Anybody see a need for this analytic?
Some regional demand response regulators (ISOs) (PJM and ERCOT, for example) require demand response providers to install independent, real-time demand monitoring on their clients’ utility meters. These are called “shadow meters.” The monitors must count pulses streamed by the meters, the rate of which is proportional to demand. Providers use the “pulse rate” stamped on the meter for the shadow metering to figure how much demand a pulse represents.
Some regulators require the provider prove that the shadow metering matches utility data. If agreement isn’t close enough, problems arise that can have serious business consequences.
Many times, the stamped pulse weight is wrong. It is easy to check and correct for this when one meter comprises an account. But many accounts aggregate multiple meters. There is no simple way to find out the correction to each of the shadow meters (channels). This drove the demand response provider that I worked for into fits.
I figured out an advanced mathematical routine to calibrate multiple channels while working for a Demand Response provider. It even diagnosed when a channel wasn’t working, and when channels were associated with the wrong meters. An Excel workbook implemented it, and it was dubbed the “Calibration Tool.” It gained great acceptance and worked very well. It was able to calibrate installations with up to eight channels and advise the overall agreement accuracy. The business was able to enroll these accounts and steer clear of related regulatory problems.
So, has this been implemented by someone else, or would this be a novel offering to the industry?
Mark Ramsay, PE, PMP Leed GA
Owner, Effective Project Solutions LLC