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In order to ensure that the power system frequency and tie-line power remain at the nominal value when the load fluctuates, while reducing the release number of decentralized sensor, this work presents a novel adaptive event-triggered scheme for the load frequency regulation via designing the decentralized dynamic output feedback controller (DOFC), where the communication delay issue is also considered due to communication constraints. Distinct from the existing ones, the proposed adaptive event-triggered strategy automatically tunes the threshold according to the local extremum of the system output signal, which can significantly reduce the number of unnecessary signal transmissions to ensure system performance. First, the proposed adaptive event-triggered transmission scheme is integrated with the decentralized DOFC and communication delays under the framework of a linear time-delay system. Then, the asymptotic stability of the closed-loop power system is analyzed through the Lyapunov stability theory and a procedure is given for the design of decentralized dynamic output load frequency controllers by solving some linear matrix inequalities (LMIs). Finally, a three-area power system is used to verify the effectiveness and usefulness of the proposed results. [ABSTRACT FROM AUTHOR]

This brief studies the distributed estimation problem for multi-area power systems where the sensor measurements encounter with false data injection (FDI) attacks. For the large load frequency control (LFC) power systems with unknown load deviation, a distributed intermediate observer based method is proposed to estimate the system states, FDI attack signals and load deviation of each area in the power system. In this case, the gain of each intermediate observer is obtained by constructing a self-relative linear matrix inequality that can be easily solved by the standard software packages. Notice that the computational cost of each estimator is low even though the scale of power systems is large. Finally, the effectiveness of the proposed method is verified by an illustrative example. [ABSTRACT FROM AUTHOR]

While distributed secondary controllers have been studied for multiple energy storage systems in islanded microgrids, information infrastructure has to be added for the extensive information transmission among these secondary controllers and the additional communication among distributed controllers is costly and increases the vulnerability surface to cyberattacks. In this work, a data-driven decentralized secondary control scheme is proposed for multiple heterogeneous battery energy storage systems (BESSs). The proposed secondary control scheme can achieve frequency regulation and the state-of-charge (SoC) balancing simultaneously for BESSs without requiring accurate BESS models. This scheme leverages an asynchronous advantage actor-critic (A3C) based multi-agent deep reinforcement learning (MA-DRL) algorithm where the centralized off-line learning with shared convolutional neural networks (CNN) is designed to maximize global rewards and ensure the performance of the entire system and a decentralized online execution mechanism is applied to each BESS. Furthermore, in view of possible denial-of-service (DoS) attack on local communication networks used for signal transfer between secondary controllers and remote sensors, a signal-to-interference-plus-noise ratio (SINR)-based dynamic and proactive event-triggered communication mechanism is proposed to alleviate the impact of DoS attacks and reduce the occupation of communication resources. Simulation results on a four-bus multiple BESS system show that the proposed decentralized secondary controller can achieve simultaneous frequency regulation and SoC balancing. Comparison results with other event-triggered mechanisms and MA-DRL algorithms show the A3C based MA-DRL algorithm with CNN can obtain a comparatively optimal policy through training and the designed event-triggered strategy can dynamically adapt the release frequency based on real-time SINR and significantly reduce the occupied network bandwidth and packet loss rate (PER) induced by DoS attacks. [ABSTRACT FROM AUTHOR]

In this article, a novel distributed fuzzy load frequency control (LFC) approach is investigated for multiarea power systems under cross-layer attacks. The nonlinear factors existing in turbine dynamics and governor dynamics as well as the uncertain parameters therein are modeled and analyzed under the interval type-2 (IT2) Takagi–Sugeno (T–S) fuzzy framework. The cross-layer attacks threatening the stability of power systems are considered and modeled as an independent Bernoulli process, including denial-of-service (DoS) attacks in the cyber layer and phasor measurement unit (PMU) attacks in the physical layer. By using the Lyapunov theory, an area-dependent Lyapunov function is proposed and the sufficient conditions guaranteeing the system’s asymptotically stability with the area control error (ACE) signals satisfying $\mathcal {H}_{\infty }$ performance are deduced. In simulations, we adopt a four-area power system to verify the resiliency enhancement of the presented distributed fuzzy control strategy against random cross-layer DoS attacks. Results show that the designed resilient controller can effectively regulate the load frequency under different cross-layer DoS attack probabilities. [ABSTRACT FROM AUTHOR]

In the distributed load frequency control (DLFC) scheme, the compromised areas by attackers may endanger the stable and reliable operation of the entire power system. A credibility‐based secure DLFC strategy is in this work proposed to sustain the stable operation of the power system under false data injection attacks. In this secure DLFC method, the gradient‐variation‐based credibility metrics are defined to detect potential attacked measurements. Then, the communication isolation decisions are made based on the adaptive thresholds. To compensate the impact of the communication isolation of misbehaving areas, predictions of future measurements by using the average gradient variation of stored healthy data are feeded back to the area controller. Simulation results of a four‐area power system show the proposed secure DLFC can identify and cut off the communication of the misbehaving areas and still maintain the stability of the power system. [ABSTRACT FROM AUTHOR]

In this paper, one new distributed load frequency regulation approach is proposed for smart power system operation under two specific practical constraints, including the limited communication resource and speed droop parametric uncertainty. To address these two constraints, the co-design of event-triggering communication scheme and distributed model-based controller is studied. Instead of using zero-order holders, the proposed model-based scheme is able to extend the maximum allowable time interval and thus reduce communication bandwidth usage. In the meantime, the proposed co-design scheme is able to get the model-based control parameters and event-triggering condition metrics simultaneously. This can loosen the conservation in the choice of control gains and event-triggering parameters faced by existing approaches where the control gains are fixed in prior. Comparisons on the multiple-area system confirm that this designed load frequency regulation method significantly reduces the number of required data transmissions without sacrificing the dynamic performance of the frequency and tie-line power. It is also shown that the proposed approach has great robustness to speed droop coefficient uncertainty. [ABSTRACT FROM AUTHOR]

This paper proposes an intrusion-detector-dependent secondary frequency control approach to enhance the attack-resilient capability of microgrid control systems. While most of the existing attack-resilient controllers assume the perfect accuracy of intrusion detection systems, we consider the possible false detection of intrusion detectors against denial-of-service attack. The proposed frequency controller adjusts its control gains based on the detected attack choice rather than the actual attack choice, as the actual attack choice can only be detected, instead of assuming surely known to a defender. Test results verify that the designed controller can sustain the stability of the microgrid under a high false detection rate. [ABSTRACT FROM AUTHOR]

In this study, a new distributed filtering approach is proposed for the load frequency control of uncertain non‐linear power systems with cyber‐physical attacks. Specifically, the non‐linear power system is firstly modelled under interval type‐2 Takagi–Sugeno fuzzy framework and the uncertainty therein is captured by designing corresponding membership functions. Both denial of service cyber attack and physical sensor attack are considered and modelled as independent Bernoulli process. Based on the Lyapunov stability theory, less conservative sufficient conditions have been derived to guarantee the robustly mean‐square asymptotic stability with an average H∞ performance standard γ for the dynamic filtering error system. Moreover, artful matrix transformation techniques have been adopted to decouple the intertwined matrix variables in designing the distributed filter gains. In simulations, a three‐area non‐linear power system with internal uncertainties is used to validate the robustness of the proposed distributed filtering strategy to system parametric uncertainties and cyber‐physical attacks. [ABSTRACT FROM AUTHOR]

An integrated model-based control and scheduling scheme is proposed for the load frequency control (LFC) of large-scale power systems under the distributed structure and uncertainties. Specifically, the limited bandwidth constraint is considered when state observation is exchanged over shared communication networks. Each area controller uses the explicit models of its own and neighboring areas to predict state observations when the actual one is not available. At each transmission instant, the state observation of the scheduled area is broadcasted to the relevant areas and the model-based controllers are partially updated. By properly scheduling the transmission sequence and intervals, the stability of the power system can be guaranteed with a substantial reduction of the bandwidth usage and this is proven by performing a thorough theoretical analysis. Simulation results of a four-area power system verify that the proposed distributed model-based control scheme integrated with a proper scheduling strategy can greatly enhance the performance and the resiliency to parameter uncertainty in large-scale power systems. [ABSTRACT FROM PUBLISHER]

Low-bandwidth communication channels are used to support the information exchange between a microgrid centralized controller and local controllers in the secondary frequency control of an islanded microgrid. However, the impact of the inherent time delay in these communication channels on the microgrid performance has not been taken into account when the secondary frequency controller is designed. This paper investigates the effect of the communication delays on the secondary frequency control of an islanded microgrid with multiple distributed generators. A small-signal model-based method is introduced for the microgrid to find delay margins below which the microgrid can remain stable. By performing a series of trial studies, the relationships between secondary frequency control gains and delay margins are obtained. A gain scheduling approach is also proposed to compensate the effect of the communication delay on the secondary frequency control. Results from the Canadian urban distribution system have verified that communication delays can adversely affect the microgrid secondary frequency control, and the proposed gain scheduling approach can improve the robustness of the microgrid secondary frequency controller to communication delays. [ABSTRACT FROM PUBLISHER]