International Conference on TIM, 2012, Nepal
Electricity Demand Side Management
in
Residential Sector of Kathmandu Valley
Sujan Adhikari
Prof Amrit Man Nakarmi
Institute of Engineering
Pulchowk Campus ,Lalitpur, Nepal
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International Conference on TIM, 2012, Nepal
Research Objectives
• Determine the current electricity consumption pattern of
residential sector of Kathmandu Valley.
• Forecast the electricity demand of residential sector
Kathmandu Valley.
• To propose suitable Demand Side Management strategies.
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International Conference on TIM, 2012, Nepal
Electricity consumption pattern
• 13% of energy consumed in Nepal is through commercial source
(WECS,2010)
• 48% of population have access to electricity of which 8% of people
reside in rural areas (MOF,2007)
• Increasing residential consumer base
• Decreasing per capita electricity consumption
Year
Total No of
Domestic
Average
Per capita
Domestic
Electricity
Household
electricity
Consumers
Consumption
Size
consumptio
(GWh)
n (KWh)
2011
1948968
1170.77
4.7
127.81
2001
713307
518.36
5.44
133.58
(Source: NEA Annual Report, 2011; CBS Preliminary Survey, 2011)
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International Conference on TIM, 2012, Nepal
Concept of Demand Side Management
• Demand Side Management
Demand side management (DSM) also known as Energy
demand management is the modification of consumer
demand for energy through various methods.
• Alternative to supply side “overspending” in energy systems
(NILSSON, 2007).
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International Conference on TIM, 2012, Nepal
Residential Sector
• In context of Nepal, residential accounts for the major share
of energy
consumption (89.1%) (Wecs, 2010).
• 44% of the total electricity consumption in Nepal is in
residential sector
Commercial
7%
Agricultural
2%
Residential
44%
Share of electricity consumption
other
9%
Transport
0.20%
Industrial
38%
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International Conference on TIM, 2012, Nepal
Kathmandu Valley
• Limitations
 Urban areas of Kathmandu Valley.
 Municipal boundaries of Kathmandu Valley considered as
the urban limits.
• Electricity consumption characteristics
 29.2% of total electricity distributed by the Nepal Electricity
Authority is consumed in Kathmandu Valley alone. (NRB,2012)
 Kathmandu municipalities alone constitutes about 36% of the
total urban households (CBS,2011)
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International Conference on TIM, 2012, Nepal
Methodology
• Questionnaire Design
• Sample Design
• Household Survey
• Analysis and conclusion
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International Conference on TIM, 2012, Nepal
Questionnaire Design
• Household Characteristics
Characteristics
Household Income
Description
Total household income per month
Nepalese Rupees (Nrs)
Household size
Number of individuals in the household
Rooms
No of Children
Number of rooms in the household
Number of children in the household
• Variables
 Number of Appliance
 Operating hour of the Appliance
Rating of the appliance
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International Conference on TIM, 2012, Nepal
Regression Result
• Average electricity consumption was regressed with the household
characteristics
Coefficients
-61.28
Standard
Error
29.20
t Stat
-2.10
0.0018
0.0002
7.49
FS
8.81
7.16
1.23
NC
21.90
16.40
1.34
6.85
3.43
2.00
ID
Intercept
Monthly Income
(Nrs)
MI
Family size
Number of
children
Number of
rooms
R
R2= 0.765
Therefore the regression equation is
E= -61.28+0.002 MI + 8.811FS+21.9 NC+6.85R
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International Conference on TIM, 2012, Nepal
Sample Design
• Size of the sample, n
2*N*(1-P)
ME2(N-1) + ( 2*P*(1-P))
Source: Source: Morgan et all.1970
Where
n = required sample size
2 = Chi square for the specified confidence level at 1
degree of freedom
N = Population size
ME = Desired Marginal error (expressed as a proportion)
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International Conference on TIM, 2012, Nepal
Household Survey
Household sample surveys have become a key source of data on social
phenomena in the last 60-70 years
S.N
Income
1
2
<15,000
Poorest
15,000-25,000 Second
3
25,000-40,000 Third
4
40,000-80,000 Fourth
5
80,0002,00,000
Total
Class
Qty
of Share
electricity used (%)
(Units/Month)
47.9
8
74.7
40
103
39
132
9
200
4
100
Richest
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International Conference on TIM, 2012, Nepal
LEAP Modelling Framework
Modeling Conditions
The base year for the model was 2012 and horizon of
18years was used, thus modeling until 2030.
Discount rate used in model was 12%.
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International Conference on TIM, 2012, Nepal
LEAP Modelling Framework
Projection
•
Household projection
Y=119519*exp (0.6025*x) where x is the number of year.
Year
2012
2015
2020
2025
2030
Households
No (Lakhs)
3.9
4.9
6.7
9.2
12.6
• Household income
• Appliance ownership
 Energy ladder hypothesis
 Regression between household income and appliance number
 Result showing R2 value greater that 75% is considered
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International Conference on TIM, 2012, Nepal
Scenario Selection
• Business As Usual (BAU) Scenario
 5.4% household income growth rate
• Medium Income Growth (MG) scenario
 5.5 % national GDP growth rate
 8.7% household income growth rate
• High Income Growth (HG) scenario
 7% national GDP growth rate
 11.1% household income growth rate
• DSM Scenario
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International Conference on TIM, 2012, Nepal
Scenario Result
Electricity Consumption (Million Kilowatt
Hours)
Scenario
2012
2015
2020
2025
2030
HG
1252
1816
3155
5368
9066
MG
1252
1766
2952
4853
7909
BAU
1252
1691
2660
4148
6427
Scenario Comparison
Electricity Consumption
(Million Kilowatt Hours)
10000
BAU-9.5%
MG-10.7%
HG- 11.6%
8000
6000
4000
2000
0
2010
2015
2020
HG
MG
2025
Year
BAU
2030
2035
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International Conference on TIM, 2012, Nepal
DSM Criteria
•
•
•
DSM Options
DSM 1
 Replacement of all of the widely used incandescent lamps of rated power 40 W
and 100 W to CFL of rated power 20W in the poorest households by the end of
2030.
 Replacement of widely used 36 W fluorescent lights and 40 W and 100 W
incandescent light in the above poorest households by LED lights of 13 W by
the end of 2030.
DSM 2
 Replacement of electrical water heater by solar water by the end of 2030.
DSM 3
 All light will be replaced by solar powered LED lights.
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International Conference on TIM, 2012, Nepal
DSM Result (Energy Savings)
• Electricity consumption under DSM implementation scenario
was compared with the MG scenario
• DSM1
 7320.6 GWh of electricity savings by the end of modeling
period.
• DSM 2
 146.2 GWh of electricity savings by the end of modeling period.
• DSM3
 7885 GWh of electricity can be saved across the modelling
period.
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International Conference on TIM, 2012, Nepal
DSM Results (Economic Analysis)
 B/C Ratio
 Discount rate of 12%
 Benefit – NPV of avoided supply cost
 Cost- NPV of programme cost
 The B/C of the DSM1 programme was 5.09, 4.43, 7.61, 11.38 and 51.2 for
poorest, second, third, fourth and richest class of households respectively
 The B/C of the DSM2 programme was 0.51, 0.3, 0.5, 0.57 and 0.25 for
poorest, second, third, fourth and richest class of households respectively
 The B/C of the DSM3 programme was 1.3, 2.3, 3.9, 7.8 and 54.8 for
poorest, second, third, fourth and richest class of households respectively
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International Conference on TIM, 2012, Nepal
Conclusion
• Electricity consumption mostly depend on household income.
• Second and Third is the highest electricity consuming category
of households and continue in future on all scenarios
• Implementation of effective DSM options would assist in
managing Nepal’s electricity deficit.
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International Conference on TIM, 2012, Nepal
Recommendations
•
Government should consider the adverse effects of unchecked increasing electricity
consumption trend and create separate DSM unit to ensure coordinated efforts for
DSM projects implementation.
•
Major steps should be taken to establish robust database of energy consumption
pattern of the region, management of available secondary information from various
relevant authorities and carries out frequent customer perception survey and energy
consumption pattern.
•
Detailed energy audit survey needed for very high end households with higher
electricity consumption
•
Special attention has to be given to the no cost/low cost energy conservation
measures such as use of daylight and other measures like energy labeling on electric
cookers ,Refrigerators etc
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International Conference on TIM, 2012, Nepal
Thank You
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