Homeostatic Utility Control in Retrospect

Homeostatic Utility Control 112/10/13

Homeostatic Utility Control in Retrospect

J.L. Kirtley [email protected]

Gridwise Architecture Council4th Transactive Energy Workshop


Homeostatic Utility Control• Arose from an initiative of Fred C.

Schweppe and his colleagues in the late 1970’s

• Was actually named by Richard Tabors • Was part of Schweppe’s efforts to re-

invent the electric utility system• Was intended to make the grid work better• Was developed in the context of regulated

public utilities• When first presentation, was rather

roundly ridiculed• Has provoked quite a lot of research


There were three basic elements of Homeostatic Utility Control:

• Frequency Adaptive Power Utility Regulator (FAPER): Fast control

• The Energy Marketplace• Marketplace Interface to Customer


FAPER• Intended to replace (or supplement) ‘Spinning Reserve’• Fast (virtually instantaneous) control• Takes advantage of ‘average power’ or ‘energy’ type loads

• Works only within the hysteresis band of an energy load

• Within that band, turns load on or off according to frequency


FAPER would help the system, but why would customers want to install them?

• There is some expense• Probably negligible impact on

comfort of equipment operation

• Here is Schweppe’s suggestion for compensation

• Charge less when frequency is high and more when frequency is low!


Later work on FAPERs at MIT: Kevin Brokish• Surprisingly large fractions of consumer

loads are amenable to FAPER operation• Brokish assumed operation to be a

modification of setpoint in a hysteresis type control


Brokish recognized • an instability that can arise with a lot of FAPERS controlling

loads by switching them on and off • Loads synchronize with each other• Solution is like Ethernet communications: use probabilistic

delay• White band is the

dead band• Outside dead band,

lighter blue is higher probability of switching


More Transactive Energy Work: Olivia Leiterman on Storage• FAPER like action need not depend on frequency• Signals from the utility system can initiate change in interchange• Energy Storage is the ultimate in ‘energy’ type load• Here is some motivation for involving real energy wiggles in ‘ancillary

services’


‘Power Signal’ could be derived from frequencyOr it could be an area power error signal

Separating high and low frequency signals


Separation of high frequency and low frequency variations• Energy Duration tells what your energy storage is doing• Ramp Duration tells what your other (slower) regulation resources are doing


Here is the bottom line: • More to this than can be quickly explained• Longer (slower) frequency cutoff reduces mean ramp rate for thermal

units• But it also means more storage energy is required


This is the Energy Marketplace as envisioned by Schweppe in 1980Note ‘Utility Generation’ is in the ‘Regulated Industry’


In The Energy Marketplace:• There would be a mix of regulated and unregulated generation• Regulation to ensure return to capital and prevent monopoly pricing• Separate ‘buy’ and ‘sell’ prices for customer generation• ‘Time of Day’ pricing was recognized as insufficient• Anticipated automation in customer premises• Recognized that there would be issues with customer acceptance and

privacy• And anticipated (maybe incorrectly) that two-way communication with

meters might be impractical


Later work on Spot Pricing: Jiankang Wang

Here we have a pretty generic explanation of why you want to get the final price right


In a deregulated market, System operators must buy electricity and keep the system balanced

Elasticity Matrix describes• instantaneous elasticity of

demand• cross-elasticity (from one time

period to others)


Demand is determined by a balance• Unit Commitment• Economic Dispatch• Price Elasticity predicts change in

demand• But see there are numerous ways

things might not balance


Better search methods can find the balance


Market Interface to Customer (MIC)• Need to get ‘price’ or ‘prices’ to Customer• Requirement may be only 5 to 10 minutes• Anticipated that there might need to be a confirming signal in reverse• Automation at the customer premises was anticipated• Some form of ‘smart meter’ was also anticipated


To avoid this fellow (who Scheweppe anticipated)• Smart Meter does not report on

customers in real time• Measures power, multiplies by price,

integrates the result

Market Interface to Customer

2412/10/13Homeostatic Utility Control

Later work at MIT:• ‘The Energy Box’• Richard Larson and

students:• Dan Livengood• Woei Ling Leow

• Anticipates forecasts of price, weather, etc. will be required

This is an image from Livengood’s thesis, (taken without permission)


Current work: using an office building for ancillary services (Young-Jin Kim)

SolarCells

Electric Car Charging

Air Conditioner Modulation


Discussion

This work was presented to the IEEE Power Engineering Society Summer Meeting in Vancouver

• Charles J. Frank of EPRI told us we were idiots• None of the group had any experience with running a utility• We don’t know what spinning reserve is (misuse the term)• FAPER would cost $60k

• Robert W. Alford of Siemens-Allis said that • Indirect load control would not be effective• Complicated pricing structures require too much customer

participation• Confirmation of prices posted every 5 minutes would require too much

bandwidth• The Electric Utility Business is not as mature as it used to be.

Homeostatic Utility Control in Retrospect

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