The operation of chillers plant in the HVAC system is not ideally efficient in major academic buildings because the chillers are operated without accounting for the cooling load demand of the air-conditioning area of the building. The current operation of the chillers plant may fall under two cooling effects, namely excessive cooling effect that will reduce the efficiency of the chillers and inadequate cooling effect that may create an unpleasant environment inside the air-conditioning area. This is because the cooling load demand of the air-conditioning area of the building is unknown and is not numerically measured. The main aim of this study is to find the optimal operation of chillers plant in HVAC system by formulating an optimization framework with the main goal of minimizing energy consumption and electricity costs. The formulation of the optimization framework for chillers plant operation is modelled as Linear Programming (LP) to establish real representation of the chillers plant. The energy consumption profile, cooling load demand, cooling capacity and COP can be obtained by using historical data analysis. The optimization framework is modelled in GAMS v38.2.1 and solved by CPLEX solver to obtain the optimum input for the chillers plant in the HVAC system. The minimum total power consumption can be achieved by optimally coordinating the operation of chillers, cooling towers and AHUs while maintaining room temperature. From the cost comparison analysis between the current and optimal chillers plant, considerable cost reduction is expected to be less than 5 % if the chillers plant is operating efficiently or greater than 30 % if the chillers plant is not functioning effectively. Therefore, this study is beneficial to the administration of academic building to find a strategic action plan to promote cost optimization in the operation of the chillers plant.
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The authors are gratefully recognised Universiti Teknikal Malaysia Melaka (UTeM) for providing financial support under short term research grant with grant number, PJP/2021/FKM/S01809.
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