Usage of PSO algorithm for parameters identification of district heating network simulation model

International Conference on Systems - Proceedings

Volumn 1, Issue , 2010, Pages 657-659

  Král, Erik ^a   Lubomír, Vašek ^a   Dolinay, Viliam ^a   Vařacha, Pavel ^a  

^a TOMAS BATA UNIVERSITY IN ZLIN   (Czech Republic)

Author keywords

District heating; Heat load modeling; Particle swarm optimization; Simulation model

Indexed keywords

DATA SETS; DISCRETE SIMULATIONS; DISTRICT HEATING NETWORKS; HEAT DISTRIBUTION; HEAT-LOAD MODELING; HEATING NETWORK; IDENTIFICATION OF MODEL; PARAMETERS IDENTIFICATION; PARTICLE SWARM; PSO ALGORITHMS; SIMULATION MODEL;

DISTRICT HEATING; HEATING; HEATING EQUIPMENT; IDENTIFICATION (CONTROL SYSTEMS); PARAMETER ESTIMATION; PARTICLE SWARM OPTIMIZATION (PSO);

COMPUTER SIMULATION;

EID: 78549281037     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

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2. Helge L., Benny B., Michael W. A comparison of aggregated models for simulation and operational optimisation of district heating networks, Energy Conversion and Management, Volume 45, Issues 7-8, May 2004, pp. 1119- 1139, ISSN 0196-8904
3. Heller J. Heat-load modelling for large systems, Applied Energy, Volume 72, Issue 1, May 2002, Pages 371-387, ISSN 0306-261
4. Kennedy J., Eberhart R. Particle Swarm Optimization. Proceedings of IEEE International Conference on Neural Networks. IV. pp. 1942-1948.
5. Martǐ L., Garcǐa J., Berlanga, A., Molina, M. An approach to stopping criteria for multi-objective optimization evolutionary algorithms: the MGBM criterion. In Proceedings of the Eleventh Conference on Congress on Evolutionary Computation. Trondheim, Norway, May 18 - 21, 2009. IEEE Press, Piscataway, NJ, 1263-1270.
6. Vařacha, P. (2009). Impact of Weather Inputs on Heating Plant - Agglomeration Modeling. Proceedings of the 10th WSEAS International Conference on Neural Networks, Prague, Mastorakis, N., pp. 159-162, ISBN 978-960- 474-065-9