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In interconnected power systems, operated by several system operators, the participating areas are strongly dependent on their neighbors. In order to identify the economically efficient generation dispatch in each area, a distributed multi-area optimal power flow (OPF) must be solved. Additionally, installation of an increasing number of HVDC lines to deal with increased power flows from renewable generation is expected to change the power system operation paradigm. The controllability introduced by the HVDC lines should be considered and incorporated in the OPF algorithm. In this paper we introduce a formulation for the distributed solution of the OPF problem in multi-area systems consisting of both HVAC and HVDC lines. We show the applicability of this formulation on two different operating schemes for HVDC grids and we compare their performance with a central solution for the mixed HVAC/HVDC grid. The proposed formulations are based on a linearized solution of the OPF problem. The only data to be exchanged between the areas pertains to the border nodes. [ABSTRACT FROM AUTHOR]

This paper discusses a recent event in the western American power system when a forced oscillation was observed at a frequency that was close to a well-known 0.38-Hz inter-area electromechanical mode frequency of the western system. The event motivates a systematic investigation in this paper on the possibility of resonant interactions between forced oscillations and electromechanical inter-area oscillatory modes in power systems. When the natural oscillatory mode of a power system is poorly damped, and the forced oscillation occurs at a frequency close to system mode frequency at critical locations for the mode, resonance is observed in simulation test cases of the paper. It is shown that the MW oscillations on tie-lines can be as high as 477 MW from a 10-MW forced oscillation in Kundur test system because of resonance. This paper discusses the underlying system conditions and effects as related to resonance in power systems caused by forced oscillations and discusses ways to detect such scenarios using synchrophasors. Simulated data from Kundur two-area test power system as well as measurement data from western American power system are used to study the effect of forced oscillations in power systems. [ABSTRACT FROM AUTHOR]

The introduction of an equivalent model for a regional power area in a large-scale power system with complex loads is essential for reducing the computation burden in real-time dynamic analyses. In this paper, we propose a generalized discrete-time equivalent model (GDEM) with specific relations among model parameters for simulating the physical characteristics of a regional power area. The GDEM facilitates the interconnection of equivalent models representing regional power areas and improving the simulation accuracy and speed in large-scale dynamic power systems. This paper first investigates the inherent relations among GDEM parameters in the discrete-time models of synchronous generators and composite loads so as to guide the GDEM parameter estimation in regional power areas. This paper then develops relations among GDEM parameters for a regional power area. Numerical experiments are conducted by simulating ground faults in the China Electric Power Research Institute system and the accuracy of the proposed GDEM is verified by analyzing the dynamic simulation results. In addition, this paper has applied the GDEM to study the regional power area of Central China, which validates the use of GDEM in practical power system analyses. [ABSTRACT FROM AUTHOR]

This paper presents parameter values and ranges of static load models used in a power system analysis for the representation of both individual electrical devices and aggregate system loads. The paper discusses and correlates load models and their parameters following statistical processing of the responses of around 100 transmission system operators and utilities around the world, who participated in a survey initiated by CIGRE Working Group C4.605, with the corresponding information on load models and their parameter values from the existing literature. According to the survey, the most frequently used static load models are voltage dependent, and voltage and frequency dependent exponential load models. The identified typical parameter values and ranges of these static load models, both for low voltage devices and for aggregate loads at higher voltage levels, are results of the analysis of a large number of data. Based on these results, the paper provides recommendations for their further use in power system studies and also introduces a novel method for obtaining the mean values and ranges of parameters of the aggregate system load models. [ABSTRACT FROM AUTHOR]

Economic dispatch (ED) considering valve-point effect, multiple fuel options, prohibited operating zones of generation units is a more accurate model compared to a conventional ED model. It is non-smooth and thus evolutionary algorithms (EAs) are so far the only feasible approaches for the model. In Part II of the paper, a new method, the dimensional steepest decline method (DSD), is proposed for the ED with non-smooth objectives. The DSD is based on the local minimum analysis of the ED problem presented in Part I of the paper. The fuel cost's decline rate between each two adjacent singular points is utilized to find the optimal solutions in a serial sequence. The computational complexity of the DSD is analyzed. The DSD has been applied to solve different types of ED problems on different test systems, including large-scale systems. The simulation results show that DSD can obtain more accurate solutions and consume much less time and its advantage is more obvious on large-scale systems, in comparison with the state-of-art EAs. [ABSTRACT FROM PUBLISHER]

This paper applies a new technique for modal decomposition based solely on measurements to test systems and demonstrates the technique's capability for partitioning a power network, which determines the points of separation in an islanding strategy. The mathematical technique is called the Koopman mode analysis (KMA) and stems from a spectral analysis of the so-called Koopman operator. Here, KMA is numerically approximated by applying an Arnoldi-like algorithm recently first applied to power system dynamics. In this paper we propose a practical data-driven algorithm incorporating KMA for network partitioning. Comparisons are made with two techniques previously applied for the network partitioning: spectral graph theory which is based on the eigenstructure of the graph Laplacian, and slow-coherency which identifies coherent groups of generators for a specified number of low-frequency modes. The partitioning results share common features with results obtained with graph theory and slow-coherency-based techniques. The suggested partitioning method is evaluated with two test systems, and similarities between Koopman modes and Laplacian eigenvectors are showed numerically and elaborated theoretically. [ABSTRACT FROM PUBLISHER]

This paper describes the design of the ERCOT modeling extensions to the IEC 61968/70 standards to enable Common Information Model (CIM) schema support of dynamic ratings methodologies. Implementation of dynamic ratings was driven by current economic and environmental constraints placed on the construction of additional electrical transmission infrastructure, thus creating a need to operate the existing equipment closer to its physical limitations. In order to effectively utilize these dynamic limits, the necessary data constructs must be modeled, so ERCOT extended the CIM representation of the balanced three-phase power system model used to operate its various grid functions, in order to support the modeling and use of dynamic ratings in its operational real-time and congestion hedging market models. This paper also explains how the process utilized in the identification and extension of the CIM model for this purpose is flexible enough for generic application within the power industry. [ABSTRACT FROM AUTHOR]

Synthetic power systems that imitate functional and statistical characteristics of the actual grid have been developed to promote researchers’ access to public system models. Developing time series to represent different operating conditions of these synthetic systems will expand the potential of synthetic power systems applications. This paper proposes a methodology to create synthetic time series of bus-level load using publicly available data. Comprehensive validation metrics are provided to assure that the quality of synthetic time series data is sufficiently realistic. This paper also includes an example application in which the methodology is used to construct load scenarios for a 10,000-bus synthetic case. [ABSTRACT FROM AUTHOR]

In this paper, a new systematic method is proposed to analyze the system frequency in power systems under uncertain variability (UV). UV gradually increases in power systems, which originates from the renewable energy generation, random loads, frequency measurement, and communication channels, exerting noteworthy impacts on dynamic system frequency. The UV is modeled as a stochastic process in this paper. Then, the stochastic differential equations are used to describe the dynamic system frequency response (SFR) of a power system under UV, which is based on the SFR model. To assess system frequency dynamics under UV, an index of intra-range probability is put forward. Based on stochastic analysis theory, an analytic method is proposed to analyze the system frequency under UV, by which the intra-range probability can be analytically solved. Compared with Monte Carlo simulation in a typical SFR case and the Iceland electricity transmission network, the proposed method shows almost the same results using much less computation resource. Finally, insights for improving the SFR under UV are provided. The proposed method can be used to quickly verify whether the system frequency could withstand the UV and stay in the security range. [ABSTRACT FROM AUTHOR]

Time-domain simulation is the basis of dynamic security assessment for power systems. Traditionally, numerical integration methods are adopted by simulation software to solve nonlinear power system dynamics for any given contingency under a specific operating condition. An alternative simulation approach promising for online applications is to offline derive a semi-analytical solution (SAS) for power system differential equations and then online evaluate the SAS over consecutive time windows regarding the operating condition and contingency until the simulation result over a desired period is obtained. This paper proposes a general semi-analytical approach that derives and evaluates an SAS in the form of a power series in time to approximate the true solution. This paper provides an error-rate upper bound of the SAS for reliable use of adaptive time windows in evaluation of the SAS. To extend the semi-analytical approach for solving general power system differential-algebraic equations, this paper also proposes a dynamic bus method to efficiently link the SAS for dynamic components with the numerical solution of the network algebraic equations. Case studies on the New England 39-bus system and the Polish 2383-bus system test the performance of the proposed approach, compare it with other methods, and show the potentials of the proposed semi-analytical approach for online simulation. [ABSTRACT FROM AUTHOR]

The paper addresses the problem of determining the maximum distributed energy resource (DER) capacity that can be connected to low-voltage (LV) networks without creating voltage-rise problems. That maximum capacity depends on the network characteristics and on the candidate sites for DER connection. When sites are multiple and LV networks are poorly characterized, such maximum capacity cannot be determined with power-flow or other admittance-matrix-based approaches. This paper proposes an approach to estimate voltage rise caused by DER under reduced network characterization. Such approach is built upon customary voltage and impedance measurements to be made at the sites of DER injection and gives sufficiently accurate results under most practical situations. The paper validates the accuracy of the proposed approach against exact power-flow results for well-characterized networks and load situations and provides guidelines for DER connection based on maximum capacity nodal allocation. [ABSTRACT FROM PUBLISHER]

The novel cascade-mitigation scheme developed in Part I of this paper is implemented within a receding-horizon model predictive control (MPC) scheme with a linear controller model. This present paper illustrates the MPC strategy with a case-study that is based on the IEEE RTS-96 network, though with energy storage and renewable generation added. It is shown that the MPC strategy alleviates temperature overloads on transmission lines by rescheduling generation, energy storage, and other network elements, while taking into account ramp-rate limits and network limitations. Resilient performance is achieved despite the use of a simplified linear controller model. The MPC scheme is compared against a base-case that seeks to emulate human operator behavior. [ABSTRACT FROM PUBLISHER]

The control of reactive power exchange between grids of different voltage levels has always been a concern for system operators. With production moving from the transmission to the distribution level, its importance increases. This paper proposes a novel approach to estimate reactive power capability of the grid as a whole. A linearized analytical model for an estimation of available reactive power exchange at the interface between two grids has been developed. The maximum estimation error for the scenarios we tested was only 2%. The model gives the relation between important grid parameters and the supported reactive power. The conclusions drawn from the model are confirmed on typical Swedish distribution network with scattered wind power and small industry consumers. Common scenarios in development of distribution grids are applied to show relevant parameters influence. One studied scenario is replacement of overhead lines with cables. It is shown that this particular change enhances the reactive power capability of the grid which is directly seen from the analytical analysis without running any optimal power flow. The analytical model proposed in this paper gives fundamental understanding of the reactive power capability of radial distribution grids. [ABSTRACT FROM AUTHOR]

This paper analyzes different models for evaluating investments in energy storage systems (ESS) in power systems with high penetration of renewable energy sources. First of all, two methodologies proposed in the literature are extended to consider ESS investment: a unit commitment model that uses the “system states” (SS) method of representing time; and another one that uses a “representative periods” (RP) method. Besides, this paper proposes two new models that improve the previous ones without a significant increase of computation time. The enhanced models are the “system states reduced frequency matrix” model which addresses short-term energy storage more approximately than the SS method to reduce the number of constraints in the problem, and the “representative periods with transition matrix and cluster indices” (RP-TM&CI) model which guarantees some continuity between representative periods, e.g., days, and introduces long-term storage into a model originally designed only for the short term. All these models are compared using an hourly unit commitment model as benchmark. While both system state models provide an excellent representation of long-term storage, their representation of short-term storage is frequently unrealistic. The RP-TM&CI model, on the other hand, succeeds in approximating both short- and long-term storage, which leads to almost 10 times lower error in storage investment results in comparison to the other models analyzed. [ABSTRACT FROM AUTHOR]

This paper presents a methodology and set of validation criteria for the systematic creation of synthetic power system test cases. The synthesized grids do not correspond to any real grid and are, thus, free from confidentiality requirements. The cases are built to match statistical characteristics found in actual power grids. First, substations are geographically placed on a selected territory, synthesized from public information about the underlying population and generation plants. A clustering technique is employed, which ensures the synthetic substations meet realistic proportions of load and generation, among other constraints. Next, a network of transmission lines is added. This paper describes several structural statistics to be used in characterizing real power system networks, including connectivity, Delaunay triangulation overlap, dc power flow analysis, and line intersection rate. The paper presents a methodology to generate synthetic line topologies with realistic parameters that satisfy these criteria. Then, the test cases can be augmented with additional complexities to build large, realistic cases. The methodology is illustrated in building a 2000 bus public test case that meets the criteria specified. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) programs must be able to provide sound operating points for power systems under different conditions while meeting a large number of constraints. These constraints, however, either due to the operating conditions at hand or by construction, can have linearly dependent gradients, thus defining ill-behaved feasible sets. This paper analyzes the use of an alternative set of optimality conditions, derived from the Fritz-John (FJ) conditions, to represent OPF solutions in such critical cases. Results are presented for realistic test systems. [ABSTRACT FROM PUBLISHER]

This paper presents a new method for studying electromechanical transients in power systems using three phase, combined transmission and distribution models (hybrid models). The methodology models individual phases of an electric network and associated unbalance in load and generation. Therefore, the impacts of load unbalance, single phase distributed generation and line impedance unbalance on electromechanical transients can be studied without using electromagnetic transient simulation (EMTP) programs. The implementation of this methodology in software is called the Three Phase Dynamics Analyzer (TPDA). Case studies included in the paper demonstrate the accuracy of TPDA and its ability to simulate electromechanical transients in hybrid models. TPDA has the potential for providing electric utilities and power system planners with more accurate assessment of system stability than traditional dynamic simulation software that assume balanced network topology. [ABSTRACT FROM PUBLISHER]

This paper presents a general framework for the doubly fed induction generator connected to a complex power system in order to facilitate the dynamic estimation of its states using noisy PMU measurements. State estimation considering the whole power system with the occurrence of electric faults is performed using the Unscented Kalman Filter (UKF) with a bad data detection scheme. Such a state estimation scheme for a DFIG is important because not all dynamic states of a DFIG are easily measurable. Furthermore, the proposed state estimation technique is decentralized and the network topology of the entire power system is taken into consideration in the estimation process. In order to enhance the error tolerance and self-correction of the power system, bad data detection technique is implemented. A performance comparison with Extended Kalman Filter (EKF) is also discussed. [ABSTRACT FROM PUBLISHER]

This paper develops a systematic framework for analyzing how low frequency forced oscillations propagate in electric power systems. Using this framework, the paper shows how to mathematically justify the so-called Dissipating Energy Flow (DEF) forced oscillation source location technique. The DEF's specific deficiencies are pinpointed, and its underlying energy function is analyzed via incremental passivity theory. This analysis is then used to prove that there exists no passivity transformation (i.e. quadratic energy function) which can simultaneously render all components of a lossy classical power system passive. The paper goes on to develop a simulation-free algorithm for predicting the performance of the DEF method in a generalized power system, and it analyzes the passivity of three non-classical load and generation components. The proposed propagation framework and performance algorithm are both tested and illustrated on the IEEE 39-bus New England system and the WECC 179-bus system. [ABSTRACT FROM AUTHOR]

This paper proposes a general framework for determining the effect of communication delays on the convergence of certain distributed frequency regulation (DFR) protocols for prosumer-based energy systems, where prosumers are serving as balancing areas. DFR relies on iterative and distributed optimization algorithms to obtain an optimal feedback law for frequency regulation. But, it is, in general, hard to know beforehand how many iterations suffice to ensure stability. This paper develops a framework to determine a lower bound on the number of iterations required for two distributed optimization protocols. This allows prosumers to determine whether they can compute stabilizing control strategies within an acceptable time frame by taking communication delays into account. The efficacy of the method is demonstrated on two realistic power systems. [ABSTRACT FROM PUBLISHER]

This paper is concerned with the security-constrained optimal power flow (SCOPF) problem, where each contingency corresponds to the outage of an arbitrary number of lines and generators. The problem is studied by means of a convex relaxation, named semidefinite program (SDP). The existence of a rank-1 SDP solution guarantees the recovery of a global solution of SCOPF. We prove that the rank of the SDP solution is upper bounded by the treewidth of the power network plus one, which is perceived to be small in practice. We then propose a decomposition method to reduce the computational complexity of the relaxation. In the case where the relaxation is not exact, we develop a graph-theoretic convex program to identify the problematic lines of the network and incorporate the loss over those lines into the objective as a penalization (regularization) term, leading to a penalized SDP problem. We perform several simulations on large-scale benchmark systems and verify that the global minima are at most 1% away from the feasible solutions obtained from the proposed penalized relaxation. [ABSTRACT FROM AUTHOR]

Recurrence quantification analysis (RQA) is a nonlinear data analysis technique that can quantify the number and duration of a dynamical system of being in nearly the same area in phase space trajectory. This paper proposes three applications of RQA to analyse power system dynamics. These are denoising of PMU data, localization of power system events, and transient stability contingency ranking of power system. All three applications have been demonstrated using a multimachine test system. [ABSTRACT FROM AUTHOR]

This paper presents an improved corrective security constrained optimal power flow (CSCOPF) for a meshed AC/DC power transmission network with voltage source converter based multi-terminal HVDC (VSC-MTDC) grids. The security constrains of N-1 contingencies for both AC and DC networks are fully considered in the CSCOPF problem. The corrective actions employed in this paper include not only the traditional long-term rescheduling control actions of the AC system, but also the short term post-contingency fast corrective control of multi-terminal VSC-HVDC. A hybrid method is developed to solve the improved CSCOPF problem and the effectiveness of the proposed method is evaluated and demonstrated in this paper by two example meshed AC/DC power systems. [ABSTRACT FROM AUTHOR]

Small isolated power systems often experience generator outages, which are responsible for the activation of the under-frequency load shedding scheme with the corresponding negative impact on electricity consumers and, hence, market loss. There are three main causes of this problem: the power system's low inertia, the speed governors' low capacity, and a poor size-ratio between generator and system. The most extensive research line in this area is focused on the optimization of the load shedding scheme, which is a partial solution. Another research line is presented to solve the problem from the point of view of the system operator. This paper proposes an online method to predict and correct possible load shedding by redistributing load dispatching. This proposal uses artificial intelligence techniques, in particular neural networks, and a special-purpose power system simulator. In order to evaluate the proposal, the achieved solution is applied to a real case study: the island of Gran Canaria. This application shows the improvement that might be achieved by implementing this simple method. The method proposed in this paper is strongly recommended for regions that have suitable geographical sites as well as energy problems similar to those of the Canary Islands (see tech. rep. “Map of the Canary Islands Power Systems” by Red Electrica de Espana). [ABSTRACT FROM AUTHOR]

Flexibility is a widely used term in planning process and real-time operation. The existing research on flexibility uses different techniques to study flexibility property from different aspects. While studying a property from various viewpoints increases the understanding on the subject, we need a consistent theoretical framework to consolidate the ideas generated in the field, compare and contrast results, and build on for future analysis. Based on the insights of the nature of flexibility, this paper proposes a unified framework for defining and measuring flexibility in power system. Under the proposed framework, we propose a flexibility metric which evaluates the largest variation range of uncertainty that the system can accommodate. Such a metric takes into account transmission network and system operations constraints, which are critical to assessing flexibility, but are often ignored in literature. A robust optimization technique is used to calculate the proposed metrics. While the illustrative example presented in this paper focuses on the flexibility in real-time system operation in the presence of wind and load uncertainty, this framework can generally be applicable to long-term studies such as system planning. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel control algorithm for improving steady-state (quasi-static) voltage stability by use of an embedded voltage source converter (VSC) based high voltage direct current (HVDC) system. In this paper, the terms “steady-state” and “quasi-static” are used interchangeably. By embedded HVDC, we refer to a meshed AC system with all HVDC terminals connected within the same AC grid. The sensitivity between VSC control input and the voltage stability margin is introduced. Based on this sensitivity, the proposed control algorithm jointly satisfies system-wide voltage stability margin as well as local voltage magnitude requirements. The proposed approach is to first migrate the entire system to have sufficient voltage stability margin, and then to correct any voltage magnitude violation while keeping that stability margin. A contour-based visualization of the VSC capability space for maintaining system voltage stability is introduced, which can effectively illustrate how the singular value sensitivity (SVS) based control achieves both the local and global voltage stability requirements. The efficacy of the proposed algorithm is shown via case studies on a 6-bus and 118-bus system with and without static VAR compensation. [ABSTRACT FROM AUTHOR]

In order to improve low voltage (LV) network visibility without extensive monitoring and integrate low carbon technologies (LCTs) in a cost-effective manner, this paper proposes a novel three-stage network load profiling method. It uses real-time information monitored from selective representative areas to develop network templates. The three stages are: clustering, classification and scaling. It can be used to identify the loading conditions of unmonitored LV systems with similar fixed data to those monitored LV substations. In the clustering stage, hierarchical clustering and K-means are used to cluster substations into groups based on the shape of the monitored load profiles. The classification tool designed with multinomial logistic regression maps an unmonitored LV substation into the most probable templates by using routinely available fixed data. Finally, clusterwise weighted constrained regression is employed to estimate peak for individual LV substations and the developed templates. The three-stage profiling is demonstrated on a practical system in the U.K. under the umbrella of a smart grid trail project. Ten LV templates are developed by using the metered data from 800 monitored LV substations. A comprehensive comparison between the estimated peaks using the three-stage process and the metered peaks suggests that the methodology can achieve superior accuracy. This is part I of the paper, introducing clustering and classification. The scaling (peak estimation) process will be introduced in part II of the paper. [ABSTRACT FROM PUBLISHER]

This paper demonstrates that machine learning can be used to create effective algorithm selectors that select between power system control algorithms depending on the state of a network, achieving better performance than always using the same algorithm for every state. Also presented is a novel method for creating algorithm selectors that consider two objectives. The method is used to develop algorithm selectors for power flow management algorithms on versions of the IEEE 14- and 57-bus networks, and a network derived from a real distribution network. The selectors choose from within a diverse set of power flow management algorithms, including those based on constraint satisfaction, optimal power flow, power flow sensitivity factors, and linear programming. The network state-based algorithm selectors offer performance benefits over always using the same power flow management algorithm for every state, in terms of minimizing the number of overloads while also minimizing the curtailment applied to generators. [ABSTRACT FROM AUTHOR]

This paper examines the application of STATCOM and battery energy storage to enhance the transient stability of large-scale multimachine power systems with synchronous and doubly-fed induction generators (DFIGs). A passivity-based control design method [interconnection and damping assignment passivity-based control (IDA-PBC)] is developed for multimachine power systems and its performance is evaluated on a two-area system consisting of two synchronous generators (SGs) and two DFIG along with STATCOM/battery energy storage system. The main contributions of this paper are threefold: 1) use of a STATCOM and battery energy storage system to enhance transient stability and provide voltage regulation with SG and DFIG; 2) demonstrating the application of nonlinear control theory (specifically the IDA-PBC methodology) for the design of a stabilizing feedback controller in large-scale power systems to improve transient system performance; and 3) developing a methodology that can use the additional degrees of freedom in large-scale power systems in order to further improve system performance, in particular the transient stability margin [measured through critical clearing time (CCT)] and the dynamic transient performance of the system. In order to achieve power angle stability along with the simultaneous regulation of frequency and voltage, the performance of the proposed control scheme after the occurrence of large disturbances is evaluated and compared with a conventional power system stabilizer and a feedback linearizing controller. [ABSTRACT FROM AUTHOR]

This paper investigates the modal repulsion happened in the sub-synchronous resonance between a synchronous generator and series-compensated transmission line. The investigation is based on the closed-loop model of the series-compensated power system consisted of the torsional and electrical open-loop subsystems. Analytical explanation is presented to show how the SSO modal repulsion is formed as the result of moving close and apart between two open-loop SSO modes. Analysis is carried out to indicate that the peak of the SSO modal repulsion occurs when the two open-loop SSO modes from the torsional and electrical subsystem are closest to each other on the complex plane, which is referred to as the open-loop modal coupling. Estimation on the peak, i.e., the maximum damping degradation of the SSO modes, is derived in the paper. Subsequently, a method of open-loop modal analysis is proposed. Applications of the proposed method of open-loop modal analysis to study the SSOs caused by the DFIGs under the condition of the modal repulsion in the power system are demonstrated and evaluated by example power systems. The concept of modal repulsion explains why the grid connection of the DFIGs may bring about the SSO instability risk in the power system. [ABSTRACT FROM AUTHOR]

This paper presents a decentralized solution algorithm for network-constrained unit commitment (NCUC) in multiregional power systems. The proposed algorithm is based on our previous work in which a local NCUC was formulated for each control entity (i.e., region) and an analytical target cascading (ATC) based distributed but partially parallelized algorithm requiring a central coordinator was presented. The primary objective of this paper is to present a decentralized approach that relaxes the need for any form of central coordinator in ATC and allows fully parallelized solutions of the local NCUCs. To achieve this objective, we formulate a bilevel optimization problem for each control entity. While the upper level solves the NCUC problem of the control entity, the lower level seeks to coordinate the control entity with its neighboring regions. The lower level is a convex optimization, which can be further replaced in the upper level problem by the Karush–Kuhn–Tucker conditions. The control entities communicate directly with each other and synchronously solve their local NCUCs. Having no need for any form of central coordinator, the proposed algorithm is potentially less vulnerable to cyber-attacks and communication failures than the distributed methods utilizing a coordinator. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to analyze impacts of uncertain variability on power system dynamics. There is considerable interest in integrating intermittent renewable energy and plug-in electric vehicles into power systems. Therefore, power systems are in an environment with increasing uncertain variability. In this paper, the uncertain variability is described as a continuous-time stochastic process, and thus, the power system under uncertain variability is modeled by stochastic differential equations. To quantify impacts of uncertain variability on power system dynamics, an intra-region probability index is presented. Based on the stochastic averaging method, an analytical method is proposed to calculate the intra-region probability. Compared to Monte Carlo simulation, the proposed method is many orders of magnitude faster without sacrificing the result accuracy. Furthermore, several insights are given to improve the power system dynamics under uncertain variability. [ABSTRACT FROM AUTHOR]

In this paper, dynamic performance of automatic generation control (AGC) of two area thermal–thermal power system is determined through the steam chest and reheater constant trajectories. In earlier AGC studies, steam chest and reheater time constants denoted as T\text{SC} and T\text{RH} are considered to be constant, irrespective of plant generation schedules. However, it is discovered that T\text{SC} and T\text{RH} follow the specific trajectories with the plant generation schedules. These time constant trajectories are determined by the power output control strategies being employed to change the plant generation schedules. These control strategies are the different combinations of steam pressure versus flow rate curves used to operate the plant at different generation schedules. In this paper, time constant versus generation schedule trajectories of T\text{SC} and T\text{RH} have been derived for different power output control strategies. Furthermore, these time constant trajectories have been utilized to investigate the dynamic performance of two area reheat thermal power system. [ABSTRACT FROM AUTHOR]

Normal form (NF) is an effective tool to quantitatively analyze nonlinear modal interaction, which is believed to contribute to the complex nonlinear dynamics in power systems. However, in conventional NF analysis, the solution under resonance condition cannot be expressed in a closed form. Hence the NF analysis of power system higher order modal interaction was limited to nonresonant cases, or directly neglecting the resonant terms. In this paper, the NF solutions under modal resonance are derived, by means of the polynomial vector space decomposition. The obtained solution is in a simple closed form, including both the nonresonant part and the resonant part. Numerical simulations are performed to verify the effectiveness of the proposed approach. The results show that, under modal resonant conditions, neglecting the resonant terms may cause significant errors to the obtained numerical solutions, whereas including modal resonant terms in NF may increase the accuracy of the analysis. Finally, the approach proposed in this paper is compared with the modal series method, which, unlike NF method, is not limited by resonant condition. The results show that the proposed method in this paper has better performance in both accuracy and computing time. [ABSTRACT FROM PUBLISHER]

Widespread three-phase imbalance causes inefficient uses of low voltage (LV) network assets, leading to additional reinforcement costs (ARCs). Previous work that assumed balanced three phases underestimated the reinforcement cost throughout the whole utility by more than 50%. Previous work that quantified the ARCs was limited to individual network components, relying on full sensory data. This paper proposes a novel methodology that will scale the ARC estimation at a utility level, when the data concerning the imbalance of circuits or transformers are scarce. A novel statistical method is developed to estimate the volume of assets that need to be invested by identifying the relationship between the triangular distribution of circuit imbalance and that of circuit utilization. When there are more data available in future, accurate probability distributions can be constructed to reflect the network condition across the whole system. In light of this, two novel generalized ARC estimation formulas are developed that account for generic probability distributions. The developed methodology is applied to a real utility system in the UK, showing that: 1) three-phase imbalance leads to ARCs that are even greater than the reinforcement costs in the balanced case; 2) a 1% increase in the demand growth rate, the maximum degree of imbalance (DIB) and the maximum nominal utilization rate leads to over 10%, approximately 1% and 2% increases in the ARCs, respectively; and 3) the ARC is not sensitive to the minimum DIB values and the minimum nominal utilization rates. [ABSTRACT FROM PUBLISHER]

Power system congestion is a major problem that the system operator (SO) would face in the post-deregulated era. Therefore, investigation of techniques for congestion-free wheeling of power is of paramount interest. One of the most practiced and an obvious technique of congestion management is rescheduling the power outputs of generators in the system. However, all generators in the system need not take part in congestion management. Development of sound formulation and appropriate solution technique for this problem is aimed in this paper. Contributions made in the present paper are twofold. Firstly a technique for optimum selection of participating generators has been introduced using generator sensitivities to the power flow on congested lines. Secondly this paper proposes an algorithm based on particle swarm optimization (PSO) which minimizes the deviations of rescheduled values of generator power outputs from scheduled levels. The PSO algorithm, reported in this paper, handles the binding constraints by a technique different from the traditional penalty function method. The effectiveness of the proposed methodology has been analyzed on IEEE 30-bus and 118-bus systems and the 39-bus New England system. [ABSTRACT FROM AUTHOR]

This paper addressed some theoretical and practical issues relevant to the problem of power system load modeling and identification. Two identification techniques are developed in the theoretical framework of stochastic system identification. The identification techniques presented in this paper belong to the family of output error models; both techniques are based on well-established equations describing load recovery mechanisms having a commonly recognized physical appeal. Numerical experiments with artificially created data were first performed on the proposed techniques and the estimates obtained proved to be asymptotically unbiased and achieved the corresponding Cramér-Rao lower bound. The proposed techniques were then tested using actual field measurements taken at a paper mill, and the corresponding results were used to validate a commonly used aggregate load model. The results reported in this paper indicate that the existing load models satisfactorily describe the actual behavior of the physical load and can be reliably estimated using the identification techniques presented herein. [ABSTRACT FROM AUTHOR]

Power router technology is maturing to the point of becoming a cost-effective enabler of increased transmission asset utilization. Power routers can enable a desirable increase in control of power systems, especially as infrastructure ages and degrades. This paper presents a formal extension to the traditional security-constrained optimal power flow (SCOPF) algorithm, named flexible security-constrained optimal power flow (FSCOPF), which utilizes power router control in the post-contingency timeframe. The operational improvement is enabled by the fast-response capability of FACTS-based power routers to change setpoints in response to power system contingencies. The FSCOPF algorithm, developed in this paper, allows for power routers to be used as a real-time dispatchable resource. We show that further power system savings are achieved when compared to the traditional SCOPF. [ABSTRACT FROM PUBLISHER]

Load modeling is essential for designing and operating power systems. This paper presents an approach for load modeling on smaller power systems that could be “islanded,” an approach that preserves the detail of a full differential equation simulation of relevant loads while requiring far less computation by employing behavioral models of important loads. Mixed domain models, e.g., stochastic, finite-state machine, and differential equation models, are employed to provide accuracy in a computationally tractable framework. Where simple load models may not be adequate, particularly for generation-constrained systems (in a paper by Sotiropoulos ), and full models are computationally unfavorable, this approach provides excellent results that enable “what-if” studies and flexible re-evaluation during power system design and operational assessment. Naval vessels, particularly warships with relatively large and increasing load power requirements, offer a unique laboratory for understanding isolated power grids. This paper examines the DDG-51 power distribution system as an example. [ABSTRACT FROM PUBLISHER]

This paper proposes some methods for the purpose of reactive power and voltage control. Real cases show them as potentially harmful for power systems, since dynamic instability and voltage collapse may appear. Control actions like tap changers, active and reactive power redispatch may help the system voltage stability, but may present reverse results for some operating conditions. This paper is firstly devoted to identify and classify an operating point under the voltage stability point of view. Following this classification, an index to assess the robustness of a bus is proposed. The studies are carried out with the help of the QV curves. Methods to change the region of operation of a bus are then discussed with the help of a real Brazilian system with all limits considered. [ABSTRACT FROM PUBLISHER]

This second part of a two-paper series gives an overview of key insights and control implications arising from the wave characteristics of power system transient stability. These insights, which are unique to traveling wave interpretation, are obtained through time-domain analysis of artificial and real test systems: “critical region for a stressed link near the end of a longitudinal system,” “dispersed control in a path,” “placement of controllers considering structure and load distribution in a system,” and “localized transient stability enhancement.” Good transient stability enhancement is successfully achieved by controllers in all test systems in terms of larger critical clearing time, which directly translates to increased maximum safe power transfer. The controller design is based on the transmission line analogy of traveling waves and load modulation effect. The concepts in this paper series can assist in improving the design of control strategies to enhance power system transient stability by considering the wave aspects. [ABSTRACT FROM AUTHOR]

This two-part paper presents a framework for the characterization and minimal representation of the feasibility regions of power systems in the demand space. These feasibility regions are called loadability sets, and they represent the projection of generation-demand-network space onto the demand space only. Loadability sets have been characterized previously for power systems with either no or a single active line flow constraint. In Part I of this two-part paper, we generalize this characterization to power systems with any number of active line flow constraints. The proposed characterization approach makes use of the Fourier–Motzkin elimination method which leads to the generation of a large number of constraints. We set course to address this shortcoming in the second part of this paper. The notion of umbrella set is revisited in Part II to identify and remove the redundant constraints produced in the loadability set characterization process. The outcome of the proposed framework is the minimal representation of the power system feasibility region in the demand space. We envision multiple applications for the proposed framework in power system planning, operations planning, and real-time operation. [ABSTRACT FROM AUTHOR]

A new hierarchical multi-area power system state estimation method is proposed in this paper. Instead of exchanging boundary measurements or state estimates, the proposed technique is based on exchanging the sensitivity functions of local state estimators. The main benefit of the proposed scheme is the improved convergence speed, which also reduces the amount of information exchange required. Extensive numerical results involving IEEE standard systems and a utility scale system are presented. [ABSTRACT FROM AUTHOR]

In this paper, an application-oriented tubular Solid Oxide Fuel Cell (SOFC) mathematical model is presented. Its dynamic behaviors in complex power systems which consist of synchronous generators of different types are then investigated where SOFC transience is studied on a small (second) timescale. Based on the mathematical model of the entire power system, SOFC dynamic states estimator is designed to track and predict the behaviors of unmeasurable states inside SOFC during normal operating and electrically faulty conditions, using stochastic filtering algorithms. The proposed estimator operates on a holistic level with all generators, transmission lines and loads taken into consideration, whereas only SOFC local electrical data are needed for the dynamic state estimation. The success of estimating SOFC internal states will lead to a higher possibility of designing state-related controllers so as to regulate the behaviors of SOFC during electric faults. [ABSTRACT FROM PUBLISHER]

This paper presents a new approach for reliability evaluation of composite power systems by combining Monte Carlo simulation and multi label k-nearest neighbor (MLKNN) algorithm. MLKNN is a classification technique in which target vector of each instance is assigned into multiple classes. In this paper, MLKNN is used to classify states (failure or success at system or bus level) of a complete power system without requiring optimal power flow (OPF) analysis, except in the training phase. As a result, the computational burden to perform OPF is reduced dramatically. For illustration, the proposed method is applied to the IEEE 30 BUS Test System and IEEE Reliability Test System. The obtained results from various case studies demonstrate that MLKNN based reliability evaluation provides promising results in both classification accuracy and computation time in evaluating the composite power system reliability. [ABSTRACT FROM AUTHOR]

The use of phasor measurement units (PMU) has enabled monitoring the power system dynamics online. There are many PMUs installed, which will give a comprehensive view in real or near real time of the entire system. In general, there are many operating conditions of power systems, which requires different tools to analyze the synchrophasor data provided by PMUs. Changes in power system monitoring must be detected as quickly as possible, so that the system operators can choose a different tool for data analysis. Therefore, in this paper, changes in the working conditions of the power system are detected using a subspace state-space based change-point detection method. The detection algorithm proposed in this paper is sequential detection, which aims at both detection accuracy and detection speed. We have tested our proposed algorithm to detect many various kinds of changes in power system operations and verified that the algorithm is able to detect changes successfully, including very small ones in the system such as the low-amplitude forced oscillations buried in the system's ambient conditions in a real-time manner. The algorithm is tested in a set of real-world data to show its practical usage in large systems with imperfect data. [ABSTRACT FROM AUTHOR]

Composite power system reliability evaluation is computationally time-consuming because the optimal power flow (OPF) with the least load curtailment is calculated for a large number of samples. Most current studies of probabilistic simulation methods focus on sampling techniques to improve the sampling efficiency and decrease the calculations of the OPF. This paper proposes a fast reliability evaluation method that accelerates the calculation of the OPF using multi-parametric linear programming (MPLP). In this paper, the sampled transmission line statuses are considered by the transmission line status dictionary (TLSD). We match the line status of each sample with the scenarios in the TLSD. For matching samples, the generation status and the sampled load are treated as MPLP parameters of the DC-OPF evaluation model. A dynamic learning algorithm is applied to solve the MPLP problem. Case studies are conducted on both IEEE Reliability Test Systems and a provincial power system in China. The results show that the proposed method improves the evaluation efficiency by 23–30 times compared with the normal DC-OPF-based model. [ABSTRACT FROM AUTHOR]

Under the deregulated environment, electric utility companies have been encouraged to ensure maximum system reliability through the employment of cost-effective long-term asset management strategies. Previously, the age based Weibull distribution has been used vastly for modeling and forecasting aging failures. However, this model is only based on asset age and does not consider additional information such as asset infant mortality period and equipment energization delay. Some works on modifying Weibull distribution functions to model bathtub-shaped failure rate function can be practically difficult due to model complexity and inexplicit parameters. To improve the existing methods, this paper proposes four modified Weibull distribution models with straightforward physical meanings specific to power system applications. Furthermore, this paper proposes a novel method to effectively evaluate different Weibull distribution models and select the suitable model(s). More importantly, if more than one suitable model exists, these models can be mathematically combined as a joint forecast model, which could provide better accuracy to forecast future asset reliability. Finally, the proposed approach was applied to a Canadian utility company for the reliability forecast of electromechanical relays and distribution poles to demonstrate its practicality and usefulness. [ABSTRACT FROM AUTHOR]

Battery energy storage is becoming an important part of modern power systems. As such, its operation model needs to be integrated in the state-of-the-art market clearing, system operation, and investment models. However, models that commonly represent operation of a large-scale battery energy storage are inaccurate. A major issue is that they ignore the dependence of the charging power on the battery state of energy. Consequently, market players might suffer great monetary losses for not being able to follow their day-ahead schedule and/or deliver the scheduled reserves. In order to bridge the gap between very detailed low-level battery charging constraints and high-level battery operation models used in the literature, this paper examines a dependence of battery charging ability on its state of energy. It proposes a laboratory procedure, which can be used for any battery type and technology, to obtain this dependence. It also formulates an accurate linear battery charging model, which closely approximates the real-life battery charging constraints. The proposed battery charging model is compared against the models commonly used in the literature. Battery operation schedules obtained by all the models are compared against experimentally obtained results in order to assess the value of the proposed model in real life. [ABSTRACT FROM AUTHOR]

This paper is devoted to the description of a new approach for large-scale electric power systems (EPS) simulation, so-called hybrid simulation approach. The design and research of EPS require solving a large number of non-trivial tasks. Due to the well-known EPS specificity, mathematical modeling is the only way to proceed. According to the hybrid approach, several simulation techniques (analogue, digital, and physical) are used to achieve the best results. An analogue part provides the elimination of methodological integration error, which appears in a case of numerical methods usage. A digital part allows the realization of control and parameter changing algorithms on software level. In a physical part, the connection and switching of modeled elements are provided in a way as in real EPS. In addition, the paper presents hardware features of the simulator—hybrid real-time power system simulator (HRTSim), which is an alternative to the digital simulators currently used. The important part of this paper is the result of comparative analysis of transient processes oscillograms obtained by HRTSim and real disturbance recorders in Tomsk region power system, as well as HRTSim and real-time digital simulator. [ABSTRACT FROM AUTHOR]