The large-scale integration of power electronic-based systems poses new challenges to the stability and power quality of modern power grids. The wide timescale and frequency-coupling dynamics of ...electronic power converters tend to bring in harmonic instability in the form of resonances or abnormal harmonics in a wide frequency range. This paper provides a systematic analysis of harmonic stability in the future power-electronic-based power systems. The basic concept and phenomena of harmonic stability are elaborated first. It is pointed out that the harmonic stability is a breed of small-signal stability problems, featuring the waveform distortions at the frequencies above and below the fundamental frequency of the system. The linearized models of converters and system analysis methods are then discussed. It reveals that the linearized models of ac-dc converters can be generalized to the harmonic transfer function, which is mathematically derived from linear time-periodic system theory. Lastly, future challenges on the system modeling and analysis of harmonic stability in large-scale power electronic based power grids are summarized.
Droop control has been widely applied in dc microgrids (MGs) due to its inherent modularity and ease of implementation. Among the different droop control methods that can be adopted in dc MGs, two ...options have been considered in this paper: I-V and V-I droop. I-V droop controls the dc current depending on the dc voltage while V-I droop regulates the dc voltage based on the output current. The paper proposes a comparative study of V-I/I-V droop control approaches in dc MGs focusing on steady-state power-sharing performance and stability. The paper presents the control scheme for current-mode (I-V droop) and voltage-mode ( V-I droop) systems, derives the corresponding output impedance of the source subsystem, including converters dynamics, and analyzes the stability of the power system when supplying constant power loads. The paper first investigates the impact on stability of the key parameters including droop gains, local control loop dynamics, and number of sources and then performs a comparison between current-mode and voltage-mode systems in terms of stability. In addition, a generalized analytical impedance model of a multisource, multiload power system is presented to investigate stability in a more realistic scenario. For this purpose, the paper proposes the concept of "global droop gain" as an important factor to determine the stability behaviour of a parallel sources based dc system. The theoretical analysis has been validated with experimental results from a laboratory-scale dc MG.
For decades, synchronous generators have dominated power system dynamics and have been the foundation for the comprehension of the physical phenomena involved in power system stability. This paradigm ...is rapidly changing; large synchronous generators that contribute to system strength are being replaced by inverter-based generators. Consequently, new kinds of instabilities are emerging. Slow-interaction converter-driven instability is one example in which undamped oscillations occur when inverter-based generators operate in weak areas. Transmission system operators have observed the phenomenon under the scope of short-term dynamics following a disturbance during a weak operating condition. This paper suggests that converter-driven oscillations can occur even in the case when the system's initial operating condition is strong. It concludes that the phenomenon can be triggered by long-term dynamics that slowly weaken the system in which small-signal and short-term simulations show an ample stability margin. The outcome is a combination of unstable long-term dynamics and undamped oscillations. Furthermore, this work suggests that classical emergency controllers that are effective against long-term instability may not be successful if undamped oscillations are also present. A method for instability detection and counteraction is proposed based on Prony analysis and time-domain simulations on the IEEE test system for voltage stability assessment.
An inevitable consequence of the global power system transition toward nearly 100% renewable-based generation is the loss of conventional bulk generation by synchronous machines (SMs), their inertia, ...and accompanying frequency- and voltage-control mechanisms. This gradual transformation of the power system to a low-inertia system leads to critical challenges in maintaining system stability. Novel control techniques for converters, so-called grid-forming strategies, are expected to address these challenges and replicate functionalities that, so far, have been provided by SMs. This article presents a low-inertia case study that includes SMs and converters controlled under various grid-forming techniques. In this article, the positive impact of the grid-forming converters (GFCs) on the frequency stability of SMs is highlighted, a qualitative analysis that provides insights into the frequency stability of the system is presented, we explore the behavior of the grid-forming controls when imposing the converter dc and ac current limitations, the importance of the dc dynamics in grid-forming control design as well as the critical need for an effective ac current limitation scheme are reported, and finally, we analyze how and when the interaction between the fast GFC and the slow SM dynamics can contribute to the system instability.
In this paper, the effects of bounded disturbances on decentralized event-triggered control systems are studied. The input-to-state (practical) stability of integral-based event-triggered control ...systems and dynamic event-triggered control systems is analyzed in a uniform framework by utilizing a new Lyapunov functional approach. An estimation on the upper bound of the input-to-state stability gain is given analytically. First, Zeno behavior is excluded with the time-regularized mechanisms, that is, a prespecified lower bound of inter-event times is introduced. Then, the conditions are presented under which the considered event-triggered control systems ensure Zeno-freeness without time regularization. Finally, a numerical example is given to illustrate the efficiency and feasibility of the proposed results.
Compared to conventional microgrids (MGs) with pre-defined and static topology, dynamic MGs feature varying electric boundaries and enhanced operational resiliency. This paper evaluates the operation ...stability of inverter-based dynamic MGs in terms of fulfilling the requested MGs topology change and associated network reconfiguration, which falls into the category of large-signal stability analysis. A complete nonlinear state-space model of inverter-based dynamic MGs is derived, where coordinated controls among inverters along with the effect of communication delays have been considered. In response to reconfiguration demands, an evaluation scheme is developed to determine whether the system could perform seamless topology variation without losing synchronism. Specifically, the system's stability region is quantified by the domain of attraction (DoA) around the desired operating point using Takagi-Sugeno fuzzy modeling (T-S multimodeling). The large-signal stability of a multi-bus inverter-based dynamic MG with both interface inverters and sectionalizing switches have been analyzed. The stability regions estimated under different scenarios of topology variation have been validated using time-domain simulation in MATLAB/Simulink. The developed evaluation scheme is used to quantify the effects of control gain designs and communication delays on system large-signal stability.
•A new serial distributed model predictive control (MPC) strategy for connected automated vehicles (CAVs).•A CAV car-following MPC strategy with guaranteed local stability.•A CAV car-following MPC ...strategy with guaranteed l∞-norm string stability.•A CAV car-following MPC strategy with guaranteed l2-norm string stability when constraints are inactive.
In this paper, a serial distributed model predictive control (MPC) approach for connected automated vehicles (CAVS) is developed with local stability (disturbance dissipation over time) and multi-criteria string stability (disturbance attenuation through a vehicular string). Two string stability criteria are considered within the proposed MPC: (i) the l∞-norm string stability criterion for attenuation of the maximum disturbance magnitude and (ii) l2-norm string stability criterion for attenuation of disturbance energy. The l∞-norm string stability is achieved by formulating constraints within the MPC based on the future states of the leading CAV, and the l2-norm string stability is achieved by proper weight matrix tuning over a robust positive invariant set. For rigor, mathematical proofs for asymptotical local stability and multi-criteria string stability are provided. Simulation experiments verify that the distributed serial MPC proposed in this study is effective for disturbance attenuation and performs better than traditional MPC without stability guarantee.
Increasing use of renewable energy sources, liberalized energy markets and most importantly, the integrations of various monitoring, measuring and communication infrastructures into modern power ...system network offer the opportunity to build a resilient and efficient grid. However, it also brings about various threats of instabilities and security concerns in form of cyberattack, voltage instability, power quality (PQ) disturbance among others to the complex network. The need for efficient methodologies for quicker identification and detection of these problems have always been a priority to energy stakeholders over the years. In recent times, machine learning techniques (MLTs) have proven to be effective in numerous applications including power system studies. In the literature, various MLTs such as artificial neural networks (ANN), Decision Tree (DT), support vector machines (SVM) have been proposed, resulting in effective decision making and control actions in the secured and stable operations of the power system. Given this growing trend, this paper presents a comprehensive review on the most recent studies whereby MLTs were developed for power system security and stability especially in cyberattack detections, PQ disturbance studies and dynamic security assessment studies. The aim is to highlight the methodologies, achievements and more importantly the limitations in the classifier(s) design, dataset and test systems employed in the reviewed publications. A brief review of reinforcement learning (RL) and deep reinforcement learning (DRL) approaches to transient stability assessment is also presented. Finally, we highlighted some challenges and directions for future studies.
This article is concerned with the problem of fixed-time (FXT) and preassigned-time (PAT) synchronization for discontinuous dynamic networks by improving FXT stability and developing simple control ...schemes. First, some more relaxed conditions for FXT stability are established and several more accurate estimates for the settling time (ST) are obtained by means of some special functions. Based on the improved FXT stability, FXT synchronization for discontinuous networks is discussed by designing a simple controller without a linear feedback term. Besides, the PAT synchronization is also explored by developing several nontrivial control protocols with finite control gains, where the synchronized time can be prespecified according to actual needs and is irrelevant with any initial value and any parameter. Finally, the improved FXT stability and the synchronization for complex networks are confirmed by two numerical examples.
Power system control and transient stability analysis play essential roles in secure system operation. Control of power systems typically involves highly nonlinear and complex dynamics. Most of the ...existing works address such problems with additional assumptions in system dynamics, leading to a requirement for a complete and general solution. This paper, therefore, proposes a novel control framework for various power system control and stability problems leveraging a learning-based approach. The proposed framework includes a two-module structure that iteratively and jointly learns the candidate Lyapunov function and control law via deep neural networks in a learning module. Meanwhile, it guides the learning procedure towards valid results satisfying Lyapunov conditions in a falsification module. The introduced termination criteria ensure provable system stability. This control framework is verified through several studies handling different types of power system control problems. The results show that the proposed framework is generalizable and can simplify the control design for complex power systems with the stability guarantee and enlarged region of attraction.
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