Study on Aggregation of Inductive Motor Loads Based on Differential Evolution Algorithm

DOI

10.2991/ammsa-17.2017.82How to use a DOI?

Keywords

power system; estimation dynamic equivalence; inductive-motor load; differential evolution; parameter identification

Abstract

In order to simplify enormous inductive-motor loads in online estimation dynamic equivalence for large-scale power systems, it is presented identification strategy based on the algorithm of differential evolution algorithm (DE) to acquired the parameter of equivalent motor loads. It presented to dynamic aggregate motors into an equivalent motor based on same or similar dynamic characteristic, the parameter of equivalent motor is identified to use modified Differential Evolution algorithm (DE) which has unique advantage in nonlinear parameter optimization, in order to solve premature convergence problem of DE, double evolution swarm which adopt different variation are formed. Simulated results indicate that it is high accuracy for identified the parameter of equivalent motors, equivalent system can preserve dynamic characteristics of original system well. The method can be used to simplify mass inductive motor loads in online estimation dynamic equivalence for large-scale power systems.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Baozhen Zhang
AU  - Chenxi Fan
PY  - 2017/05
DA  - 2017/05
TI  - Study on Aggregation of Inductive Motor Loads Based on Differential Evolution Algorithm
BT  - Proceedings of the 2017 International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2017)
PB  - Atlantis Press
SP  - 365
EP  - 368
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-17.2017.82
DO  - 10.2991/ammsa-17.2017.82
ID  - Zhang2017/05
ER  -