Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy
Nowadays, haze has become a big trouble in our society. One of the significant solutions is to introduce renewable energy on a large scale. How to ensure that power system can adapt to the integration and consumption of new energy very well has become a scientific issue. A smart generation control w...
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doaj-42b1ca934db94278a131f65f6c510fe82020-11-24T21:35:58ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/27823142782314Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack StrategyLei Xi0Lang Liu1Yuehua Huang2Yanchun Xu3Yunning Zhang4College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaCollege of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002, ChinaNowadays, haze has become a big trouble in our society. One of the significant solutions is to introduce renewable energy on a large scale. How to ensure that power system can adapt to the integration and consumption of new energy very well has become a scientific issue. A smart generation control which is called hierarchical and distributed control based on virtual wolf pack strategy is explored in this study. The proposed method is based on multiagent system stochastic consensus game principle. Meanwhile, it is also integrated into the new win-lose judgment criterion and eligibility trace. The simulations, conducted on the modified power system model based on the IEEE two-area load frequency control and Hubei power grid model in China, demonstrate that the proposed method can obtain the optimal collaborative control of AGC units in a given regional power grid. Compared with some smart methods, the proposed one can improve the closed-loop system performances and reduce the carbon emission. Meanwhile, a faster convergence speed and stronger robustness are also achieved.http://dx.doi.org/10.1155/2018/2782314 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lei Xi Lang Liu Yuehua Huang Yanchun Xu Yunning Zhang |
spellingShingle |
Lei Xi Lang Liu Yuehua Huang Yanchun Xu Yunning Zhang Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy Complexity |
author_facet |
Lei Xi Lang Liu Yuehua Huang Yanchun Xu Yunning Zhang |
author_sort |
Lei Xi |
title |
Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy |
title_short |
Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy |
title_full |
Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy |
title_fullStr |
Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy |
title_full_unstemmed |
Research on Hierarchical and Distributed Control for Smart Generation Based on Virtual Wolf Pack Strategy |
title_sort |
research on hierarchical and distributed control for smart generation based on virtual wolf pack strategy |
publisher |
Hindawi-Wiley |
series |
Complexity |
issn |
1076-2787 1099-0526 |
publishDate |
2018-01-01 |
description |
Nowadays, haze has become a big trouble in our society. One of the significant solutions is to introduce renewable energy on a large scale. How to ensure that power system can adapt to the integration and consumption of new energy very well has become a scientific issue. A smart generation control which is called hierarchical and distributed control based on virtual wolf pack strategy is explored in this study. The proposed method is based on multiagent system stochastic consensus game principle. Meanwhile, it is also integrated into the new win-lose judgment criterion and eligibility trace. The simulations, conducted on the modified power system model based on the IEEE two-area load frequency control and Hubei power grid model in China, demonstrate that the proposed method can obtain the optimal collaborative control of AGC units in a given regional power grid. Compared with some smart methods, the proposed one can improve the closed-loop system performances and reduce the carbon emission. Meanwhile, a faster convergence speed and stronger robustness are also achieved. |
url |
http://dx.doi.org/10.1155/2018/2782314 |
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