measurement based dynamic load modeling in power ... - …€¦ · measurement based dynamic load...

Measurement Based Dynamic Load Modeling in Power Systems

Alireza Rouhani1

Bilgehan Donmez2

Ali Abur

Northeastern University

1Currently with Dominion Power (Received his PhD in Spring 2017)2Cuurently with AMSC (part-time PhD Student)

Importance of Load Modeling• ZIP models are not suitable for Voltage Stability Analysis• Voltage collapse, FIDVR events• Evolution of distribution feeders (smart grid, DER, etc.)

2Source: NERC LMTF

Difficulty In Model Development• Day-to-day variations in load composition• Various equipment scattered along the feeder. What

feeder impedance to use? How to break down the load into its components? Induction motors Lighting Power electronics Distributed generation Static load Feeder impedance Protection settings

3Source: NERC LMTF

Two Approaches1. Component Based Comprehensive models: requires detailed engineering analysis Significant effort needed to survey the load composition Accurate given that the right model can be constructed Good fit for offline transmission planning studies

2. Measurement Based Simple but accurate load model Ease of implementation in online applications (e.g., online dynamic

state estimation, real-time transient stability analysis) Model accuracy is a function of measurement frequency Automatic real-time tracking of model parameters

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Component Based Models• CMLD: The best component based model we currently

have• Works great given that engineering analysis are done to

figure out the correct load composition and parameters• Great for offline voltage/transient stability analysis

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Measurement Based Models• Real-time parameter tracking• First, second, third order models depending on load

complexity• Any measurement data can be used: SCADA, PMU, DFR,

smart meters, etc.• The time constant determined by measurement frequency

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[5] H. Renmu, M. Jin, and D. Hill, “Composite load modeling via measurement approach,” IEEETrans. Power Syst., vol. 21, no. 2, pp. 663–672, May 2006.

First Order Model [2]

1. A step in voltage triggers a step in power2. The power settles to a new steady-state value3. The recovery appears to be of exponential form

(typically undamped)4. The size of the step and steady-state value are

nonlinearly related to voltage

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[2] D. Karlsson and D. J. Hill, “Modelling and Identification of Nonlinear Dynamic Loads in Power Systems," IEEE Transactions on Power Systems, vol. 9,no. 1, Feb 1994.

First Order Model Examples (1)

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Voltage recovery depends on percentage of motor load

Source: AMSC

First Order Model Examples (2)

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Voltage recovery depends on distribution impedance

Source: AMSC

This work [1] considers a first order model (the exponential dynamic load model) and aims to identify and track its parameters on-line.

Unscented Kalman Filter (UKF) is used as a dynamic state/parameter estimator to track the unknown parameters associated with exponential dynamic load model.

[1] A. Rouhani and A. Abur, "Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model," IEEE Transactions on Smart Grid, vol. 7,no. 3, pp. 1530-1536, July 2015. 10

Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model

Exponential dynamic load model:

The active power consumed by the load are assumed to be related to the voltage in the following non-linear manner :

Similar equations are valid for reactive power.

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Proposed approach:

UKF is implemented and used to track the state vector which includes the unknown parameters associated with the exponential dynamic load model :

Dynamic state variables of generators again will be updated by discretions of the generators. The measurement is assumed to :

UKF

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Here the parameters associated with the load are assumed to be:

Now considering the following scenario the proposed approach will be evaluated:

1. is reduced from -0.32 to -0.37.

2. is increased from 1.65 to 1.7.

3. is increased from 70 sec. to 80 sec.

Testing of the proposed approach using simulated measurements:

[sec].70&65.1,32.0 ==−= pts Tαα

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Using simulated measurements:

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Testing the proposed approach by using actual recorded measurements:

Here, the proposed approach is evaluated based on actual recorded measurement data where synchronized voltage and power measurements are acquired every 6 seconds for a utility distribution feeder. The total duration of the recordings is 1440 minutes or 24 hours.

The following figure shows that the voltage of the feeder (V)increases during this period (from almost 115 kV to 116.5 kV).

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Test results:

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Validation of the proposed approach using actual recorded measurements:

In order to quantify the accuracy, the following error metric is used to evaluate the performance of the UKF in tracking the real-time model of the active power demand:

The following figure illustrates how the MSE value is gradually reduced finally settling below an acceptablelevel of 0.25, validating the satisfactory performance of UKF.

0 500 1000 15000

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

time [min]

MS

E

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Second Order Model [3]

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[3] C. Lin et al., “Dynamic Load Models in Power Systems Using the Measurement Approach," IEEE Transactions on Power Systems, vol. 8,no. 1, Feb 1993.

• Consider a second order model where T’s are time constants and K’s are gain coefficients:

• Better capability to represent load behaviors during system disturbances

Order Comparison [3], [4]

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[4] E. Welfonder, H. Weber and B. Hall, “Investigations of the frequency and voltage dependence of load part systems using a digital self-acting measuring and identfication system," IEEE Transactions on Power Systems, vol. 4, pp. 19-25, 1989.

Other Models [5]

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• A combination of ZIP model and induction motor model• This 14 parameter model provides good generalization

capability• Good voltage sag match during faults• Can be interpreted physically

[5] H. Renmu, M. Jin, and D. Hill, “Composite load modeling via measurement approach,” IEEETrans. Power Syst., vol. 21, no. 2, pp. 663–672, May 2006.

Use Case for Measurement Based Models• Simple models• Suitable for online applications (Dynamic State

Estimation, Real-time Transient Stability)• Can be a complementary tool to the CMLD model for

feeders with adequate sensors• Any measurement data can be used: SCADA, PMU, DFR,

smart meters, etc.

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What is next?• Take advantage of high frequency meters (PMUs, smart

meters, etc.) to develop real-time measurement models• Case studies using recorded system data

22Source: AMSC

• References[1] A. Rouhani and A. Abur, "Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model," IEEE Trans. Smart Grid, vol. 7,no. 3, pp. 1530-1536, July 2015.

[2] D. Karlsson and D. J. Hill, “Modelling and Identification of Nonlinear Dynamic Loads in Power Systems,"IEEE Transactions on Power Systems, vol. 9,no. 1, Feb 1994.

[3] C. Lin et al., “Dynamic Load Models in Power Systems Using the Measurement Approach," IEEETransactions on Power Systems, vol. 8,no. 1, Feb 1993.

[4] E. Welfonder, H. Weber and B. Hall, “Investigations of the frequency and voltage dependence of load partsystems using a digital self-acting measuring and identfication system," IEEE Transactions on PowerSystems, vol. 4, pp. 19-25, 1989.

[5] H. Renmu, M. Jin, and D. Hill, “Composite load modeling via measurement approach,” IEEE Trans.Power Syst., vol. 21, no. 2, pp. 663–672, May 2006.

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measurement based dynamic load modeling in power ... - …€¦ · measurement based dynamic load...

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