Energy optimization methodology of multi-chiller plant in commercial buildings. (15th March 2017)

• Record Type: Journal Article
• Authors: Thangavelu, Sundar Raj; Myat, Aung; Khambadkone, Ashwin
• Is Part Of: Energy. Volume 123(2017)
• Page Start: 64
• Page End: 76
• Publication Date: 2017-03-15
• Subjects: Energy savings -- Buildings -- Absorption chillers -- Optimization -- Multi-chiller plants; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2017.01.116
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions. Highlights: Energy optimization methodology improves the performance of multi-chiller plant. Overall energy model of chiller plant accounts all equipment and the interactions. Operation decisions are derived at regular interval based on time-varying factors. Three case studies confirmed 20 to 40% of energy savings than conventional method.