Dynamic equivalence by an optimal strategy
TL;DR: A robust dynamic equivalence is proposed to reduce the computational burden and time consuming that the transient stability studies of large power systems represent, based on a multi-objective optimal formulation solved by a genetic algorithm.
About: This article is published in Electric Power Systems Research.The article was published on 2012-03-01. It has received 20 citations till now. The article focuses on the topics: Dynamic and formal equivalence & Electric power system.
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01 Feb 2014
TL;DR: This paper summarizes major results of the work of the CIGRE working group on load modeling of new types of load including renewables using measurement data and historical data after two years' activities.
123 citations
16 Jun 2013
TL;DR: In this paper, a survey of the existing approaches is presented and a critical overview is provided regarding their application to active distribution network cells and micro-grids, as well as technical requirements are identified and recommendations are provided.
Abstract: Large deployment of distributed generation into distribution systems brings new challenges regarding the shift from the passive to the active control paradigm. These challenges have been extended to the field of dynamic equivalence. Developing effective reduced order models for active distribution network cells for dynamic and stability studies require a careful evaluation of the techniques that have been used in conventional power systems. Thus, a survey of the existing approaches is presented in this paper. Also a critical overview is provided regarding their application to active distribution network cells and microgrids. Technical requirements are identified and recommendations are provided.
32 citations
Cites background from "Dynamic equivalence by an optimal s..."
...Typical approaches to derive aggregated models of power systems rely on system reduction and measurement based approaches [6], [7]....
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01 Jan 2014
TL;DR: In this article, the authors discuss the management of distribution networks with an increased microgrid penetration, that is, corresponding to a situation where most of the low voltage (LV) networks turn into active microgrids.
Abstract: This chapter discusses the management of distribution networks with an increased microgrid penetration, that is, corresponding to a situation where most of the low voltage (LV) networks turn into active microgrids. It is therefore assumed that the microgrid concept is extended, leading to the development of a new concept - the multi-microgrid. A full exploitation of this concept involves the design of a new control architecture as well as the development of new management tools or the adaptation of existing distribution management systems (DMS) tools. Bearing in mind the relevance of some of the functionalities available at the central autonomous management controller (CAMC) level and the need to perform some of the key studies, the following topics are addressed: coordinated voltage/var support for normal operation; coordinated frequency control for islanded operation; local black start - restoration of the MV grid following a blackout; and definition of dynamic equivalents for microgrids.
25 citations
TL;DR: In this article, a non-linear area-based equivalent model of power systems to express the inter-area oscillations using synchronised phasor measurements is proposed, where the generators that remain coherent for interarea disturbances over a wide range of operating conditions define the areas, and the reduced model is obtained by representing each area by an equivalent machine.
Abstract: A new approach is proposed for obtaining a non-linear area-based equivalent model of power systems to express the inter-area oscillations using synchronised phasor measurements. The generators that remain coherent for inter-area disturbances over a wide range of operating conditions define the areas, and the reduced model is obtained by representing each area by an equivalent machine. The parameters of the reduced system are identified by processing the obtained measurements, and a non-linear Kalman estimator is then designed for the estimation of equivalent area angles and frequencies. The simulation of the approach on a two-area system shows substantial reduction of non-inter-area modes in the estimated angles. The proposed methods are also applied to a ten-machine system to illustrate the feasibility of the approach on larger and meshed networks. © The Institution of Engineering and Technology 2014.
18 citations
TL;DR: In this article, the authors proposed a new approach for state estimation of angles and frequencies of equivalent areas in large power systems with synchronized phasor measurement units, where generators are aggregated and system reduction is performed in each area of interconnected power systems.
16 citations
References
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TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Abstract: Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN/sup 3/) computational complexity (where M is the number of objectives and N is the population size); (2) their non-elitism approach; and (3) the need to specify a sharing parameter. In this paper, we suggest a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN/sup 2/) computational complexity is presented. Also, a selection operator is presented that creates a mating pool by combining the parent and offspring populations and selecting the best N solutions (with respect to fitness and spread). Simulation results on difficult test problems show that NSGA-II is able, for most problems, to find a much better spread of solutions and better convergence near the true Pareto-optimal front compared to the Pareto-archived evolution strategy and the strength-Pareto evolutionary algorithm - two other elitist MOEAs that pay special attention to creating a diverse Pareto-optimal front. Moreover, we modify the definition of dominance in order to solve constrained multi-objective problems efficiently. Simulation results of the constrained NSGA-II on a number of test problems, including a five-objective, seven-constraint nonlinear problem, are compared with another constrained multi-objective optimizer, and the much better performance of NSGA-II is observed.
37,111 citations
Book•
01 Jan 2001
TL;DR: This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
Abstract: From the Publisher:
Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. · Comprehensive coverage of this growing area of research · Carefully introduces each algorithm with examples and in-depth discussion · Includes many applications to real-world problems, including engineering design and scheduling · Includes discussion of advanced topics and future research · Features exercises and solutions, enabling use as a course text or for self-study · Accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design and evolutionary computing. This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.
12,134 citations
TL;DR: Goldberg's notion of nondominated sorting in GAs along with a niche and speciation method to find multiple Pareto-optimal points simultaneously are investigated and suggested to be extended to higher dimensional and more difficult multiobjective problems.
Abstract: In trying to solve multiobjective optimization problems, many traditional methods scalarize the objective vector into a single objective. In those cases, the obtained solution is highly sensitive to the weight vector used in the scalarization process and demands that the user have knowledge about the underlying problem. Moreover, in solving multiobjective problems, designers may be interested in a set of Pareto-optimal points, instead of a single point. Since genetic algorithms (GAs) work with a population of points, it seems natural to use GAs in multiobjective optimization problems to capture a number of solutions simultaneously. Although a vector evaluated GA (VEGA) has been implemented by Schaffer and has been tried to solve a number of multiobjective problems, the algorithm seems to have bias toward some regions. In this paper, we investigate Goldberg's notion of nondominated sorting in GAs along with a niche and speciation method to find multiple Pareto-optimal points simultaneously. The proof-of-principle results obtained on three problems used by Schaffer and others suggest that the proposed method can be extended to higher dimensional and more difficult multiobjective problems. A number of suggestions for extension and application of the algorithm are also discussed.
6,411 citations
Book•
30 Apr 1980TL;DR: In this paper, the authors present a mathematical model of the Synchronous Machine and the effect of speed and acceleration on the stability of a three-phase power system with constant impedance load.
Abstract: Preface.Part I: Introduction.Chapter 1: Power System Stability.Chapter 2: The Elementary Mathematical Model.Chapter 3: System Response to Small Disturbances.Part II: The Electromagnetic Torque.Chapter 4: The Synchronous Machine.Chapter 5: The Simulation of Synchronous Machines.Chapter 6: Linear Models of the Synchronous Machine.Chapter 7: Excitation Systems.Chapter 8: Effect of Excitation on Stability.Chapter 9: Multimachine Systems with Constant Impedance Loads.Part III: The Mechanical Torque Power System Control and Stability.Chapter 10: Speed Governing.Chapter 11: Steam Turbine Prime Movers.Chapter 12: Hydraulic Turbine Prime Movers.Chapter 13: Combustion Turbine and Combined-Cycle Power Plants.Appendix A: Trigonometric Identities for Three-Phase Systems.Appendix B: Some Computer Methods for Solving Differential Equations.Appendix C: Normalization.Appendix D: Typical System Data.Appendix E: Excitation Control System Definitions.Appendix F: Control System Components.Appendix G: Pressure Control Systems.Appendix H: The Governor Equations.Appendix I: Wave Equations for a Hydraulic Conduit.Appendix J: Hydraulic Servomotors.Index.
3,249 citations
TL;DR: This article has reviewed the reasons why people want to love or leave the venerable (but perhaps hoary) MSE and reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems.
Abstract: In this article, we have reviewed the reasons why we (collectively) want to love or leave the venerable (but perhaps hoary) MSE. We have also reviewed emerging alternative signal fidelity measures and discussed their potential application to a wide variety of problems. The message we are trying to send here is not that one should abandon use of the MSE nor to blindly switch to any other particular signal fidelity measure. Rather, we hope to make the point that there are powerful, easy-to-use, and easy-to-understand alternatives that might be deployed depending on the application environment and needs. While we expect (and indeed, hope) that the MSE will continue to be widely used as a signal fidelity measure, it is our greater desire to see more advanced signal fidelity measures being used, especially in applications where perceptual criteria might be relevant. Ideally, the performance of a new signal processing algorithm might be compared to other algorithms using several fidelity criteria. Lastly, we hope that we have given further motivation to the community to consider recent advanced signal fidelity measures as design criteria for optimizing signal processing algorithms and systems. It is in this direction that we believe that the greatest benefit eventually lies.
2,601 citations