ck2017: electricity use in urban households - data and demand aggregation
TRANSCRIPT
A product of WRI Ross Center for Sustainable Cities
SUMEDHA MALAVIYA, SENIOR PROJECT ASSOCIATE, INDIA ENERGY PROGRAM
ELECTRICITY USE IN URBAN HOUSEHOLDS
DATA AND DEMAND AGGREGATION
Co
mm
on
Se
rvic
es
(20
%)
ELECTRICITY USE IN APARTMENT COMPLEX
Sources- BEE Design guidelines for energy efficient multistorey residential
buildings for hot and dry and composite climates
Water pumping (17%)
Common lighting (21%)
Lifts (62%)
Individual Households (80%)
Space cooling (45%) Lighting (28%), Refrigeration (13%) and others (14%)
River Water Utility
Power Utility
WHAT ARE WE TRYING TO DO?
1
2
3
1. Reduce aggregate electricity demand from one/more
residential community(ies) through EE interventions
3. Through efficient pumping, reduce water
demand in community(ies) and energy
burden on water utility during distribution
2. Meet portion of reduced demand
through Renewables (mainly solar PV)
WHY WORK WITH RESIDENTIAL SECTOR?
Sources: IEA ETP 2016, GBPN 2014
The challenge
• Residential floor area escalation-400-500% by 2050
• GDP growth
• Limited data
• Limited understanding
The Opportunity
• Understand energy use in residential buildings
• Establishing baselines and benchmarking energy performance
• DSM and/DR
• Supply planning
APPROACHES FOR ENERGY USE DATA COLLECTION
Bottom up
Top down
Most techniques use a combination of following –
Surveys (Household level)
Administrative Sources
Individual in-site measurements
Modeling
METHODS USED GLOBALLY
• US- Residential Energy Consumption Survey (RECS)
• Europe- All member states use household level surveys
Administrative sources (55%) + modelling (45%)
In-site measurements (30%)
• China- Ad-hoc surveys done by several agencies; China
Residential Energy Consumption Survey (C-RECS) done
in 1998
WHAT IS KNOWN ON RESIDENTIAL ELECTRICITY
CONSUMPTION IN INDIA?
Source: Prayas Energy Group, 2017
Questions addressed
Data/studies Gaps
Electricity used by households
National- MOSPI Energy Statistics and CEA Electrical Power Surveys (EPS)State- CEA Annual General Reviews
(1)electricity generated from local sources (2)generators, solar rooftop and micro-grids(3)use of unauthorized electricity by households; (c)
distinction between consumer categories as determined by connections
Household- NSSO Seasonal variation of electricity consumption
End-uses for electricity
World Bank 2008, Prayas2010, Niti Aayog 2012
No systematic surveys done at national, state, city level
Appliance ownership
National- NSSO 2012, IHDS 2012
State- Prayas, DISCOM studies in specific states
No national level data on number of appliances owned and their type
WHAT IS KNOWN ON RESIDENTIAL ELECTRICITY
CONSUMPTION IN INDIA?
Source: Prayas Energy Group 2017
Questions addressed
Data/studies Gaps
Appliance efficiencies
BEE data BEE collected available only until 2010
Usage of appliances
DISCOM load researchstudies+surveys commissioned by BEE, Prayas, World Bank, NitiAayog, Murthy et al.
Combination of feeder line analysis and survey of households
Factors effecting electricity consumption
Prayas ESMI, World Bank 2008, NSSOBuildings studies- CEPT University, GBPN, Indo-Swiss BEEP
Limited program evaluation studies, on awareness of star labelled appliances and on impact of human behaviour
Future projections
World Bank 2008, CEA EPS, NitiAayog 2012
Difficult to completely trust projections made by any study since generally data is not robust
INTERDISCIPLINARY RESEARCH
Source: Zhou and Yang 2016
Interdisciplinary research areas of energy, social and information sciences
OUR APPROACH
Identify aggregators
Collect baseline data
Identify energy conservation measures
Implement
Monitoring and reporting results
EXPECTED OUTCOMES
• Energy demand reduction- Through EE and RE for aggregator
community(ies)
• Cost-effective EE projects- Potential application of short payback
period EE investments in large gated communities
• Engaged utilities and regulators- Inform and influence DSM
decision making by power utility and regulators
Co
mm
on
Se
rvic
es
(20
%)
STARTING POINT
Water pumping (17%)
Common lighting (21%)
Lifts (62%)
Individual Households (80%)
Space cooling (45%) Lighting (28%), Refrigeration (13%) and others (14%)
River Water Utility
Power Utility
We don’t know- Appliance ownership, type and usage
- Appliance efficiency information
We don’t know- Power consumption
by common services
- Availability/capacity
for solar
interventions
- Willingness of
communities to
adopt EE and RE
- Economics
Co
mm
on
Se
rvic
es
(20
%)
WHERE WE HOPE TO REACH
Water pumping (17%)
Common lighting (21%)
Lifts (62%)
Individual Households (80%)
Space cooling (45%) Lighting (28%), Refrigeration (13%) and others (14%)
River Water Utility
Power Utility
Known: Existing efficiency levels
Behavioural and operational patterns of
appliances
EE and EC practices
Known: Power
consumption by
common services
Efficiency levels of
appliances and
equipment
Possibility for
efficiency gains