Measurement-Based Dynamic Load Models: Derivation, Comparison, and Validation

Choi, Byoung-Kon; Chiang, Hsiao‐Dong; Li, Yinhong; Li, Hua; Chen, Yung‐Tien; Huang, Der-Hua; Lauby, M. G.

doi:10.1109/tpwrs.2006.876700

Cited by 144 publications

(60 citation statements)

References 25 publications

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“…Substituting (11)-(13) into (9) and denoting the trajectory sensitivity of the dynamic states with respect to the parameter as we have (14) Thus, the trajectory sensitivities can be calculated by solving the time-variant linear equations (14). Since the trajectory sensitivities of states with respect to the parameters should be constant in the steady state, the initial values of and can be derived by solving the following equations: (15) In Subsection IV-B, (14) and (15) will be applied to evaluate the effects of equivalent motor parameters on load dynamics.…”

Section: A Trajectory Sensitivity Methodsmentioning

confidence: 99%

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Reducing Identified Parameters of Measurement-Based Composite Load Model

Jin

Han

et al. 2008

IEEE Trans. Power Syst.

146

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A load model is one of the most important elements in power system simulation and control. Recently, the constant impedance, constant current, and constant power load in combination with the induction motor load have been widely used as the composite load model, whose parameters are all identified from the field measurements in measurement-based load modeling practices so far. However, there is virtually no research conducted on whether all these parameters could really be identified. This paper investigates the possibility on reducing the number of composite load model parameters to be identified from field measurements. This paper first shows that direct application of the IEEE load motor parameters in the composite load model may be inadequate on describing the load dynamics over different operating status. Then the perturbation method is used to derive the trajectory sensitivities of the equivalent motor parameters, based on which the reduction on the identified parameters of the composite load model is presented. Two cases of measurement-based load modeling in North China and Northeast China are studied to illustrate the validity of the reduction method. It is shown that the reduction does not lose the model's capability on describing the load dynamics. The reduction on the number of identified parameters not only provides a possible way to solve the multi-valued load model problem based on the current practices on measurement-based load modeling, but it also facilitates building of the load model with more components included in it. Meanwhile, reducing the identified parameters reduces the identification time; thus, the proposed strategy significantly enhances the efficiency of the load modeling work.Index Terms-Composite load model, field measurements, power system stability, trajectory sensitivity.

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Section: A Trajectory Sensitivity Methodsmentioning

confidence: 99%

“…Since the trajectory sensitivities of states with respect to the parameters should be constant in the steady state, the initial values of and can be derived by solving the following equations: (15) In Subsection IV-B, (14) and (15) will be applied to evaluate the effects of equivalent motor parameters on load dynamics.…”

Section: A Trajectory Sensitivity Methodsmentioning

confidence: 99%

Reducing Identified Parameters of Measurement-Based Composite Load Model

Jin

Han

et al. 2008

IEEE Trans. Power Syst.

146

View full text Add to dashboard Cite

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“…In addition, this modelling approach is also more tolerable to modifications compared with the component-based approach. Therefore a great deal of load modelling work has been undertaken with this approach especially at substation levels [13][14][15][16][17][18]. Similar to the component-based approach, the modelling work can only commence with the possession of sufficient data.…”

Section: Introductionmentioning

confidence: 99%

Dynamic load modelling of a paper mill for small signal stability studies

Wong¹,

Haque²

2014

IET Generation, Transmission & Distribution

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This study considers a power system with half the demand comprises of industrial loads with large rotating machines. The dynamic behaviour of these loads during disturbance is crucial to system stability. This study describes a practical approach to develop Laplace transfer function (TF) model of a mill load connected to this power system. A PSCAD/EMTDC™ simulation model of the mill ('the detailed model') is built from information on the types of load within the mill and verified in a piece-wise manner, i.e., against individual motor starts. Instead of using generic load models, system identification theory is applied to evaluate the TF load model from simulated disturbance responses for both voltage and frequency changes. The main objective is to accurately represent the load behaviour particularly during small signal disturbances. It is recognised that large signal requirements of a load model for transient stability studies are important but the inevitable non-linearity of such a model would tend to saturate the loads' behaviour during smaller disturbances. The developed small signal load model is then tested using practical disturbance profiles from this power system. This modelling approach allows development work to commence before real-life disturbance measurements are available since such data are currently scant.

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“…Load modeling is the process of defining load characteristics via mathematical formulas that describe the characteristics of load changes in response to voltage and frequency variations. Load modeling techniques can be classified as either component based [7][8][9][10][11] or measurement based [12][13][14][15][16][17][18][19][20][21][22][23][24], depending on the modeling procedure. In component-based load modeling, measuring devices need not be installed in the field.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, most current research on load modeling is focused on measurement-based methods, even though these methods require installation of an additional measuring device for every load in the power system. Measurement-based load modeling can be sub-classified into static load modeling [12][13][14] and dynamic load modeling [15][16][17][18][19][20][21][22][23][24]. Although dynamic load modeling can reflect the transient characteristics of loads, it requires high-density data samples on the time axis.…”

Section: Introductionmentioning

confidence: 99%

EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level

Nam

Kang

Lee³

et al. 2013

Energies

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This paper proposes a linearized load model to evaluate the effect of conservation voltage reduction at a national level. In this model, the respective active and reactive linearizing parameters for active and reactive loads in a power system are estimated using energy management system (EMS) data resulting from conservation voltage reductions. To verify the validity of the linearized load model, PSS/E simulations were conducted for a test power system. Given that conservation voltage reductions are usually executed in the range of 2.0%-5.0%, the proposed model was found to be sufficient to accurately evaluate the effect of conservation voltage reduction. Additionally, Korean EMS data were used to estimate the linearizing parameters for aggregated loads in an actual power system.

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Measurement-Based Dynamic Load Models: Derivation, Comparison, and Validation

Cited by 144 publications

References 25 publications

Reducing Identified Parameters of Measurement-Based Composite Load Model

Reducing Identified Parameters of Measurement-Based Composite Load Model

Dynamic load modelling of a paper mill for small signal stability studies

EMS-Data-Based Load Modeling to Evaluate the Effect of Conservation Voltage Reduction at a National Level

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