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Optimal control of energy hub systems by use of SQP algorithm and energy prediction

Author
Kampouropoulos, K.; Sala, E.; Andrade, F.; Romeral, L.
Type of activity
Presentation of work at congresses
Name of edition
40th Annual Conference of the IEEE Industrial Electronics Society
Date of publication
2014
Presentation's date
2014-11
Book of congress proceedings
IECON 2014: 40th annual conference of the IEEE Industrial Electronics Society: Dallas, Octorber 29-November 1, 2014: proceedings
First page
202
DOI
10.1109/IECON.2014.7048503
Repository
http://hdl.handle.net/2117/27224 Open in new window
URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7048503 Open in new window
Abstract
This paper presents an energy optimization methodology applied on industrial plants with multiple energy carriers. The methodology combines an adaptive neuro-fuzzy inference system to calculate the short-term load forecasting of a plant, and the sequential quadratic programming algorithm to optimize its energy flow. Furthermore, the mathematical models of the plant's equipment are considered into the optimization process, in order to calculate the dynamic system response and the equipment's iner...
Citation
Kampouropoulos, K. [et al.]. Optimal control of energy hub systems by use of SQP algorithm and energy prediction. A: IEEE International Conference on Industrial Electronics. "Proceedings of the 40th Annual Conference of the IEEE Industrial Electronics Society". Dallas, TX: 2014.
Keywords
adaptive neuro-fuzzy inference system, energy hub, energy optimization, energy prediction, sequential quadratic programming algorithm
Group of research
MCIA - Motion Control and Industrial Applications Research Group
PERC-UPC - Power Electronics Research Centre

Participants