An Extended Composite Load Model Taking Account of Distribution Network

Qu, Xiaoyan; Li, Xinran; Song, Junying; He, C. X.

doi:10.1109/tpwrs.2018.2865186

Cited by 19 publications

(8 citation statements)

References 11 publications

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“…Take the reference voltage for the network average rates voltage and the transformer ratio for the average rates voltage ratio, then . Set the induction motor voltage reference , the conversion matrix of the "reference transformation " could be deduced by the principle of voltage level conversion and the per-unit value conversion, which is shown in (8).…”

Section: ) Power Of the Header And End Point Of The Distribution Line...mentioning

confidence: 99%

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Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

Wang,

Yan

2024

Chinese J. Elect.

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With the rapid development of industrial parks, its load model research has become a hot spot. In order to study the load of power system in industrial park, based on the characteristics of the industrial park load, a comprehensive load admittance static model with full voltage range adaptability is considered, and a comprehensive load model of distribution network of the industrial park is established. A complete parameter identification of the model is carried out through chaos particle swarm optimization. The simulation results show that the model can effectively describe the load characteristics of the distribution network in industrial parks.

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Section: ) Power Of the Header And End Point Of The Distribution Line...mentioning

confidence: 99%

“…With the distributed power supply in the low-voltage distribution network, a variety of integrated load models which were more in line with the actual situation were proposed on the basis of the original classic load model (CLM) [8]- [13]. However, the current study of the industrial park load model has not attracted enough attention.…”

Section: Introductionmentioning

confidence: 99%

Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

Wang,

Yan

2024

Chinese J. Elect.

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“…These methods were mainly applicable to the analysis and research of linear models. With the improvement of the load model structure, the synthesis load model considering the impedance of the distribution network has been widely used [5,6]. Therefore, the linear methods used to identify the synthe-This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.…”

Section: Introductionmentioning

confidence: 99%

“…These methods were mainly applicable to the analysis and research of linear models. With the improvement of the load model structure, the synthesis load model considering the impedance of the distribution network has been widely used [5,6]. Therefore, the linear methods used to identify the synthe-sis load model had the problems of convergence difficulty and poor identification accuracy.…”

Section: Introductionmentioning

confidence: 99%

Novel method for power system synthesis load identification

et al. 2020

IET Generation Trans & Dist

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Power load parameters are one of the most important parameters for power system model. The load has the characteristics of time‐varying, diversity and non‐linearity. Therefore, obtaining the load parameters accurately is crucial to the safe and stable operation of the power system. The research in this paper is based on the synthesis load model which takes into account the impedance of distribution network. The multi‐fault curves identification method and chaos‐whale algorithm are adopted to improve the accuracy and practicability of load parameter identification. First, the algorithm proposed in this paper applies chaos algorithm to whale algorithm, and uses the randomness and ergodicity of chaos algorithm to make up for the shortcomings of the whale algorithm that the solution accuracy is not high and it is easy to fall into local optimum. Secondly, the identification method of multi‐fault curves is to select several different faults for parameter identification, and the average value of each group of results obtained is regarded as the final result. Then compared with single curve identification, the multi‐fault curves method is more superior. Finally, the accuracy of the results is verified by other faults. Simulation results show that the method is reliable to a certain extent.

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“…In order to describe the load behavior under unbalanced disturbances, an improved ZIP model with three-phase dq0 voltage components is formed in [6]. For considering the impact of high-voltage network, an extended composite load model is proposed in [7]. In terms of the parameter identification techniques in a given load model structure, reference [8] adopts the crossover operation of genetic algorithm and particle swarm optimization algorithm.…”

Section: Introductionmentioning

confidence: 99%

Recursive Bayesian-Based Approach for Online Automatic Identification of Generalized Electric Load Models in a Multi-Model Framework

et al. 2019

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Electric loads are essential for power system dynamic simulation. However, load modeling is one of the most challenging topics due to the diversity and time-varying behavior of the load. When considering the intervention of rapidly developing distributed generation (DG), load modeling becomes more difficult. In this paper, a new solution for determining the unknown generalized load model is proposed. The radial basis function (RBF) neural network-based sub-models of generalized load are stored in the form of a sub-model bank. A recursive Bayesian approach is used to identify the sub-models and then merge them into one generalized load model according to their probabilities. The proposed method can be implemented online and adapt to describing the diversity and time-varying behavior of the generalized load. Numerical studies are carried out using both simulation data and actual measurements. The comparisons with other load modeling methods verify the advantages of the proposed method.

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An Extended Composite Load Model Taking Account of Distribution Network

Cited by 19 publications

References 11 publications

Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

Research on Modeling and Parameter Identification of Comprehensive Load Model of Distribution Network in Industrial Park

Novel method for power system synthesis load identification

Recursive Bayesian-Based Approach for Online Automatic Identification of Generalized Electric Load Models in a Multi-Model Framework

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