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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]

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]

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]

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]

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]

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]

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]

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 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]

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]

The co-optimization of security-constrained unit commitment and dispatchable transmission network is a large-scale and computationally complex optimization problem that brings big challenges for the traditional centralized and/or master–slave based decomposition approaches. This paper proposes a fully parallel approach to achieve an efficient and fast solution while considering post-contingency corrective actions. In this paper, the original co-optimization problem is decomposed into six major solution modules for unit commitment, optimal power flow, and transmission switching in base case and contingencies, respectively. Moreover, each major solution module is further decomposed by unit, period, dispatchable line, and/or contingency to make the proposed approach favorable in a fully parallel computing environment. The effectiveness and efficiency of the proposed fully parallel approach are justified using numerical cases on a high-performance computing (HPC) platform. [ABSTRACT FROM AUTHOR]

This paper deals with the impact of linear approximations for the unknown nonconvex confidence region of chance-constrained ac optimal power flow problems. Such approximations are required for the formulation of tractable chance constraints. In this context, we introduce the first formulation of a chance-constrained second-order cone (SOC) OPF. The proposed formulation provides convergence guarantees due to its convexity, while it demonstrates high computational efficiency. Combined with an ac feasibility recovery, it is able to identify better solutions than chance-constrained nonconvex ac-OPF formulations. To the best of our knowledge, this paper is the first to perform a rigorous analysis of the ac feasibility recovery procedures for robust SOC-OPF problems. We identify the issues that arise from the linear approximations, and by using a reformulation of the quadratic chance constraints, we introduce new parameters able to reshape the approximation of the confidence region. We demonstrate our method on the IEEE 118-bus system. [ABSTRACT FROM AUTHOR]

Cyber-attack is recognized as an emerging risk in smart grids. In this paper, we reveal a potential link between data attack and physical consequences and analyzed how the attacker can launch a malicious data attack to trigger sequential outages and thus impose large damages to the grid. In this attack mechanism, the attacker constructs an optimal false data injection attack to intentionally trigger a targeted branch outage sequence that trips multiple branches and then leads to subsequent failures. The studied attack mechanism integrates constructing an optimal data attack and identifying critical lines, and imposes a substantial security impact with a high chance of occurring. Simulations on the IEEE 118-bus system verify that the introduced attack mechanism and highlight the risk of such attacks in today's smart grids. [ABSTRACT FROM AUTHOR]

This paper presents a method for harmoniously coordinating roles between generators and faster-acting energy storage systems (ESSs), e.g., batteries, to improve their frequency response and regulation services to the grid, particularly at the high wind penetration. This paper theoretically demonstrates that the proposed droop with the state of charge (SOC) feedback (DaSOF) provides a unified frequency control framework for distributed and energy-constrained ESS, seamlessly fitting the conventional primary and secondary frequency control practice. The ESS autonomously takes charge of high-frequency components of a frequency deviation and thus complements the frequency controls of the incumbent generators. By securing the SOC of the ESS at the desired level, the method provides the capability to provide other ancillary services from the energy-constrained ESS. These coordinated roles are represented and validated through time- and frequency-domain analyses. Rigorous case studies using DIgSILENT/PowerFactory demonstrate the efficacy of the proposed method to support the high level of variable renewable energy, which should help in improving the value of operating the ESS and scale up renewable energy. [ABSTRACT FROM AUTHOR]

The paper proposes a new adaptive approach to power system model reduction for fast and accurate time-domain simulation. This new approach is a compromise between linear model reduction for faster simulation and nonlinear model reduction for better accuracy. During the simulation period, the approach adaptively switches among detailed and linearly or nonlinearly reduced models based on variations of the system state: it employs unreduced models for the fault-on period, uses weighted column norms of the admittance matrix to decide which functions to be linearized in power system differential-algebraic equations for large changes of the state, and adopts a linearly reduced model for small changes of the state. Two versions of the adaptive model reduction approach are introduced. The first version uses traditional power system partitioning where the model reduction is applied to a defined large external area in a power system and the other area defined as the study area keeps full detailed models. The second version applies the adaptive model reduction to the whole system. The paper also conducts comprehensive case studies comparing simulation results using the proposed adaptively reduced models with the linearly reduced model and coherency-based reduced model on the Northeast Power Coordinating Council 140-bus 48-machine system. [ABSTRACT FROM AUTHOR]

This paper focuses on economic dispatch (ED) in power systems with intermittent wind power, which is a very critical issue in future power systems. A stochastic ED problem is formed based on the recently proposed versatile probability distribution of wind power. The problem is then analyzed and proved to be strictly convex. Although such convex optimization is tractable in many cases, it may take a long time to solve due to its large scale. This paper proposes a dual decomposition method to decompose the large problem. Then, two methods are employed to solve the decomposed problem, namely, the subgradient method and a faster method, limited-memory BFGS with box constraints (L-BFGS-B, a quasi-Newton method). Case studies were conducted to verify the efficiency of the dual decomposition and L-BFGS-B method for solving the stochastic ED problem. [ABSTRACT FROM AUTHOR]

Transient stability simulation studies of large-scale power systems often generate large amounts of data. This can make it difficult for power system planners to understand the overall system response or to identify portions of the system with unusual signals. In this paper we present a novel approach that utilizes clustering to extract common features in the voltage magnitude and frequency response signals, and to identify outliers. The geographic visualization of the results is also discussed. Results are demonstrated using the IEEE 118-bus system and a 16\thinspace000-bus real-world system model. [ABSTRACT FROM AUTHOR]

Identification of optimal locations to deploy the phasor measurement units (PMUs) is a preliminary task in wide area monitoring and control of power systems. Given the cost and other associated restrictions, it is highly unlikely for any utility to install all the required number of PMUs to ensure the complete observability of the network. This necessitates judicious identification of locations in the network to deploy the PMUs. Ideally, the choice of location must depend on the intended purpose. In this paper, an approach for placement of PMUs considering both the stability and topological aspects is presented. First, a probabilistic framework based on proximity to instability is proposed to rank the generators/load buses in the order of vulnerability. Subsequently, a binary integer linear programming formulation is proposed to identify the optimal locations considering both stability and topological aspects. The optimal locations obtained using the proposed approach ensures a priori observability of most vulnerable buses in addition to enhancing the network observability. Results on IEEE 39-bus system and 246-bus equivalent system of Indian southern grid are presented to illustrate the proposed approach. [ABSTRACT FROM PUBLISHER]

This paper introduces a screening method to determine the potential risk of interactions between a dynamic device and a generator with torsional oscillations. The proposed method introduces a factor called the radiality factor (RF) which is an indicator of the radialness of the network between the device and the generator. TheRF is calculated in the sub-synchronous frequency range and plotted against the frequency (RF curves). The RF curves can then be used for screening of torsional interactions between the generator and other dynamic devices. The critical value for the RF is determined through a large number of sensitivity studies on a test system. This method surpasses the available screening method: unit interaction factor (UIF) calculations which is only applicable for inductive networks without series compensated lines. [ABSTRACT FROM AUTHOR]

In this paper we present a framework to efficiently characterize the available operational flexibility in a multi-area power system. We focus on the available reserves and the tie-line flows. The proposed approach is an alternative to the current calculation of the available transfer capacity (ATC), as it considers location and availability of reserves, transmission constraints, and interdependencies of tie-line flows between different areas, while it takes into account the N-1 security criterion. The method is based on computational geometry using polytopic projections. It requires only a limited amount of information exchange and does not need central coordination. The method has two versions: a passive approach, and an active approach where neighboring areas can share reserves. In that respect we also introduce the term “exportable flexibility”. Case studies demonstrate the improved tie-line utilization, especially if reserves are shared, and the visualization benefits. [ABSTRACT FROM PUBLISHER]

Recent years have witnessed significant interest in convex relaxations of the power flows, with several papers showing that the second-order cone relaxation is tight for tree networks under various conditions on loads or voltages. This paper shows that ac-feasibility, i.e., to find whether some generator dispatch can satisfy a given demand, is NP-hard for tree networks. [ABSTRACT FROM AUTHOR]

This paper presents a method that in real-time determines remedial actions, which restore stable operation with respect to aperiodic small signal rotor angle stability (ASSRAS) when insecure or unstable operation has been detected. An ASSRAS assessment method is used to monitor the stability boundary for each generator in real-time. The ASSRAS boundary represents the condition when a generator reaches the maximum steady state active power injection. The proposed control method exploits analytically derived expressions for the ASSRAS boundary and other characteristic curves in the injection impedance plane to determine an active power redispatch among selected generators to restore stable and secure operation. Since the method is purely based on analytically derived expression, the computation of the remedial actions is fast and well suited for real-time operation. The method was tested on the IEEE 14-bus and the Nordic32 test systems where results show that the method can efficiently determine the required active power redispatch to avoid an imminent instability. [ABSTRACT FROM AUTHOR]

Emerging smart-grid-enabling technologies will allow an unprecedented degree of observability and control at all levels in a power system. Combined with flexible demand and storage, they could allow procuring energy at minimum cost and environmental impact. That however presupposes real-time coordination of demand of individual households and industries down at the distribution level, with generation at the transmission level. This is closely related with the balancing market economic dispatch (ED) problem, which currently does not take into account distribution network constraints and flexible demand characteristics. Still, assuming a suitably modified form of that problem was available, due to both computational and communications requirements, its centralized solution in its full detail would not be tractable. While there is currently a wealth of literature dealing with distributed optimization applications in power systems, it typically focuses on smaller parts of the overall energy management problem (e.g., transmission area synchronization or electric vehicles management) often without considering its full scale or establishing any association with energy market mechanisms. The target of this paper is twofold: 1) identify a flexible demand and distribution network inclusive formulation for ED and 2) propose a solution method. [ABSTRACT FROM AUTHOR]

Increasing penetration of renewable power sources (RESs) is bringing more uncertainties to power systems. Real-time economic dispatch should be able to handle the fluctuations caused by the load as well as RESs, and obtain new optimal operating points after deviating from original generation schedules. This paper proposes a generation adjustment algorithm based on the base point and participation factor method. The objective of the method is to obtain fast adjustments to generators’ real power outputs in real-time economic dispatch. The proposed method achieves significant and consistent improvements comparing to the original participation factor method by using a more precise model of transmission losses in the optimization process. The computational burden and execution time of the proposed method is much less than OPF and heuristic economic dispatch methods. The proposed method and its effectiveness are tested using IEEE 30-bus system, IEEE 118-bus system, and GuangDong 1018-bus system. Simulation results are demonstrated with comparisons and discussions. [ABSTRACT FROM AUTHOR]

Several transient stability software packages are widely used for power grid planning and operations. Prior research and software documentations have shown that packages can vary in the implementations of dynamic models, and hence could potentially yield different results for the same system simulation. This paper presents a systematic methodology to determine the sources of the discrepancies seen in results obtained from different transient stability packages. This methodology can be applied to various types of dynamic models and is illustrated with generator-associated dynamic models in this paper. Consistent metrics, data mining techniques, and engineering heuristics are used to determine the discrepancy sources. This hybrid top-down+bottom-up method has been implemented on a practical, large-system case to demonstrate its scalability and transferability to real-world system studies. [ABSTRACT FROM AUTHOR]

This paper proposes a bi-level branch-and-bound ((B&B) method to solve the economic dispatch problem with prohibited zones and network losses. The approach employs binary variables for each prohibited zone and utilizes the B-coefficient for network losses, which can be transformed into a mixed-integer quadratically constrained quadratic programming (MIQCQP), where linear relaxation technique is applied on each bilinear term. Due to the complexity in solving the MIQCQP problem, this paper proposes a bi-level B&B method to achieve global optimum. A spatial B&B method is utilized in the higher level to solve the quadratically constrained quadratic programming (QCQP) problem, whereas a simple B&B method is employed in the lower level to solve a mixed-integer quadratic programming (MIQP) problem. The bi-level B&B algorithm that combines spatial and simple B&B methods is actually a deterministic optimization method and can produce global optimal solutions. Numerical results on 6-unit, 15-unit, and 40-unit test systems show that the bi-level B&B method can solve the MIQCQP problem with superior solution quality and convergence characteristics. [ABSTRACT FROM PUBLISHER]

This paper proposes using phasor measurement unit (PMU) data to trigger one-shot control in response to loss of synchronism detection. Decision trees (DTs) are trained to associate voltage magnitude and angle measurements with loss of synchronism. Different approaches to the DT construction process are illustrated in an early section of the paper by restricting the input vector to only two elements. Response-based control is obtained by triggering one-shot control the first time the DT classifies measurements as “Unstable”. The same combination of one-shot controls is applied to any event the first time the DT outputs “Unstable”. The method is demonstrated on a 176-bus reduced-order model of the western U.S. interconnection. An effective one-shot control consists of a combination of fast power changes on four buses. This control is similar to 500-MW fast power increases on two HVDC interties and it reduces angle differences in the AC network. [ABSTRACT FROM PUBLISHER]

This paper extends the dynamic coherency determination (DCD) method by including Type-3 wind power plants (WPPs) models in the coherency evaluation process and quantifies impacts of the high depth of wind power penetration on the coherency phenomena of interconnected power systems. The method is based on frequency-deviation signals, measured at nongenerator buses and terminal buses of WPPs and synchronous generators. Salient features of the presented method are its ability to account for the hybrid nature of enhanced generic models of Type-3 WPPs and expanding notion of the power system coherency beyond the classical definition by including models of Type-3 WPPs. This paper also investigates impacts of the high depth of wind power penetration; i.e., up to 30%, on the coherency structure of the 16-machine/68-bus NPCC equivalent system. The studies are based on time-domain simulations in PSS/E software. The investigations reveal that Type-3 WPPs can introduce new coherent areas, significantly change areas’ boundaries and number of areas, and alter frequencies/dampings of interarea modes. [ABSTRACT FROM AUTHOR]

This paper proposes a fast and robust unscented Kalman filter based decentralized dynamic state estimator (DSE) for power system online monitoring and control. The proposed robust DSE is able to detect, identify, and suppress three types of outliers, namely the observation, innovation, and structural outliers. Observation outliers refer to the received PMU measurements providing unreliable metered values due to gross errors or cyber attacks; innovation outliers are typically caused by impulsive system process noise, whereas structural outliers are induced by incorrect parameters of the generators or its associated controllers, such as exciters and speed governors. To enable the fast estimation of generator states of large-scale power systems in a decentralized manner, two model decoupling approaches are presented and compared. It is shown that the generator decoupling approach presented in this paper achieves higher statistical efficiency than the ones proposed in the literature in the presence of both small and large measurement noise. To detect and distinguish three types of outliers, projection statistics based multiple hypothesis testing approach is proposed. Specifically, three hypotheses corresponding to the occurrence of three types of outliers are assumed by constructing three innovation matrices; these matrices are made up by time-correlated innovation vectors, and/or predicted states, and/or measurements; then projection statistics are applied to each of the innovation matrix and its calculated projection values are checked by a statistical test to validate the assumed hypothesis. The identified outliers are further suppressed by a generalized maximum-likelihood-type estimator. Numerical results carried out on the IEEE 39-bus system demonstrate the effectiveness and robustness of the proposed method. [ABSTRACT FROM AUTHOR]

As the power system evolves to better address environmental and reliability concerns, its overall dynamics changes and consequently challenges the adequacy of established operating procedures. This evolution brings a significant increase in the number of integrated renewable energy sources (RES) and HVDC connections. RES are normally connected to the grid through power electronic converters, which reduces or completely eliminates their electrical coupling to the power grid. As a result, such units are unable to contribute to the inertia of the system, posing a potential threat to the grid's physical security. More specifically, postfault frequency characteristics, such as rate of change of frequency (RoCoF), frequency nadir, and quasi-steady-state frequency, depend on the system inertia and their respective limits may potentially be violated. One way to address this problem is adding constraints to the unit commitment formulation so that operations maintain their frequency characteristics within acceptable limits. This paper studies how such changes affect the system frequency deviation from its rated value. The power system is modeled as an enterprise control that combines multiple layers of control operations into one package. Such integration allows capturing how the effects of wind integration and the addition of unit commitment inertia constraints propagate through control layers to impact the system frequency. [ABSTRACT FROM AUTHOR]

The uncertainties of renewable energy may bring impacts to power system reliability. This paper proposes a novel generation rescheduling algorithm, which adjusts generation outputs to mitigate the variations of branch power flows and relieve the overload probability. This algorithm helps prevent power congestion and balance the aggregate renewable generations and loads in power systems. Besides, the paper also proposes a probabilistic method evaluating the system uncertainty issue in the power system considering generation rescheduling operation. The proposed generation rescheduling algorithm has been tested on the Arizona transmission system. The generation rescheduling method enhances power system reliability analysis with a high penetration of renewable energy resources. [ABSTRACT FROM PUBLISHER]

In this paper, we model topology control through transmission switching as a recourse action in the day-ahead operation of power systems with large-scale renewable generation resources. We prove that transmission switching could only reduce the linear objective value of direct current optimal power flow when congestion exists. However, we also show, through a simple example, that unit commitment cost could be reduced by transmission switching even in the absence of congestion. To solve the stochastic unit commitment with topology control within reasonable computational time, we proposed a heuristic that first decomposes a practical system into zones and then solves the problem for each zone in parallel. The benefit of topology control recourse is demonstrated on a network representing the Central European System. We compare the costs of the network with different loading and renewable generation conditions. The cost reduction of the test system can reach 3.34% with heavy load and large-scale renewable generation while in a single zone the cost reduction can be above 7%. [ABSTRACT FROM PUBLISHER]

This paper jointly addresses two major challenges in power system operations: 1) dealing with non-convexity in the power flow equations, and 2) systematically capturing uncertainty in renewable power availability and in active and reactive power consumption at load buses. To overcome these challenges, this paper proposes a two-stage adaptive robust optimization model for the multi-period AC optimal power flow problem (AC-OPF) with detailed modeling considerations, such as reactive capability curves of conventional and renewable generators and transmission constraints. This paper then applies strong second-order cone programming (SOCP)-based convex relaxations of AC-OPF combined with the use of an alternating direction method to identify worst-case uncertainty realizations, and also presents a speed-up technique based on screening transmission line constraints. Extensive computational experiments show that the solution method is efficient and that the robust AC OPF model has significant advantages both from the economic and reliability standpoints as compared to a deterministic AC-OPF model. [ABSTRACT FROM PUBLISHER]

Today the dq0 reference frame is mainly used for modeling and control of traditional electric machines and small power sources. A current challenge is to merge various dq0-based models appearing in recent literature to obtain a complete model of a large power system. To this end, in this paper we propose a model describing the dynamics of large transmission networks based on dq0 quantities. The proposed model is based on a standard network topology, uses sparse system matrices, and is of minimal order. We also demonstrate how this model may be used to construct a small-signal description of a complete system that includes the transmission network, generators, and loads. Results are illustrated on the basis of a long transmission line, and using the 118-bus test case network. This paper is accompanied by a free software package. [ABSTRACT FROM PUBLISHER]

The increasing penetration of variable energy resources has led to more uncertainties in power systems. Flexible Ramping Products (FRP) have been adopted by several electricity markets to manage the uncertainties. We reveal that neglected line congestion for FRP may not only cause infeasibility, but also result in a failure of cost recovery. To address the deliverability issues on FRP, this paper proposes a new concept, Deliverable Robust Ramping Products (DRRP), in real-time markets. The DRRP includes generation ramping reserve and generation capacity reserve. The DRRP is deliverable and immunized against any predefined uncertainty. It also fully addresses the bid cost recovery issue caused by the line congestion in existing FRPs. The prices of DRRP are derived within the Affine Adjustable Robust Optimization (AARO) framework. These prices can be used to identify valuable reserves among available reserves and quantify the values of flexible resources that provide reserves. This paper also proposes a general approach to obtaining the time-decoupled prices for DRRP and generation, which can be used for the market settlement of the first interval only in real-time markets. Simulations on a 3-bus system and the IEEE 118-bus system are performed to illustrate the concept of DRRP and the advantages of DRRP compared to existing FRP. [ABSTRACT FROM PUBLISHER]

Integrating wind power into power systems contributes to existing variability in system operations. Current methods to mitigate this variability and uncertainty focus on using conventional generator ramping capability. There is also the option of using wind power itself to mitigate the variability and uncertainty that it introduces into the system. This paper introduces the concept of a flexible dispatch margin as a means for wind to participate in mitigating net variability and net uncertainty. In providing a flexible dispatch margin, wind generators under-schedule in the hour-ahead energy market in order to have additional expected flexibility available for the real-time market. The implementation of the flexible dispatch margin is analyzed in a two-stage optimization model with recourse to the flexible dispatch margin, flexible demand and generator ramping. This modeling framework combines Monte Carlo simulations with AC OPF analysis, using the IEEE 39-bus test system. Results show that use of the flexible dispatch margin decreases the reliance on peaking generators to mitigate net variability and uncertainty, and also decreases the frequency of price spike events, particularly as wind penetration increases from 10% to 30%. The analysis emphasizes the importance of increasing flexible resource capability as power system variability and uncertainty increase. [ABSTRACT FROM PUBLISHER]

All-electric ship power systems include less generation capacity and smaller rotating inertia compared with large power systems. The systems include large portions of nonlinear loads and dynamic loads, which may reduce the stability margin. Moreover, various operational constraints, such as system frequency constraint, motor voltage constraint and dynamic cable constraint, need to be satisfied in operational real time. Further, pulse loads draw very high short-time power in an intermittent way, which may significantly deteriorate the power quality of the system. In this paper, a novel multi-agent system cooperative controller for a medium voltage AC (MVAC) system of all-electric ship power systems is developed to balance load and generation in real time while satisfying system's operational constraints and considering load priorities. The new method coordinates the pulse load and the propulsion load to reduce the impact of pulse load changes on the power quality of all-electric ship power systems. The dynamic behavior of the new method is evaluated using case studies in PSCAD software. [ABSTRACT FROM PUBLISHER]

The screening curve method (SCM) is an intuitive and fast model that estimates the least-cost generation mix for generation planning purposes. It calculates an economically adapted generation mix for a target load duration curve within a few seconds, but lacks many detailed considerations of the generation system. In order to improve SCM, many developments have been made in recent years. However, one of the biggest limitations had always been that the SCM assumed all capacity to be new with no existing capacity. This drawback made SCM less useful compared to other generation planning models. In this paper, we develop a direct way to model existing capacity in SCM. The proposed method is studied in this paper and is illustrated with an example. Finally, an ERCOT year 2030 case is simulated. [ABSTRACT FROM AUTHOR]

Wind power generators will become increasingly useful in modern power systems; therefore, they should be able to support the system frequency in a way similar to that of conventional generators. Droop and virtual inertia are the most reported methods in the literature. However, their impact on the generator and system frequency stability, when the double-mass mechanical dynamics of a wind power generator are considered, has not been addressed thoroughly. In this paper, small-signal modeling, analysis, and eigenvalues studies are used to show that incorporating a wind power generator in the frequency regulation can expose its shaft to forces stimulating its natural resonance frequency dynamics and lead to instability. This paper shows that the mechanical resonance of frequency-regulating wind generators must be studied and enhanced not individually but as a part of the whole power system stability analyses. To overcome the stability problem caused by implementing frequency regulation in wind generators, this paper investigates different alternatives to stabilize the generator dynamics and, at the same time, minimize undesirable interference in the conventional wind power generator controllers. Time-domain simulation results validate the analytical results and discussions. [ABSTRACT FROM AUTHOR]

Electromechanical wave propagation is present in power systems as a transient spatial delay of generator rotor angle variations when a disturbance occurs. The control and mitigation of the this wave phenomenon, which spreads out to different locations at a comparably slow speed, is important for enhancing power system transient stability, as shown in part two of this two-paper series. In an idealized power system consisting of infinitesimal generators and line impedances, this traveling wave can exist to infinite frequencies, its speed can be derived from a wave equation and its reflection can be eliminated by a characteristic termination. Part one of this paper series examines realistic power systems with finite size generators and line impedances. It shows that there is a finite approximation of the traveling wave in real power systems as the wave can exist only within a finite frequency range. This paper also examines aspects such as reflections due to discrete elements, controller design based on the load modulation effect, and the existence of traveling wave and its attenuation in the Australian power system. [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]

This paper proposes a new approach for power system transient stability simulation, which is based on a semi-analytical solution (SAS) of power system differential-algebraic equations. In this paper, an SAS is derived using the Adomian decomposition method as a closed-form explicit function of symbolic variables such as time, the initial state, and other variables on system conditions and; hence, it can directly give a power system's dynamic trajectory being accurate for a certain time window. Unlike a traditional numerical integration based simulation approach, the proposed new approach offline derives an SAS and online evaluates the SAS by plugging in values of symbolic variables for a series of time windows making up the desired simulation period. This paper further studies the maximum length of the time window for an SAS being accurate and proposes a divergence indicator for simulation using adaptive time windows. Implementation of this new approach on parallel computers is also studied. The new approach is validated through contingency simulation of the IEEE 10-generator 39-bus system with detailed generator models. [ABSTRACT FROM AUTHOR]

This paper summarizes the technical activities of the Task Force on Power System Dynamic State and Parameter Estimation. This Task Force was established by the IEEE Working Group on State Estimation Algorithms to investigate the added benefits of dynamic state and parameter estimation for the enhancement of the reliability, security, and resilience of electric power systems. The motivations and engineering values of dynamic state estimation (DSE) are discussed in detail. Then, a set of potential applications that will rely on DSE is presented and discussed. Furthermore, a unified framework is proposed to clarify the important concepts related to DSE, forecasting-aided state estimation, tracking state estimation, and static state estimation. An overview of the current progress in DSE and dynamic parameter estimation is provided. The paper also provides future research needs and directions for the power engineering community. [ABSTRACT FROM AUTHOR]

Since forced oscillations are exogenous to dynamic power system models, the models by themselves cannot predict when or where a forced oscillation will occur. Locating the sources of these oscillations, therefore, is a challenging problem which requires analytical methods capable of using real time power system data to trace an observed oscillation back to its source. The difficulty of this problem is exacerbated by the fact that the parameters associated with a given power system model can range from slightly uncertain to entirely unknown. In this paper, a Bayesian framework, via a two-stage maximum a posteriori optimization routine, is employed in order to locate the most probable source of a forced oscillation given an uncertain prior model. The approach leverages an equivalent circuit representation of the system in the frequency domain and employs a numerical procedure, which makes the problem suitable for real time application. The derived framework lends itself to successful performance in the presence of phasor measurement unit measurement noise, high generator parameter uncertainty, and multiple forced oscillations occurring simultaneously. The approach is tested on a four-bus system with a single forced oscillation source and on the WECC 179-bus system with multiple oscillation sources. [ABSTRACT FROM AUTHOR]

A continuous Online Monitoring System (OMS) for power system stability based on Phasor Measurements (PMU measurements) at all the generator buses is proposed in this paper. Unlike the state-of-the-art methods, the proposed OMS does not require information about fault clearance. This paper proposes a convolutional neural network, whose input is the heatmap representation of the measurements, for instability prediction. Through extensive simulations on standard IEEE 118-bus and IEEE 145-bus systems, the effectiveness of the proposed OMS is demonstrated under varying loading conditions, fault scenarios, topology changes, and generator parameter variations. Two different methods are also proposed to identify the set of critical generators that are most impacted in the unstable cases. [ABSTRACT FROM AUTHOR]

This paper studies the optimal transmission switching (OTS) problem for power systems, where certain lines are fixed (uncontrollable) and the remaining ones are controllable via on/off switches. The goal is to identify a topology of the power grid that minimizes the cost of the system operation while satisfying the physical and operational constraints. Most of the existing methods for the problem are based on first converting the OTS into a mixed-integer linear program (MILP) or mixed-integer quadratic program (MIQP), and then iteratively solving a series of its convex relaxations. The performance of these methods depends heavily on the strength of the MILP or MIQP formulations. In this paper, it is shown that finding the strongest variable upper and lower bounds to be used in an MILP or MIQP formulation of the OTS based on the big- $M$ or McCormick inequalities is NP-hard. Furthermore, it is proven that unless $P=NP$ , there is no constant-factor approximation algorithm for constructing these variable bounds. Despite the inherent difficulty of obtaining the strongest bounds in general, a simple bound strengthening method is presented to strengthen the convex relaxation of the problem when there exists a connected spanning subnetwork of the system with fixed lines. With the proposed bound strengthening method, remarkable improvements in the runtime of the mixed-integer solvers and the optimality gaps of the solutions are achieved for medium- and large-scale real-world systems. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear power flows and excitation voltage dynamics. Salient features of the proposed distributed control strategy are fourfold, first, nonlinearity is considered to cope with large disturbances, second, only a part of generators are controllable, third, no load measurement is required, fourth, communication connectivity is required only for the controllable generators. To this end, benefiting from the concept of “virtual load demand,” we first design the distributed controller for the controllable generators by leveraging the primal-dual decomposition technique. We then propose a method to estimate the virtual load demand of each controllable generator based on local frequencies. We derive incremental passivity conditions for the uncontrollable generators. Finally, we prove that the closed-loop system is asymptotically stable and its equilibrium attains the optimal solution to the associated economic dispatch problem. Simulations, including small and large-disturbance scenarios, are carried on the New England system, demonstrating the effectiveness of our design. [ABSTRACT FROM AUTHOR]

Battery energy storage system (BESS) services will be of great help when operating power systems at high renewable energy penetrations. This paper demonstrates the requirements for effective frequency and inertia services. Some system operators currently apply scalars to financially reward improved performance. This paper demonstrates a method of validating and improving these scalars by considering the delay time and ramp time of the BESS. The importance of the method used to measure the rate of change of frequency is discussed in the paper. While the rate of change of frequency services improves with reduced delivery times, limits are identified where further reductions produce a negligible impact. This demonstrates the tangible benefits of a rapid response, and that current technology could meet the criteria. A variety of BESS capacities are trialed, which demonstrate consistency in performance and the occurrence of diminishing returns [ABSTRACT FROM AUTHOR]

This paper describes the use of large electric grids in university electric power system courses. Since much actual power system information is not publicly available, the application of public domain synthetic grids developed by the authors is presented including a 2000-bus grid. Discussion of the educational applications utilized in a senior level class are given for power flow analysis and sensitivity, economic dispatch, contingency analysis, optimal power flow (OPF), security-constrained OPF, transient stability, and real-time dynamic operations. In each of these, the application of the large synthetic grids give students insights and experience with cases closer to actual power systems in complexity and size. [ABSTRACT FROM AUTHOR]

With the wide deployment of synchrophasor technology, measurement-based dynamic modeling and studies have been becoming increasingly useful for real-time grid operations. This paper considers the problem of estimating the power system frequency response from ambient synchrophasor measurements. Specifically, we develop the analytical conditions for establishing the equivalence between the cross correlation of ambient generator speed data and the system frequency response between any two locations. Our conditions, relying on uniformly damped and equally excited oscillation modes, extend earlier work on electromechanical wave propagation modeling to nonhomogeneous power networks. Numerical results suggest that the validity of the cross correlation approach would hold for more realistic conditions such as nonuniform damping and high-order generator model. Its practical value is further corroborated by real-data results, which closely match with the actual propagation time of electromechanical waves recorded during the 2008 Florida blackout in the Eastern Interconnection system. [ABSTRACT FROM AUTHOR]