06-02-2013, 03:31 PM
Advanced Electrical Load Monitoring: A Wealth of Information at Low Cost
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Introduction
This paper describes a low-cost approach to obtain and analyze electrical power data that
are very useful for performance monitoring and fault detection.
Goals:
· Reduce the energy consumption and associated environmental degradation of
commercial buildings in California, the U.S. and throughout the world;
· Reduce energy costs.
How to meet these goals?
· Deployment of appropriate methods for monitoring building performance and
automatically detecting and diagnosing faults in energy-consuming equipment or in
building components that directly affect energy usage.
HVAC Monitoring
Measurement of electrical power at the distribution panel for a large HVAC plant serving
three connected buildings:
· One-megawatt plant consists of multiple chillers, ventilation fans and pumps;
· Data averaged over one-second intervals;
· A 20 kW chilled-water pump was cycled on and off four times during the test period.
Looking at electricity data:
· The pump on-off transitions appear as very small variations in the total power (Figure
1). The pump transitions are partially masked by large noise spikes, which are caused
by power electronics used in variable-speed drives (Figure 2);
· A median filter rejects the spikes but retain the step transitions [5];
· A signal-processing technique known as the generalized-likelihood ratio (GLR) was
used to detect the on-off events [6-10]. This method searches over a sliding window
for the maximum value of the ratio of probability distributions of data points about
pre- and post-event mean values. If there is no step change, the ratio is small; if a
motor or lamp bank or other equipment switches on, the ratio is large as the window
slides through the event.
Fault Detection
Detection and diagnosis of HVAC faults:
· The test site is a research building run by the Iowa Energy Center and known as the
Energy Resource Station. It consists of two sets of test rooms, each with a separate
variable-air-volume (VAV) ventilation system, and a set of rooms occupied by
research staff, served by a third VAV system.
· MIT and Loughborough University, UK, are currently demonstrating FDD methods,
under ASHRAE sponsorship. A detailed description of this work will be publicly
available when MIT and Loughborough have completed their work and ASHRAE has
approved a final report.
· We are comparing results from analysis of two different data streams, one from
traditional (and more expensive) submetered power measurements and the other from
MIT’s latest NILM hardware platform. The hardware platform consists of a Pentiumbased
personal computer with an installed digital signal processor (DSP) board.
· The DSP board analyzes real and reactive power, at the fundamental and higher
harmonics.
· The PC can deliver information remotely, over the web (http://nilm.mit.edu).
· The host and the DSP board together cost about $500.
Parameter Identification
Our third and last example focuses on wringing the most information out of the highfrequency
data collected and analyzed within the DSP board:
· Focus on the start-up period of electrically powered equipment. This start-up period
can vary in duration from about 0.1 second for instant-start fluorescent lamps to
several minutes for variable-speed motor drives. In all cases, the transient behavior of
a typical electrical load is strongly influenced by the physical task that the load
performs.
· Measurement of real power demanded by a variable-speed fan drive in an HVAC
system (Figure 7). The drive begins with an "open loop" spin-up to operating speed
during the first 40 seconds of operation. From 100 seconds on, the drive is operating
under closed loop control as it attempts to regulate the pressure in a distant duct by
varying fan speed.
· Distinctive transient profiles like those shown in Figure 7 tend to appear even in loads
which employ steady-state active waveshaping or power-factor correction, which
tends to make reactive loads appear as purely resistive loads in steady state.