Autonomous Microgrid - Explore the Science & Experts | ideXlab


Scan Science and Technology

Contact Leading Edge Experts & Companies

Autonomous Microgrid

The Experts below are selected from a list of 1389 Experts worldwide ranked by ideXlab platform

Autonomous Microgrid – Free Register to Access Experts & Abstracts

Arindam Ghosh – One of the best experts on this subject based on the ideXlab platform.

  • improved control strategy for accurate load power sharing in an Autonomous Microgrid
    Iet Generation Transmission & Distribution, 2017
    Co-Authors: Blessy John, Firuz Zare, Arindam Ghosh, Sumedha Rajakaruna

    Abstract:

    This study proposes a decentralised droop control method for guaranteeing precise load sharing among distributed resources in an islanded Microgrid. Distributed resources are usually fed through power electronic converters and the switching harmonics produced by them are eliminated by third-order output LCL filters. Output impedance is considered as a major factor for finding exact power-angle droop coefficient in droop design – neglecting this factor can affect the load sharing accuracy. Even though an acceptable active power sharing can be achieved with higher droop gains, increased droop gain may adversely affect the Microgrid stability. Here, a modified angle droop control is proposed such that the dependence on the output inductance on the real power sharing is removed. Thus, the lower droop coefficients are sufficient for droop sharing and the system stability is not endangered. It has been assumed that the Microgrid is converter-dominated, where a proportionalresonant controller has been utilised for converter switching control. This controller has an outer voltage loop and an inner current loop. A harmonic term has been added to the voltage loop to facilitate more accurate reactive power sharing. Simulation studies are conducted using PSCAD/EMTDC to validate the efficacy of the proposed controller.

    Free Register to Access Article

  • Power sharing control of batteries within Autonomous Microgrids based on their state of charge
    2015 Australasian Universities Power Engineering Conference (AUPEC), 2015
    Co-Authors: Tahoura Hosseinimehr, Farhad Shahnia, Arindam Ghosh

    Abstract:

    This paper presents a new power sharing approach among parallel battery storage systems within an Autonomous Microgrid. The proposed approach considers the state of charge (SoC) of the batteries to control the ratio of their output powers. To facilitate this, a new SoC-based droop control is proposed. In this method, the ratio of output power for all the batteries is determined as a function of their SoC level. This ratio will be varied over time. In order to make the output power of each storage unit independent from the SoC level of the rest of storage units, a modified droop-based voltage control technique is applied for the other energy resources of the Microgrid. By the help of the modified control system, the output power reduction of batteries is only picked up by the energy resources. The studies and discussions are validated through PSCAD/EMTDC simulation studies.

    Free Register to Access Article

  • Overload prevention in an Autonomous Microgrid using battery storage units
    2014 IEEE PES General Meeting | Conference & Exposition, 2014
    Co-Authors: Megha Goyal, Arindam Ghosh, Farhad Shahnia

    Abstract:

    A new control strategy for smooth transition of a battery storage unit (BSU) is proposed in this paper to prevent overloading in an Autonomous hybrid Microgrid. The BSU is controlled to come online to prevent overloading to the distributed generators (DGs) in the Autonomous Microgrid and to go offline when the load demand is less than the total rating of the DGs in the Microgrid. The Microgrid can contain either inertial DG or non-inertial DGs, which are controlled in a frequency droop. The sensing of switching on and switching off of the BSU depends on the frequency signal, which is developed in the paper. The proposed strategy is validated through PSCAD/EMTDC simulation studies.

    Free Register to Access Article

Firuz Zare – One of the best experts on this subject based on the ideXlab platform.

  • improved control strategy for accurate load power sharing in an Autonomous Microgrid
    Iet Generation Transmission & Distribution, 2017
    Co-Authors: Blessy John, Firuz Zare, Arindam Ghosh, Sumedha Rajakaruna

    Abstract:

    This study proposes a decentralised droop control method for guaranteeing precise load sharing among distributed resources in an islanded Microgrid. Distributed resources are usually fed through power electronic converters and the switching harmonics produced by them are eliminated by third-order output LCL filters. Output impedance is considered as a major factor for finding exact power-angle droop coefficient in droop design – neglecting this factor can affect the load sharing accuracy. Even though an acceptable active power sharing can be achieved with higher droop gains, increased droop gain may adversely affect the Microgrid stability. Here, a modified angle droop control is proposed such that the dependence on the output inductance on the real power sharing is removed. Thus, the lower droop coefficients are sufficient for droop sharing and the system stability is not endangered. It has been assumed that the Microgrid is converter-dominated, where a proportionalresonant controller has been utilised for converter switching control. This controller has an outer voltage loop and an inner current loop. A harmonic term has been added to the voltage loop to facilitate more accurate reactive power sharing. Simulation studies are conducted using PSCAD/EMTDC to validate the efficacy of the proposed controller.

    Free Register to Access Article

  • enhancing stability of an Autonomous Microgrid using a gain scheduled angle droop controller with derivative feedback
    International Journal of Emerging Electric Power Systems, 2010
    Co-Authors: Ritwik Majumder, Arindam Ghosh, Gerard Ledwich, Firuz Zare

    Abstract:

    This paper discusses the stability of an Autonomous Microgrid in which, load sharing by a gain scheduled angle droop controller with derivative feedback is proposed. It is assumed that all the DGs are connected through Voltage Source Converter (VSC). The VSCs are controlled by state feedback controller to achieve desired voltage and current outputs that are decided by a droop controller. First a load sharing strategy is derived in terms of droop controller gain and converter output inductance, combining angle droop controller and DC load flow analysis. Then state space models of converters with its associated feedback controller are derived to investigate system stability as a function of the droop controller gain and converter output inductance through eigen value analysis. It is shown that with proposed angle droop controllers, where the droop gains are scheduled based on the output power along with derivative feedback it is possible to achieve a higher stability margin with better load sharing. These observations are then verified through simulation studies using PSCAD/EMTDC. It will be shown that the simulation results closely agree with stability behavior predicted by the eigenvalue analysis.

    Free Register to Access Article

  • Enhancing the stability of an Autonomous Microgrid using DSTATCOM
    International Journal of Emerging Electric Power Systems, 2010
    Co-Authors: Ritwik Majumder, Arindam Ghosh, Gerard Ledwich, Firuz Zare

    Abstract:

    This paper proposes a method for enhancing stability of an Autonomous Microgrid with distribution static compensator (DSTATCOM) and power sharing with multiple distributed generators (DG). It is assumed that all the DGs are connected through voltage source converter (VSC) and all connected loads are passive, making the Microgrid totally inertia less. The VSCs are controlled by either state feedback or current feedback mode to achieve desired voltage-current or power outputs, respectively. A modified angle droop is used for DG voltage reference generation. Power sharing ratio of the proposed droop control is established through derivation and verified by simulation results. A DSTATCOM is connected in the Microgrid to provide ride through capability during power imbalance in the Microgrid, thereby enhancing the system stability. This is established through extensive simulation studies using PSCAD.

    Free Register to Access Article

Ritwik Majumder – One of the best experts on this subject based on the ideXlab platform.

  • Advanced Battery Storage Control for an Autonomous Microgrid
    Electric Power Components and Systems, 2013
    Co-Authors: Ritwik Majumder, Gerard Ledwich, Saikat Chakrabarti, Arindam Ghosh

    Abstract:

    Abstract A new control method for battery storage to maintain acceptable voltage profile in Autonomous Microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the Microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the Microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high g…

    Free Register to Access Article

  • Advanced battery storage control for an Autonomous Microgrid
    Science & Engineering Faculty, 2013
    Co-Authors: Ritwik Majumder, Gerard Ledwich, Saikat Chakrabarti, Arindam Ghosh

    Abstract:

    A new control method for battery storage to maintain acceptable voltage profile in Autonomous Microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the Microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the Microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a Microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.

    Free Register to Access Article

  • Control of battery storage to improve voltage profile in Autonomous Microgrid
    2011 IEEE Power and Energy Society General Meeting, 2011
    Co-Authors: Ritwik Majumder, Gerard Ledwich, Saikat Chakrabarti, Arindam Ghosh

    Abstract:

    This paper proposes a new control method for battery storage in an Autonomous Microgrid. The battery output is controlled in such a manner that the bus voltages in the Microgrid system are maintained during disturbances such as load change, loss of micro sources or power limit in the DGs. An artificial neural network (ANN) based controller is used to determine the reference power for the battery to hold the Microgrid voltage within regulation limit. The pattern of drop in local bus voltage during power imbalance is used to train the controller offline. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period the battery power injection is reduced to zero using slow reverse droop characteristics ensuring a slow rate of increase in power demand from the other DGs. The proposed control method is tested for various operating conditions in a Microgrid with both inertial and converter interfaced sources.

    Free Register to Access Article