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Applying reinforcement learning method to optimize an Energy Hub operation in the smart grid
Rayati, M ; Sharif University of Technology
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- Type of Document: Article
- DOI: 10.1109/ISGT.2015.7131906
- Abstract:
- New days, the concepts of 'Smart Grid' and 'Energy Hub' have been introduced to improve the operation of the energy systems. This paper introduces a new conception entitling Smart Energy Hub (S. E. Hub), as a multi-carrier energy system in a smart grid environment. To show the application of this novel idea, we present a residential S. E. Hub which employs Reinforcement Learning (RL) method for finding a near optimal solution. The simulation results show that by applying the S. E. Hub model and then using the proposed method for a residential customer, running cost is reduced substantially. While, comparing with the classical ones, the RL method does not require any data about the environment and either equipment's parameters
- Keywords:
- Energy management system ; Reinforcement learning (RL) ; Smart energy hub (S. E. Hub) ; Smart grids ; Electric power transmission networks ; Energy management systems ; Housing ; Optimization ; Reinforcement learning ; Energy systems ; Multi carrier ; Near-optimal solutions ; Reinforcement learning method ; Residential customers ; Running cost ; Smart energies ; Smart grid ; Smart power grids
- Source: IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2015, 18 February through 20 February 2015 ; 2015 ; 9781479917853 (ISBN)
- URL: http://ieeexplore.ieee.org/document/7131906