CLASP, in partnership with Bureau of Energy Efficiency, conducted a 'first of its kind' study which included a survey on residential electricity consumption (RECS) of 5,000 households and a Non- Intrusive Load Monitoring (NILM) of electricity end-use of 200 households representing the various socio-economic classes and climatic zones.
The project has been managed and executed by CLASP implementing partner Environmental Design Solutions (EDS). The household survey was done by Market Xcel, and meters for load monitoring were procured from Zenatix.
The survey findings and monitoring data analysis will help in establishing a realistic end-use baseline on appliance energy consumption and consumer behavior patterns which can be used for better future electricity demand projection and demand side strategies. A comprehensive dashboard 'National Energy End-use Monitoring (NEEM)', developed captures the survey findings and the end-use monitoring data.
This dashboard displays live energy use of the all the monitored households across India as well as outcomes of detailed appliance use household survey. It presents information on energy use, peak demand and other performance metrics across time that may be customized based on geography, climate and household type. It is anticipated that the dashboard will catalyze discussions towards a roadmap for future policy work for energy efficiency.
India is one of the fastest growing economies and with a four-fold growth rate over the global average; it is expected to remain so over the next several years. Economic development, urbanization, growing per capita income and increasing population are key drivers of this growth. Expectedly, energy demand will increase significantly in the coming years, primarily driven by increasing usage of appliances and equipment.
Residential sector accounted for 4% of the total electricity consumption in 1971, to 24% in 2016 and is projected to rise more than eight times by 2050. (Figure 1).
Figure 1 India's sector-wise distribution of electricity consumption in 2016. Source- Ministry of Statistics and Programme Implementation-MOSPI (2017)
However, there is limited data on residential energy end-use and absence of appliance energy consumption data at the household level. Also, India has a well-established appliance energy efficiency standards and labeling (S&L) program covering 23 products of which 13 are under mandatory regulation. Several more residential appliances are slated to come under its purview over the next few years.
Currently in India, all data related to appliance use and residential energy end-use is based on assumptions and limited information. As the penetration of appliances and subsequent energy use expands in Indian households, it is pertinent to establish real time end-use consumption and behavior patterns to be factored in formulating energy policies, assessing the actual impacts from these energy policies like S&L and developing outreach and awareness strategies for the consumers.
The program has two key components:
A preliminary research of census data led to a national representative sample of 8,448 households, which included urban and rural households. The primary sampling units were based on the five climatic zones.
Each climatic zone was largely allocated a proportionate population sample. To capture the gamut of urban households, the study scope was restricted to metropolitan cities and, Tier 2 and 3 cities. Accordingly, representative sample has been adjusted to 5,242 households for the survey.
The study scope was restricted to upper socio-economic classifications (SECs) (High/Rich and Middle SEC), as lower SEC may not yield diversity of appliances and therefore lesser utilization potential for monitoring hardware.
Further, upper socio-economic classifications (SECs) were given more representation for potential engagement during monitoring stage with diverse groups with variety of appliances. This was a key differentiator amongst target audience, thus making broad segmentation possible. A household with mere bulbs, fans etc. would have limited value, when compared to a household with variety of equipment and appliances. Hence the study focused at targeting the Urban Upper and Middle class.
1. High Income Group: The high-income group consists of individuals who fall under SEC A1, A2, A3 and
B1. They constitute 22% of the total households. In terms of appliance/ goods ownership, the high-income
group tends to own more than 70% of the common household items up to 60% of the high-end items and about
30% of the other premium products.
2. Middle Income Group: The middle-income group consists of individuals who fall under SEC B2, C1 and C2. They constitute 34% of the total households. In terms of appliance/ goods ownership, the middle-income group tends to own more than 70% of the basic household items up to 60% of the common household items and about 30% of the other products.
3. Low Income Group: This is the lowest rung in the income group strata and constitute 43% of the total households. In terms of appliance/ goods ownership, this group tends to own more than 70% of the most basic household items up to 60% of the other basic house hold items like and about 30% of the products.
The data represents urban-electrified population with skew towards upper and middle-class families on account of higher penetration of wider range of appliances.
As per census, Urban India population to rural population.
The sample size is representing of an urban population of 38 Crores. Within the urban population segment, it further represents urban upper and middle-class population.
Further, this dataset was compared to a relatively robust database from NSSO, which accounts for 42,000 urban households.
The survey dataset largely corresponds with the NSSO database. Although there are variations, these can be attributed to: increase in spending power, especially in comparison over the last 5 years. The bias of the surveyed dataset is towards higher SECs.
The findings reflected in the survey in comparison to the NSSO survey, electronic assets owned by the Indian Population is given below –
Metering, Monitoring and Analysis
Sample Size Calculation
In view of the research objective, NEEM survey covered all the climatic zones (Thereby picking representative sample largely in proportion to the population residing in respective climatic zones).
In phase 2, reference was made to the cities from amongst the different climatic zones that were studied in household survey. Overall, 21 representative cities were studied in phase 1. In phase 2, a sample size of 200 was considered across the climatic zones and across 13 cities.
|Climatic Zone||Population Proportion||Number of Cities||Sample||Sample Percentage Allocation|
*Sample percentage allocation for cold and temperate climatic zone was revised to have fair representation from the same.
At micro level, factors such as ownership of household, electricity consumption and the SEC, etc. were considered.
Sample was finalized by giving a higher weightage to upper and middle consumer profile and inverse allocation to lower Income band. For cities like Mumbai one room dwellings were considered, as middle-class families owning certain appliances also dwell in such houses owing to space constraints.
The finalized sample:
Dwelling Type Penetration in Phase 2
|Census Data||Sample As Emergent As Per Dwelling Types|
|Center||Sample||1 Room||1 BHK||2 BHK||3 BHK||More thank 3 BHK||1 Room||1 BHK||2 BHK||3 BHK||More thank 3 BHK|
The dashboard on actual electricity consumption states approximately 138 units per month per household. However, when benchmarked with Urban India it is approximately 90 units per month.
The difference is on account of small sample and more coverage of middle-class families as compared to a representative sample.
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This dashboard is representative of our reasonable effort to produce and publish accurate information for the study period. The NEEM team makes no warranty, expressed or implied; representation; or guarantee as to the content, accuracy, or completeness of the data provided.
The NEEM team shall assume no liability for any decisions made or actions taken or not taken by the user of this dashboard, or third parties in reliance upon any information or data furnished hereunder. The use of this information indicates the user’s unconditional acceptance of the above disclaimer.