Abstract

Increasing roof reflectance reduces absorption of solar radiation, roof surface temperature and heat ingress into the building. This leads to an increase in indoor comfort and reduction in room air temperature that in turn results in energy saving by reducing AC demand. To assess this impact of cool roofs on buildings in rural and peri-urban areas of India, a study was performed on two un-conditioned school buildings in Hyderabad (ZPH School) and Nagpur (VNHM School). Two classrooms of same size, function, and occupancy from both the school buildings were monitored for a period of ten weeks starting from March 2014 till May 2014. The data from the experiments and their analyses showed promising results. The average reduction and peak reduction in indoor air, roof underdeck and roof overdeck surface temperatures are 2.1 ◦C, 5.0 ◦C and 12.3 ◦C and 4.3 ◦C, 10.0 ◦C and 26.3 ◦C respectively for the room with white roof as opposed to grey roof in ZPH School and 1.5 ◦C, 4.0 ◦C and 9.5 ◦C, and 3.3 ◦C, 4.2 ◦C, and 25.2 ◦C respectively in VNHM School. The results from the experiment prove that white roof has a significant effect in reducing the indoor air temperatures in buildings due to reduction in outdoor and indoor roof surface temperature

Abstract

Selecting a high albedo (solar reflectance) waterproofing layer on the top of a roof helps lower the roof’s surface temperature and reduce the air conditioning energy consumption in the top floor of a building. The annual energy savings depend on factors including weather, internal loads, and building operation schedule. To demonstrate the energy saving potential of high albedo roofs, an apparatus consisting of two nearly identical test chambers (A and B) has been built in four Indian climates: Chennai (hot & humid), Bangalore (temperate), Jhagadia (Hot & dry) and Delhi (composite). Each chamber has well-insulated walls to mimic the core of an office building. Both chambers have the same construction, equipment, and operating schedule, differing only in roof surface. The reinforced cement concrete roof of Chamber A is surfaced with a low-albedo cement layer, while that of Chamber B is surfaced with a high-albedo water proof membrane (change in solar reflectance of 0.28). The experiment will be carried out for one year to explore seasonal variations in energy savings. Initial results in the month of July (post summer) shows that savings from high albedo roof ranges from 0.04 kWh/m2/day in temperate climates, to 0.08 kWh/m2/day in hot & dry climate.

Abstract

This paper demonstrates the application of Autotune, a methodology aimed at automatically producing calibrated building energy models using measured data, in two case studies. In the first case, a building model is de-tuned by deliberately injecting faults into more than 60 parameters. This model was then calibrated using Autotune and its accuracy with respect to the original model was evaluated in terms of the industry-standard normalized mean bias error and coefficient of variation of root mean squared error metrics set forth in ASHRAE Guideline 14. In addition to whole-building energy consumption, outputs including lighting, plug load profiles, HVAC energy consumption, zone temperatures, and other variables were analyzed. In the second case, Autotune calibration is compared directly to experts’ manual calibration of an emulated-occupancy, full-size residential building with comparable calibration results in much less time. The paper concludes with a discussion of the key strengths and weaknesses of auto-calibration approaches.

Abstract

SURROGATE CITY FINDER - WEATHER DATA TOOLVishal Garg, T.V.S Nikhil, Hema Rallapalli,Aviruch Bhatia, Jegibabu Subhash, Chetan Kasireddy International Institute of Information Technology, Hyderabad, India. ABSTRACTWeather data is the one of the important inputs for the building energy simulation and is available for almost all major cities of the world. However, there are still some cities, for which weather data is not readily available in the format suitable for energy simulation. To address this problem, we have developed a web-based tool called Surrogate City Finder (SCF). For a given location, for which there is no weather file available, the tool shortlists the best-matched weather files based on parameters such as the latitude, altitude, and temperature range of the given location. The SCF tool has been tested by analysing the annual energy consumption of 16-reference building models simulated for eight locations from different international climate zones and their surrogate cities. In most cases, the deviation in annual energy consumption was within two percent.

Abstract

To make roofs energy efficient, typically two types of techniques are followed: surface treatments (coolroofs, radiant barriers) and thermal property modifications (roof insulation). The interplay between thesetwo techniques has been studied using energy simulations. A single storey, daytime operational, officebuilding of 200 m2area has been simulated forfive climatic zones in India. A total of 88 different roofcombinations have been studied for each climatic zone. An economic analysis using Internal Rate ofReturn has been performed to identify a suitable roof insulation thickness for a roof with high albedo,and radiant barrier combination. The incremental benefits in energy savings reduces by adding insulationafter a limit. For a roof with albedo of 0.6 and radiant barrier emittance of 0.2, the optimized roofR-valueis 0.49 m2K/W in hot and dry and composite climates, 0.31 m2K/W in warm and humid and temperateclimates, and 1.02 m2K/W for cold climates

Abstract

Plug loads accounts for 20% to 30% of building energy consumption and has an increasing trend. Automatic plug load identification is one of the technique for effectively managing the plug load consumption.There are several studies on Non Intrusive load monitoring (NILM) but limited studies on Intrusive load monitoring (ILM). ILM is a technique that uses a low end power meter on every plug load to monitor it’s power consumption. In this paper, machine-l earning techniques are applied on low-frequency ILM data for identification of plug load and it’s state (ON/Sleep).The results show the identification accuracies are close to 98%

Abstract

Energy utilization can be improved by precise plug load monitoring and control. Plug load energy consumption is nearly 30% of the total building energy consumption. Therefore, plug load identification is a key requirement for energy conservation in buildings. Intrusive load monitoring techniques identify loads precisely but have not been tested widely so far for their performance in changing operating conditions. Hence, the present research proposes a robust low frequency intrusive load monitoring technique to identify load accurately. A smart power strip using proposed load identification technique is designed and developed. Linear regression is applied on the acquired data to capture the behavioral trends of a particular device more explicitly and concisely. Further, weighted K-NN classifier is applied on the transformed data set for device. Experimental results show that the proposed algorithm performs better than the standard classifiers, and can offer tangible savings.

Abstract

Fault detection and diagnostics (FDD) is a method to monitor a system, identify when a fault has occurred, and point out the type of fault and its location. This method improves comfort, and reduces the operation, maintenance, and utility costs, thus reducing the environmental impact. In this paper, the design of FDD lab is presented where a user can create different types of faults in Heating, Ventilation and Air-conditioning (HVAC) systems, and develop and test algorithms for the detection and diagnostics of faults. This facility will help identify and analyse the faults pertaining to HVAC systems that are prevalent in India nowadays.

Abstract

Increasing roof reflectance reduces absorption of solar radiation, roof surface temperature and heat ingress into the building. This leads to an increase in indoor comfort and reduction in room air temperature that in turn results in energy saving by reducing AC demand. To assess this impact of cool roofs on buildings in rural and peri-urban areas of India, a study was performed on two un-conditioned school buildings in Hyderabad (ZPH School) and Nagpur (VNHM School). Two classrooms of same size, function, and occupancy from both the school buildings were monitored for a period of ten weeks starting from March 2014 till May 2014. The data from the experiments and their analyses showed promising results. The average reduction and peak reduction in indoor air, roof underdeck and roof overdeck surface temperatures are 2.1 ◦C, 5.0 ◦C and 12.3 ◦C and 4.3 ◦C, 10.0 ◦C and 26.3 ◦C respectively for the room with white roof as opposed to grey roof in ZPH School and 1.5 ◦C, 4.0 ◦C and 9.5 ◦C, and 3.3 ◦C, 4.2 ◦C, and 25.2 ◦C respectively in VNHM School. The results from the experiment prove that white roof has a significant effect in reducing the indoor air temperatures in buildings due to reduction in outdoor and indoor roof surface temperature.

Abstract

This article presents the effect of envelope measures on thermal environmental conditions of a naturally ventilated building block in composite climate of India. Envelope measures such as roof U-value, wall U-value, glass U-value and glass solar heat gain coefficient, roof reflectance and two combinations of these measures (total seven cases) are analysed as recommended by National Energy Conservation Building Code-India (ECBC) through prescriptive route. Subject building is modelled and simulated using dynamic thermal simulation tool. Two approaches of thermal comfort have been used in this study such as heat balance model based on laboratory study and adaptive model of thermal comfort based on field findings. Thermal environmental conditions are evaluated based on operative temperature with and without considering the effect of thermal adaptation. This study found that comfortable temperature …