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Californial Industrial Energy Efficiency Potential

Californial Industrial Energy Efficiency Potential. CALMAC/MAESTRO Meeting San Francisco, CA July 27, 2006 Fred Coito fred.coito@kema.com. Acknowledgements. Key study contributors: KEMA, LBNL, Quantum Consulting Study funded through the California public goods charge for energy efficiency

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Californial Industrial Energy Efficiency Potential

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  1. Californial Industrial Energy Efficiency Potential CALMAC/MAESTRO Meeting San Francisco, CA July 27, 2006 Fred Coito fred.coito@kema.com

  2. Acknowledgements • Key study contributors: KEMA, LBNL, Quantum Consulting • Study funded through the California public goods charge for energy efficiency • Managed for the CPUC by PG&E • Review and input from the California IOUs • PG&E • SCE • SCG • SDG&E

  3. Types of DSM Potential Technical Economic Achievable Program Naturally Occurring Technical – complete penetration of measures analyzed in applications where deemed technically feasible from an engineering perspective. Economic – technical potential of measures that are cost-effective when compared to supply-side alternatives Achievable Program – subset of economic potential captured with specific program funding and measure incentive levels (Incorporates real-world customer behavior) Naturally Occurring – the amount of reduction estimated to occur as a result of normal market forces, that is, in the absence of any utility programs

  4. Estimating DSM Potential (Achievable)

  5. Key Inputs • Measure data • Costs, savings, applicability, saturation • Source: LBNL-process measures, KEMA-lighting/HVAC • Industrial energy consumption data • Electricity and natural gas use by end use and industry • Utility billing data, MECS, Program evaluations • Economic data • Avoided costs, energy rates, discount rates, inflation rate • CPUC avoided cost study, CEC rate forecast, current California assumptions • Utility program data • Budgets, accomplishments, goals • California utilities

  6. Measures

  7. Baseline Energy Consumption

  8. Baseline Energy Consumption

  9. Estimated Technical and Economic Potential

  10. Technical and Economic Potential

  11. Technical and Economic Potential

  12. Technical and Economic Potential

  13. Technical and Economic Potential

  14. Electricity Supply Curve O&M cost savings are not included.

  15. Natural Gas Supply Curve O&M cost savings are not included.

  16. Program Funding Scenarios Average Expenditures Over the 2005-2016 Analysis Period in Millions of $ per Year *Incentives are not paid on equipment maintenance measures.

  17. Achievable Electricity Potential

  18. Achievable Electricity Potential

  19. Achievable Natural Gas Potential

  20. Potential Savings by Utility Cumulative net savings: 2005-2016

  21. Potential Savings by Industry Group Cumulative net savings: 2005-2016

  22. Potential Savings by End Use Cumulative net savings: 2005-2016

  23. Key Measures

  24. Electric Cost - Benefit Cumulative: 2005-2016 Value of benefits and costs over life of measures, nominal discount rate = 8 percent, inflation rate = 3 percent.

  25. Natural Gas Cost - Benefit Cumulative: 2005-2016 Value of benefits and costs over life of measures, nominal discount rate = 8 percent, inflation rate = 3 percent.

  26. Summary of Net Achievable Potential Results Cumulative: 2005-2016 Value of benefits and costs over life of measures, nominal discount rate = 8 percent, inflation rate = 3 percent.

  27. Summary and Conclusions • Over the 2005-2016 period: • Achievable electric potential: 5% - 8% of base usage • Achievable gas potential: 1% - 5% of base usage • Maximum achievable savings are 60% higher than base achievable savings for electricity and 300% higher than base savings for natural gas • Considerable uncertainty in Maximum achievable estimates, especially for natural gas savings • Improved process controls, system optimization, and operation and maintenance measures are key components of potential savings. • These measures are more difficult to implement than typical efficiency measures and customer adoption questions contribute to forecast uncertainty.

  28. Report • The full report is available at the CALMAC website (www.calmac.org) • Main Report: http://www.calmac.org/publications/Industrial_Potential_Vol_1_Main_Report_KEMA.pdf • Appendices http://www.calmac.org/publications/Industrial_Potential_Vol_2_Appendixes_KEMA.pdf

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