Abstract
As the improvement of smart grids, the customer participation has reinvigorated interest in demand-side features such as load control for domestic users. A genetic based reinforcement learning (RL) load controller is proposed. The genetic is used to adjust the parameters of the controller. The RL algorithm, which is independent of the mathematic model, shows the particular superiority in load control. By means of learning procedures, the proposed controller can learn to take the best actions to regulate the energy usage for equipments with the features of high comfortable for energy usage and low electric charge meanwhile. Simulation results show that the proposed load controller can promote the performance energy usage in smart grids.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
