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A novel online system‐identification‐based control design for damping inter‐area oscillations in power systems using supplementary wide‐area excitation control is presented. The identification is based on a partly reduced‐order and a partly full‐order model of the grid. Assuming the grid to be divided into coherent areas with phasor measurement units located across the grid, the coherent states of the generators are averaged while the non‐coherent states, such as the internal states of each power system stabilizer, are not. A hybrid state vector consisting of these averaged and non‐averaged states is computed, and used for identifying a hybrid linear time‐invariant state‐space model. A linear quadratic regulator based on this hybrid model is, thereafter, designed. The reduced‐order part of the model is found to save significant amount of online time for both learning and control, while the full‐order part serves to enhance closed‐loop stability. N4SID with randomized singular value decomposition (rSVD) is used for making the identification loop fast. The reduced‐dimensional controller is finally implemented using a broadcast control strategy. The design is extended to non‐linear models of power systems using Carleman bilinearization. Results for linear and bilinear control designs are validated using the IEEE 68‐bus power system model. [ABSTRACT FROM AUTHOR]

This paper presents a mathematical analysis of how wind generation impacts the slow coherency property of power systems. Slow coherency arises from time-scale separation in the dynamics of synchronous generators, where generator states inside a coherent area synchronize over a fast time-scale due to stronger coupling, while the areas themselves synchronize over a slower time-scale due to weaker coupling. This time-scale separation is reflected in the form of a spectral separation in the weighted Laplacian matrix describing the swing dynamics of the generators. However, when wind farms with doubly-fed induction generators (DFIG) are integrated into the system then this Laplacian matrix changes based on both the level of wind penetration and the location of the wind farms. The modified Laplacian changes the effective slow eigenspace of the generators. Depending on the penetration level, this change may result in changing the identities of the coherent areas. We develop a theoretical framework to quantify this modification, and propose an equivalent Laplacian matrix to compute the modified coherent areas. Results are validated using the IEEE 68-bus test system with one and multiple wind farms. The model-based slow coherency results are compared with measurement-based principal component analysis to substantiate our derivations. [ABSTRACT FROM AUTHOR]

In this paper, we address several growing concerns of wind power integration from the perspective of power system dynamics and stability. We propose a new control design technique called retrofit control, by which one can control the rotor voltages of doubly fed induction generators to suppress the oscillations in the tie-line power flows caused by a disturbance inside the wind farm. The controller can be designed in a modular way, and also implemented in a completely decentralized fashion using only local feedback from the wind generator states and the voltage at the point of common coupling without depending on the states of any of the synchronous machines in the rest of the system. We show the effectiveness of the design using simulations of the IEEE 68- bus, 16-machine power system model with two wind farms. [ABSTRACT FROM PUBLISHER]

In this paper a distributed Model Predictive Control design is presented for inter-area oscillation damping in power systems under two critical cyber–physical constraints — namely, communication constraints that lead to sparsification of the underlying communication network, and actuation constraints that respect the saturation limits of generator controllers. In the current state-of-art, distributed controllers in power systems are executed over fixed communication topologies that are most often agnostic of the magnitude and location of the incoming disturbance signals. This often leads to a sub-optimal closed-loop performance. In contrast, the communication topology for the proposed controller is selected in real-time after a disturbance event based on event-specific correlations of the generator states with the dominant oscillation modes that are excited by that event. Since these correlations can differ from one event to another, so can the choice of the communication topology. These correlations are used to identify the most important sets of generators that must exchange state information for enhancing closed-loop damping of the inter-area modal frequencies. Effectiveness of this strategy is shown via simulations on the 48-machine, 140-bus model for the Northeast Power Coordinating Council. [ABSTRACT FROM AUTHOR]

In a recent paper, we proposed a system identification method for constructing reduced-order models for the electro-mechanical dynamics of large power systems, divided into multiple coherent clusters, using Synchrophasors. Every cluster in the actual model was represented as an aggregate generator in the reduced-order model. An aggregate network graph connected one aggregate generator to another. In this paper, we extend this identification approach to differential-algebraic (DAE) models. First, every cluster is associated with a unique terminal bus, referred to as the pilot bus, that couples its internal network to the rest of the system. The proposed algorithm uses Synchrophasor measurements from the pilot buses to identify the dynamic model of the aggregate generator for each cluster using nonlinear least squares while retaining the identity of all the pilot buses. The resulting reduced-order model is in the form of a nonlinear electric circuit described by aggregate differential and algebraic equations. We illustrate our results using two case studies, one for the IEEE 9-bus power system and another for the IEEE 39-bus power system. We also discuss how these reduced-order DAE models may be useful for designing shunt controllers at the pilot buses by using Synchrophasor feedback. [ABSTRACT FROM AUTHOR]

We propose a novel hierarchical frequency and voltage control design for multi-area power system integrated with inverter-based resources (IBRs). The design is based on the idea of prioritizing the use of IBRs over conventional generator-based control in compensating for sudden and unpredicted changes in loads and generations, and thereby mitigate any undesired dynamics in the frequency or the voltage by exploiting their fast actuation time constants. A new sequential optimization problem, referred to as Area Prioritized Power Flow (APPF), is formulated to model this prioritization. It is shown that compared to conventional power flow APPF not only leads to a fairer balance between the dispatch of active and reactive power from the IBRs and the synchronous generators, but also limits the impact of any contingency from spreading out beyond its respective control area, thereby guaranteeing a better collective dynamic performance of the grid. This improvement, however, comes at the cost of adding an extra layer of communication needed for executing APPF in a hierarchical way. Results are validated using simulations of a 9-machine, 6-IBR, 33-bus, 3-area power system model, illustrating how APPF can mitigate a disturbance faster and more efficiently by prioritizing the use of local area-resources. • A new concept of "area-prioritization"-based power flow (APPF) dispatch is proposed to maximize the participation of inverter-based resources (IBRs) in frequency and voltage control. • A hierarchical computation architecture is developed to implement this prioritization. • Implementation steps are showcased via simulation of a 33-bus power system with 9 generators and 6 IBRs. [ABSTRACT FROM AUTHOR]

We address the problem of sparsity-promoting optimal control of cyber–physical systems (CPSs) in the presence of communication delays. The delays are categorized into two types — namely, an inter-layer delay for passing state and control information between the physical layer and the cyber layer, and an intra-layer delay that operates between the computing agents, referred to here as control nodes (CNs), within the cyber-layer. Our objective is to minimize the closed-loop H 2 -norm of the physical system by co-designing an optimal combination of these two delays and a sparse state-feedback controller while respecting a given bandwidth cost constraint. We propose a two-loop optimization algorithm for this. Based on the alternating directions method of multipliers (ADMM), the inner loop handles the conflicting directions between the decreasing H 2 -norm and the increasing sparsity level of the controller. The outer loop comprises a semidefinite program (SDP)-based relaxation of non-convex inequalities necessary for closed-loop stability. Moreover, for CPSs where the state and control information assigned to the CNs are not private, we derive an additional algorithm that further sparsifies the communication topology by modifying the row and column structures of the obtained controller, resulting in a reassignment of the communication map between the cyber and physical layers, and determining which physical agent should send its state information to which CN. Proofs for closed-loop stability and optimality are provided for both algorithms, followed by numerical simulations. [ABSTRACT FROM AUTHOR]

Highlights: [•] We present graph-theoretic interpretations of model reduction in large power system networks. [•] We develop two PMU placement algorithms to identify reduced-order power system models with channel observability constraints. [•] We illustrate the two algorithms using examples from WECC and IEEE prototype models. [•] We present statistical analyses of the algorithms to highlight their robustness against network size and meshness. [ABSTRACT FROM AUTHOR]

In this paper we develop measurement-based methods for estimating a two-machine reduced model to represent the interarea dynamics of a radial, two-area power system with intermediate dynamic voltage control. Two types of voltage control equipment are considered, namely, a static VAr compensator (SVC), and a synchronous condenser. The methods use synchronized bus voltage phasor data at several buses including the voltage control bus, and the line currents on the power transfer path. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we propose two different time-scale separation based robust redesign techniques which recover the trajectories of a nominal control design in the presence of uncertain nonlinearities. We first consider additive input uncertainties and design a high-gain filter to estimate the uncertainty. We then employ the fast variables arising from this filter in the feedback control law to cancel the effect of the uncertainties in the plant. We next extend this design to systems with uncertain input nonlinearities in which case we design two sets of high gain filters—the first to estimate the input uncertainty over a fast time-scale, and the second to force this estimate to converge to the nominal input on an intermediate time-scale. Using singular perturbation theory we prove that the trajectories of the respective two-time-scale and three-time scale redesigned systems approach those of the nominal system when the filter gains are increased. We illustrate the redesigns by applying them to various physically motivated examples. [Copyright &y& Elsevier]

This paper develops a measurement-based method for estimating a two-machine reduced model to represent the interarea dynamics of a radial, multimachine power system. The method uses synchronized bus voltage phasor measurements at two buses and the line current on the power transfer path. The innovation is the application of the interarea oscillation components in the voltage variables resulting from disturbances for extrapolating system impedances and inertias beyond the measured buses. Expressions for the amplitudes of the bus voltage and bus frequency oscillations as functions of the location on the transmission path are derived from a small-signal perturbation approach. The reduced model provides approximate response to disturbances on the transfer path and offers an alternative to model reduction techniques based on detailed system models and data. [ABSTRACT FROM AUTHOR]

Many large interconnected power systems such as the U.S. eastern interconnection and the U.S. western power system are characterized by many power transfer paths or interfaces with high loading. Disruptions of these transfer paths frequently lead to increased loading on neighboring transfer paths, which themselves will become less secure and could cause further disruptions. State estimators have limited performance under large system disruptions, because of low sampling rates and potentially poor solution quality due to topology errors. Furthermore, disruptions in external power systems cannot be readily seen by control room operators because most state estimators only use reduced models for external systems. A system of well-placed phasor measurement units (PMUs) that provide voltage and current magnitude and phase at a high sampling rate can provide useful system dynamic security information. In this paper we apply energy function analysis using phasor data to monitor the dynamic status of power transfer paths. The ideas will be illustrated using actual data captured by several PMUs in the U.S. western power system. [ABSTRACT FROM AUTHOR]

Recent years have seen several new directions in the design of sparse control of cyber–physical systems (CPSs) driven by the objective of reducing communication costs. One common assumption made in these designs is that the communication happens over a dedicated network. For many practical applications, however, communication must occur over shared networks, leading to two critical design challenges, namely — time-delays in the feedback and fair sharing of bandwidth among users. In this paper, we present a set of sparse H 2 control designs under these two design constraints. An essential aspect of our design is that the delay itself can be a function of sparsity, which leads to an interesting pattern of trade-offs in the H 2 performance. We present three distinct algorithms. The first algorithm preconditions the assignable bandwidth to the network and produces an initial guess for a stabilizing controller. This is followed by our second algorithm, which sparsifies this controller while simultaneously adapting the feedback delay and optimizing the H 2 performance using alternating directions method of multipliers (ADMM). The third algorithm extends this approach to a multiple user scenario where an optimal number of communication links, whose total sum is fixed, is distributed fairly among users by minimizing the variance of their H 2 performances. The problem is cast as a difference-of-convex (DC) program with mixed-integer linear program (MILP) constraints. We provide theorems to prove the convergence of these algorithms, followed by validation through numerical simulations. [ABSTRACT FROM AUTHOR]

The feasible equilibria of operation of distribution-level power system models interfaced with solid-state transformers (SST) are analyzed and presented through a set of analytical relationships. The active and reactive power balances in the SST are realized through control of power electronic converters with appropriate choices for voltage and current setpoints. These setpoints parameterize the nonlinear model of the SST. Therefore, choosing them appropriately in sync with the generation and load profiles in the system is critical for maintaining a feasible equilibrium. These equilibrium sets are derived by first considering a fundamental physics-based model of a single-SST system, and thereafter, by extending them to systems with multiple SSTs connected to a radial distribution feeder. Power sharing methods are developed by which multiple SSTs can share a given change in load by generating an appropriate set of feasible setpoints for their input stage rectifiers. A control architecture is proposed for executing these load-sharing methods for both instantaneous and predictive load commands. The algorithms are verified by simulations on a representative distribution test system with nine SSTs. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive state-space dynamic model of a future power distribution system for plug-and-play interface of distributed renewable energy resources and distributed energy storage devices. The system, called the future renewable electric energy delivery and management (FREEDM) system, comprises of multiple solid-state transformers (SSTs), and load, generation, and storage connected to each SST in a distributed network. The system allows for high penetration of renewable generation with energy storage at the distribution level. A physics-based 70th-order state-space average model is first developed considering the physical and controller properties of a single-SST FREEDM system along with its distribution components. This fundamental model is then extended to build a multi-SST FREEDM system for feasibility and dynamics behavior analysis of the entire system, which is essential to ensure system power balance. The full average model with multiple SSTs has been incorporated in an IEEE 34 bus distribution testbed for a scaled analysis of the system. [ABSTRACT FROM AUTHOR]

In this paper we address the problem of wide-area control of power systems using Synchrophasor measurements in the presence of network delays. We propose a novel cyber-physical architecture that uses an arbitrated network control systems approach for mitigating the destabilizing effects of delays in power systems. The approach consists of: (1) utilization of Synchrophasor measurements from distributed measurements across different buses in the power network, (2) estimation of delays that control messages experience, (3) a delay-aware control design that explicitly accommodates the delays and judiciously utilizes estimated system states when needed, and (4) a switching control strategy that aborts the computation of control signals when delays exceed a certain threshold to improve resource utilization. While the control gains are determined using a centralized power system model and state feedback, it is shown that the delay-aware aspects of the proposed architecture allow both distributed measurements and distributed implementation of the control law. The results are illustrated using a 50-bus, 14-generator, 4-area power system model. The results clearly demonstrate that the proposed controller recovers the ideal system performance (such as deviations in frequency < 3 mHz ) even in the presence of large intra-area and inter-area delays with a small amount of additional control effort. Using the proposed overrun strategy, the results also confirm that about 30% drops can be accommodated with the proposed arbitrated network control systems approach. [ABSTRACT FROM AUTHOR]

In our recent work [1] , we constructed a reduced-order model of the Western Electricity Coordinating Council (WECC) power system using mathematically derived parameters from real Synchrophasor data. These parameters include inter and intra-area impedances, inertias, and damping factors for aggregate synchronous generators representing five geographical, and yet coherent, areas of WECC. In this paper, we use this reduced-order model as a tool to design a supplementary controller for a Static VAr Compensator (SVC), located at the terminal bus of one of the aggregate generators. Wide-area feedback consisting of phase angle and frequency measurements from Phasor Measurement Units (PMUs) in the other areas is used to design this controller. The objective is to damp the inter-machine oscillation modes of the reduced-order model, which in the full-order system corresponds to inter-area oscillations. The controller input is chosen via statistical variance analysis, and its parameters are tuned to improve the damping factors of the slow modes. The model is implemented in a real-time digital simulator, and validated using a wide range of disturbance scenarios. The closed-loop system is observed to be highly robust to all of these disturbances as well as the choice of operating points. Detailed experimental analyses of the capacity of the SVC to satisfy the damping specifications of supplementary control are also presented via multiple contingencies. The results are promising in aiding damping of inter-area modes in WECC, especially at a time of increasing penetration of wind and other renewable resources. [ABSTRACT FROM AUTHOR]

We present an extended linear quadratic regulator (LQR) design for continuous-time linear time invariant (LTI) systems in the presence of exogenous inputs with a novel feedback control structure. We first propose a model-based solution with cost minimization guarantees for states and inputs using dynamic programming (DP) that out-performs classical LQR with exogenous inputs. The control law consists of a combination of the optimal state feedback and an additional optimal term which is dependent on the exogenous inputs. The control gains for the two components are obtained by solving a set of matrix differential equations. We provide these solutions for both finite horizons and steady state cases. In the second part of the paper, we formulate a reinforcement learning (RL) based algorithm which does not need any model information except the input matrix, and can compute approximate steady-state extended LQR gains using measurements of the states, the control inputs, and the exogenous inputs. Both model-based and data-driven optimal control algorithms are tested with a numerical example under different exogenous inputs showcasing the effectiveness of the designs. [ABSTRACT FROM AUTHOR]

We present a set of model-free, reduced-dimensional reinforcement learning (RL) based optimal control designs for linear time-invariant singularly perturbed (SP) systems. We first present a state feedback and an output feedback based RL control design for a generic SP system with unknown state and input matrices. We take advantage of the underlying time-scale separation property of the plant to learn a linear quadratic regulator (LQR) for only its slow dynamics, thereby saving significant amount of learning time compared to the conventional full-dimensional RL controller. We analyze the sub-optimality of the designs using SP approximation theorems, and provide sufficient conditions for closed-loop stability. Thereafter, we extend both designs to clustered multi-agent consensus networks, where the SP property reflects through clustering. We develop both centralized and cluster-wise block-decentralized RL controllers for such networks, in reduced dimensions. We demonstrate the details of the implementation of these controllers using simulations of relevant numerical examples, and compare them with conventional RL designs to show the computational benefits of our approach. [ABSTRACT FROM AUTHOR]

The eigensystem realization algorithm (ERA) is a data-driven approach for subspacesystem identification and is widely used in many areas of engineering. However, the computationalcost of the ERA is dominated by a step that involves the singular value decomposition (SVD) ofa large, dense matrix with block Hankel structure. This paper develops computationally efficientalgorithms for reducing the computational cost of the SVD step by using randomized subspaceiteration and exploiting the block Hankel structure of the matrix. We provide a detailed analysis ofthe error in the identified system matrices and the computational cost of the proposed algorithms.We demonstrate the accuracy and computational benefits of our algorithms on two test problems:the first involves a partial differential equation that models the cooling of steel rails, and the secondis an application from power systems engineering. [ABSTRACT FROM AUTHOR]

• An optimal control design on a transmission-level model of the New York state grid. • PMU-only design without knowing the full-scale transmission model. • Tools from data analytics, system identification and control theory are used. • Techniques are engineered to improve the dynamic performance of NYS power grid. • Bridges the gap between the design advancements and the implementation opportunities. This paper focuses on designing and testing a supplementary controller for an ultra-large, utility-scale power system, namely the New York State (NYS) Power Grid from a completely measurement-based perspective. We present the control design using the Flexible AC Transmission System (FACTS) facility at the NYS grid. We use the utility-scale Eastern Interconnection (EI) model consisting of over 70 , 000 buses in the PSS/E platform for this research. The coherency structure of the NYS grid is analyzed by performing Principal Component Analysis (PCA) on frequency measurements obtained from multiple contingency simulations. Thereafter, we use the frequency measurements from PMU-enabled buses to identify a reduced-order state space model of the grid such that it matches the input-output characteristics along with identifying the inter-area modes. This model is then used to design the Linear Quadratic Gaussian (LQG) based optimal FACTS controller. Then the controller is implemented in the PSS/E model of the Eastern Interconnection (EI) as a PSS/E-FORTRAN based user defined module. The effectiveness of the control performance is shown using the non-linear simulations under different contingencies provided by the New York Independent System Operator (NYISO). [ABSTRACT FROM AUTHOR]

The comprehensive integration of instrumentation, communication, and control into physical systems has led to the study of Cyber-Physical Systems (CPSs), a field that has recently garnered increased attention. A key concern that is ubiquitous in CPS is a need to ensure security in the face of cyber attacks. In this paper, we carry out a survey of systems and control methods that have been proposed for the security of CPS. We classify these methods into three categories based on the type of defense proposed against the cyberattacks: prevention, resilience, and detection & isolation. A unified threat assessment metric is proposed in order to evaluate how CPS security is achieved in each of these three cases. Also surveyed are the risk assessment tools and the effect of network topology on CPS security. Furthermore, an emphasis has been placed on power and transportation applications in the overall survey. [ABSTRACT FROM AUTHOR]