Analyzing a Decade Data with Proposed Indexes for HVAC Energy Management of Designated Buildings in Thailand

This paper presents the analysis of Energy Conservation Measures (ECMs) data of Heating, Ventilation, and Air Conditioning (HVAC) systems of designated buildings in Thailand to help decisions for applying ECMs in future energy management. Data acquired from annual energy management reports applied to the Department of Alternative Energy Development and Efficiency and used verification methods to enhance the accuracy of annual energy consumption and ECMs, in terms of annual investment, energy saving, and power reduction then calculate indexes to analyze 1. total energy saving, 2. energy saving ratio and 3. investment ratio. Indexes will be used to support further decisions for high-potential ECMs. First of all, the total energy saving from ECMs in Thailand is increasing consistently at 0.98% yearly. From the perspective of processes, Machine change (MC) has the highest proportion at 56.95% of energy saving with 49.61% of distributions of measures. From equipment point of view, split-type air conditioners (Split ACs) and Chillers were high energy saving at 40.66% and 37.15%, respectively. Secondly, the energy saving ratio of Chillers shows that MC process is 4.33 times more effective than Housekeeping (HK). While applying same HK process to Chillers is 2.35 times more effective than Split ACs. Lastly, the investment ratio of Chillers shows that MC requires 15.29 times higher investment than HK to achieve the same power reduction. Moreover, analyzing proposed indexes of designated buildings in this paper shows that if prioritized MC in Chillers will achieve higher energy saving compared to Split ACs while the investment ratio is only 1.77 times higher. In otherwise, from a number of unimplemented ECMs in the designated buildings show that Split ACs has 1.13 times higher potential of the overall energy saving when compared to Chillers. Finally, based on the equipment timelines, MC will require for all equipment by the end. However, considering investment and equipment conditions shows that at some point, HK and PI might be better in specific conditions and times.