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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Sankur, M. Arnold, D. Auslander, D. |
| Copyright Year | 2015 |
| Description | Author affiliation: Dept. of Mech. Eng., Univ. of California, Berkeley, Berkeley, CA, USA (Sankur, M.; Arnold, D.; Auslander, D.) |
| Abstract | Plug-loads are often neglected in commercial demand response (DR) despite being a major contributor to building energy consumption. Improvements in technology like smart power strips are prompting the incorporation of plug-loads as a DR resource alongside building HVAC and lighting. Office scale battery storage (OSBS) systems are also candidates as a DR resource due to their ability to run on battery power. In this work, we present a model predictive control (MPC) framework for optimal load-shedding of plug-loads and OSBS.We begin with discussion of the context of this work, and present two models of OSBS systems. A model predictive controller for OSBS and plug-load load-shed scheduling is presented. We discuss casting the MPC as a dynamic program, and an algorithm to solve the dynamic program. Simulation results show the efficacy and utility of dynamic programming, and quantify the performance of OSBS systems. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 196550 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467380409 |
| DOI | 10.1109/PESGM.2015.7285755 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-07-26 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Batteries System-on-chip Uninterruptible power systems Buildings Load modeling Mathematical model Dynamic programming Battery Storage Optimization Demand Response Load Following Model Predictive Control Distributed Plug Load Control |
| Content Type | Text |
| Resource Type | Article |
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