论文信息 - A New Swarm Intelligence Approach for Optimal Chiller Loading for Energy Conservation

A New Swarm Intelligence Approach for Optimal Chiller Loading for Energy Conservation

This paper employs a recent swarm intelligence technique to solve optimal chiller loading (OCL) problem, namely differential search (DS) algorithm. In general, significant energy savings can be obtained by optimizing chiller operation and design in heating, ventilation and air-conditioning (HVAC) systems. In this paper, partial load ratio (PLR) of the chiller is used as parameters to be optimized where the power consumption in kW is used as objective function to be minimized. In order to show the effectiveness of the proposed technique, the comparison with other techniques has been done and analyzed.

[1] Lung-Chieh Lin,et al. Optimal Chiller Loading by Team Particle Swarm Algorithm for Reducing Energy Consumption , 2009, Energies.

[2] Viviana Cocco Mariani,et al. Improved firefly algorithm approach applied to chiller loading for energy conservation , 2013 .

[3] Pinar Civicioglu,et al. Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm , 2012, Comput. Geosci..

[4] Seyed Hossein Hosseinian,et al. A novel approach for optimal chiller loading using particle swarm optimization , 2008 .

[5] Wen-Shing Lee,et al. Optimal chiller loading by differential evolution algorithm for reducing energy consumption , 2011 .