Area decomposition for electromechanical models of power systems

Avramovic, B.; Kokotović, P.V.; Winkelman, J.; Chow, Joe H.

doi:10.1016/0005-1098(80)90006-0

Cited by 95 publications

(26 citation statements)

References 8 publications

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“…Methods were proposed for this previously by the authors [l] and others [ 7 ] - [8]. The authors technique, unlike others require no eigenvalues and no matrix manipulations.…”

Section: S E G M E N T I -D Y N a M I C C L U S T E R I N G A N D T Hmentioning

confidence: 99%

Stability monitoring on the large electric power system

Zaborsky

Huang

Leung

et al. 1985

1985 24th IEEE Conference on Decision and Control

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The objective 9f this work is development of techniques which provide on line decision on the stability of a large interconnected power system faced by assumed or actual disturbances. Since the system is very large and nonlinear and the time scale only a few seconds at best the only hope for results which are mathematically honest, computable on line, and of sufficient accuracy lies in a set of carefully coordinated approximations founded on precise mathematical theory. Such an approach is discussed in this paper. It divides the problem into four segments in order to narrow down those parts of the sys tern which are actively involved and then represent the critical elements by using approximate transformations and graded precision for remote elements. IRTRODUCTIONMonitoring of the stability of power systems has never really become an o n line tool even in the project sponsored by the US Department of Energy now security, contingency sense. A three year research is attempting to devise approaches which will remedy this situation and, potenzially, even go beyond to m o n i t o r o n g o i n g d y n a m i c p h e n o m e n a o n l i n e , Attainability of the latter goal is not assured but making on line dynamic security monitoring practically feasible would be an accomplishment of major importance. Also valuabie theoretical insights are being developed in this project. This paper s u mmarizes the approach used and the results and insights being achieved at this point in the project The fundamental aim is to establish whether the state will return from a post disturbance initial state to its stable equilibrium, without full pole slips between the various system fragments. Systems and their protection are not built for such asynchronous performances.This, of course, is a formidable computational task for fast moving dynamic phenomena. A combination of organization, precomputation, approximation, new insights, and new results is needed to complete it.This process is divided in Fig.

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“…Methods were proposed for this previously by the authors [l] and others [ 7 ] - [8]. The authors technique, unlike others require no eigenvalues and no matrix manipulations.…”

Section: S E G M E N T I -D Y N a M I C C L U S T E R I N G A N D T Hmentioning

confidence: 99%

Stability monitoring on the large electric power system

Zaborsky

Huang

Leung

et al. 1985

1985 24th IEEE Conference on Decision and Control

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“…In fact, the whole power system is described by equations (8) and the division in study and external area can be done over every region of the power system using the actual buses as interconnecting lines between the two areas. This approach has the advantage of improving the fidelity of the simulation of the power system.…”

Section: A Power System Modelmentioning

confidence: 99%

“…The mechanical input powers T Mi Determine a linearized model, e.g. (9) Inspect W (ιω) of (9) and order the frequency features in Σ Inspect σ(A) and order the modes in Λ have been computed from these quantities and equations (8) written at the equilibrium point. The damping coefficients D i have been generated with the function rand.…”

Section: Nets-nyps Systemmentioning

confidence: 99%

“…The system to be reduced has n = 26, m = 3, p = 13. The parameters of system (8) have been computed in MATLAB T M as follows. With the script Init MultiMachine.m, which can be downloaded from [28], the line data, the power flow results, the generator direct axis transient reactance and the inertia values H i of the machines have been generated.…”

Section: Nets-nyps Systemmentioning

confidence: 99%

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Low Computational Complexity Model Reduction of Power Systems With Preservation of Physical Characteristics

Scarciotti¹

2017

IEEE Trans. Power Syst.

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A data-driven algorithm recently proposed to solve the problem of model reduction by moment matching is extended to multi-input, multi-output systems. The algorithm is exploited for the model reduction of large-scale interconnected power systems and it offers, simultaneously, a low computational complexity approximation of the moments and the possibility to easily enforce constraints on the reduced order model. This advantage is used to preserve selected slow and poorly damped modes. The preservation of these modes has been shown to be important from a physical point of view and in obtaining an overall good approximation. The problem of the choice of the socalled tangential directions is also analyzed. The algorithm and the resulting reduced order model are validated with the study of the dynamic response of the NETS-NYPS benchmark system (68-Bus, 16-Machine, 5-Area) to multiple fault scenarios.Index Terms-Dynamic equivalents, model reduction of power systems, coherency, model reduction from data.

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“…It should be pointed out that these techniques, by taking one or two generating units as subsystems, often impose artificial partitioning to the system which does considerable violence to the system and produces excessively conservative results [9,10]. Recently [10][11][12], there has been a growing interest in developing physical decomposition schemes which particularly take into account the dynamic interactions among the system components. These methods, which are also called 'natural' because they exploit the system structure [13], are based on the observation that a large power system is almost invariably composed of weakly connected groups of tightly coupled machines; and they provide, after quantifying the interactions among the generating units, a system subdivision which reflects these system structural features.…”

Section: Introductionmentioning

confidence: 99%

Natural decomposition of interconnected power systems for stability Studies

Brucoli

Torelli

Trovato

1984

IEE Proc. C Gener. Transm. Distrib. UK

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The paper describes the development of a decomposition method which exploits the structure of large power systems. As large power systems are almost invariably composed of weakly connected subsystems, each consisting of strongly interacting machines, the proposed decomposition technique provides, by analysing and quantifying the dynamic interactions among the generating units on the basis of a linearised model, a natural subdivision which reflects the structural features of the system. The method is rigorous and can be carried out systematically. The resulting decomposition scheme can be used to simplify the stability analysis of large power systems under both small and large disturbances. The capability and the usefulness of the proposed method are illustrated by carrying out simulation studies on a sample power system. List of principal symbolsfd D P A = current, p.u. = voltage, p.u. = flux linkage, p.u. = reactance, p.u. = time constant, s = rotor angle, rad = rated frequency = 60 Hz = inertia constant, s; M = H/nf 0 = mechanical torque, p.u. = field voltage referred to armature circuit, p.u = damping coefficient, p.u. MWs/rad; = differential operator d/dt = prefix denoting a small change Subscripts D, Q = common reference frame D-and Q-axis / = field i = refers to the ith synchronous machine h = refers to the hth load md = magnetising Superscripts ' = synchronous machine transient quantities t = denotes transpositionVectors and matrices are defined as they are introduced in the text.

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Area decomposition for electromechanical models of power systems

Cited by 95 publications

References 8 publications

Stability monitoring on the large electric power system

Stability monitoring on the large electric power system

Low Computational Complexity Model Reduction of Power Systems With Preservation of Physical Characteristics

Natural decomposition of interconnected power systems for stability Studies

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