Submetering I: No Guessing with Gas

A Tokyo Gas Company employee displays the data logger used to collect the gas usage information.

In the past, submetering home gas appliances has been awkward and expensive. Now the Tokyo Gas Company is testing a new method to gather individual gas appliance consumption data in Tokyo homes. The method does not require expensive equipment or intrusive installations. Instead, it relies on relatively simple hardware and very sophisticated computer algorithms.

There are three conventional approaches to estimating energy use of individual gas appliances. The first is to put a gas meter on each gas appliance in each home. This technique is expensive, making it difficult to monitor a statistically representative sample of homes. Also, energy auditors and residents are reluctant to have gas lines cut into. As a result, most studies monitor selected appliances in a few homes and settle for "typical" values, rather than a true average.

In other studies, researchers have inserted thermal sensors in the major combustion appliances and measured elapsed time to calculate consumption. Although this technique is much cheaper than direct metering of gas use, there is greater uncertainty about actual consumption.

The third traditional technique uses monthly gas billing data for a large number of homes combined with details of the appliances present in each home. These conditional demand studies reconcile variations in appliance ownership with differences in energy use. Such studies have been undertaken both in Japan and in the United States. But when there is little variation in appliance ownership from one house to another (as in many parts of Japan), the results are susceptible to large uncertainties.

Disaggregation Without Aggravation

Figure 1. Schematic of the new Japanese gas metering system.

Figure 1 shows the configuration of the Japanese metering system. A mechanical meter sends an electronic pulse every time 0.0318 ft³ (0.9 liter) of gas has flowed. Each meter is equipped with a data logger that time-stamps each pulse and thus records the elapsed time between consecutive pulses. When more gas is being used, the pulses occur more rapidly.

Each day, the logger records tens to thousands of pulses, depending on the amount of gas appliance activity. Periodically, data collectors download the list of time stamps. For the Tokyo study, we collected data from each customer site four times a year at most; downloading each logger took only a few seconds.

Estimation of end uses consists of two steps: decomposition and identification. In the decomposition step, the computer notices changes in gas use. By assuming that only one appliance is being turned on at a time, the computer can keep track of how many appliances are operating, and at what flow rates. When there is a significant increase or decrease in gas flow, we assume that one appliance has been turned on or off. The computer keeps track of the number of active appliances, and of gas consumption by each one.

The identification step combines audit information and the decomposed consumption data. When we install the meters, we record what gas appliances a house has, and their rated capacities. Using this information, the computer matches appliances with the flow rate and duration of gas use. Table 1 lists typical Japanese gas appliances, their rated input, and the elapsed time (in seconds) between pulses at the rated consumption.

Gas heaters, such as the one on the wall of this Japanese apartment, can be submetered using the new data gathering method.

We installed 20 of the data loggers in utility employees' houses and apartments to test the hardware and procedures. Then we compared the estimates with data obtained through an interview. Examination with the logged data from the different samples showed at least 95% accuracy in estimation.

The algorithms can still be confused by some relatively common situations. For example, in Japan, many space heaters have continuously variable combustion, with more gas flowing when the heating load is greater. If a window is opened when a heater is operating, the heater's gas flow changes from low to high, making the algorithm "think" another appliance has turned on. Improved algorithms should allow identification of variable-rate gas appliances.

Nevertheless, the system was judged sufficiently accurate to broaden the study. By the end of 1996, over 900 homes in the Tokyo area will have been monitored with the nonintrusive technique.

Although the nonintrusive monitoring system has worked well in Japanese homes, there are several differences in the way gas is used in North America. For instance, American appliances often have pilot lights, which are rare in Japan. While the algorithms could be easily adjusted to account for the constant load created by pilot lights, they will not be able to determine the amount of energy consumed by each appliance's pilot. This may require additional measurements during the audit. American homes also typically have more gas appliances than Japanese homes: clothes dryers, decorative fireplaces, pool and spa heaters, and exterior radiant heating elements are all more common in North America. This makes disaggregation more complicated, and computing requirements increase substantially. Finally, American appliances are more likely to have variable combustion rates, which can mislead the computer. However, none of these appears to be an insurmountable obstacle.

Table 1. Elapsed Time Between Pulses for Gas Flow from Typical Japanese Appliances.
Input (Btu/h)	Elapsed Time Between Pulses (seconds)	Appliances Corresponding to Inputs
4,000	35.4	Rice cooker
8,000	17.7	Small cooking stove, dryer
12,000	11.8	Large cooking stove
20,000	7.1	Oven
40,000	3.5	Bath heater Small instantaneous water heater
120,000	1.2	Large instantaneous water heater

Nonintrusive submetering has already given us new insights into customer behavior. For example, we now know that family size and number of faucets in a home are much more accurate predictors of water heating energy use than the type of water heater. The data have also helped the gas utility to determine the variables affecting the demand for gas in Japanese homes. This permits more efficient operation of the supply and distribution system and more accurate demand forecasting. In addition, the impacts of fuel switching, retrofits, and behavioral changes can now be easily observed.

For more information, see Yamagami, Shin, Hajime Nakamura, and Alan Meier. "Nonintrusive Submonitoring of Residential Gas Appliances." In Proceedings, ACEEE 1996 Summer Study on Energy Efficiency in Buildings. Washington, D.C.: ACEEE, 1996.
 
 

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