KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 10 of 10

Some of the metrics are blocked by your
consent settings
Intelligence-Driven Grid-Forming Converter Control for Islanding Microgrids
(2025-01-01)
Ngamroo, Issarachai
;
Surinkaew, Tossaporn
;
Mitani, Yasunori
In modern microgrids (MGs) with high penetration of distributed energy resources (DERs), system reconfiguration occurs more frequently and becomes a significant issue. Fixed-parameter controllers may not handle these tasks effectively, as they lack the ability to adapt to the dynamic conditions in such environments. This paper proposes an intelligence-driven grid-forming (GFM) converter control method for islanding MGs using a robustness-guided neural network (RNN). To enhance the adaptability of the proposed method, traditional proportional-integral controllers in the GFM primary control loops are entirely replaced by the RNN. The RNN is trained by a robustness-guided strategy to replicate their robust behaviors. All the training stages are purely data-driven methods, which means that no system parameters are required for the controller design. Consequently, the proposed method is an intelligence-driven modelless GFM converter control. Compared with traditional methods, the simulation results in all testing scenarios show the clear benefits of the proposed method. The proposed method reduces overshoots by more than 71.24%, which keeps all damping ratios within the stable region and provides faster stabilization. In comparison to traditional methods, at the highest probability, the proposed method improves damping by over 14.7% and reduces the rates of change of frequency and voltage by over 59.97%. Additionally, the proposed method effectively suppresses the interactions between state variables caused by inverter-based resources, with frequencies ranging from 1.0 Hz to 1.422 Hz. Consequently, these frequencies contribute less than 19.79% To the observed transient responses.
Some of the metrics are blocked by your
consent settings
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.
Some of the metrics are blocked by your
consent settings
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.
Some of the metrics are blocked by your
consent settings
EVs Charging Power Control Participating in Supplementary Frequency Stabilization for Microgrids: Uncertainty and Global Sensitivity Analysis
(2021-01-01)
Jamroen, Chaowanan
;
Ngamroo, Issarachai
;
Dechanupaprittha, Sanchai
Electric vehicle (EV) potential has broadly been highlighted in providing ancillary services in a microgrid, such as grid reserve and regulation support. However, uncertain behaviors of EV charging raise crucial concerns for both the utilities and EV owners. In this paper, the impacts of EV charging uncertainties for EV charging power control participating in supplementary frequency stabilization are assessed separately based on the two perspectives, i.e., power capacity for the utility perspective and expected EV energy for the EV owner perspective. On the one hand, the power capacity accessed by the utility directly relates to the stabilization capability, which depends on the number of EVs that are willing to participate in the frequency stabilization program and the rated charging power of EV. On the other hand, the variance of expected EV energy realized by the EV owners is considered in terms of the remaining state of charge (SoC), energy capacity, and available charging time. Besides, a variance-based global sensitivity analysis (GSA) is essentially applied to identify the influential parameters of these uncertainties. The simulation studies are conducted using a microgrid environment via DIgSILENT Powerfactory software to reveal such impacts of EV charging uncertainties based on the two perspectives. The results indicate that the number of participating EVs is the most influential parameter for frequency stabilization capability, followed by the rated charging power of EV. From the EV owner's perspective, the energy capacity is the dominant parameter affecting the expected EV energy variance, followed by the remaining energy and available charging time.
Some of the metrics are blocked by your
consent settings
Coordinated Control of Electric Vehicles and Renewable Energy Sources for Frequency Regulation in Microgrids
(2020-01-01)
Jampeethong, Phoompat
;
Khomfoi, Surin
A Control technique of electric vehicles (EVs) cooperating with ac microgrids is considered as an important role with integration of renewable energy sources (RES), i.e. wind and solar farms. As known, the intermittent power generations of these RESs can provide significant changes of the frequency in microgrids. Consequently, outputs of these generations are regarded as continuous disturbances. Previously, the ability to permit frequency stabilizing effect was usually neglected in microgrid design; thereupon, the performance of controller may be ineffective to regulate the frequency in such a microgrid. To address this problem, a new coordination of EV, wind farm (WF), and photovoltaic (PV) for microgrid frequency regulation is proposed in this article. In the control design, the proposed adaptive PI controller is developed by using practical proportional integral (PI) controllers. An effect of a small delay is also considered in input-output pairs of the adaptive PI controllers. Simulation model is developed for validating the proposed controller. Simulation results demonstrate that the proposed coordinated control technique of EVs, WF, and PV power generation provides a better frequency regulation performance than a fixed PI controller under various uncertainties such as wind and solar power fluctuations, N-1 outages, disconnection of RESs, load variations, and the number of EVs.
Some of the metrics are blocked by your
consent settings
Transient respond comparison between modified droop control and virtual synchronous generator in standalone microgrid
(2019-07-01)
Leng, Darith
;
Polmai, Sompob
The inverter-based distributed generator (DG) plays a major role to solve the worldwide energy demand increasing and the environmental concern. The DG which controls by traditionally grid-connected current control confront some problems such as lacking the grid-forming ability and inertia. Therefore, the DG could not operate in standalone, and the DG's penetration rate is limited. To address these issues, the control strategy which imitates the synchronous's generator characteristic called droop control and virtual synchronous generator (VSG) are proposed recently. Seeing the potential of both control; this paper aims to investigate the dynamic performance of modified droop control and VSG. A simulation model of parallel DGs supply to a group of the load in the form of a standalone microgrid is implemented in MATLAB/Simulink. Two case studies such as power-sharing and load transient are carried out. The results have shown that VSG provides the outperform compare to the modified droop control when a large load transition is applied.
Some of the metrics are blocked by your
consent settings
Coordinated PHEV, PV, and ESS for Microgrid Frequency Regulation Using Centralized Model Predictive Control Considering Variation of PHEV Number
(2018-01-01)
Pahasa, J.
;
Ngamroo, I.
The integration of plug-in hybrid electric vehicles (PHEVs), photovoltaic (PV) generators, and energy storage systems (ESSs) into microgrids is highly anticipated. A coordinated control of PHEVs, PVs, and ESS will support frequency control in a microgrid. However, the size of the ESS depends on the surplus power of PV. The lower the surplus power is, the smaller the size of ESS. Furthermore, the number of available PHEVs vary with the cumulative number of the participating PHEVs. This variation of the number of PHEVs may reduce the PHEVs' control effect in the microgrid. This paper proposes a coordinated control of PHEVs, PVs, and ESSs for frequency control in the microgrid using a centralized model predictive control (CMPC) considering the variation of PHEV numbers. The objectives of the coordinated control are: 1) to suppress the system frequency fluctuation and 2) to minimize the surplus power of PV and, therefore, reduce the size of ESS. Simulation studies indicate that the coordinated control of PHEVs, PVs, and ESSs by the proposed CMPC is superior to that of the proportional integral derivative control and the distributed MPC in terms of minimizing the frequency fluctuation, the PV surplus power, and the ESS size.
Some of the metrics are blocked by your
consent settings
Microgrid stabilization by SMES with SOC control
(2016-04-15)
Ngamroo, Issarachai
;
Vachirasricirikul, Sitthidet
In the isolated microgrid with wind and photovoltaic power, the intermittent power produced from such power sources is an inevitable problem. In addition, under the occurrence of short circuits, the transient power swing may deteriorate the system stability. To deal with these problems, this paper focuses on the new power controller design of superconducting magnetic energy storage (SMES) considering the state-of-charge (SOC) control for microgrid stabilization. The structure of active and reactive power controllers of SMES is a proportional-integral (PI) controller. The optimization of PI parameters based on the minimization of the SOC deviation and the power output deviation of wind and PV sources is carried out. Simulation study confirms that the SMES with SOC control not only guarantees the stabilizing performance under normal and faulted conditions, but also prevents the over-charge and deep-discharge operations.
Some of the metrics are blocked by your
consent settings
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.
Some of the metrics are blocked by your
consent settings
Design of active power controller of a BESS in AC microgrids
(2015-08-17)
Prompinit, Krisada
;
Khomfoi, Surin
Active power control of a battery energy storage system (BESS) in ac microgrids is presented in this paper. PI controller design is also proposed. The simulation model using PSIM 9.0 is used to validate the designed controller. Actual data collected from data acquisition system in ac microgrids is used to validate the designed controller including photovoltaic (PV) generation profile, wind generation profile and demand load profile. All actual profiles are recorded from a real microgrid application. A BESS controller is validated into two scenarios. First, a BESS operates with PV generation and demand load. Second, a BESS operates with PV generation, wind generation and demand load. The simulation results suggest that the designed PI controller can perform active power compensation in the ac microgrid satisfactorily.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results