Application of Dynamic State and Parameter Estimation Techniques on Real-World Data

Fan, Lingling; Miao, Zhixin; Wehbe, Yasser

doi:10.1109/tsg.2012.2230031

Cited by 31 publications

(7 citation statements)

References 12 publications

(23 reference statements)

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“…, and parameters G ij and B ij can be estimated by applying such standard techniques as the least square method [23] to equivalent network equations in (9). Although real-time estimation is possible, system topology may change, and estimation error may not be neglectable.…”

Section: A Data-driven Calculation Of H Ijmentioning

confidence: 99%

Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

Harvey

et al. 2021

IEEE Trans. Power Syst.

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A novel wide-area control design is presented to mitigate inter-area power frequency oscillations. A large-scale power system is decomposed into a network of passivity-short subsystems whose nonlinear interconnections have a state-dependent affine form, and by utilizing the passivity shortage framework, a two-level design procedure is developed. At the lower level, any generator control can be viewed as one that makes the generator passivity-short and L2 stable, and the stability impact of the lower-level control on the overall system can be characterized in terms of two parameters. While the system is nonlinear, the impact parameters can be optimized by solving a data-driven matrix inequality (DMI), and the high-level wide-area control is then designed by solving another Lyapunov matrix inequality in terms of the design parameters. The proposed methodology makes the design modular, and the resulting control is adaptive to operating conditions of the power system. Standard test systems are used to illustrate the proposed design, including DMI and the wide-area control, and simulation results demonstrate its effectiveness in damping out inter-area oscillations.

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Section: A Data-driven Calculation Of H Ijmentioning

confidence: 99%

Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

Harvey

et al. 2021

IEEE Trans. Power Syst.

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“…In the other paradigm (see e.g. [9] and the references therein), rotor angles and rotor speeds of generators are chosen as state variables, and the classic dynamic model of generators is considered. The DSE of such a paradigm is concerned with the low frequency electromechnical dynamics.…”

Section: M)mentioning

confidence: 99%

A Constrained Optimization Approach to Dynamic State Estimation for Power Systems Including PMU and Missing Measurements

Wang

Rahman

et al. 2015

IEEE Trans. Contr. Syst. Technol.

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Abstract-In this paper, a hybrid filter algorithm is developed to deal with the state estimation problem for power systems by taking into account the impact from the phasor measurement units (PMU). Our aim is to include PMU measurements when designing the dynamic state estimators for power systems with traditional measurements. Also, as data dropouts inevitably occur in the transmission channels of traditional measurements from the meters to the control centre, the missing measurement phenomenon is also tackled in the state estimator design. In the framework of extended Kalman filter (EKF) algorithm, the PMU measurements are treated as inequality constraints on the states with the aid of the statistical criterion, and then the addressed state estimation problem becomes a constrained optimization one based on the probability-maximization method. The resulting constrained optimization problem is then solved by using the particle swarm optimization (PSO) algorithm together with the penalty function approach. The proposed algorithm is applied to estimate the states of the power systems with both traditional and PMU measurements in the presence of probabilistic data missing phenomenon. Extensive simulations are carried out on the IEEE 14-bus test system and it is shown that the proposed algorithm gives much improved estimation performances over the traditional EKF method.

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“…Due to the easiness of working with phasors, PMUs have been used in many different applications, such as analysis of perturbations and oscillations [6][7][8], topology monitoring and parameter estimation [9]. Regarding inertia estimation, literature normally divides the topic in small perturbation studies [8,10,11], large perturbation studies [12][13][14] and studies under ambient conditions [15,16].…”

Section: Introductionmentioning

confidence: 99%

A Perturbation-Based Methodology to Estimate the Equivalent Inertia of an Area Monitored by PMUs

et al. 2021

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This paper proposes a novel methodology to estimate equivalent inertia of an area, observed from its boundary buses where Phasor Measurement Units (PMUs) are assumed to be installed. The areas are divided according to the measurement points, and the methodology proposed can obtain the equivalent dynamic response of the area dependent of or independent of coherency of the generators inside, which is the first contribution of this paper. The methodology is divided in three parts: estimating the frequency response, estimating the power imbalance and estimating inertia through the solution of the swing equation by Least-Squares Method (LSM). The estimation of the power imbalance is the second contribution of this paper, enabling the study of areas that contain perturbations and attending the limitation of methods of the literature that rely on assumptions of slow mechanical power. It can be further divided in three steps: accounting the total power injected, estimating an equivalent load behavior and estimating an equivalent mechanical power. The quality of results is proved with test systems of different sizes, simulating different types of perturbations.

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Application of Dynamic State and Parameter Estimation Techniques on Real-World Data

Abstract: Abstract

Cited by 31 publications

References 12 publications

Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

Data-Driven Wide-Area Control Design of Power System Using the Passivity Shortage Framework

A Constrained Optimization Approach to Dynamic State Estimation for Power Systems Including PMU and Missing Measurements

A Perturbation-Based Methodology to Estimate the Equivalent Inertia of an Area Monitored by PMUs

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