Aggregation and Control of Populations of Thermostatically Controlled Loads by Formal Abstractions
- Submitting institution
-
University of Newcastle upon Tyne
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 261443-227916-1292
- Type
- D - Journal article
- DOI
-
10.1109/TCST.2014.2358844
- Title of journal
- IEEE Transactions on Control Systems Technology
- Article number
- 3
- First page
- 975
- Volume
- 23
- Issue
- -
- ISSN
- 1063-6536
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2014
- URL
-
https://doi.org/10.1109/TCST.2014.2358844
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
1
- Research group(s)
-
A - Advanced Model-Based Engineering and Reasoning (AMBER)
- Citation count
- 48
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper introduced a new formal two-step abstraction procedure to generate a finite stochastic dynamical model as the aggregation of the dynamics of a collection of thermal loads. The approach relaxes the limiting assumptions of previous methods by providing a model based on the native probabilistic evolution of temperature in each load. As a result of the significant theoretical and application-based contribution of this work, Soudjani’s PhD thesis won the DISC Best Thesis Award for the best thesis defended in the field of System and Control in the Netherlands in 2015.0).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -