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The transience and unpredictability of processes in electric power systems (EPS) determine complexity of its control. This problem is especially relevant for EPS with renewable energy sources and flexible alternating current transmission systems technologies. Automatic control systems simplify the solution of this problem. Despite this, many issues related to EPS state control are solved by power system operators. Decision support systems (DSS) are applying to increase efficiency of operators work. However, existing algorithms in practice are inoperable in some cases: unrealizable decisions are formed, or decision cannot be found at all, etc. Another important problem is impossibility to preliminarily verify the proposed solution. In this regard, operators can additionally use EPS simulators, which are usually limited either by the size of simulated scheme or by the details of equipment mathematical models. The limitations are a consequence of numerical methods using, which are badly applicable for large-scale power systems simulation. In this article, a novel DSS has been developed based on a hybrid approach to EPS modeling combining properties and capabilities of several simulation techniques: analog, physical and digital. The implicit integration of differential equations in analog way makes possible modeling faster than real time. Such opportunity allows operator to verify more decisions and select the most effective ones. The algorithm for DSS application has been developed and described in the article. The properties and capabilities of the developed DSS are confirmed by experimental studies and tests in a real EPS. [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]

This work considers the task of finding an ac-feasible operating point of a severely damaged transmission network while ensuring that a maximal amount of active power loads can be delivered. This AC maximal load delivery (AC-MLD) task is a nonconvex nonlinear optimization problem that is incredibly challenging to solve on large-scale transmission system data sets. This work demonstrates that convex relaxations of the AC-MLD problem provide a reliable and scalable method for finding high-quality bounds on the amount of active power that can be delivered in the AC-MLD problem. To demonstrate their effectiveness, the solution methods proposed in this work are rigorously evaluated on 1000 $N$ - $k$ scenarios on seven power networks ranging in size from 70 to 6000 buses. The most effective relaxation of the AC-MLD problem converges in less than 20 seconds on commodity computing hardware for all 7000 of the scenarios considered. [ABSTRACT FROM AUTHOR]

Measurements from the on-board systems of marine vessels are increasingly available for data analysis and are growing in importance as the ship industry enters a phase of digitalization. The purposes of the data analysis from vessels in operation include the verification of the power system design in general and improvement of the electrical power load analysis in particular. In this paper, we show how to extract valuable information from the data-driven operational profile analysis, which reveals the real power demand, and how the vessel was operated. Using the real power range analysis, we emphasize the significance of rarely occurring high power demands, which are critical for power system design and optimization. We propose a methodology for the quantification of variability in the generated power, which explains the tails of probability distributions of a power signal based on signal decomposition. The proposed methodology makes use of the data and it can facilitate the selection of the optimal size, number, and configuration of generators or batteries when designing new power systems. Measurements from a data collection system are used to demonstrate the methodology for dynamic positioning mode of the operation of a platform supply vessel. [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]

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]

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]

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]

The system frequency response (SFR) model describes the average network frequency response after a disturbance and has been applied to a wide variety of dynamic studies. However, the traditional literature does not provide a generic, analytical method for obtaining the SFR model parameters when the system contains multiple generators; instead, a numerical simulation-based approach or the operators’ experience is the common practice to obtain an aggregated model. In this paper, an analytical method is proposed for aggregating the multi-machine SFR model into a single-machine model. The verification study indicates that the proposed aggregated SFR model can accurately represent the multi-machine SFR model. Furthermore, the detailed system simulation illustrates that the SFR model can also accurately represent the average frequency response of large systems for power system dynamic studies. Finally, three applications of the proposed method are explored, with system frequency control, frequency stability, and dynamic model reduction. The results show the method is promising with broad potential applications. [ABSTRACT FROM AUTHOR]

Interarea power oscillation damping enhancement in large interconnected power systems is often accomplished using supplementary controls at the synchronous machines involved and with the use of flexible ac transmission system devices. The power system literature has demonstrated that wide area signals could be more effective than the local signals for these controllers. In some cases where phasor measurement units are used, all the required control signals may not be available. To alleviate these cases, control signals are obtained using estimated signals from a “dynamic state estimator,” and a robust supplementary controller is deployed. In this paper, the cited strategy is illustrated using a static var compensator. The feasibility of the proposed method has been demonstrated on the IEEE 50-generator test system. [ABSTRACT FROM AUTHOR]

This paper develops a generalized framework that allows us to investigate the vulnerability of the power system nonlinear state estimator to false data injection attacks (FDIAs) from the operator's perspective and to initiate some countermeasures. Unlike most existing FDIA methods, which assume a perfect knowledge of the system measurements and topology by a hacker, we derive and analyze the uncertainties for launching successful FDIAs along with their upper bounds. To effectively defend against an FDIA, we propose a robust detector that checks the measurement statistical consistency using a subset of secure PMU measurements. We first show that if these secure PMU measurements are free of bad data while making the system observable, the FDIA is detectable. We then show that detectability is also ensured if these conditions are relaxed while using alternative redundant measurements from short-term nodal synchrophasor predictions together with the robust Huber M-estimator. Numerical simulation results on the IEEE 30-bus and 118-bus systems demonstrate the effectiveness and robustness of the proposed method even the secure measurements contain noise and bad data. [ABSTRACT FROM AUTHOR]

Many power systems applications such as power flow and short-circuit analysis require very large sparse matrix computations. With the increase in reliance on our electric infrastructure, power systems are continually growing in size, creating greater computational complexity in solving these large linear systems within reasonable time. For sparse matrix applications, it is desirable to have an algorithm with low runtime complexity in terms of the number of nonzeros in the matrix. There have been several recent advances in computational methods in other fields that, if applied to power system, could make real-time dynamic simulation a reality. Much work has been done for specific types of these problems where the system is symmetric and diagonally dominant, similar to the form of power system matrices. This paper details an expansion on the current work in fast linear solvers to develop power system specific methods that show potential for accurate solutions in $O(m \log ^2 n)$ run times, where $n$ represents the number of nodes and $m$ represents the number of nonzeros in the power system matrix. This paper presents the simulation validation of a recently developed recursively solved iterative chain method for sparse matrices using a low stretch spanning tree preconditioner. [ABSTRACT FROM PUBLISHER]

Future power systems with high penetrations of variable renewables will require increased levels of flexibility from generation and demand-side sources in order to maintain secure and stable operation. One potential flexibility source is large-scale energy storage, which can provide a variety of ancillary services across multiple time scales. In order for appropriate levels of investment to take place, and in order for existing assets to be utilized optimally, it is essential that market signals are present which encourage suitable levels of flexibility, either from storage or alternative sources. Suboptimal storage plant dispatch due to uncertainty and inefficient market incentives are represented as operational constraints on the storage plant, and the impact of these inefficiencies are highlighted. Thus, changes required in operational practices for storage plant at different installed wind capacity levels, and the challenges that private storage plant operators will face in generating appropriate bids in a market environment at high variable renewable penetrations are explored. The impacts on system generating costs and storage profits are explored under different plant operating assumptions. [ABSTRACT FROM PUBLISHER]

The motivation and training of a proficient and diverse pool of power engineers, system operators, and policymakers is an important challenge for the electric industry. Power system experts are increasingly in demand globally to facilitate transitions to more environmentally friendly energy systems. More generally, citizens with a basic understanding of load balancing and renewable energy sources are more effective partners in increasingly complex power economies and political decisions. To address the need for an accessible general introduction to power systems, we are developing Griddle, an educational video game that introduces secondary school students to the basics of power system design, scheduling, and operation. We describe the design of Griddle's gameplay and underlying simulation, improvements made in response to user feedback, alignment with emerging teaching standards, and a high school classroom evaluation (n = 178) of Griddle's significant transformative impact, with the goal of validating the game-based learning approach and sharing “lessons learned” with designers of related tools. We find that Griddle is effective at engaging students and presents evidence that it helps students integrate key concepts, and we identify areas where further development and study are needed. [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]

The small-signal stability analysis of power systems concerns the critical modes as well as the modes associated with a physical meaning, e.g., the interarea oscillation modes for weakly connected systems and the modes sensitive to a particular parameter. As the order of the power-system state matrix increases, it becomes more difficult to determine these modes. In this paper, a method is proposed to compute the interarea oscillation modes of large-scale power systems. The deviation in the active power of the transmission section is selected to identify the interarea oscillation modes. Then, the two-sided Jacobi-Davidson method combined with this selection is employed to compute these modes. Participation factors are used to separate the electromechanical oscillation modes. Numerical tests show that the proposed method is valid and efficient. [ABSTRACT FROM PUBLISHER]

This paper presents a fully analog demonstrator based on power system emulation for high-speed power system stability analysis. A benchmark using a fixed two-machine topology has been implemented. The characteristics of the emulated components (i.e., generators and transmission lines) are reprogrammable and short circuits can be emulated at different distances from the generator. This first realization is limited to transient stability analysis, as the main focus during design was put on computation speed. Indeed, the emulated phenomena are 10\thinspace000 times faster than real time. Moreover the authors aim to emphasize that such highly dedicated computation architectures are not only competitive in terms of speed, but also in terms of modularity. [ABSTRACT FROM PUBLISHER]

This paper presents an ultra-high speed hardware platform dedicated to power system dynamic (small signal) and transient (large signal) stability. It is based on an intrinsic parallel architecture which contains hybrid mixed-signal (analog and digital) circuits. For a given model, this architecture overcomes the speed of the numerical simulators by means of the so-called emulation approach. Indeed, the emulation speed does not depend on the power system size. This approach is nevertheless not competing against high-performance numerical simulators in term of accuracy and model complexity. It targets to complement the numerical simulators with the advantage of speed, portability, low cost and autonomous functioning. The proof of concept is a flexible and modular 96-node hardware platform. It is based on a reconfigurable array of power system buses called Field Programmable Power Network System (FPPNS). Details on this hardware are given. Two benchmark topologies with, respectively, 17 nodes and 57 nodes are provided. Comparisons with a digital simulator are done in terms of speed and accuracy. The calibration of the system is explained and different applications are proposed and discussed. The promising results of this hardware platform show that the design of a fully integrated solution containing hundreds of power system buses can be achieved in order to provide a low cost solution. [ABSTRACT FROM PUBLISHER]

This paper presents a mixed-integer linear programming (MILP) reformulation of the thermal unit commitment (UC) problem. The proposed formulation is simultaneously tight and compact. The tighter characteristic reduces the search space and the more compact characteristic increases the searching speed with which solvers explore that reduced space. Therefore, as a natural consequence, the proposed formulation significantly reduces the computational burden in comparison with analogous MILP-based UC formulations. We provide computational results comparing the proposed formulation with two others which have been recognized as computationally efficient in the literature. The experiments were carried out on 40 different power system mixes and sizes, running from 28 to 1870 generating units. [ABSTRACT FROM PUBLISHER]

This paper proposes two methods to speed up the demanding time-domain simulations of large power system models. First, the sparse linear system to solve at each Newton iteration is decomposed according to its bordered block diagonal structure in order to solve only those parts that need to be solved and update only submatrices of the Jacobian that need to be updated. This brings computational savings without degradation of accuracy. Next, the Jacobian structure is further exploited to localize the system response, i.e., involve only the components identified as active, with an acceptable and controllable decrease in accuracy. The accuracy and computational savings are assessed on a large-scale test system. [ABSTRACT FROM PUBLISHER]

Electromagnetic Transients Program (EMTP) is widely used in power system dynamics studies. However, in most cases EMTP is found inadequate for dealing with the realistic size power systems due to the small time step resulting in relatively slow simulation speeds. To accelerate the EMTP simulations of power system dynamics, a novel frequency-adaptive methodology is proposed. In this method, a new transformation is presented. The properties of the transformation and the numerical solutions based on the transformation are discussed. The component models obtained by discretizing the differential equations at the branch level are also given which are convenient for EMTP implementation. The proposed method allows using large time steps without sacrificing accuracy, which greatly improves the simulation speed. To validate the proposed methodology, a general program has been developed. Furthermore, various case studies substantiate the claims and demonstrate the application of the method. [ABSTRACT FROM PUBLISHER]

Time-domain scheduling simulation is the most effective tool for predicting the operational costs in wind-integrated power systems, because it can represent the inter-temporal constraints that limit the balancing actions of the thermal plant, storage, and demand-side measures. High wind penetrations demand just-in-time commitment decisions that reflect the uncertainties in the wind infeed, so that it is desirable to generate the scheduling decisions using stochastic unit commitment (SUC) with rolling planning. However, the computational burden can make such methods impractical in long simulations. We present an efficient formulation of the SUC problem that is designed for use in scheduling simulations of single-bus power systems. Unlike traditional SUC techniques, the proposed formulation uses a quantile-based scenario tree structure that avoids the need for exogenous operating reserves. We compare the performance of various tree topologies in year-long simulations of a large system. Simple quantile-based trees give statistically significant cost improvements over fixed-quantile deterministic methods and compare favorably with trees based on Monte Carlo-generated scenarios. [ABSTRACT FROM PUBLISHER]

In power system reconfiguration, the status (ON/OFF) of switches are optimized such that maximum power is delivered to loads after the occurrence of a fault. The optimized reconfiguration is achieved by prioritizing power delivered to vital loads over semi-vital and nonvital loads. The formulation presented in this paper considers a new balanced hybrid (AC and DC) shipboard power system (SPS). Analysis of the nonconvex reconfiguration formulation is done by an appropriate nonconvex solver and by convex approximation. Unlike the nonconvex solution that is based on branch-and-bound methods, convex approximation significantly reduces complexity. It is shown that for the hybrid SPS reconfiguration problem, low complexity convex approximations are effective in finding optimal solutions. Cumulative distribution function (CDF) of the power delivered to loads is presented to showcase the system robustness against random fault scenarios. A combined objective of maximizing power delivery and minimizing the number of switching actions is included in the analysis. Tradeoff between power delivered and number of switching operations after reconfiguration has been discussed at steady state. A separate analysis is also included to observe the intermediate dynamic switch states while the reconfiguration is in progress to capture the trade-off more prominently. [ABSTRACT FROM PUBLISHER]

Classic linear models of fossil fired steam units have been used for decades in power system dynamic analyses. The effect of main steam pressure is often ignored or the more complex models of boiler and its control systems should be adopted in the simulations. Moreover, the variations of turbine enthalpy drop are not considered in those models, which may result in a great deviation of output power during a transient period after a disturbance. A new model with little increase in complexity is built in this paper to improve the accuracy of classic models, where the boiler effect and the enthalpy droop variations are considered by a simplified boiler model and replacements of three turbine model parameters. Test data of a 600-MW coal fired generation unit are adopted to compare the performance of the proposed model with that of a classic one. Higher accuracy of the new model are observed and it is proposed to replace the classic models in power system dynamic analyses. [ABSTRACT FROM PUBLISHER]

Grid modernization strategies often focus on replacing aging distribution control equipment with state-of-the-art devices capable of remote monitoring, communication, and control. However, wholesale replacement of the existing distribution infrastructure may not be practical or economical. Additionally, even with improved capabilities, “smart” devices may still be ignorant of changes in circuit topology. This paper presents a model-based distribution control scheme that is independent of circuit topology and integrates legacy and modern control equipment. Simulation results indicate the proposed method can improve circuit performance under both normal and abnormal conditions. [ABSTRACT FROM PUBLISHER]

This paper proposes a method for online identification of modes corresponding to low-frequency oscillations in a power system. The proposed method has considered the effect of colored Gaussian noise produced due to filters used for signal preprocessing. In order to mitigate the effect of colored Gaussian noise, the paper first proposes a modified total least square estimation of signal parameters via rotational invariance techniques (TLS-ESPRIT) that utilizes first and second rotational shift invariance properties of the signal. In the next step, the modified TLS-ESPRIT utilizes the signal transformed in an orthogonal basis. The proposed method has been compared with the improved Prony, the TLS-ESPRIT and the fourth-order cumulant-based TLS-ESPRIT (4CB-TLS-ESPRIT) using a test signal for identification of the modes at different noise levels. Robustness of the proposed method is established in the presence of colored Gaussian noise through Monte Carlo simulations. Estimation of modes for a two-area power system, using the proposed method, is carried out in the present work. Comparison of the proposed method with other methods is also performed on real-time probing test data obtained from the Western Electricity Coordinating Council (WECC) network. [ABSTRACT FROM PUBLISHER]

This paper compares four different methods for determining the electrical damping of a power system seen from one generator as a function of frequency. This information is useful when the risk for subsynchronous resonance (SSR) in the system is evaluated. The study compares one frequency scanning method which is implemented in a time-domain digital simulation program with three methods of different complexity based on analytical calculations. The time-domain simulation method is easily implemented with a detailed model of the power system including complex load and generator models, whereas the analytical methods are based on simpler models of the power system. The computational effort is much larger for the time-domain method than for the analytical methods. In the study, all methods were used to determine the damping characteristics of a four-machine power system in different configurations. The study shows that fast analytical methods may provide results which closely agree with the detailed method of time-domain simulation. However, the study also shows that the level of accuracy in the analytical model is very important. [ABSTRACT FROM AUTHOR]

This paper presents a model for the simulation of the optimal medium-term operation of a hydrothermal system. System stochastic parameters are modeled by Monte Carlo scenarios, which are solved on distributed processors. For each scenario a yearly hydrothermal scheduling (HTS) problem with hourly time resolution is formulated and solved as a large mixed integer linear program (MILP). HTS modeling includes unit commitment, start-up costs and minimum up/down time constraints. The model is applied to the Greek Power System, comprising 29 thermal units and 13 hydroplants; 100 simulation scenarios are generated and solved on 18 distributed processors. Test results include both medium-term objectives, such as reservoir water management, and short-term decisions such thermal unit start-up decisions. [ABSTRACT FROM AUTHOR]

This paper presents an overview of a complex approach to optimal planning of ancillary services ensuring reliable power balancing of a transmission system in liberalized market conditions that is performed by a transmission system operator (TSO). To accomplish this goal analytical computations together with optimizations and Monte Carlo simulations are performed. The designed decision support tool serves the TSO not only for a year-ahead planning task but also for carrying out various analyses and sensitivity tests, e.g., how costs of ancillary services are related to the level of reliability. Attention is also paid to mutual substitutability of ancillary services and its impact on transmission system operation and corresponding expenses. [ABSTRACT FROM AUTHOR]

In isolated power systems, frequency stability is traditionally considered to be assured by maintaining sufficient spinning reserve that is usually equal to the largest generation output of all the units in operation. However, the system security depends on the spinning reserve allocation to the units in operation and the provision of adequate emergency or fast reserve that need be available in the first crucial seconds after a loss of generation event. The system emergency reserve is usually much lower than that expected if only the unit droops are taken into account. Also, the generating units can be overloaded for a short time period and this capability can contribute to a faster frequency restoration. This paper presents an improved speed governor model that utilizes the short time overloading capability of the generating units. The efficient computational method described in the paper for the optimal spinning reserve allocation in isolated power systems was developed by taking into account a composite security criterion in the most economic way. Furthermore, a statistical analysis is presented in order to investigate the contribution of spinning reserve to the short-term system security. In the paper the developed method is applied to a typical isolated power system and it demonstrates its advantages. [ABSTRACT FROM AUTHOR]

Parameters of power system models, in particular load models, are seldom known exactly, yet dynamic security assessment relies upon simulation of those uncertain models. This paper proposes a computationally feasible approach to assessing the influence of uncertainty in simulations of power system dynamic behavior. It is shown that trajectory sensitivities can be used to generate accurate first-order approximations of trajectories that arise from perturbed parameter sets. The computational cost of obtaining the sensitivities and perturbed trajectories is minimal. The mathematical structure of the trajectory approximations allows the effects of uncertainty to be quantified and visualized using worst-case analysis and probabilistic approaches. [ABSTRACT FROM AUTHOR]

A new simultaneous-solution approach named the sub-tree reduction method is proposed for fast dynamic simulation of large-scale interconnected power system. In this method, a power system is represented by a component tree; the correction factors in Newton iteration of system simulation are calculated by a tree-traversing procedure called forward reduction and backward evaluation. This method can remarkably reduce computation burden of the Newton-type simultaneous-solution approach with greater programming flexibility. Case studies on two power systems verify the correctness and efficiency of this method. [ABSTRACT FROM AUTHOR]

This paper explores the use of a new technique, the probabilistic collocation method (PCM), to enable the evaluation of uncertainty in power system simulations. The PCM allows the uncertainty in transient behavior of power systems to be studied using only a handful of simulations. The relevant theory is outlined here and simple examples are used to illustrate the application of PCM In a power systems setting. In addition, an Index for Identifications of key uncertain parameters, as well as an example with a more realistic power system, are presented. [ABSTRACT FROM AUTHOR]