A self-learning scheme for residential energy system control and management

@article{Huang2011ASS,
  title={A self-learning scheme for residential energy system control and management},
  author={Ting Huang and Derong Liu},
  journal={Neural Computing and Applications},
  year={2011},
  volume={22},
  pages={259-269}
}
In this paper, we apply intelligent optimization method to the challenge of intelligent price-responsive management of residential energy use, with an emphasis on home battery use connected to the power grid. For this purpose, a self-learning scheme that can learn from the user demand and the environment is developed for the residential energy system control and management. The idea is built upon a self-learning architecture with only a single critic neural network instead of the action-critic… CONTINUE READING
Highly Cited
This paper has 83 citations. REVIEW CITATIONS

9 Figures & Tables

Topics

Statistics

0102030201320142015201620172018
Citations per Year

84 Citations

Semantic Scholar estimates that this publication has 84 citations based on the available data.

See our FAQ for additional information.