GB2461915A

GB2461915A - Utility meter

Info

Publication number: GB2461915A
Application number: GB0813143A
Authority: GB
Inventors: James Donaldson; Malcolm Mcculloch
Original assignee: Oxford University Innovation Ltd
Current assignee: Oxford University Innovation Ltd
Priority date: 2008-07-17
Filing date: 2008-07-17
Publication date: 2010-01-20
Anticipated expiration: 2028-07-17
Also published as: GB2461915B; GB2464634A; GB0813143D0; GB2464634B; GB201000899D0

Abstract

A utility meter 20 for metering the use of at least one utility supplied to a plurality of appliances 12 is disclosed. An input section 22 is arranged to receive values representative of the use of a first utility and may receive values representative of a second utility. A store 28 contains appliance data characteristic of the use of utilities by each of a plurality of appliances. A processor is arranged to analyse the received values and to determine information on the use of the second utility by each appliance, based on the received values and appliance data. The resulting information is output by an output section 40 to a user terminal 42. The information on the use of the second utility may be determined by further utilizing known characteristics of the appliances. The utilities may be for example water, electricity, oil or gas.

Description

UTILITY METER

The present invention concerns an apparatus for metering the use of a utility, for example electricity, gas, oil or water, supplied to one or more appliances.

There is an increasing concern to reduce the consumption of resources, both at a domestic level in residential buildings, and at a commercial level in offices, shops, factories and so forth. The reasons for this are both to save costs and also because of concerns for the environment, such as the conservation of scarce resources, for example water in regions where rainfall is low, to reduce CO2 emissions, and to conserve finite resources such as coal, gas and oil.

Conventionally, consumers receive bills from utility companies which may indicate the quantity of the utility used since the last bill, for example monthly or quarterly, based on periodic meter readings or even based on estimates of consumption since the last meter reading. For example, in the case of electricity supply, the information is presented to the consumer in terms of the number of kilowatt hours of electrical energy that has been used, which is meaningless to many people, and gives very little idea about how they are actually using the energy and where they can cut back. Studies have shown that the effect of providing consumers with real-time detailed information about the energy they are using is that their consumption reduces by up to 20%. In order to provide this information, it is necessary to identify where the energy drawn from this supply is ending up, i.e. which appliances are being used, how much and when. It is a problem to provide this information.

Devices are known which can be plugged into a conventional electricity outlet socket which can monitor the energy consumption by a particular appliance plugged into that socket. However, this information is inconvenient to obtain, and for fully monitoring the consumption at a particular site, such as a house, a separate metering device would have to be plugged into every socket to monitor every appliance, and it is generally not possible to connect such metering devices to permanently-wired appliances, such as cookers, which are typically some of the largest consumers of energy.

I

Other devices are known which attempt to detect signatures in the supply of the utility that are characteristic of particular appliances, including, for example, monitoring to detect events when appliances are switched on or off. For example, US 4,858,141 (Hart et al.) discloses monitoring the voltage and current of the electricity supply to a residence to determine which appliances are running at any particular time and to determine the energy consumed by each. Similarly, Yarnagami et al., "Non-Intrusive Submetering of Residential Gas Appliances", Proceedings of the American Council for an Energy Efficient Economy (ACEEE) Summer Study, Pacific Grove, California, August 25-31, 1996, 1.265-1.273, discloses accurately metering gas consumption in individual homes, then analysing the data to estimate use by particular types of gas appliance, such as cooker, stove, water heater etc. However, there is the problem of distinguishing between appliances which have very similar characteristics with regard to consumption of the same ti1ity, for exmpie pplin' which present substantially the same electrical load.

The present invention aims to alleviate, at least partially, one or more of the above problems.

Accordingly, the present invention provides apparatus for metering the use of a utility, the apparatus comprising: an input section arranged to receive values representative of use of a first utility; and a processor arranged to analyse the received values and to determine information on the use of a second utility based on the received values; and an output section for outputting said information.

Another aspect of the present invention provides a method for metering the use of a utility, comprising: receiving values representative of use of a first utility; and analysing the received values to determine information on the use of a second utility based on the received values; and outputting said information.

The present invention further provides a computer program comprising computer-executable code that when executed on a computer system, causes the computer system to perform a method according to the above aspect of the invention.

The invention also provides a computer-readable medium storing a computer program according to the invention above, and a computer program product comprising a signal comprising a computer program according to the invention above.

Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings in which: Figure 1 depicts schematically a system using a utility meter apparatus according to an embodiment of the invention; and Figure 2 depicts schematically a system using a utility meter apparatus according to another embodiment of the invention.

An apparat, referred to as a utility ntr, cnrding to a first embodiment of the invention will now be described. Figure 1 shows the hardware components of a system incorporating the utility meter. In this embodiment, the invention is applied to an electricity supply system, by way of example, and so the utility in question is electricity, or more correctly, electrical energy.

In Figure 1, the electricity supply to the site, for example a house, apartment, office, shop, school and so forth is denoted 10. The electricity is supplied to a plurality of appliances 12A, 12B, 12C, 12... by means of conventional wiring 14.

The appliances and wiring are simply shown schematically in Figure 1, but may, of course, be configured in any appropriate way, such as via a consumer unit with circuit breakers or fuses, and with one or more ring main circuits with branches or spurs. A sensor 16 is provided to measure the total instantaneous current being provided to all of the appliances 12 from the supply 10, and also to measure the instantaneous voltage of the electricity supply 10. The current is measured by any suitable sensor, for example a current clamp placed around one of the conductors of the electricity supply wiring 14. The current clamp typically comprises a magnetizable material, such as ferrite, which forms a magnetic circuit around the conductor, and acts as a transformer to induce a voltage in a secondary winding around the magnetizable material, from which the current flowing in the supply wiring 14 can be obtained. As an alternative to this current-transformer, a Hall-effect sensor can be used to measure the magnetic field in the loop of magnetizable material around the wire which is related to the current flowing through the wire.

Other suitable ways may, of course, be used for sensing the current.

The voltage of the electricity supply can also be measured by any suitable volt meter. This, of course, typically requires access to tvo of the conductors in the wiring 14. This can be achieved, for example, by probes which strap around the respective cables and have spikes which penetrate the insulation to make contact with the conductor. Alternatively, connections could be made to terminals in the consumer unit, or, for example, at a location where fuses or circuit breakers are insertable. Non-invasive capacitive voltage detectors could also be used.

As shown in Figure 1, the sensor 16 is connected to the utility meter 20. It is, of euuis, pussiblo that omc or all of th cncor 16 is ino rtl within the utility meter 20, for example that wires connect the supply wiring 14 to the utility meter 20, and the voltage is measured within the utility meter 20. Alternatively, in a different embodiment, the sensor 16 may be self-contained and may communicate with the utility meter wirelessly, sending analogue or digital values of the instantaneous current and instantaneous voltage. In one option, the utility meter 20 can derive its own power supply by virtue of being connected to the portion of the sensor 16 for measuring voltage. In one particular form of this, the utility meter 20 is simply plugged into an electrical outlet in the same way as an appliance 12 to obtain its power supply and also to measure the supply voltage. However, in the preferred embodiment, the utility meter 20 and sensor 16 are conveniently located near where the utility supply 10 enters the building, such as near where the conventional electricity meter is or would be located.

The utility meter 20 comprises a number of different units. It is possible to implement each of the various units as dedicated hard-wired electronic circuits; however the various units do not have to be separate from each other, and could all be integrated onto a single electronic chip. Furthermore, the units can be embodied as a combination of hardware and software, and the software can be executed by any suitable general-purpose microprocessor, such that in one embodiment the utility meter 20 could be a conventional personal computer (PC).

The utility meter 20 comprises an input section 22 that receives current and voltage values from the sensor 16. The values are input or measured preferably multiple times per cycle of the alternating electricity supply to a level of accuracy as required by the application. If the values are supplied as analogue voltages, then the input section 22 may comprise, for example, an analogue to digital converter, such that the rest of the utility meter 20 can be implemented using digital electronics. The input section 22 also receives time data from a clock 24 which provides the actual present time. The clock 24 could, of course, be integral with other components of the utility meter, or could be part of the sensor 16, or could receive a clock signal from an external source such as a transmitter broadcasting time data. In one preferred embodiment the clock 24 comprises a quartz oscillator together with other iiina iiuut1y that i3 an intcgral pert f a proceor 26 (rihed below). In this case, the input section 22 for receiving the time data is also an integral part of the processor 26.

The voltage and current values together with the time data are received by a processor 26. From the raw data, the processor calculates a number of coefficients to characterise the present usage. Examples of suitable coefficients include, but are not limited to: (a) the total real power consumption; (b) the phase difference (angle) between the current and voltage which depends on the load applied by the various appliances 12 and whether it is purely resistive or also reactive, i.e. containing capacitive or inductive loads such as motors and transformers; (c) the root-mean-squared (RMS) current.

Clearly some of the coefficients mentioned above are averages, typically over a minimum of one cycle of the electricity supply, typically supplied at 50 or 60 hertz so one cycle is 0.02 seconds. However, mean values of all of the various coefficients can be calculated over a longer predetermined time interval. The present values of the coefficients are compared with the running mean value of each coefficient over the previous cycle or cycles to obtain a change or delta' in each coefficient.

The processor 26 then uses inference techniques to assign a probability to the state of all of the appliances 12 connected to the supply 10, in terms of whether each appliance is on or off, and the present power consumption by each appliance 12. The inference can assign a probability to the ensemble of appliances being in any particular state based on the calculated probability that the appliances were in any particular state during the previous cycle or at the previous calculation, together with the new evidence from the changes in the various coefficients calculated as described above, together with appliance data obtained from a store 28 of the utility meter 20.

In one preferred form, the appliance data comprises statistical information on the probability of a specific appliance consuming a particular amount of power. For a simple appliance, such as a purely resistive load of an incandescent light bulb, then ihe ptobaility 0f it con;uming a specific amount of power, wheii wifrhed nn.

within a small range of the nominal power, and with negligible change in the phase angle between the current and voltage, would be extremely high, approaching 100%.

Thus if a change in the magnitude of the power consumption equalled approximately that value, and that light was not previously on, then the inference would be extremely likely that the new state of the appliances would include that light bulb being on.

Suitable inference techniques to perform the analysis include, for example, probablistic methods such as Bayesian inference, classifiers such as neural networks, and possiblistic methods such as fuzzy logic. Other suitable methods may of course be used.

However, the analysis is not simply limited to monitoring onloff events of appliances. The power consumption of some appliances is variable. For example, a washing machine will consume considerably different amounts of power during different portions of a washing program and this will differ from program to program. All these power consumptions and their probabilities for each appliance are kept in the store 28 to enable the processor 26 to assign a probability to the new state of all of the appliances 12, for example using Bayes' theorem.

In this embodiment, the appliance data is in the form of a database in which, for each appliance, a probability distribution is stored for each of the above coefficients, for example in the form of a probability of the appliance operating with a power consumption within each of a plurality of ranges of power. The statistical data to derive the probability distributions can be obtained by a training process in which the appliance is operated a number of times, and the mean and variance of the coefficients are calculated. In one simple form, the appliance data for each coefficient is a top hat distribution, centred on the mean value of the coefficient and with a width of three times the variance of the coefficient in question. Outside that range, the probability is zero. Another form is a step probability distribution, for example with three levels, highest nearest the mean and stepping down on either side. Other distribution shapes can, of course, be used. It is also possible that the distribution does not have a single peak, for example in the case of an electric heater with iiucc pucr sttiug5, thcrc would be three pek with low probhilitv cf power consumption for values in between the three settings.

Naturally, the state of the appliances with the highest probability is assumed to be the correct present state of all of the appliances 12. A confidence-limit can also be assigned to the present state. If a new appliance 12 is connected about which the store 28 does not have information, then this will be picked up as a low confidence, in which case the utility meter can enter a learning mode to obtain information about the power characteristics of the new appliance, either autonomously, or by prompting the user to input new appliance information.

The above processing provides a first layer of analysis. However, it may be further refined. As a second layer, the appliance information in the store 28 also contains statistical information on the probability of each particular appliance 12 being used at any particular time of day. This could, for example, be expressed as a probability of a particular appliance being used in any specific time-slot during the day, by dividing the day into, for example, half hour intervals. This time of day probability distribution information would be included in the database of appliance data. Known inference principles can then also be applied using this extra information to assign a new probability to the state of the appliances i.e. whether any particular appliance is on or off and the power it is consuming. Thus, for example, there would be a low probability that particular lights were on during the middle of the day or that a toaster was on in the middle of the night.

A third layer of analysis can also be performed, again using inference based 011 the probable duration of usage of any particular appliance also stored as duration data as part of the appliance data in the store 28. Thus, it would be highly probable that a television might be in use continuously for several hours, but improbable that a kettle would be in continuous use for more than a few minutes. This duration probability distribution information would be included in the database of appliance data. Using this expected duration data, the assigned probability of the state of the appliances can be recalculated to obtain a new highest probability state configuration.

According to further preferred enhancement of this embodiment of the invcntion, additional evidence in the form f ip1iane data in the store 28 can be used to refine the state of the appliances 12. This can include information on likely groupings of devices, for example there would be an increased probability that a television set and a DVD player would be operating simultaneously, or that a computer, printer and monitor would all be operating simultaneously. Another example would be information on the stages of operation of an appliance, for example, during a washing program of a washing machine, if it has previously undergone a water-heating stage, then there would be a high probability that the machine would then enter the next stage, such as operating the motor to rotate the drum of the washing machine. Optionally, the appliance data may include other characteristics, such as data on the likelihood of the appliance being used at a range of ambient temperatures, to capture the fact that an electric heater is more likely to be used in cold weather, and an air-conditioning unit in hot weather. The utility meter can be connected to internal andlor external temperature sensors (not shown in the figures), and can then include ambient temperature as another parameter in the inference of the state of the appliances in terms of utility usage.

In the above-described embodiment, both current and voltage of the electricity supply are measured. However, the analysis could also be done using only the current, though with potential reduction in accuracy.

Using the intrinsic information in the electricity supply signals together with inference techniques can successfully discriminate between a large number of different appliances 12. However, there can still be a problem with distinguishing between appliances with similar electrical characteristics. For example, consider an electric room heater and a so-called "power shower' (which uses electricity to instantaneously heat water for a shower) of the same power rating in terms of kiloWatts; both are essentially purely resistive loads and draw the same current.

Similarly, consider a washing machine and a tumble dryer; each has a resistive heating element and an electric motor for rotating a drum under a similar load. The present invention uses information on the use of another utility to assist in ditinguihiiig between use by such simi1r pplinces; or to increase the confidence that the correct inference has been made regarding the state of the appliances, as will now be described.

In the embodiment of the invention shown if Fig. 1, the appliance 1 2A, such as a washing machine or power-shower, is connected to the supply 30 of another utility, in this case water. A water meter 32 detects the flow of water and conveys values representative of use of water to the input section 22 of the utility meter 20.

These values are used in the inference performed by the processor 26, in conjunction with known characteristics of the appliances 12 read from store 28, and the electrical information as already described above, to generate an improved inference of the state of the appliances 12, or an inference with greater confidence that the assessment is correct. For example, if it is detected from the current measurements that an electrical appliance is consuming a particular amount of power, and simultaneously there is a flow of water corresponding to that of a power-shower, then the probability is high that the electrical power is being supplied to a power-shower. Conversely, if the same electrical power consumption by an appliance is determined, but in the absence of the water flow, then the inference will be that a different electric heater is in use.

Although not shown in Figure 1, the water can be supplied to multiple appliances, some of which also use electricity, and some of which do not use electricity. By including the water usage information in the inference analysis, the state of the electrical appliances can be derived with greater accuracy (for example because different appliances uses different flow rates of water, and some none at all, and such characteristic data is included in the store 28). Similarly, the inference can be performed the opposite way round such that the knowledge of electricity usage can enable or improve detennination of which appliances are using water.

Effectively the available utility usage information is aggregated, and used in the overall inference of the present state of all appliances, and can be used to refine the previous estimates of the past states of the appliances. In this way, the utility meter can act as a combined meter for multiple utilities.

The invention is not limited to the utilities comprising the pair of water and electricity. For example, gas and electricity could be monitored. If it is inferred from gas flow data that a gas hob is being used, and also that some electric appliances are switched on, then it would be more probable that the electric appliances are associated with the kitchen, for example an extractor hood or kitchen light, rather than say a bathroom extractor fan or light. In this way the confidence of the assessment of which appliances are in use can be improved. The general principle is that values representing the use of a first utility, such as water or gas, are used to determine information on the usage of a second utility, such as electricity, or vice versa.

The stored appliance characteristics data is not just limited to flow rates of water or gas, but could include, for example, typical total consumption per use of appliances, the time of day of their usage and the duration of typical usage.

Therefore, even by measuring just the flow rate, discrimination can be made on a probabilistic basis, between, say, running a shower in the middle of the night (unlikely) compared with using a washing machine programmed to operate overnight (more likely).

Referring again to Fig. 1, the store 28 in this embodiment may be any suitable computer-readable storage medium, such as a solid-state computer memory, a hard drive, or a removable disc-shaped medium in which information is stored magnetically, optically or magneto-optically. The store 28, may even be remote from the utility meter and accessible, for example, via a telephone line or over the internet. The store 28 may be dynamically updateable, for example by downloading new appliance data. This could be done via the supply wiring 14 itself or, in one optional version, the store 28 is provided as an IC-card insertable by the user into a slot in the utility meter 20. Manufacturers of electrical appliances provide the necessary appliance data either directly to the consumer, or to the utility company.

New IC-cards can be mailed to the user to update their utility meter 26. The software that the processor 26 runs to perform the analysis may also be stored in the store 28 and updated as desired in the same ways as the appliance data (e.g. by downloading, by inserting a new medium such as a disc or IC-card, and so on) Following the analysis, in this example, the processor produces a log of the electrical energy utilisation for each appliance, comprising total energy consumption, time of day and duration of each usage. This information is output by an output section 40 to a user terminal 42 (such as a PC or a dedicated device for utility-use feedback) so that the information can be conveniently presented to the user. The output section 40 in the preferred embodiment communicates wirelessly, for example by radio frequencies (RE) link, or optically, or by infrared, or acoustically. However, it is also possible that the communication with the user terminal 42 is done through the supply wiring 14 if the user terminal 42 is plugged into one of the supply outlets as an appliance. In a further embodiment, the output section 40 can also act as a receiver, such that communication between the utility meter 20 and user terminal 42 is two-way. This enables the user terminal 42 to be used as a further means for updating the appliance data in the store 28.

The user terminal 42 can be a standard desktop or laptop computer with an attached monitor and/or printer, or can be a dedicated device. Although the utility meter 20 and the user terminal 42 are shown as separate devices in Figure 1, they could, of course, be part of the same device.

The first stage in using the utility meter is the analysis stage as already described to identify which appliances are being used at any particular time and how much of the or each particular utility they are consuming. The second stage is to provide the user with short-term feedback via the user terminal 42. For example, if the user terminal is a dedicated device in a prominent place in the house, it could give immediate feedback, for example that a particular appliance was left on overnight when that is not usual. It could also highlight changes in the behaviour of appliances, for example if an electric water heater were running more frequently than usual, then the thermostat might be faulty, or if the energy consumption by a refrigerator or any other appliance showed an increase above an expected level, then the user terminal could suggest that the appliance needs servicing. Other examples of instant feedback, for utilities other than electricity, might include warning the user that a tap has been left running, or that a valve in a toilet cistern needs replacing, or that a gas appliance has inadvertently been left on.

A further use of the apparatus is to change the way billing is done, by acting as a "smart meter". The data from the utility meter 20 can be transmitted automatically to a central unit via radio frequency/mobile links which would eliminate the necessity for manual reading of a meter and would also eliminate estimation of meter readings. Billings and hence feedback can be carried out more frequently which also has a positive impact on the quantity of energy or other resource being consumed.

A third stage in the use of the apparatus is long-term feedback. For example, the user can perform trend analysis with the user terminal 42, particularly if it is a personal computer. The user can assess what behavioural changes have made the greatest impact on reduced consumption; the user can compare his energy usage profile with other users of similar sized properties, and conimunities of users can engage in interactive activities, such as exchanging tips on reducing usage and also in introducing a competitive element to achieve the greatest reductions.

According to a further embodiment of the invention, one or more of the appliances 12 connected to the supply wiring 14 can be a generator of electrical power, for example a solar photovoltaic panel or a wind turbine generator. As these devices generate power, which is either fed to other appliances 12, or even back to the supply utility 10, then the current and voltage detected by the sensor 16 would also change, and the processor 26 can perform exactly the same analysis based on appliance data stored in the store 28 to determine when each device is generating power and the quantity generated. This gives convenient feedback about the precise savings achieved by using the solar panel or wind turbine, and also information about optimal siting of such devices.

Another embodiment of the invention will be described with reference to Fig. 2 in which the same reference numerals indicate the same parts as in Fig. 1. In this case oil is supplied from a supply 50, such as an oil storage tank, via a pump 52 to an oil-burning heater 54, such as a domestic central heating boiler. The utility meter 20 calculates when the pump 52 is operating, from its electrical characteristics and so forth, in the same way as for any other appliance 12 connected to the electricity supply 10. From this operating information and known calibration characteristics of the pump 52, the amount of oil delivered to the heater 54 can be derived. In this way it is not necessary to provide a separate oil meter, and the utility meter 20 can act as a combined utility meter. Again this embodiment uses the general principle that values representing the use of a first utility, in this case electricity, are used to determine information on the usage of a second utility, in this case oil.

In the embodiments of the invention described above, pairs of utilities are discussed, but the invention is not intended to be limited to only two utilities. The utility meter could be concerned with more than two utilities; for example measuring two utilities to derive information about usage of a third utility, or measuring one utility to infer information about the usage of two others, or in general aggregating information about multiple utilities to improve confidence in the inferred usage (for example by particular appliances) of each one of the utilities.

Claims

CLAIMS1. Apparatus for metering the use of a utility, the apparatus comprising: an input section arranged to receive values representative of use of a first utility; and a processor arranged to analyse the received values and to determine information on the use of a second utility based on the received values; and an output section for outputting said information.
2. Apparatus according to claim 1, wherein said input section is further arranged to receive values representative of total use of the second utility.
3. Apparatus according to claim 2, wherein said second utility is supplied to a plurality of appliances and said processor is further arranged to determine information on the usage of said second utility by individual ones of said appliances.
4. Apparatus according to claim 3, wherein the processor is arranged to determine information on the use of the second utility by each specific appliance based on inference of the most probable appliance or combination of appliances to be operating based on the received values.
5. Apparatus according to any one of the preceding claims, wherein the processor is arranged to determine information on the use of the second utility further using known characteristics of the or each appliance to which said second utility is supplied.
6. Apparatus according to any one of the preceding claims, wherein said received values represent the supply of a utility as a function of time.S
7. Apparatus according to claim 6, wherein one of said utilities is electricity and the input values represent at least instantaneous current of the supply, optionally both instantaneous current and voltage of the supply.
8. Apparatus according to any one of the preceding claims, wherein the first and second utilities respectively comprise one of the following pairs: water and electricity; electricity and oil; or gas and electricity.
9. Method for metering the use of a utility, comprising: receiving values representative of use of a first utility; and analysing the received values to determine information on the use of a second utility based on the received values; and outputting said information.
10. Method according to claim 9, wherein further comprising receiving values representative of total use of the second utility.
11. Method according to claim 10, wherein said second utility is supplied to a plurality of appliances, and wherein said method further comprises determining information on the usage of said second utility by individual ones of said appliances.
12. Method according to claim 11, wherein the analysing process comprises determining information on the use of the second utility by each specific appliance based on inference of the most probable appliance or combination of appliances to be operating based on the received values.
13. Method according to any one of claims 9 to 12, wherein information on the use of the second utility is determined further using known characteristics of the or each appliance to which said second utility is supplied.
14. Method according to any one of claims 9 to 13, wherein said received values represent the supply of a utility as a function of time.
15. Method according to claim 14, wherein one of said utilities is electricity and the input values represent at least instantaneous current of the supply, optionally both instantaneous current and voltage of the supply.
16. Method according to any one of claims 9 to 15, wherein the first and second utilities respectively comprise one of the following pairs: water and electricity; electricity and oil; or gas and electricity.
17. A computer program comprising computer-executable code that when executed on a computer system, causes the computer system to perform a method according to any one of claims 9 to 16.
18. A computer-readable medium storing a computer program according to claim 17.
19. A computer program product comprising a signal comprising a computer program according to claim 17.