State-Space Model Parameter Identification in Large-Scale Power Systems

Dehghani, Maryam; Nikravesh, S.K.Y.

doi:10.1109/tpwrs.2008.922632

Cited by 70 publications

(36 citation statements)

References 23 publications

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“…Consider a smart grid system consisting of n generators. The mechanical and electrical dynamics of the ith (i = 1, ..., M) generator can be described by [1] …”

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

“…Then in the second component of the vector in (8), dt P mi (t), becomes zero and can be dropped. Plugging (4)- (7) into (8), after simplification, approximations, and manipulation [1], we obtain the continuous-time noise-free state equation…”

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

“…The state equation in (10) can be further simplified using similar approximations [1], and then converted to a discretetime version using standard manipulations to get…”

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

“…As we have just shown, a smart grid system can be modeled using a linear state space model using approximations frequently made in the power system literature [1], [2]. Let x k be an N dimensional vector which denotes the state of the system at time k [1], [2].…”

Section: Discrete-time Linear State Space Modelmentioning

confidence: 99%

“…The use of a state space model to describe the dynamics of a power system has been justified in the past [1], [2]. In order to allow this paper to be self contained, we will also provide explicit justification in Section II of this paper.…”

Section: Introductionmentioning

confidence: 99%

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New hypothesis testing-based methods for fault detection for smart grid systems

Blum

2011

2011 45th Annual Conference on Information Sciences and Systems

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Abstract-Fault detection plays an indispensable role in ensuring the security of smart grid systems. Based on the dynamics of the generators, we show the time evolution of the smart grid system can be modeled by a discrete-time linear state space model. We focus on faults that can be described by changes in system matrices of the state space model. Newly developed locally optimum tests are discussed and utilized to improve the performance for detecting small changes. Numerical results are provided which demonstrate the superiority of the new approaches when compared to existing methods, especially in the detection of small changes.

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“…Consider a smart grid system consisting of n generators. The mechanical and electrical dynamics of the ith (i = 1, ..., M) generator can be described by [1] …”

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

“…The state equation in (10) can be further simplified using similar approximations [1], and then converted to a discretetime version using standard manipulations to get…”

Section: State Space Model For Smart Grid Systemsmentioning

confidence: 99%

Section: Discrete-time Linear State Space Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New hypothesis testing-based methods for fault detection for smart grid systems

Blum

2011

2011 45th Annual Conference on Information Sciences and Systems

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A networked hierarchical control scheme for wide‐area systems: A power system application

Khayyer

Farsangi

Bijami

2019

Asian Journal of Control

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This paper presents a new networked hierarchical predictive sliding mode controller for the design of stabilizing signals to damp low frequency oscillations observed in geographically distributed networked power systems subject to communication network constraints. Firstly, through the generic framework of networked systems, a networked model is used for a distributed networked system in which network delays and data packet loss are considered in a wide area measurement system (WAMS). Then a hierarchical predictive sliding mode controller with robust reaching law is proposed to compensate the influence of WAMS communication latency and damp the inter-area oscillations. For this, firstly, the overall system is decomposed into small subsystems with non-sparse matrices and lower order; then a new suitable predictive sliding mode controller is designed to provide optimal performance. Furthermore, in order to coordinate the entire system, the gradient of interaction errors is used. The effectiveness of the proposed control framework is illustrated through numerical simulations on a 5-area, 16-machine power system with several interconnected areas. Simulation results show the capability of the proposed approach to enhance the networked power systems' damping in comparison with a conventional networked control method. KEYWORDS hierarchical control, networked control, power system stability, predictive sliding mode, wide area system 1 | INTRODUCTION Distributed wide-area systems commonly appear in the real world, in the form of, for example, power grids, chemical plants, water distribution networks, traffic systems, etc. Systems are wide-area systems if they can be decoupled or decomposed into a number of interconnected/interacting subsystems or if their dimensions are so large that using the usual analysis, optimization, and control methods cannot achieve an acceptable answer during reasonable computational time and efforts [1]. Such typical motivating problems arise in the control of widely distributed multi-area power systems with severe interactions. These problems are mainly due to large dimensions, modeling errors, disturbances, and uncertainties in such systems. The stability of modern power grids is one of the most important issues in the operation of these systems. The increasing size of wide-area electric power grids and the interconnection of these systems via weak tie

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Optimal coordinated control of multiple HVDC links for power oscillation damping based on model identification

Eriksson

Söder

2010

Int Trans Elec Energy Syst

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SUMMARY This paper deals with optimal coordinated control of several high voltage direct current (HVDC) links based on an estimated model of large power systems. The model of the power system is estimated by using subspace system identification techniques. An optimal controller is designed based on the estimated model with the aim to improve the damping in the system. The main contribution of this paper is the development of a new method which uses global Phasor measurement units (PMUs) signals for coordinated damping control of multiple HVDC links. The input signals are the controllable set‐points of the HVDC links, the output signals are the speed signals of selected generators obtained from PMU. The PMU signals are used to estimate the current state of the model, i.e., the state of the system, an appropriate control action can then be applied to dampen the system. The benefit of the method is that the used output signals, i.e., the used PMU signals, are independent of the system equilibrium and therefore makes it possible to use state‐feedback control, i.e., coordinated control. The method is applied to the Cigré Nordic 32‐bus system including two HVDC links. The consistent results show that the damping can be significantly increased. Copyright © 2010 John Wiley & Sons, Ltd.

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State-Space Model Parameter Identification in Large-Scale Power Systems

Cited by 70 publications

References 23 publications

New hypothesis testing-based methods for fault detection for smart grid systems

New hypothesis testing-based methods for fault detection for smart grid systems

A networked hierarchical control scheme for wide‐area systems: A power system application

Optimal coordinated control of multiple HVDC links for power oscillation damping based on model identification

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