How Energy Efficiency and Demand Response can Help Air Quality Presentation to the California Electricity and Air Quality Conference October 3, 2006 Mary Ann Piette Demand Response Research Center Lawrence Berkeley National Laboratory drrc.lbl.gov Sponsored by the California Energy Commission PIER Program

Presentation Outline  Summary of Major Energy Efficiency and Demand Response Goals in California  Demand Side Management Framework  Valuing Emissions  Current Research – Automating Demand Response  Findings and Future Research Needs

Integrated Demand Side Management Model Analysis Energy Conservation Energy Efficiency Business Operations Reliability Price Time of Use Load and Bill Management Demand Response Self Generation Source – PG&E

California’s Aggressive Energy Efficiency & Demand Response Goals  Electricity - 16,000 GWh and 2 MW by enough for 1.8 million homes and double past goals  Natural Gas - savings doubled - savings in 2010 supply 250,000 to 300,000 homes  Demand Response - Price-responsive DR goal = 5% of peak by 2007 (~ 10 GW)  Combined Savings - reduces CO2 by more than 9 million tons/yr by 2013, equivalent to 1.8 million vehicles (40% of Bay Area) off the road Source – NRDC and Flex Your Power

Energy Efficiency, Load Management, DR Efficiency and Conservation (Daily) Peak Load Management (Daily) Demand Response (Dynamic Event Driven) Customer Motivation 1.Utility Bill Savings 2.Civic Duty/ Environmental Protection 1.TOU Bill Savings 2.Peak Demand Charge Bill Savings 1.Economic (price) 2.Reliability (emergency) 3.Civic Duty/Grid Protection Building Design Efficient Shell, Equipment & Systems Low Power Design Dynamic Control Capability Building Operations Integrated System Operations Demand - 1.Limit 2.Shift 1.Demand - Limit 2.Shift 3.Shed Environmental Factors Change in emissions based on time of day and season of kWh reduction Change in emissions based on time of day, season, and net change in kWh InitiationLocal Remote

Western Region Electricity Generation Change or reduction in emission from efficiency and DR depend on electricity generation mix during the time the electricity is reduced or shifted Source – Holland and Mansur, Is Real Time Pricing Green? Environmental Impacts of Electricity Demand Variance, August 2004, CSEM

Environmental Adders Adjust Costs For Emissions Source - Energy and Environmental Economics, Inc. (E3), CPUC Avoided Cost Methodology

Time Dependant Valuation in Building Codes Considers when Electricity is Used

 Provide large (>200kW) customers with electronic, Internet-based price and reliability signals  Automatically link price and reliability signals into the facility control systems  Customer’s program automated response customized to facility and client / tenant needs  Develop facility response strategies that ‘optimize’ load reduction, economic savings and customer acceptance Introduction to Automated Demand Response in Large Buildings

Auto-DR System Communications Demand Response Automation Server (DRAS) Internet Relay Client & Logic with Integrated Relay (CLIR) Utility Utility or IOU Event Trigger XML Modbus

 Significant short-term peak reductions demonstrated for several dozen sites (avg. 10%)  Cost to automate DR is minimal  Minimal impact to occupants and tenants  Persistent savings demonstrated over 4 summers of field tests  Automation reduces labor costs for participation  Automation increases reliability to utilities and ISO  Automation standardizes response strategies  Vast majority of sites shed rather than shift electricity use Automated Demand Response Results

2004 Hot Weather Test: 5 sites 2005 Auto-CPP Test: 10 sites Automated DR Results from Previous Year

 California has aggressive goals for energy efficiency and demand response  The majority of efficiency and demand response measures provide direct reductions in emissions by displacing supply  Continue advanced controls and automation research for key market segments  Lack of feedback hampers change in end-use  Future Research  Need better data on end-use operating strategies and motivations to change energy use technologies and patterns  Need better feedback to customers on energy use data, costs, and emissions associated with consumption Findings and Future Research Needs