Model-based optimal control of VAV air-conditioning system using genetic algorithm
S Wang, X Jin - Building and Environment, 2000 - Elsevier
S Wang, X Jin
Building and Environment, 2000•ElsevierA control strategy using a system approach based on predicting the responses of overall
system environment and energy performance to the changes of control settings of VAV air-
conditioning systems is developed. Incremental dynamic models with 'self-tuning'of the VAV
system are developed and used. A genetic algorithm is used by the strategy to solve the on-
line optimisation problem of multiple parameters. The strategy is tested and evaluated in a
simulated 'living'environment under various weather conditions.
system environment and energy performance to the changes of control settings of VAV air-
conditioning systems is developed. Incremental dynamic models with 'self-tuning'of the VAV
system are developed and used. A genetic algorithm is used by the strategy to solve the on-
line optimisation problem of multiple parameters. The strategy is tested and evaluated in a
simulated 'living'environment under various weather conditions.
A control strategy using a system approach based on predicting the responses of overall system environment and energy performance to the changes of control settings of VAV air-conditioning systems is developed. Incremental dynamic models with ‘self-tuning’ of the VAV system are developed and used. A genetic algorithm is used by the strategy to solve the on-line optimisation problem of multiple parameters. The strategy is tested and evaluated in a simulated ‘living’ environment under various weather conditions.
Elsevier
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