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Author: search.filters.author.Pahasa, JonglakSubject: search.filters.subject.microgrid

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    Improved Resilient Model Predictive Control for Enhanced Microgrid Virtual Inertia Emulation by Virtual Energy Storage System Under DoS Attacks
    (2023-01-01)
    Muangchuen, Satawat
    ;
    Pahasa, Jonglak
    ;
    Ngamroo, Issarachai
    The distributed control of a microgrid is fully dependent on advanced information and communication technologies that are sensitive to cyber-physical systems. Cyberattacks, such as denial-of-service (DoS) attacks, can cause unstable operation of low-inertia microgrids. This paper proposes enhanced microgrid virtual inertia control under DoS attacks using an improved resilient model predictive control (IRMPC)-based virtual energy storage system (VESS). IRMPC comprises an attack detector, an autoregressive (AR)-based signal estimator, and an MPC-based VESS controller. An attack detector was used to detect the DoS attacks. An AR-based signal estimator is then used to estimate the feedback data that are subjected to DoS attacks. The firefly algorithm was used to optimize the AR parameters. The effectiveness of the proposed IRMPC was compared with that of conventional model predictive control, conventional model predictive control-based VESS, and resilient model predictive control-based VESS. The simulation results revealed that under a DoS attack, the proposed IRMPC can successfully improve the microgrid virtual inertia emulation. Additionally, the proposed IRMPC has a performance effect over the compared techniques in terms of the reduction in RoCoF deviation and frequency deviation during normal situations, DoS attacks, and disconnection of wind turbine generation. The simulation results also confirmed that IRMPC is robust to microgrid parameter variations when compared to the other methods.
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    MPC-Based Virtual Energy Storage System Using PV and Air Conditioner to Emulate Virtual Inertia and Frequency Regulation of the Low-Inertia Microgrid
    (2022-01-01)
    Pahasa, Jonglak
    ;
    Potejana, Potejanasak
    ;
    Ngamroo, Issarachai
    Grid-connected large-scale power converter-based intermittent renewable energy sources (RES) reduce system inertia, increase frequency fluctuation, and increase the rate of change of frequency (RoCoF). An energy storage system (ESS) is an indispensable component of a smart grid, and is used to overcome low-inertia problems. However, the capital and maintenance costs of ESS are high and high RoCoF events are less frequent in power systems. Therefore, the introduction of a virtual energy storage system (VESS) to provide the function of a conventional ESS for power system ancillary services is an innovative and cost-effective method. This study investigated a VESS using photovoltaic (PV) generators and inverter air conditioners (IACs) to provide virtual inertia and frequency regulation for a low-inertia microgrid. A model predictive control (MPC)-based VESS regulates indoor temperature, microgrid frequency, and RoCoF. The impact of parameter variation, that is, the microgrid frequency weight, indoor temperature weight, virtual inertia gain, and number of IACs, was studied and selected by considering the ability of the parameters to provide virtual inertia and frequency regulation. Finally, the efficiency and robustness of the proposed MPC-based VESS technique are compared with those of a conventional VESS. Simulation results revealed that the proposed MPC-based VESS can improve the virtual inertia, reduce the frequency deviation, and reduce the RoCoF of the studied microgrid. In addition, the proposed method is robust to variations in the system parameters.
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    Coordinated Control of Wind Turbine Blade Pitch Angle and PHEVs Using MPCs for Load Frequency Control of Microgrid
    (2016-03-01)
    Pahasa, Jonglak
    ;
    Ngamroo, Issarachai
    This paper proposes coordinated control of blade pitch angle of wind turbine generators and plug-in hybrid electric vehicles (PHEVs) for load frequency control of microgrid using model predictive controls (MPCs). The MPC is an effective model-based predictive control, which calculates future control signals by optimization method using plant model, current, and past signals of the system. The MPC-based PHEVs' power control can be used to reduce frequency fluctuation of microgrid effectively. However, for large system, large number of PHEVs is needed to produce satisfying frequency deviation. In order to reduce the number of PHEVs, the smoothing of wind power production by pitch angle control using MPC method is proposed and is coordinated with PHEVs control in this paper. The simulation results confirm that the coordinated control of pitch angle and PHEVs using MPCs is able to reduce the number of PHEVs and the frequency fluctuation can be maintained significantly. In addition, the proposed method is robust to the system parameters variation over proportional-integral derivative controllers.