Development of Composite Load Models of Power Systems using On-line Measurement Data

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

doi:10.5370/jeet.2006.1.2.161

Cited by 23 publications

(16 citation statements)

References 10 publications

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“…In the case of composite load model [14], however, the direct axis voltage and quadrature axis voltage components, and respectively are needed as input voltage values. Thus, the three phase voltage also needs to be converted into d-axis and q-axis voltages by using Park's abc to dq transformation.…”

Section: A Data Processingmentioning

confidence: 99%

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Automatic Identification of Power System Load Models Based on Field Measurements

Zhu

Milanović

2018

IEEE Trans. Power Syst.

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With an ever growing complexity, the power grids are designed and operated with an increasingly reduced stability margin. Under such circumstances, the adequate modeling of existing and new power system loads, with all its challenges, is receiving renewed attention. To simplify and to large extent automate the task of load modelling, this paper presents a methodology and associated software tool-Automated Load Modelling Tool (ALMT) to automatically (without human intervention) develop load models and derive corresponding model parameters from recorded power system responses. The approach facilitates automatic identification of load models and derivation of corresponding parameters for three different types of load models, i.e. polynomial, dynamic exponential, and composite load model. Several case studies using real life measurements at 11 kV distribution buses are used to test and validate developed methodology and software tool.

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Section: A Data Processingmentioning

confidence: 99%

“…The composite load model is the most advanced and widely used load model in dynamic studies [6,18], as it is valid under most power system stability analysis scenarios. The most commonly used composite load model consist of parallel connection of ZIP load model and an IM model [6,14,[19][20][21][22], as shown in Fig. 10.…”

Section: Wherementioning

confidence: 99%

Automatic Identification of Power System Load Models Based on Field Measurements

Zhu

Milanović

2018

IEEE Trans. Power Syst.

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“…The value of load power factor is considered 0.9 lagging and value of q n is used 3 for this paper [24] [25].…”

Section: Probabilistic Load Disturbancesmentioning

confidence: 99%

“…With a poor load model we would need to operate the system with a higher safety margin. Many papers have been published about composite load modelling which includes the composite load as a combination of static and dynamic load model [23]- [25].…”

Section: Probabilistic Load Disturbancesmentioning

confidence: 99%

Effect of Probabilistic Pattern on System Voltage Stability in Decentralized Hybrid Power System

Saxena¹,

Kumar²

2015

WJET

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This paper presents an proportional integral (PI) based voltage-reactive power control for wind diesel based decentralized hybrid power system with wide range of disturbances to demonstrate the compensation effect on system with intelligent tuning methods such as genetic algorithm (GA), artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). The effect of probabilistic load and/or input power pattern is introduced which is incorporated in MATLAB simulink model developed for the study of decentralized hybrid power system. Results show how tuning method becomes important with high percentage of probabilistic pattern in system. Testing of all tuning methods shows that GA, ANN and ANFIS can preserve optimal performances over wide range of disturbances with superiority to GA in terms of settling time using Integral of Square of Errors (ISE) criterion as fitness function.

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“…The task of parameter estimation is formulated as a nonlinear least squares problem where the output mismatch error is an objective function [6].…”

Section: Introductionmentioning

confidence: 99%

Measurement-based Static Load Modeling Using the PMU data Installed on the University Load

Han¹,

Kim²,

Lee³

et al. 2012

Journal of Electrical Engineering and Technology

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-Load modeling has a significant influence on power system analysis and control. In recent years, measurement-based load modeling has been widely practiced. In the load modeling algorithm, the model structure is determined and the parameters of the established model are estimated. For parameter estimation, least-squares optimization method is applied. The model parameters are estimated so that the error between the measured values and the predicted values is to be minimized. By introducing sliding window concept, on-line load modeling method can be performed which reflects the dynamic behaviors of loads in real-time. For the purpose of data acquisition, the measurement system including PMU is implemented in university level. In this paper, case studies are performed using real PMU data from Korea Univ. and Seoul National University of Science and Technology. The performances of modeling real and reactive power behaviors using exponential and ZIP load model are evaluated.

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Development of Composite Load Models of Power Systems using On-line Measurement Data

Cited by 23 publications

References 10 publications

Automatic Identification of Power System Load Models Based on Field Measurements

Automatic Identification of Power System Load Models Based on Field Measurements

Effect of Probabilistic Pattern on System Voltage Stability in Decentralized Hybrid Power System

Measurement-based Static Load Modeling Using the PMU data Installed on the University Load

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