NAESB UPDATE MEETING MAY 30, 2008 DSM EE RETAIL GROUP

Project Objective Verify load reductions that are expected from Demand response Programs Be able to state the confidence level of load reductions for Demand Response Programs

Matrix Status 11 demand response programs 5 utility submitters Revise headings with new M&V characteristics Target more submitters for better geographical coverage ( i.e. RTO regions, NERC regions) Evaluate program diversity

Data Collection Develop list of additional submitters Review RTO and NERC territory maps Phone interviews to collect additional examples Focus on existing programs and existing M&V processes Ask submitters to provide info on all of their applicable programs

M&V Characteristics –Sample Accuracy: For M&V where sampled data is used to verify load reductions, what is the confidence level of the sampled load study? ( i.e. +/- 10% with 90 % confidence) –Sample Size: What sample size is required to achieve the target confidence level (i.e. 200 in control group, 200 in non-control group, blind study – participants are not informed about when control actions occur) –Frequency of Data Collection: How often is load reduction data sampled (i.e. 5 minute intervals with daily downloads) –Communication Protocol: How is load reduction data collected (i.e. telemeter – real time data collection) –Notification Testing: How is the customer notified of a curtailment event and how is the communication protocol tested. (i.e. ping the control device at the customer premise and verify its receipt)

M&V Characteristics –Demographics: Do customer demographics pay a roll in M&V - undecided – (i.e. Residential, Commercial, Industrial, Governmental, size) –Meter Accuracy: What are the meter accuracy requirements (i.e. clock time interval) –VEE (Validation/Editing/Estimation): How is data evaluation performed (i.e. validation of data, methodology for editing erroneous data, estimation techniques for missing data) – Market: What is the target market (i.e.. mass market usually has a standard watt hour revenue meter vs. large commercial/industrial market that may have a interval data recorder) –Baseline Method: How is the amount of load drop determined (i.e. the method to determine the customer baseline before a curtailment event)

Discussion Points Will not concentrate on cost benefit issues surrounding DR programs. AMI has the potential to significantly affect DR programs and M&V but is not expected to be part of initial standards. Will focus first on dispatchable programs, however, data will be collected on all DR programs. Will stay closely linked with the RTO effort as many utility retail programs feed into the RTOs

Next Steps Refine the matrix with more specific headings based on M&V characteristics (Rae McQuade) A conference call will be set up to review the refine the matrix (Rip Newcomb) Current data will be entered into the matrix (Rae McQuade, Rip Newcomb, Neal Allen, Submitters) Amend the work plan to reflect the new assignments (Rae McQuade/Rip Newcomb) Review matrix coverage in the United States and contact additional utilities (Rae McQuade, Neal Allen, Rip Newcomb) Continue calls to further populate the matrix (Rae McQuade, Neal Allen, Rip Newcomb) Mary Edwards and Phil Precht will begin to draft a format for the retail standard