Advanced demand response solutions based on fine-grained load control
| Autor: | Michal Pioro, Rim Kaddah, Daniel Kofman |
|---|---|
| Přispěvatelé: | Laboratory of Information, Network and Communication Sciences (LINCS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT), Télécom ParisTech, Institute of Telecommunications, Warsaw University of Technology [Warsaw], Department of Electrical and Information Technology (EIT), Lund University [Lund] |
| Rok vydání: | 2014 |
| Předmět: |
0209 industrial biotechnology
Load control switch Distributed computing Control (management) Real-time computing 020206 networking & telecommunications 02 engineering and technology Optimal control computer.software_genre News aggregator Demand response [INFO.INFO-NI]Computer Science [cs]/Networking and Internet Architecture [cs.NI] Load management 020901 industrial engineering & automation Computer appliance Scalability 0202 electrical engineering electronic engineering information engineering Business computer |
| Zdroj: | IEEE IWIES 2014 IEEE IWIES 2014, 2014, pp.38-45. ⟨10.1109/IWIES.2014.6957044⟩ |
| DOI: | 10.1109/iwies.2014.6957044 |
| Popis: | International audience; —We consider demand response solutions having the capability to monitor different variables at users' premises, like presence and temperature, and to control individual appliances. We focus on the optimal control of the appliances during time periods where the available capacity is not enough to satisfy the demand generated by houses operating freely. We propose an approach to define the utility of appliances as a function of monitored variables, as well as control schemes to optimize this utility. Global optimums can be reached when a centralized entity (i.e., an aggregator) can gather information from each user and control each individual appliance. This may not be always possible, for example for privacy and/or scalability reasons. We therefore consider, in addition, a system where decisions are taken partially at a centralized site (global power allocation per home) and partially at customer premises (sharing of the allocated power among local appliances). Performances of proposed control mech-anisms are evaluated and compared. We show the potential value of introducing demand response mechanisms at fine granularity. |
| Databáze: | OpenAIRE |
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