Environmentally-Induced Voltage Limitations in Large Space Power Systems

Modern electric power systems are large and complicated, and, in many regions, the generation and transmission systems are operating near their limits. Eigenanalysis is one of the tools used to analyze the behavior of these systems. Standard eigenvalue methods require that simplified models be used for these analyses; however, these simplified models do not adequately model all of the characteristics of large power systems. Thus, new eigenanalysis methods that can analyze detailed power system models are required. The primary objectives of the work described in this report were I) to determine the availability of eigenanalysis algorithms that are better than methods currently being applied and that could be used an large power systems and 2) to determine if vector supercomputers could be used to significantly increase the size of power systems that can be analyzed by a standard power system eigenanalysis code. At the request of the Bonneville Power Administration, the Pacific Northwest Laboratory (PNL) conducted a literature review of methods currently used for the eigenanalysis of large electric power systems, as well as of general eigenanalysis algorithms that are applicable to large power systems. PNL found that a number of methods are currently being used for the this purpose, and all seem to work fairly well. Furthermore, most of the general eigenanalysis techniques that are applicable to power systems have been tried on these systems, and most seem to work fairly well. One of these techniques, a variation of the Arnoldi method, has been incorporated into a standard power system eigenanalysis package. Overall, it appears that the general purpose eigenanalysis methods are more versatile than most of the other methods that have been used for power systems eigenanalysis. In addition, they are generally easier to use. For some problems, however, it appears that some of the other eigenanalysis methods may be better. Power systems eigenanalysis requires the computation of eigenvalues of nonsymmetric matrices. Such computations are fairly difficult, however, and they constitute an area of active research. Thus, research in this area should be closely monitored, and, as new methods become available, they should be tested on large power systems. PNL also investigated the use of vector supercomputers to enlarge the size of power systems that can be analyzed by MASS, a standard power system eigenanalysis code. MASS was converted to run on a Cray supercomputer. On a conventional computer, MASS is limited to power system problems with about 500 states because of computer time constraints. Running MASS on a Cray X-MP EA/232, however, PNL found that a problem with about 2200 states could be solved in about 26 minutes. Furthermore, by moving to a larger Cray, it should be possible to use MASS to analyze power systems with 5,000 to 10,000 states. Problems with 5,000 states would probably take about 5 Cray hours, while a problem with 10,000 states would probably take about 43 Cray hours, though the actual execution times will depend on the type of Cray used. Problems requiring 5 Cray hours are not uncommon. Problems requiring 43 Cray hours, however, would be fairly expensive. Thus, power systems with about 5000 states probably represent an upper limit on the size of problems that one would want to routinely solve using a Cray version of MASS.

The present work is based on developing a control strategy to mitigate the impact of reduced inertia due to significant DFIG penetration in a large power system. The paper aims to design a supplementary control for the DFIG power converters such that the effective inertia contributed by these wind generators to the system is increased. The paper also proposes the idea of adjusting pitch compensation and maximum active power order to the converter in order to improve inertial response during the transient with response to drop in grid frequency. Results obtained on a large realistic power system indicate that the frequency nadir following a large power impact in the form of generators dropping out is effectively improved with the proposed control strategy. The proposed control is also validated against the sudden wind speed change in the form of wind gust downs and wind ramp downs occurring in conjunction with the generators dropping out. A beneficial impact in terms of damping power system oscillations is also observed, which is validated by eigenvalue analysis. The affected mode is then excited with a large disturbance in time domain. The damping improvement observed in time domain and subsequent Prony analysis support the result obtained from eigenvalue analysis.

This paper presents a novel fast frequency response and power oscillation damping control by large-scale PV plants controlled as STATCOM, termed PV-STATCOM, to simultaneously enhance frequency regulation and small signal stability of power systems. Frequency deviations typically occur together with power oscillations in large power systems. The proposed controller comprises: first, power oscillation damping controller based on reactive power modulation and second, fast frequency response controller based on real power modulation, both of which are applied to the plant level controller of PV-STATCOMs. The proposed composite control is shown to successfully reduce frequency deviations, damp power oscillations, and provide voltage regulation both during over-frequency and under-frequency events. The proposed smart inverter control makes effective utilization of the PV inverter capacity and available solar power. For large power flows, the proposed control is shown to be superior than the conventional droop control recommended by North American Electric Reliability Corporation for generating plants. MATLAB/Simulink-based simulations are conducted on two-area power system using generic PV plant dynamic models developed by Western Electricity Coordinating Council, for a wide range of system operating conditions. Such grid support functionality is expected to bring new revenue making opportunities for PV solar farms.

This paper presents transient stability assessment of a large actual power system using the probabilistic neural network (PNN) with enhanced feature selection and extraction method. The investigated large power system is divided into five smaller areas depending on the coherency of the areas when subjected to disturbances. This is to reduce the amount of data sets collected for the respective areas. Transient stability of the power system is first determined based on the generator relative rotor angles obtained from time domain simulations carried out by considering three phase faults at different loading conditions. The data collected from the time domain simulations are then used as inputs to the PNN. An enhanced feature selection and extraction methods are then incorporated to reduce the input features to the PNN which is used as a classifier to determine whether the power system is stable or unstable. It can be concluded that the PNN with enhanced feature selection and extraction methods reduces the time taken to train the PNN without affecting the accuracy of the classification results.

A power system is composed of various components such as generators, transformers, transmission lines, switching devices and loads. They have their mathematical model and graphical representation. Sometimes, a power system’s change of topology occurs due to events like short circuits, lightning striking a transformer, or a reconfiguration of the transmission system. In this thesis, a new way of simulating large scale power systems is presented from the modeling point of view. In the literature, a lot of modeling methods and mathematical tools are available to tackle this subject. However, this thesis mainly focuses on the time domain simulation of large scale power systems - and in particular, transients which appear after a change of topology. A change of topology in electrical networks impact time domain simulations on two levels. The first impact is that it is necessary to update or re-compute the set of equations. The computation time of this action on the topology can be significant - especially for large scale power systems. The second impact of this change of topology is the transient that will occur. Usually, this change will impose to numerically compute fast oscillations in currents and voltages until they reach a new steady state...

This paper presents a new efficient solution approach for solving the unit commitment schedule of thermal generating units of a realistic large scale power system. The approach is based on the equivalencing like concept of network reduction which reduces the number of units in the large power system to the lowest possible number according to their fuel/generation cost characteristics. The reduced system is then solved and from that overall solution to the original unit commitment problem of the entire system is obtained. Test results for real-life systems of up to 79 units and comparisons with results obtained using Lagrangian relaxation and truncated dynamic programming (DP-TC) are also reported.

The quality of power system operating need to assess maturity of small oscillation stability issues of regional power grid thoroughly, analysis level of operating, controller installation allocating and parameter optimization scheme from different develop stage of regional power grid accurately. The assessment scheme is based on damping torque analysis of real large scale power system. Small oscillation stability is to be evaluated through the mechanism of damping torque analysis with automatic voltage regulator and other power system stabilizers. By analyzing the characteristic of the link between damping torque provided or transferred through each generator and the oscillation mode detected in the power system, the maturity indice has been established. This indice may cover the information of the contribution of controllers towards the power system and the dispatching within each generator in power system. Practical application effects in a real large scale power grid indicates this assessment can thoroughly describe the action of control elements in the power grid, help to depict the whole picture of impact applying power system controllers. A novel maturity evaluation of small oscillation in power grid is presented.

This paper proposes approaches to estimate the dominant swing mode sensitivity by utilizing Wide Area Measurements. The proposed methods are suitable to situations where availability of information of system model and operating condition is limited to a subsystem in which the control action resides. Modal frequency and mode shape of the dominant swing mode are estimated from a Wide Area Measurement System (WAMS) based mode identification technique. This information is used along with the subsystem model for estimation of eigenvalue sensitivity. Such a scenario is indeed faced in large interconnected power systems, where effect of a control action in the subsystem on a dominant inter-area mode needs to be estimated before actual implementation. Analytical formulations of sensitivity are derived using special modal characteristics (identified based on simplified system models) and a hybrid representation of the system, in which the subsystem is treated as a controller in a feedback loop to the rest of the system. Case studies with detailed models of two area four machine and IEEE 16 machine 68 bus system validate these formulations.

Power System study and analyses are important parts of power system engineering. This innovative concept deals with a 132 kV Grid simulation in Electrical Transient Analyzer Program (ETAP). Existing power distribution system in Pakistan consists of approximately 6000 11 kV feeders, which are mainly analyzed by software FDR-ANA (Feeder Analyses). This software does not have capability to provide comprehensive analyses for integrated power system which is essential. This research paper focused on the detailed analyses and monitoring by using the most modern software ETAP, which performs numerical calculations of large integrated power system with fabulous speed besides, generating output reports. In a developing country like Pakistan it is first time that Off-line monitoring is made which includes current flowing in every branch, power factor, active and reactive power flow, harmonic distortion etc. of large power system. Based upon the recorded data obtained from an actual 132 kV grid which has been implemented in ETAP for Off-line monitoring and analyses.

This paper provides an integrated algorithm to identify a cutset for a large power system for the application of a slow coherency based controlled islanding scheme. Controlled islanding is employed as a corrective measure of last resort to prevent cascading outages caused by large disturbances. The large scale power system is represented as a graph and a simplification algorithm is used to reduce the complexity of the system. Generators belonging to the same slowly coherent group are collapsed into a dummy node, and a graph partition library is used to split the graph into a given number of parts. Some extra islands formed by the partition library are merged into their adjacent large islands and the original cutset of the actual power system is recovered from the highly simplified graph. A software package was developed to test the efficiency of the algorithm, and dynamic simulations were run on the WECC system to verify the effectiveness of the cutset obtained. The WECC system has more than 15 000 buses and 2300 generators. Detailed steps to develop an islanding strategy for a specified contingency for a large system are described in this paper.

Over the last few decades several innovative ideas have been explored in the energy storage areas, ranging in size, capacity, design complexity, and targeted applications. Some of them are designed for large scale power system applications, others for smallor medium-scale renewable energy or hybrid power systems, while the others are designed to perform short-term energy storage ride through for critical infrastructure (communication systems, hospitals, military facilities, etc.). Energy storage has become an enabling technology for renewable energy applications, grid integration and enhancing power quality and stability in the power transmission and distribution, having a great potential to improve power grid quality and stability and to provide an alternative to fossil fuel-based energy generation. The major constraints for renewable energy penetration are the availability, intermittency, and variability, which can be addressed through energy storage. The energy storage choice depends on specific usage requirements, often incorporating several energy storage systems in order to increase system reliability, capacity, and supply security. In the electric power system, the renewable energy promise lies in its potential to increase grid efficiency, reliability, or in optimizing power flows and supporting variable power supplies. The parameters used in comparisons of various energy storage technologies include efficiency, energy capacity and density, run time, costs, system's response time, lifetime in years and cycles, self-discharge, and maturity of each energy storage technology. The most common energy storage technologies include compressed air, pumped hydro, batteries, fuel cells, flywheels, and super-capacitors. The last four are suitable for the medium scale applications. The chapter discussed energy storage technologies and gives an up to date comparative summary of their performances. After completing this chapter, the readers are able to understand the role, importance, configurations and topologies of energy storage systems, operation principles, characteristics, performances, and operation of major energy storage systems used in power systems, buildings, and industrial facilities. Another benefit is that readers are able to understand the critical role and necessity of energy storage systems in power and renewable energy systems, the differences between large-, mediumand small-scale energy storage systems, and how a system is selected on specific applications based on system characteristics and performances. Major energy storage technologies discussed in this chapter are compressed air energy storage, pumped hydropower storage systems, batteries, flywheels, hydrogen energy storage, fuel cells, supercapacitors, and superconducting energy storage systems. Thermal energy storage systems are covered in detail in the next chapter. This chapter provides comprehensive reviews of the energy storage technologies and gives an up to date comparative summary of their performances, characteristics, and applications.

With the deepening of national efforts toward green energy transformation, the power system is evolving into one characterized by “double high”—a high proportion of new energy integration and a high level of power electronic systems. This results in a more complex system topology, necessitating improvements in various prevention and control measures. Traditional model-based methods for locating power oscillation disturbance sources in power systems are no longer sufficient to meet the operational demands of modern power systems. With the rapid development of wide-area measurement systems (WAMS), there is growing interest in disturbance source localization using system response data. System dynamics provide a wealth of easily extractable data that can accurately reflect the power system’s behavior under normal conditions. This paper proposes a numerical method for locating disturbance sources, combining energy functions with normal distribution identification, based on power oscillation mechanisms and system response data. The method identifies potential disturbance sources, including small random load fluctuations and large forced power oscillations. The innovation lies in the introduction of a 3 Sigma value criterion to pinpoint the disturbance source location, addressing the limitations of traditional energy function methods that require manual intervention. By quantifying the localization of power oscillation disturbance sources, this method significantly improves both efficiency and accuracy.

This paper deals with some improvements of the Waveform Relaxation method for large power systems transient stability analysis. In this context, the classical Waveform Relaxation iterative method is usually not efficient due to its slow convergence. The convergence speed depends on a lot of parameters such as the model, the disturbance nature, the number of subdomains created by the decomposition, the initialization, the time domain length, etc. In order to make the method competitive with usual and mastered sequential methods, some important points are here investigated such as an initialization of nonlinear integrations with linear solutions and a preconditioning technique to deal with a large number of subsystems. These innovative methods can bring interesting speedups for large power systems as illustrated in the presented numerical experiments on a large and realistic European power system.

As there is a huge growth in the renewable energy sources, the solar farm based power plants are getting more popular among all researchers. In the large power systems, the sudden variations in the load requirements are more common. The variations in the load lowers the power quality in the power system. This paper concentrates on the power quality improvement in 100kW solar based standalone power system. In order to improve the power quality in the large power systems, the FACTS devices such as Static Synchronous Series Compensator (SSSC), Static Shunt Compensator (STATCOM), Unified Power Flow Controller (UPFC) etc., are used. Here, the STATCOM is implemented to improve the voltage profile of the power system under varying load conditions. The Distribution Static Compensator (D-STATCOM) balances the deficiency of reactive power by maintaining the voltage profile in the system.

Nonlinearity of power system is always one of the difficulties when dealing with dynamic simulation of power systems. Solving differential-algebraic equations representing power systems are difficult without losing nonlinearity, especially for large power systems. This thesis shows an alternative method to solve nonlinear dynamical power system by producing a purely differential representation of the power systems. This new representation converts the algebraic equations to differential equations in order to have an absolute differential system. By using Runge-Kutta algorithm to solve this differential system, the results of the power system simulations are compared to trapezoidal integration algorithm commonly used to solve the differential-algebraic equations. In this thesis, IEEE 14-bus system and IEEE 118-bus system are tested with both classical generator model generator model and two-axis generator model in MATLAB. The proposed algorithm shows significantly faster convergence comparted to trapezoidal integration method in larger power systems. It is a great improvement to shorten the simulation time in while keeping the same accuracy in large power systems.