled electric vehicle charging on the network.

Peter Richardson - One of the best experts on this subject based on the ideXlab platform.

  • local versus centralized charging strategies for electric vehicles in low voltage Distribution systems
    Power and Energy Society General Meeting, 2013
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Summary form only given. Controlled charging of electric vehicles offers a potential solution to accommodating large numbers of such vehicles on existing Distribution networks without the need for widespread upgrading of network infrastructure. Here, a local control technique is proposed whereby individual electric vehicle charging units attempt to maximize their own charging rate for their vehicle while maintaining local network conditions within acceptable limits. Simulations are performed to demonstrate the benefits of the technique on a Test Distribution network. The results of the method are also compared to those from a centralized control method whereby electric vehicle charging is controlled by a central controller. The paper outlines the advantages and disadvantages of both strategies in terms of capacity utilization and total energy delivered to charging vehicles.

  • Local versus centralized charging strategies for electric vehicles in low voltage Distribution systems
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Controlled charging of electric vehicles offers a potential solution to accommodating large numbers of such vehicles on existing Distribution networks without the need for widespread upgrading of network infrastructure. Here, a local control technique is proposed whereby individual electric vehicle charging units attempt to maximise their own charging rate for their vehicle while maintaining local network conditions within acceptable limits. Simulations are performed to demonstrate the benefits of the technique on a Test Distribution network. The results of the method are also compared to those from a centralized control method whereby EV charging is controlled by a central controller. The paper outlines the advantages and disadvantages of both strategies in terms of capacity utilization and total energy delivered to charging EVs.

  • impact assessment of varying penetrations of electric vehicles on low voltage Distribution systems
    Power and Energy Society General Meeting, 2010
    Co-Authors: Peter Richardson, Damian Flynn, Andrew Keane
    Abstract:

    Advances in the development of electric vehicles, along with policy incentives will see a wider uptake of this technology in the transport sector in future years. However, the widespread implementation of electric vehicles could lead to adverse effects on power system networks, especially existing Distribution networks. This work investigates some of the potential impacts from various levels of uncontrolled electric vehicle charging on a Test Distribution network. The network is examined under worst case scenario conditions for residential electricity demand in an effort to assess the full impact from electric vehicles. The results demonstrate that even for relatively modest levels of electric vehicle charging, both the voltage and thermal loading levels can exceed safe operating limits. The results also indicate the importance of assessing each phase on the network separately in order to capture the full effects of uncontrolled electric vehicle charging on the network.