development of a functioning centrally located electrical-load monitor

8/11/2019 Development of a Functioning Centrally Located Electrical-Load Monitor

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Project 2.2

Equipment Scheduling and Cycling

Task 2.2.3

Automated Diagnostics ased on Start!"p Signals

Deli#era$le 2.2.3%a&

De#elopment o' a (unctioning Centrally )ocated Electrical!

)oad *onitor

Su$mitted to Architectural Energy Corporation

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Cali'ornia Energy Commission+s

Pu$lic ,nterest Energy -esearch %P,E-& Program

Energy!E''icient and A''orda$le

Small Commercial and -esidential uildings

Cali'ornia Energy Commission Contract //!00!/11

. D. )ee ). . 4or'ord and S. . )ee$

*assachusetts ,nstitute o' Technology

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De#elopment o' a (unctioning Centrally )ocated Electrical!)oad

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detection of faults& instead concentrated on further developing load-trac%ing algorithms andcoding them for on-line use in the NILM. This report will be supplemented by a # with NILMcode. The remainder of this summary highlights the ma5or advances documented in this reportand identifies future wor%.

Use of both steady-state load detection and analysis of start-up transients

This research has developed a load disaggregator that analy2es both step changes in steady-stateloads and start-up transients and automatically arbitrates the results in cases where the twomethods disagree. The step-change analy2er is significantly more powerful than that used inprevious versions of the NILM but is still sub5ect to bac%ground electrical noise. The transientdetector is relatively immune to white noise but can be fooled by colored noise and is not usefulfor abrupt shut-down signals. If single-event load detection fails& the signal is sent to a multi-event detector that searches a binary tree of possible combinations of temporally overlappingloads. The step-change analy2er& the multi-event detector and the state estimator& discussed net&ma%e use of a consistent signal-analysis framewor% that considers load signals to be stochastic

events& each associated with a mean and variance.

State estimation

vent detection is susceptible to occasional errors7 turn-on and turn-off events will be missedentirely or mislabeled. uch errors can accumulate and reduce the value of the NILM. +urther&the NILM needs a starting point when it is first started& so that the status of individual loads canbe determined before turn-on or turn-off events are detected. To address these issues& a stateestimator was developed to determine the most li%ely set of loads associated with a given steadypower signal.

Estimation of power drawn by variable-speed drive (VSD) loads

ince its inception& the NILM has successfully detected only constant-power loads. 8#s are incommon use and have posed significant challenges. ven if the power drawn by a 8# fan werenearly constant over the day& or could be approimated as such with acceptable loss of accuracy&detection of the start-up of a 8# is nearly impossible with either step-change or start-uptransient algorithms& due to the very long (order of /4 minutes) start-up period. This reportdocuments a fully functional approach to trac%ing 8#s that is based on observing the higherharmonics& particularly the fifth and seventh harmonics of real and reactive power that areassociated with 8#s. This method cannot separate individual 8# devices but can trac% theiraggregated power use.

estin! of software

NILM algorithms were developed in Matlab and tested off-line with NILM-collected data&primarily from the test office building in an +rancisco. The algorithms were converted to 99&compiled& and embedded in the on-line NILM in the office building. The code was sub5ected tolimited testing& in two phases. +irst& the disaggregator for constant-power loads was tested byin5ecting off-line data into the NILM. This procedure was necessary at the time to isolate

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constant-power loads. The code successfully identified loads and maintained a log of their on-offstatus& presenting this information via a :eb-based interface. econd& the 8# trac%ingsoftware was loaded and tested. It successfully separated the supply- and return-fan 8# powerfrom the 18! total.

"uture wor#

everal important steps need to be ta%en7

Trac%ing of variable-power& constant-speed loads. This last remaining load class includesmost chillers and those fans still using inlet vanes. ,elations between real and reactive powerfor these loads will be eplored. #irectly trac%ing a chiller is preferable to assigning to thechiller that portion of 18! power not due to constant-power and 8# loads& becausechiller power 'by subtraction* is sub5ect to errors in following other loads. 1owever& thesubtraction approach is possible if the NILM is mounted at the 18! service entrance.

Integration of the disaggregator for constant-power loads and the 8# trac%er. The code wasdesigned to be integrated. 1owever& most constant-power loads are for pumps and towerfans associated with operation of a chiller. ;ntil the chiller can be detected or is assignedremaining 18! power& the integration has reduced practical value.

Testing of the NILM and determination of its commercial value. This wor%& the mostimportant& reuires that NILM load-trac%ing output be compared with submeters and that apotential commerciali2er determine whether NILM output& either load trac%ing or powersignatures associated with faults& has value to its customers.

!utomated training of the NILM. The state estimator is a good start here& because it ma%es a

best guess of the loads in operation at the time the NILM is turned on. 1owever& the stateestimator and the load disaggregator rely on a %nowledge of the characteristics of individualloads& including steady-state real and reactive power and start-up transients. To date& thisinformation has been gathered manually& by turning on and off individual loads several timesand analy2ing the power data. +or commercial applications& the training must be automatedto the etent possible and clear instructions must be prepared for remaining& manual steps.

!utomated detection of faults. !s a starting point& detection of faults associated withoscillatory power signals should be automated& based on freuency analysis. !utomatic faultdetection will aid those potential users who have limited time or ability to analy2e NILMdata.


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Ta$le o' Contents

Introduction..........................................................................................................................0/./ Motivation and bac%ground of research.....................................................................0/.3 ystem overview and eample power waveforms..................................................... rief history of non-intrusive power monitoring..................................................... /3/.? @b5ectives and outline of thesis .............................................................................. /?urrent 1armonic "owers7 Mathematical Theory and "ractices....................................... /A

3./ Introduction............................................................................................................../A3.3 +undamental powers................................................................................................ /

development of a functioning centrally located electrical-load monitor

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