The Experts below are selected from a list of 62733 Experts worldwide ranked by ideXlab platform

J Tenreiro A Machado - One of the best experts on this subject based on the ideXlab platform.

  • numerical study of the nonlinear anomalous reaction subdiffusion process arising in the electroanalytical chemistry
    Journal of Computational Science, 2021
    Co-Authors: O Nikan, Zakieh Avazzadeh, J Tenreiro A Machado
    Abstract:

    Abstract This paper presents a meshless method based on the finite difference scheme derived from the local radial basis function (RBF-FD). The algorithm is used for finding the approximate solution of nonlinear anomalous reaction–diffusion models. The time discretization procedure is carried out by means of a weighted discrete scheme covering second-order approximation, while the spatial discretization is accomplished using the RBF-FD. The theoretical discussion validates the stability and convergence of the time-discretized formulation which are analyzed in the perspective to the H 1 -norm. This approach benefits from a local collocation technique to estimate the differential operators using the weighted differences over local collection Nodes through the RBF expansion. Two test problems illustrate the computational efficiency of the approach. Numerical simulations highlight the performance of the method that provides accurate solutions on complex domains with any Distribution Node type.

O Nikan - One of the best experts on this subject based on the ideXlab platform.

  • numerical study of the nonlinear anomalous reaction subdiffusion process arising in the electroanalytical chemistry
    Journal of Computational Science, 2021
    Co-Authors: O Nikan, Zakieh Avazzadeh, J Tenreiro A Machado
    Abstract:

    Abstract This paper presents a meshless method based on the finite difference scheme derived from the local radial basis function (RBF-FD). The algorithm is used for finding the approximate solution of nonlinear anomalous reaction–diffusion models. The time discretization procedure is carried out by means of a weighted discrete scheme covering second-order approximation, while the spatial discretization is accomplished using the RBF-FD. The theoretical discussion validates the stability and convergence of the time-discretized formulation which are analyzed in the perspective to the H 1 -norm. This approach benefits from a local collocation technique to estimate the differential operators using the weighted differences over local collection Nodes through the RBF expansion. Two test problems illustrate the computational efficiency of the approach. Numerical simulations highlight the performance of the method that provides accurate solutions on complex domains with any Distribution Node type.

Zakieh Avazzadeh - One of the best experts on this subject based on the ideXlab platform.

  • numerical study of the nonlinear anomalous reaction subdiffusion process arising in the electroanalytical chemistry
    Journal of Computational Science, 2021
    Co-Authors: O Nikan, Zakieh Avazzadeh, J Tenreiro A Machado
    Abstract:

    Abstract This paper presents a meshless method based on the finite difference scheme derived from the local radial basis function (RBF-FD). The algorithm is used for finding the approximate solution of nonlinear anomalous reaction–diffusion models. The time discretization procedure is carried out by means of a weighted discrete scheme covering second-order approximation, while the spatial discretization is accomplished using the RBF-FD. The theoretical discussion validates the stability and convergence of the time-discretized formulation which are analyzed in the perspective to the H 1 -norm. This approach benefits from a local collocation technique to estimate the differential operators using the weighted differences over local collection Nodes through the RBF expansion. Two test problems illustrate the computational efficiency of the approach. Numerical simulations highlight the performance of the method that provides accurate solutions on complex domains with any Distribution Node type.

Indrani Kar - One of the best experts on this subject based on the ideXlab platform.

  • A model of Electric Vehicle charging station compatibles with Vehicle to Grid scenario
    2012 IEEE International Electric Vehicle Conference, 2012
    Co-Authors: Mukesh Singh, Praveen Kumar, Indrani Kar
    Abstract:

    A large penetration of Electric Vehicles (EVs) will demand a huge infrastructure for power handling of the Distribution network. In this paper, EVs charging station has been modelled which can fulfil different demands of the EV vehicles owners. The owner's demand can be to limit on the charging rate (Crate), or limit to the state of charge (SOC) or proper power management of the battery. A suitable fuzzy controller has been designed to control the Crate of the individual battery based on power available with the battery and the power required by the grid. An algorithm has been designed which can handle different situations like charging and discharging of EVs batteries based on the Distribution Node voltage. The algorithm updates the power requirement, if certain vehicles arrive or leave the charging station.

  • Implementation of vehicle to grid infrastructure using fuzzy logic controller
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Mukesh Singh, Praveen Kumar, Indrani Kar
    Abstract:

    With high penetration of electric vehicles (EVs), stability of the electric grid becomes a challenging task. A greater penetration level would demand a proper coordination amongst the various EVs as they charge or discharge to the grid. Coordination here refers to controlling the charging and discharging patterns of different EVs depending on their individual battery states and the present grid condition. Therefore, a good coordination between EVs is required for making the grid stable. With high penetration of EVs, the vehicle to grid (V2G) concept can be explored where excess energy of the battery can be supplied back to the grid in controlled fashion. Discharging EVs' battery energy to the grid in coordination can make V2G utilization as distributed energy storage. Charging EVs in coordination can flatten the voltage profile of a Distribution Node. In this work, a typical Distribution system of a city is modeled to demonstrate V2G capabilities such as meeting peak demand and voltage sag reduction. The simulation of the Distribution system with V2G capabilities are tested using fuzzy logic controller (FLC). Two controllers have been developed, namely the charging station controller and the V2G controller. Together they decide the proper energy flow between the EVs and the grid. Energy discharge to the grid from EVs or energy required for charging EVs is controlled and tested for the real time scenario.

Mukesh Singh - One of the best experts on this subject based on the ideXlab platform.

  • A model of Electric Vehicle charging station compatibles with Vehicle to Grid scenario
    2012 IEEE International Electric Vehicle Conference, 2012
    Co-Authors: Mukesh Singh, Praveen Kumar, Indrani Kar
    Abstract:

    A large penetration of Electric Vehicles (EVs) will demand a huge infrastructure for power handling of the Distribution network. In this paper, EVs charging station has been modelled which can fulfil different demands of the EV vehicles owners. The owner's demand can be to limit on the charging rate (Crate), or limit to the state of charge (SOC) or proper power management of the battery. A suitable fuzzy controller has been designed to control the Crate of the individual battery based on power available with the battery and the power required by the grid. An algorithm has been designed which can handle different situations like charging and discharging of EVs batteries based on the Distribution Node voltage. The algorithm updates the power requirement, if certain vehicles arrive or leave the charging station.

  • Implementation of vehicle to grid infrastructure using fuzzy logic controller
    IEEE Transactions on Smart Grid, 2012
    Co-Authors: Mukesh Singh, Praveen Kumar, Indrani Kar
    Abstract:

    With high penetration of electric vehicles (EVs), stability of the electric grid becomes a challenging task. A greater penetration level would demand a proper coordination amongst the various EVs as they charge or discharge to the grid. Coordination here refers to controlling the charging and discharging patterns of different EVs depending on their individual battery states and the present grid condition. Therefore, a good coordination between EVs is required for making the grid stable. With high penetration of EVs, the vehicle to grid (V2G) concept can be explored where excess energy of the battery can be supplied back to the grid in controlled fashion. Discharging EVs' battery energy to the grid in coordination can make V2G utilization as distributed energy storage. Charging EVs in coordination can flatten the voltage profile of a Distribution Node. In this work, a typical Distribution system of a city is modeled to demonstrate V2G capabilities such as meeting peak demand and voltage sag reduction. The simulation of the Distribution system with V2G capabilities are tested using fuzzy logic controller (FLC). Two controllers have been developed, namely the charging station controller and the V2G controller. Together they decide the proper energy flow between the EVs and the grid. Energy discharge to the grid from EVs or energy required for charging EVs is controlled and tested for the real time scenario.