TY - RPRT KW - Load as a Resource KW - LR00-001 KW - Controllable loads AU - Josh L Bode AU - Michael J Sullivan AU - Joseph H Eto AB -

Several recent demonstrations and pilots have shown that air conditioner (AC) electric loads can be controlled during the summer cooling season to provide ancillary services and improve the stability and reliability of the electricity grid. A key issue for integration of air conditioner load control into grid operations is how to accurately measure shorter-term (e.g., ten's of minutes to a couple of hours) demand reductions from AC load curtailments for operations and settlement. This report presents a framework for assessing the accuracy of shorter-term AC load control demand reduction measurements. It also compares the accuracy of various alternatives for measuring AC reductions — including methods that rely on regression analysis, load matching and control groups — using feeder data, household data and AC end-use data. A practical approach is recommended for settlement that relies on set of tables, updated annually, with pre-calculated load reduction estimates. The tables allow users to look up the demand reduction per device based on the daily maximum temperature, geographic region and hour of day and simplify the settlement process.

C2 - LBNL-5330E CY - Berkeley DA - 01/2012 N2 -

Several recent demonstrations and pilots have shown that air conditioner (AC) electric loads can be controlled during the summer cooling season to provide ancillary services and improve the stability and reliability of the electricity grid. A key issue for integration of air conditioner load control into grid operations is how to accurately measure shorter-term (e.g., ten's of minutes to a couple of hours) demand reductions from AC load curtailments for operations and settlement. This report presents a framework for assessing the accuracy of shorter-term AC load control demand reduction measurements. It also compares the accuracy of various alternatives for measuring AC reductions — including methods that rely on regression analysis, load matching and control groups — using feeder data, household data and AC end-use data. A practical approach is recommended for settlement that relies on set of tables, updated annually, with pre-calculated load reduction estimates. The tables allow users to look up the demand reduction per device based on the daily maximum temperature, geographic region and hour of day and simplify the settlement process.

PB - LBNL PP - Berkeley PY - 2012 EP - 120 TI - Measuring Short-term Air Conditioner Demand Reductions for Operations and Settlement ER -