Power System Load Modeling Based on Genetic Programming

DOI

10.2991/lemcs-14.2014.31How to use a DOI?

Keywords

Load Model; Genetic Programming; Model Structure; Model Identification; Simulation

Abstract

Genetic Programming (GP) is a new evolutionary algorithm based on genetic algorithm, which has self-adaptive, self-organizing, self-learning and other advantages, and has significant advantages in terms of symbolic regression to solve long-term problems of the model structure automatically recognizes the problem. In this paper, the genetic programming is introduced to the power system load modeling to solve long-standing problems of automatic identification model structure in the power system.

Copyright

© 2014, 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  - Jian Zhang
AU  - Chaohui Zhang
PY  - 2014/05
DA  - 2014/05
TI  - Power System Load Modeling Based on Genetic Programming
BT  - Proceedings of the International Conference on Logistics, Engineering, Management and Computer Science
PB  - Atlantis Press
SP  - 133
EP  - 136
SN  - 1951-6851
UR  - https://doi.org/10.2991/lemcs-14.2014.31
DO  - 10.2991/lemcs-14.2014.31
ID  - Zhang2014/05
ER  -