Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

Research of Reactive Power Planning Optimization Based on Improved Adaptive Genetic Algorithm for Wind Power Plant

Authors
Shijie Liu
Corresponding Author
Shijie Liu
Available Online November 2016.
DOI
10.2991/aiie-16.2016.29How to use a DOI?
Keywords
wind power plant; multi-scenario modeling; reactive power planning optimization; improved adaptive genetic algorithm
Abstract

Contrapose the randomness of wind speed and the wind power, use the method of multi-scenario based on probability analysis to study reactive power planning of wind power system and make the multi-scenario expectation model. On this basis, use improved adaptive genetic algorithm with subsection self-adaption selection strategy and the continuous changing mutation probability calculation method. Algorithm stability has been improved. The convergence of generation number has been reduced. And global optimization ability has been improved. The analysis of examples has verified the correctness and effectiveness of the model and the algorithm.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
978-94-6252-271-8
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.29How to use a DOI?
Copyright
© 2016, 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/).

Cite this article

TY  - CONF
AU  - Shijie Liu
PY  - 2016/11
DA  - 2016/11
TI  - Research of Reactive Power Planning Optimization Based on Improved Adaptive Genetic Algorithm for Wind Power Plant
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 118
EP  - 121
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.29
DO  - 10.2991/aiie-16.2016.29
ID  - Liu2016/11
ER  -