Anant Sudarshan Dr. James Sweeney

Transcription

1 Anant Sudarshan Dr. James Sweeney

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3 KWh per capita 5,000 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, Residential California Commercial California Industrial California Residential US Industrial US Commercial US Data shows retail electricity sales over three economy sectors Source: California Energy Commission and Energy Information Administration

4 Wyoming Kentucky District of Columbia Alabama South Carolina Tennessee Louisiana North Dakota Indiana Arkansas West Virginia Mississippi Nebraska Idaho Oklahoma North Carolina Texas Georgia Montana Delaware Iowa Virginia Kansas Ohio Missouri Nevada Washington Minnesota Oregon Wisconsin Florida South Dakota Maryland Pennsylvania Arizona Illinois Michigan New Mexico Colorado Utah Connecticut Vermont New Jersey Maine Alaska Massachusetts New Hampshire Hawaii New York Rhode Island California KWh per person Per Capita Electricity Consumption (2005) World High Income Middle Income Low Income United States 400, , , , , , ,000 50,000 0 State Electricity Consumption (million KWh)

5 Context Methodology and sector details Results Conclusions Concerns and next steps

6 Is this the best representation to use? What would this comparison look like if California had the same characteristics as the US as a whole? How much has demographics, climate, industry structure contributed to this picture? What role has policy played here? Is there empirical data out there that can help answer some of these questions? How can we best use the limited data that exists?

7 Identify multiple influencing factors that could cause reductions in observed electricity consumption Show that statistically significant effects are associated with these factors Use the limited empirical data available to arrive at first cut quantifications Compare this estimate with CEC model projections

8 Identify basic consuming unit: e.g. Households Identify an influencing factor: e.g. Income Obtain state and national level distributions : % of HH in different income groups Obtain national level data on the variation of electricity use as a function of the chosen factor: KWh/HH = f(income Group) Substitute CA household income for US household income, all else unchanged.

9 1. Household income 2. Householder age 3. Household size 4. Climate characteristics Population weighted CDD, HDD 5. Urbanization 6. Housing unit floor space 7. Housing unit age 8. Fuel choices (space heating and water heating) 9. Appliance use patterns ( lifestyles ) Basic unit of consumption: Household

10 Air Conditioning ~ cool cac cac CDDca E ca Eus CDD α i ca CDD i E i us E cool us rac ca E rac us CDD CDD Fraction of households using central (i=cac) or room (i=rac) air-conditioning Population weighted cooling degree days (i = CA or US) National average electricity consumption for air-conditioning (KWh/HH) by households using equipment type cac or rac respectively (i=cac/rac) Estimate of per household air-conditioning electricity consumption for an average US household transplanted to a CA climate. ca us E us Empirically estimated national average household electricity consumption for air-conditioning Test Hypothesis: ~ E cool Eˆ us

11 H i ca E i us T ca Household Size E si us i i HcaE T California households in size group i National average household energy consumption in size group i Total number of households in California ca i us α us E si E us Electricity as a fraction of household energy (US) Estimate of per household air-conditioning electricity consumption for an average US household corrected to have CA household sizes Empirically estimated national average household electricity consumption Test Hypothesis: E si Eˆ us

12 1. Industry profile Nature of manufacturing units 2. Number of employees by NAICS code (industry type) 3. Distribution by unit size within each industry type 4. On-site electricity generation 5. Process differences reflected in fuel mix differences

13 E ind i j p P ij i ij E ind α ij η i p ij P Estimated industrial electricity use per capita for CA, correcting US figures for industry structure energy use per employee in industry type i belonging to size group j (US av.) electricity as a percentage of total energy consumption in industry I (US av.) employees in industry type i of size group j (CA) Total state population (CA) National on-site generation in 2002: KWh (15.54 percent of industrial sales) State on-site generation in 2002: KWh (35.45 percent of industrial sales)

14 1. Sector profile Nature of commercial services 2. Percentage of total building floor space used for different services 3. Floor space per capita for different services (Building intensity ) E com f P Basic unit of consumption: Buildings (Floor Space) i i i Where, E com = Estimated commercial sector KWh per capita for CA, correcting US figures for floorspace differences α i = US average KWh per square foot for service type i f i = floor space occupied by service type i in CA P = total state population

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16 Context Motivation and objectives Methodology and sector details Conclusions Concerns and next steps

17 KWh per capita Unexplained Commercial 272 Unexplained Industrial Unexplained Residential, 545 Self Generation, Industry Composition Cooling Load, 332 Heating Load, 340 Household Size, 382 Water Heating, 238 Commercial Floorspace 1036 Urbanization, 321 Household Income,

18 California Energy Commission estimates savings that are reasonably expected to occur Savings figures from overall energy model Individual econometric models for some programs Utility estimates for their programs

19 KWh per capita Unexplained Industry Unexplained Commercial Unexplained Residential CEC Efficiency Estimates 1000 Unexplained Industry Unexplained Commercial CEC Efficiency Estimates Unexplained Residential

20 Can we obtain comparisons for past years? Can we explain why differences were so much smaller a few decades ago? Household Sizes in the US and CA US CA 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% California Electric A/C Saturation

21 KWh per capita Unexplained, Unexplained, 117 Urban Rural, 103 Water Heating, 239 Urban Rural, 321 Unexplained, 376 Urban Rural, 147 Size, 382 Size, 135 Water Heating, 269 Water Heating, Climate, 606 Climate, 545 Climate, California Actual 2116 California Actual 2281 California Actual Income, -41 Income, -118 Income,

22 KWh per capita KWh per capita Unexplained Reductions Reductions from Floorspace Differences CA Commercial Sector Electricity Consumption 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, Industrial California Industrial US

23 Context Motivation and objectives Methodology and sector details Results Concerns and next steps

24 Evidence to suggest a substantial role for policy (~23 percent of observed differences) Empirical evidence suggests that many factors influence electricity use. Can policy be made more innovative? Should energy efficiency policy have a broader ambit? Lifestyles may have a significant role to play Important to be aware of fuel mix differences and self generation differences (false economies?)

25 Context Motivation and objectives Methodology and sector details Results Conclusions

26 Endogeneity and dependence Difficult to correct without better data No data for states other than NY, TX, CA, FL Possible option: Multivariate model for household sector using 2005 RECS microdata Functional forms of dependence (Linearity not necessary) Better analysis of time periods before 2001 esp. for the industrial sector Spillover benefits ignored Extension of work From electricity to energy Include transport sector From California to the US From California to international Account for behavioral differences and the role of education and awareness programs.

27 Questions?

28 Percentage share Percentage share Decreasing energy use Increasing economic output Daytime Unoccupied Temperature Profile California United States Sleeping Temperature Profile California United States

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30 19.00% Energy Use by Sector 18.00% 41.00% 22.00% Percentage Electricity Consumption 6.00% 9.00% 37.00% 16.00% 32.00% Transportation Industrial Commercial Residential Commercial Residential Industrial Mining and Agriculture Transport and Street Lighting Source: California Integrated Energy Policy Report (2007)

31 Schipper, L. & McMahon, J. E. (1995), 'Energy Efficiency in California: A Historical Analysis.'(ERCDC A.24 S336a 1995), Technical report, American Council for an Energy-Efficient Economy. Loughran, D. & Kulick, J. (2004), 'Demand Side Management and Energy Efficiency in the United States', Energy 25(1), Bernstein, M.; Lempert, R.; Loughran, D. & Santana-Ortiz, D. (2000), 'The Public Benefit of California's Investments in Energy Efficiency'(MR CEC), Technical report, RAND. Auffhammer, M.; Blumstein, C. & Fowlie, M. (2007), 'Demand Side Management and Energy Efficiency Revisited'(CSEM WP 165r), Technical report, Center for the Study of Energy Markets: University of California, Multi-Campus Research Unit.

32 Roy, J.; Sanstad, A.; Sathaye, J. & Khaddaria, R. (2006), 'Substitution and price elasticity estimates using intercountry pooled data in a translog cost model.'(lbnl ), Technical report, Lawrence Berkeley National Laboratories Report. Reiss, P. C. & White, M. W. (2005), 'Household electricity demand revisited', Review of Economic Studies 72, Branch, E. (1993), 'Short run income elasticity of demand for residential electricity using consumer expenditure survey data.', Energy 14(4),

33 Source: Presentation by Arthur Rosenfeld to the Power Association of Northern California (2006)

34 Source: 2006 CEC Demand Forecasts

35 Objectives Methods and Sector Details Results Conclusions Concerns, caveats and next steps