Estimating India’s commercial building stock to address the energy data challenge

ABSTRACT

Estimating the commercial building stock in terms of energy and area usage can be a tricky exercise in the absence of reliable and structured data. While the benefits of such an exercise are widely understood in some countries, no standard framework works in all countries due to the differences in workforce capacity and resources, national priorities, and energy data and analytics maturity of various countries. Hence, this paper documents an energy-accounting exercise that first collects commercial building sector data in India from multiple sources. An approach is then proposed that first divides the commercial building sector into categories and subcategories and then estimates the floor area (1.1 billion m²) and energy intensity (69 kWh/m²) of the entire commercial stock in 2017. Based on macro-economic parameters, the floor area (1.78 billion m²) and energy intensity (81 kWh/m²) are projected for 2027 in a business-as-usual scenario. This research sends a clear signal to other researchers and policy-makers in the central and state government about the need and potential to refine and adopt more rigorous data-collection and analytical methods by institutionalizing the process and advancing data-driven policies and evaluation in future.

KEYWORDS:

• big data
• building stock
• commercial buildings
• energy data
• energy intensity
• floor area
• India

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Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 An example of the data-proficient category includes the socioeconomic data survey in India by the National Sample Survey Office (NSSO), although it does not belong to commercial building sector. The survey data are used for different purposes by different ministries to achieve their respective development goals. For instance, the Ministry of Human Resource Development (MHRD), having access to high-quality MoSPI literacy rate data, launched various successful policy reforms to address literacy rates in India (MHRD, 2016).

2 The analyses presented here use data points and assumptions that have been discussed and, in some cases, validated by the following industry stakeholders and experts through consultations, surveys and interviews. The authors acknowledge the efforts of the following professionals: Bimal Tandon, Carrier UTC, Gohul Deepak, Glazing Society of India, Karan Mangotra, TERI, L. Venkatesh, C R Narayana Rao (Consultants) Pvt. Ltd, Ramendra Sahai, Symphony, SMH Adil, Global Evolutionary Energy Design, Tanmay Tathagat, EDS, Y P Singh, Fenesta Building Systems, Ashish Rakheja, AEON Integrated Building Design Consultants LLP, K. M. Prashanth, Narayana Hospitals, Kishor Kumar, KKSC, Markus Wypior, GIZ India, Mili Mujumdar, GBCI, Naveen Gupta, CBRE, Parag Parekh, J P Parekh & Son, Architects, Punit Desai, Infosys, Rajan Rawal, CEPT, Rajsekhar Inglay, WIPRO, Rohit Chashta, Schneider Electric, Roopesh Sharma, 75F, Rumi Engineer, Godrej & Boyce Mfg. Co. Ltd, S Srinivas, IGBC, Sandeep Dahiya, Independent Consultant, Building, Sanjay Seth, TERI, Varun Vermani, JLL, Vishal Garg, IIIT, Vishwajeet Poojary and Vivek Gilani, and cBalance Solutions Pvt. Ltd.