Surinkaew, Tossaporn
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Surinkaew, Tossaporn
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tossaporn.su@kmitl.ac.th
40 results
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Item type:Publication, Enhanced robust frequency stabilization of a microgrid against simultaneous cyber-attacks(2024-03-01); A microgrid (MG) is a smart grid cyber-physical system, with component coordination relying on cyber resilience. Weak communications, protocols, and tools make the MG's secondary frequency control vulnerable to various cyber-attacks, posing new challenges and stability risks. In response to this challenge, this paper introduces the enhanced robust H<inf>∞</inf> technique considering the dynamic impacts of cyber-attacks on secondary frequency control to develop a secondary frequency control loop, improving the regulation performance and cyber resiliency of the MG frequency. The secondary control cyber-attack strategies mainly rely on false data injection (FDI), denial of service (DoS), and controller hijacking. These attack techniques are simultaneously considered in formulating the H∞ problem and control synthesis as unstructured parametric uncertainty, attenuating the concurrent cyber impacts. The study extends a load frequency control model to illustrate how cyber-attacks can be represented mathematically and physically in the MG. The results reveal that cyber-attacks affect secondary frequency control elements differently depending on the type of cyber threats used. By implementing an enhanced H∞ controller, the MG can effectively maintain stable frequency levels even when faced with malicious attacks and disruptions caused by renewable energy sources and loads. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Small-Signal Stability Enhancement Through Integration of Distributed Grid-Forming Loads Considering Multi-Agent Collaboration(2025-01-01); ; Mitani, YasunoriThe integration of distributed controllable loads in future islanding microgrids (MGs) is growing. This creates new opportunities to actively shape grid frequency and voltage. As a result, it leads to the development of distributed grid-forming loads (DGFM-Ls). Simultaneously, it is equally crucial to ensure robustness, particularly in preserving small-signal stability amid the multi-agent collaboration. This paper presents a strategy for the small-signal stability enhancement in islanding MGs with DGFM-Ls. The small-signal models of the MG with DGFM-Ls are mathematically developed and analyzed. The multi-agent cooperation is modelled to improve the small-signal stability of the MG with DGFM-Ls. Additionally, uncertainties from multi-agent cooperation, such as partial or complete lack of measured signal observability, are considered. Data quality issues are also taken into account under various conditions. Simulation results are conducted in a MG with a significant penetration of inverter-based resources under various MG operating points and conditions such as topology changes and unavailability of certain agents. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Synthetic Inertia-Power Sharing in High Renewable Power Grids Through Vehicle-to-Grid Topology(2024-01-01); With the increasing integration of renewable energy sources (RESs), the overall inertia of the power system is expected to decline. The remaining inertia is crucial for regulating system frequency and mitigating excessive rates of change. The deployment of dispatchable loads, such as electric vehicles (EVs), offers a promising solution. This paper presents a synchronized inertia support framework utilizing a vehicle-to-grid (V2G) system through its bidirectional chargers. This concept is realized by integrating a large-scale energy storage system (ESS) composed of controllable EVs into an enhanced inertia emulation structure. The synthetic inertia control strategy has been refined to account for EV user convenience and synchronized state of charge (SOC) management, facilitating synchronized inertia power sharing. This approach enhances the grid's dynamic performance and resilience. Simulation results demonstrate that the proposed method effectively delivers rapid inertia support from the onboard ESS of EVs, improving frequency stability. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Adaptive Data-Driven-Based Control for Voltage Control Loop of Grid-Forming Converters in Variable Inertia MGs(2024-01-01); Marungsri, BoonruangIn the transition towards sustainable energy systems, microgrid (MG) plays a pivotal role, especially in the context of variable-inertia MGs that integrate renewable energy sources (RESs) and distributed energy resources (DERs). Maintaining stable voltage control within such grids is imperative for reliable operation. This paper presents an adaptive data-driven control technique for the voltage control loop of grid-forming converters in variable-inertia MGs. The primary objective is to enhance control performance while accommodating the unpredictable nature of renewable energy sources. The approach utilizes advanced data-driven algorithms to continuously monitor and adjust control parameters based on real-time grid conditions. This adaptability allows for effective management of varying inertia and load demand, ensuring optimal grid performance. The data-driven nature of the approach enables self-adaptability, making it suitable for the dynamic MG environment. This new approach is a noteworthy advancement in controlling RESs and DERs to maintain stable voltage in MGs, without needing precise knowledge of the MG's parameters. Simulation tests and real-world examples confirm that the adaptive data-driven control method effectively optimizes voltage control in MGs with variable inertia, especially those with a high presence of RESs and DERs. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Inter-Area Oscillation Damping Control Design Considering Impact of Variable Latencies(2019-01-01); It is ubiquitously accepted that system latency causes a serious problem in an oscillatory stability, especially when it involves with the centralized damping controllers using wide-area input signals. Previously, the latency was assumed to be constant in the centralized controller design and nonlinear time simulation. However, variable latencies, which vary area-to-area depending on the distances between stabilizing devices and control center, inevitably occur in large power systems. Thus, the damping performance may be deteriorated when variable latencies are ignored in the control design. This paper presents an inter-area oscillation damping controller design considering the impact of variable latencies. Selection of suitable stabilizing devices and input signal is conducted by taking variable latencies into account. Stability studies are carried out in IEEE 50-machine 145-bus to analyze an influence of variable latencies on the oscillation damping and the signal selection. The proposed damping controller can achieve desired damping performance as well as robustness against variable latencies, various operating conditions, and severe disturbances. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Control of Distributed Converter-Based Resources in a Zero-Inertia Microgrid Using Robust Deep Learning Neural Network(2024-01-01); Considering the evolution of future microgrids (MGs) towards zero-inertia level due to the penetrations of distributed converter-based resources (DCRs), a large number of data produced by these generations will lead the control decisions to be more complicated than conventional power systems. This paper presents a control strategy for a zero-inertia MG with DCRs using a robust deep learning neural network (RDeNN). In a training phase, a sub-space state-based identification method is employed to monitor and analyze the data regarding stability indices, i.e., damping and frequency of dominant modes, and robustness against uncertainties. In addition, a mixed H2/H∞ control strategy is applied to enhance the training efficacy in the frequency and voltage control loops of DCRs. The trained RDeNN is activated to make quick and effective control decisions by using only measured signals from the MG. Simulation results are verified in the zero-inertia MG (or the grid with 100% DCRs) and compared with several existing control techniques. The study results demonstrate the advantages of the proposed RDeNN in many aspects such as low computational time, require-less physical controller models, fast and flexible stabilizing responses, and high robustness against various time delays, data quality issues, and MG uncertainties. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Two-Stage Small-Signal Stability-Assisted Framework Using Controllable Loads in Reconfigurable Microgrids(2025-01-01); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Robust decentralized power oscillation dampers design of DFIG wind turbines for stabilization of inter-area oscillation(2014-01-01); A new decentralized power oscillation dampers (POD) design of doubly-fed induction generator (DFIG) wind turbines for damping of inter-area oscillation is presented in this paper. The practical 2<sup>nd</sup>-order lead/lag compensator with single input signal is used for the POD structure. The POD is equipped with the voltage controller of rotor side converter of DFIG. With the damping signal from POD, the reactive power output of DFIG can be modulated to damp out the oscillations. The parameters optimization of decentralized PODs is conducted over a wide range of tie-line power flow levels so that the damping performance of PODs can be enhanced. The improved firefly algorithm is used to achieve the optimal POD parameters automatically. Study results in a two-area four-machine interconnected system show that the stabilizing effect of proposed decentralized POD is higher than the conventional POD under severe faults, heavy power flows, and wind speeds. © 2014 IEEE. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Cyber-Attacks on Power System Frequency Control(2024-01-01); Pinthurat, WatcharakornDue to the increasing number of cyber hacking activities, cyber-Attacks become urgent concerns to power system security worldwide. A power system is vulnerable to cyber-Attacks due to the exchanged information in its area. In this study, cyber-Attacks on power system frequency control are studied by corrupting the exchange of information. Considering the frequency measurement of the system, essential attack strategies from hackers' perspectives, which are usually concerned with cyber-Attacks on critical infrastructure, have been modeled concerning the false data injection. Simulation results analyze the strengths and weaknesses of different attacks against frequency control of the system. The exogenous cyber-Attacks on frequency power measurements can cause severe frequency excursions, which lead to system instability and power blackouts. Such attack methods require effective detection from defenders to guarantee system security before hackers further deteriorate the system's stability. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Communication-Driven Learning-Based Harmonic Mitigation Approach for Grid-Forming Converters(2025-01-01); This paper proposes a harmonic mitigation framework for multi-bus microgrids (MGs) that utilizes a communication-driven learning-based approach. A dedicated neural network is used to model additional intelligent control loops. We also develop a global harmonic distortion (GHD) matrix, formulated by the total harmonic distortion at each point of common coupling (PCC). The GHD specifically focuses on harmonic orders that exceed acceptable limits observed from multi-bus systems. The GHD is used as an input signal of the neural network. Based on the system conditions, the developed GHD allows the system to intelligently trigger the control signal whenever dominant harmonic orders are detected and need mitigation. Other input signals include the voltage and current vectors from all PCCs, which contain local harmonics. To train the network, various critical system operating points are collected as time-series data. At this stage, system parameters are not needed; however, secure communication for data transfer is considered instead. Consequently, the collected data are used to train the network using the developed loss functions that focus on harmonic mitigation. After network training, the output signal is sent to the summing points in the direct axis of the inner voltage and current control loops of different models of grid-forming IBRs units. Simulation results are verified in a modified multi-bus MG with IBRs under various operating conditions.