| Título: | Metropolis Criterion Based Fuzzy Q-Learning Energy Management for Smart Grids |
| Autores: |
Li, Xin; Shenyang University Zang, Chuanzhi; Chinese Academy of Sciences Liu, Wenwei; Shenyang University Zeng, Peng; Chinese Academy of Sciences Yu, Haibin; Chinese Academy of Sciences |
| Fecha: | 2012-12-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | No aplica |
| Descripción: | For the energy management problems for demand response in electricity grid, a Metropolis Criterion based fuzzy Q-learning consumer energy management controller (CEMC) is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for the consumer behavior in electricity grid. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference and Metropolis Criterion are introduced in order to facilitate generalization in large state space and balance exploration and exploitation in action selection in Q-learning individually. Simulation results show that the proposed controller can learn to take the best action to regulate consumer behavior with the features of low average end-user financial costs and high consumer satisfaction. |
| Idioma: | Inglés |