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Energy efficiency improvement of solar water heating systems – An IoT based commissioning methodology

Abstract This paper studies a mechanism to investigate and to improve the energy efficiency of a solar water heating system (SWH) in a hospital building located in Singapore. We utilize the data collected from Internet-of-Things (IoT) to gain information on different environmental and operational aspects of the considered system, that determine opportunities for improving the efficiency of various sub-systems of the SWH, and develop control strategies for efficient operation of the overall system. Through the data collected by IoT, such as water flow, heat pump and water pump operational schedule, availability of solar, and electricity consumption, we perform a comprehensive energy audit to analyze the efficiency of sub-systems and the performance of overall system as well. Based on the insights obtained from data analysis, corresponding control strategies for various sub-systems are developed to improve the efficiency of the overall system and reduce the operational cost of the SWH. Finally, the effectiveness of the proposed control strategies is confirmed through experiment on the site of the considered SWH.
- Queensland University of Technology Australia
- Khoo Teck Puat Hospital Singapore
- University of Queensland Australia
- Singapore University of Technology and Design Singapore
- University of Queensland Australia
690, 2208 Electrical and Electronic Engineering, Hot water, 2205 Civil and Structural Engineering, 2210 Mechanical Engineering, Energy conservation, Energy analysis, Solar thermal, Energy efficiency, 2215 Building and Construction
690, 2208 Electrical and Electronic Engineering, Hot water, 2205 Civil and Structural Engineering, 2210 Mechanical Engineering, Energy conservation, Energy analysis, Solar thermal, Energy efficiency, 2215 Building and Construction
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).31 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
