Abstract
Time-varying wireless channel as well as the variability of renewable energy supply and energy prices are practically unknown in advance. To address such dynamic statistics of wireless networks, this letter develops an adaptive strategy inspired by combinatorial multiarmed bandit model for energy storage management and cost-aware coordinated load control at the base stations. The proposed strategy makes online foresighted decisions on the amount of energy to be stored in storage to minimize the average energy cost over long-time horizon. Simulation results validate the superiority of the proposed strategy over a recently proposed storage-free learning-based design.
| Original language | English |
|---|---|
| Article number | 7932545 |
| Pages (from-to) | 1044-1048 |
| Number of pages | 5 |
| Journal | IEEE SIGNAL PROCESSING LETTERS |
| Volume | 24 |
| Issue number | 7 |
| Early online date | 23 May 2017 |
| DOIs | |
| Publication status | Published - 1 Jul 2017 |
Keywords
- Online learning
- Storage management
Access to Document
- Adaptive Energy Storage Management_ZHANG_Accepted15May2017_GREEN AAM
(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.