Optimal thermal generating unit commitment of large power system: a novel approach

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.

Using suitable solution techniques to the unit commitment (UC) and economic load dispatch (ELD) problems play major role on finding an optimal power scheduling in electrical power system. The UC and ELD problems are to decide when and which generating units to commit and decommit, in order to minimize the total fuel cost over specified period subject to a large number of difficult constraints. Lagrangian relaxation (LR) has been widely used to solve UC and ELD. Recently bundling method (BM) has appeared to be one of the best multipliers updated techniques for LR. This method has promising and the fastest convergence characteristics for UC and ELD problems. For that reason, this paper is to solve the UC and ELD problems via LR, BM and interior point method. This paper explores also the best possible way of updating Lagrangian multipliers with minimum computation time using fast programming techniques.

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.

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 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.

This paper presents a Lagrangian relaxation based technique for solving the power system thermal unit commitment problem. As a general approach, Lagrangian relaxation has proven to be an efficient method of solving the thermal unit commitment problem. The specific technique described in this paper focuses on finding a feasible commitment, then attempting to improve on the optimality of the solution. A new method for processing ramp rate constraints is also introduced. The algorithm has been implemented on a large scale power system and results are shown using actual power system data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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.

One of the most important tasks for day-ahead electricity markets is to do the Security-Constrained Unit Commitment (SCUC). SCUC generally combines the needs of unit commitment, network limits, and regulation in a constrained optimization problem for different time frames. Different electricity markets utilize different SCUC methods. The main goal of this work is to introduce SCUC operation experience in several electricity markets and summarize significant issues in the current SCUC problem. For instance, in addition to traditional constraints in the SCUC process, this work also investigates the effect of frequency stability, transmission switching, or optimal generation scheduling on the SCUC methods. Additionally, the integration of renewable energy also bring the impact to the traditional SCUC methods. The above mentioned issues concerning the SCUC topic will be studied herein.

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.

This paper presents a Lagrangian relaxation based technique for solving the power system thermal unit commitment problem. The specific technique described in this paper focuses on finding a feasible commitment, then attempting to improve on the optimality of the solution. A new method for processing ramp rate constraints is also introduced. The algorithm has been implemented on a large scale power system. >

Deterministic methods to evaluate unit commitment and spinning reserve requirements cannot explicitly recognise the stochastic nature of a power system. Probabilistic techniques can, however, be used to incorporate a wide range of stochastic system parameters. The usual techniques of probabilistic unit commitment in an interconnected power system consider the tie-line constraints but not the transmission facilities within the systems. In a real power system, the transmission facilities within the systems have limits and do fail. Units committed from only probabilistic generation studies, therefore, provide optimistic values. In the paper, the usual techniques of unit commitment are extended to calculate a risk value from a composite system point of view. The effect on the risk value of rapid start and hot reserve units are considered.

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...

Renewable power systems dynamic security using a new coordination of frequency control strategy based on virtual synchronous generator and digital frequency protection

Short term voltage stability poses a significant threat to system stability and reliability. This paper applies dynamic VAr injection to ensure short term voltage stability following a large disturbance in a power system with high concentration of induction motor loads. Decelerating and stalling of induction motor loads is considered to be the major cause of fault induced delayed voltage recovery (FIDVR) and short term voltage stability. If system dynamics are not taken into account properly, the proposed control solution may be an expensive over design or an under design that is not capable of eliminating FIDVR problems completely. In this work, the optimal amount and locations for installing dynamic reactive resources are found by control vector parameterization (CVP), a dynamic optimization approach. The efficiency and effectiveness of this approach is improved by utilizing results from trajectory sensitivity analysis, singular value decomposition and linear programming optimization. Dynamic optimization based on CVP approach is tested in an IEEE 162-bus system and a realistic large scale utility power system.

Unit commitment, one of the most critical tasks in electric power system operations, faces new challenges as the supply and demand uncertainty increases dramatically due to the integration of variable generation resources such as wind power and price responsive demand. To meet these challenges, we propose a two-stage adaptive robust unit commitment model for the security constrained unit commitment problem in the presence of nodal net injection uncertainty. Compared to the conventional stochastic programming approach, the proposed model is more practical in that it only requires a deterministic uncertainty set, rather than a hard-to-obtain probability distribution on the uncertain data. The unit commitment solutions of the proposed model are robust against all possible realizations of the modeled uncertainty. We develop a practical solution methodology based on a combination of Benders decomposition type algorithm and the outer approximation technique. We present an extensive numerical study on the real-world large scale power system operated by the ISO New England. Computational results demonstrate the economic and operational advantages of our model over the traditional reserve adjustment approach.