1. International Conference on TIM, 2012, Nepal 1 Electricity Demand Side Management in Residential Sector of Kathmandu Valley Sujan Adhikari Prof Amrit Man Nakarmi Institute of Engineering Pulchowk Campus,Lalitpur, Nepal

2. International Conference on TIM, 2012, Nepal 2 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. Research Objectives

3. International Conference on TIM, 2012, Nepal 3 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 Consumers Domestic Electricity Consumption (GWh) Average Household Size Per capita electricity consumptio n (KWh) 201119489681170.774.7127.81 2001713307518.365.44133.58 (Source: NEA Annual Report, 2011; CBS Preliminary Survey, 2011)

4. International Conference on TIM, 2012, Nepal 4 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). Concept of Demand Side Management

5. International Conference on TIM, 2012, Nepal 5 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 Residential Sector

6. International Conference on TIM, 2012, Nepal 6 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) Kathmandu Valley

7. International Conference on TIM, 2012, Nepal 7 Questionnaire Design Sample Design Household Survey Analysis and conclusion Methodology

8. International Conference on TIM, 2012, Nepal 8 Household Characteristics CharacteristicsDescription Household Income Total household income per month Nepalese Rupees (Nrs) Household sizeNumber of individuals in the household RoomsNumber of rooms in the household No of ChildrenNumber of children in the household Variables  Number of Appliance  Operating hour of the Appliance  Rating of the appliance Questionnaire Design

9. International Conference on TIM, 2012, Nepal 9 Average electricity consumption was regressed with the household characteristics IDCoefficients Standard Errort Stat Intercept-61.2829.20-2.10 Monthly Income (Nrs)MI0.00180.00027.49 Family sizeFS8.817.161.23 Number of childrenNC21.9016.401.34 Number of roomsR6.853.432.00 R 2 = 0.765 Therefore the regression equation is E= -61.28+0.002  MI + 8.811  FS+21.9  NC+6.85  R Regression Result

10. International Conference on TIM, 2012, Nepal 10 Size of the sample, n  2 *N*(1-P) ME 2 (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) Sample Design

11. International Conference on TIM, 2012, Nepal 11 Household sample surveys have become a key source of data on social phenomena in the last 60-70 years S.NIncomeClassQty of electricity used (Units/Month) Share (%) 1<15,000Poorest 47.98 215,000-25,000Second 74.740 325,000-40,000Third 10339 440,000-80,000Fourth 1329 580,000- 2,00,000 Richest 2004 Total 100 Household Survey

12. International Conference on TIM, 2012, Nepal 12 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%.

13. International Conference on TIM, 2012, Nepal 13 LEAP Modelling Framework Household projection Y=119519*exp (0.6025*x) where x is the number of year. Household income Appliance ownership  Energy ladder hypothesis  Regression between household income and appliance number  Result showing R2 value greater that 75% is considered Year20122015202020252030 Households No (Lakhs) 3.94.96.79.212.6 Projection

14. International Conference on TIM, 2012, Nepal 14 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 Scenario Selection

15. International Conference on TIM, 2012, Nepal 15 Scenario Electricity Consumption (Million Kilowatt Hours) 20122015202020252030 HG 12521816315553689066 MG 12521766295248537909 BAU 12521691266041486427 BAU-9.5% MG-10.7% HG- 11.6% Scenario Result

16. International Conference on TIM, 2012, Nepal 16 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. DSM Options DSM Criteria

17. International Conference on TIM, 2012, Nepal 17 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. DSM Result (Energy Savings)

18. International Conference on TIM, 2012, Nepal 18  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 DSM Results (Economic Analysis)

19. International Conference on TIM, 2012, Nepal 19 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. Conclusion

20. International Conference on TIM, 2012, Nepal 20 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 Recommendations

21. International Conference on TIM, 2012, Nepal 21 Thank You