GB2464927A - Apparatus and method for metering the use of electricity - Google Patents

Abstract

The apparatus (20) has an input section (22) arranged to receive values representative of the current supplied to an installation (14), such as a house. A store (28) contains appliance data characteristic of the use of electricity by each of a plurality of appliances. A processor (26) is arranged to analyse the received values to detect when an appliance (12x) is switched on and determine the fractional change in resistance of a heating appliance from the when it is switched on until it reaches its operating temperature. This information is used to identify what the particular appliance is, and to determine the electrical energy consumption by that appliance.

Description

APPARATUS AND METHOD FOR METERING THE USE OF

ELECTRICITY

The present invention concerns an apparatus and method for metering the use of electricity supplied to a plurality of appliances, and in particular determining the electrical power consumed by one or more individual appliances among the plurality of 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 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.

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 try to determine which appliances are running at any particular time and to determine the energy consumed by each. US 5,483,153 (Leeb and Kirtley) discloses a transient event detector' that attempts to match various transient basis shapes' with an observed electrical waveform to assist with the appliance classification and identification process.

However, there is the problem of distinguishing between appliances that have very similar characteristics with regard to consumption of electricity, for example appliances that present substantially the same electrical load. A particular problem is with heating appliances which generally have a resistive heating element which presents a purely resistive load, making it difficult to distinguish between say a toaster and a kettle. Therefore it may not be possible to separately totalize the power consumed by two 1200 W resistive appliances e.g. a toaster and a quartz space heater.

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

Accordingly, the present invention provides an apparatus for metering the use of electricity supplied to a plurality of appliances, the apparatus comprising: an input section arranged to receive values representative of the total supply of electrical power as a function of time; a transient detector arranged to detect the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; an analysis section arranged to analyse the received values and to determine: (i) a first value related to the resistance of said appliance at the time of being switched on detected by said transient detector; and (ii) a second value related to the resistance of said appliance when operating in a steady state; and a processing section arranged to identify said appliance based on at least said first and second values, and to determine the electrical energy consumed by said appliance.

Preferably, the analysis section is arranged to determine a further classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and the identification of said appliance by said processing section is further based on said further classification value.

Another aspect of the invention provides an apparatus for metering the use of electricity supplied to a plurality of appliances, the apparatus comprising: an input section arranged to receive values representative of the total supply of electrical power as a function of time; a transient detector arranged to detect the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; an analysis section arranged to analyse the received values and to determine: (i) the time when the electrical power being used by the appliance has reached a steady state; and (ii) a classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; a processing section arranged to identify said appliance based on at least said classification value, and to determine the total electrical energy consumed by said appliance.

Another aspect of the present invention provides a method for metering the use of electricity supplied to a plurality of appliances, the method comprising: receiving values representative of the total supply of electrical power as a function of time; detecting the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; analysing the received values and determining: (i) a first value related to the resistance of said appliance at the time of being switched on; and (ii) a second value related to the resistance of said appliance when operating in a steady state; and identifying said appliance based on at least said first and second values, and determining the electric energy consumed by said appliance.

Preferably, the method comprises determining a further classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and wherein the identification of said appliance is further based on said further classification value.

Another aspect of the invention provides a method for metering the use of electricity supplied to a plurality of appliances, the method comprising: receiving values representative of the total supply of electrical power as a function of time; detecting the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; analysing the received values and determining: (i) the time when the electrical power being used by the appliance has reached a steady state; and (ii) a classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and identifying said appliance based on at least said classification value, and determining the total electrical energy consumed by said appliance.

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.

The present invention has the advantage of being less computationally intensive and more accurate than previous metering apparatus and methods.

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 an apparatus for metering the use of electricity according to an embodiment of the invention; Figure 2 is a graph of total power supplied to an installation as a function of time, during which an appliance is switched on; Figure 3 is a graph of power consumption for two different appliances from the time they are switched on; Figure 4 is a graph of resistance of two different appliances from the time they are switched on; Figure 5 is a graph of power consumption for two further different appliances from the time they are switched on; and Figure 6 is a graph of power consumption for an appliance from the time it is switched on until it reaches a steady operating state.

An apparatus according to a first embodiment of the invention will now be described. Figure 1 shows the hardware components of a system incorporating the apparatus for metering the use of electricity, or more correctly for metering electrical energy. The apparatus will be referred to simply as the meter.

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 ioop 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 two 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 meter 20. It is, of course, possible that some or all of the sensor 16 is incorporated within the meter 20, for example that wires connect the supply wiring 14 to the meter 20, and the voltage is measured within the meter 20. Alternatively, in a different embodiment, the sensor 16 may be self-contained and may communicate with the meter wirelessly, sending analogue or digital values of the instantaneous current and instantaneous voltage. In one option, the 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 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 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 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 meter 20 could be a conventional personal computer (PC).

The 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 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 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 timer circuitry that is an integral part of a processor 26 (described 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 approximately 002 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 raw data andlor coefficients may also be filtered to reject spurious noise.

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 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 the probability of it consuming a specific amount of power, when switched on, 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, probabilistic methods such as Bayesian inference, classifiers such as neural networks, and possibilistic 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 arid 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 three power settings, there would be three peaks with low probability of 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 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 on 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 invention, additional evidence in the form of appliance 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 meter 20 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.

Using the basic coefficient information from 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, those which present essentially a purely resistive load and have a heating function, such as space heaters, kettles, toasters, irons, cooking hobs, ovens, tumble dryer heating elements, water heaters and so on. These loads are purely resistive, so there is no phase angle information between the current and voltage to distinguish between them, and there is a considerable overlap in the magnitude of the power consumption of different appliances within this class. The present invention is particularly concerned with discriminating between these appliances. As will be explained below, the invention can also be used to assist in determining what type of appliance each unknown resistive appliance is likely to be, for example to identify that a particular unknown appliance is a kettle. This information can then be used to identify the kettle in future with a higher degree of accuracy.

Figure 2 is a graph of electrical power consumption (vertical axis) as a function of time (horizontal axis) for a particular installation, such as a house. At time to a further appliance is switched on and the power consumption rises extremely rapidly to a peak. The power consumption then falls more slowly to a steady state value. The processor 26 analyses the total power consumption using a transient detector circuit or software module to detect such a large increase in power consumption, for example in excess of 50 watts over one cycle of the alternating current electrical supply and then monitors the power until the magnitude of the gradient (rate of change of power with respect to time) is below a predetermined threshold and identifies that as the time t1 at which a new steady state has been reached. The time from to to ti is denoted t in Figure 2, i.e. t is the time from switching on the new appliance until a substantially steady state has been reached.

The shaded area in Figure 2 represents the base load, i.e. the power consumption by other appliances. This is subtracted from the power values plotted in Figure 2 to obtain the power consumed by only the appliance that is switched on at t0. One method is to take the base load power as being the measured power immediately prior to and subtract this from each subsequent power value. This assumes the base load is constant. One way to account for a varying base load is to calculate the mean and variation in the base load over a longer period of operation and thus obtain a representative average power which is then subtracted from the measured power. A further possibility is to measure the base load mean and variation also after the further appliance has switched off (by detecting the switch off event) and if this is different from the base load prior to the appliance being switched on, then a linear variation in base load between the on and off events of the appliance under observation can be assumed and accordingly subtracted from the measured total power to obtain the power consumption of the appliance in question.

Figure 3 shows the power consumption for two different appliances after the base load has been subtracted. Figure 4 is a plot of the corresponding resistance of the appliances which can be obtained by dividing the voltage by the current (for example RMS values over one cycle in each case), or can be obtained by dividing the power by the square of the RMS current. In Figures 3 and 4 to is at cycle number 0 of the plot, and clearly t1 is significantly different for appliance 1 and appliance 2.

The physical process underlying these graphs is that the resistance of a heating element varies as a function of temperature. When the appliance is switched on, the resistance has a value R0 at time to. The element then heats up which increases its resistance until it reaches a maximum value R1 at time t1. This occurs when the appliance has reached its steady state operating temperature. This is an equilibrium at which the rate of electrical energy input to the heating element is

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balanced by the rate of cooling of the element (by conduction, radiation and convection). As can be seen from Figure 3, both appliances have a steady state power of approximately 2.4 kilowatts and so would be indistinguishable by that parameter alone. However, appliance 1 has much lower heat losses than appliance 2, and so has a higher operating temperature for its heating element and therefore greater change in resistance from its value when cold before being switched on.

The resistance of a heating element is related to its temperature as follows: = a.AT Equation (1) where R0 is the initial resistance of the element, AR is the change in resistance as the element heats up, a is the temperature coefficient of resistivity, and AT is the change in temperature of the element.

In one embodiment of the invention, one coefficient or parameter (also called a classification value) that characterizes the electrical appliance is the ratio AR/R0, where AR = R1 -R0, i.e. the difference in resistance at between times ti and to. For appliance 1 and appliance 2 whose electrical characteristics are given in Figures 3 and 4, the value of this ratio is as follows: Appliance AR / R0 Appliance 1 0.206 1 Appliance 2 0.0138 Clearly this resistance ratio (fractional change in resistance) can be used to distinguish between appliances that have very similar steady state power consumption. Values of this ratio for different appliances or classes of appliances can be kept in the store 28. Then when an appliance is switched on and a value of the resistance ratio obtained, that value can be included in the inference calculation, along with the other coefficients discussed elsewhere, to produce the most probable estimate of which appliances are on any particular time, and the energy consumption by each appliance. Even when a new appliance is used for the first time, the resistance ratio can be used to identify the class of the appliance (eg. whether it is a toaster or a kettle) from known values of such appliances in general, without any a priori knowledge of the new appliance itself.

In a further enhancement, one can substitute a value for the temperature coefficient of resistivity a in Equation (1) and then solve directly for the temperature change AT to assist in identifying the appliance. The value of a for nichrome could be assumed because that is the most common heating element material. In fact one can iteratively solve for AT using various common values for a to further increase confidence in the identification of an appliance. For example, having detected what appears to be a light bulb, one could substitute in the value of a for tungsten (as used for incandescent light bulb filaments) and solve for AT in Equation (1). If the resulting AT is around 3000 K, then this supports the inference that the appliance is a light bulb. IfATis 100 K however, then the likelihood is that it is not a light bulb.

Although the specific embodiment described above envisages using the value of the ratio AR/R0 as being characteristic of specific appliances, this is not essential.

Ratios of other quantities such as power or current could equally well be used; they are both related to the value of the resistance, which is what is fundamentally physically changing as the heating element of the appliance reaches its operating temperature. Furthermore, in the preferred embodiment, in Figure 2, the power plotted was the product of the current and voltage; however a simplifying assumption could be made that the voltage is substantially constant and so the power is just directly proportional to the current, and the resistance of the appliance is simply inversely proportional to the current through that appliance, and therefore it is not essential to measure the voltage. A further possibility when considering the power used by an appliance is to base the calculation on the power in the first harmonic of the alternating supply rather than the total power.

Another alternative is that, instead of determining the time t when the current, power or resistance reaches a steady state, the apparatus simply detects when the appliance switches off and measures the resistance at that point and uses the "switch-off' resistance in place of R1 when calculating AR (or equivalently measures the switch-off current or switch-off power from the from the change in electrical

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parameters when the appliance switches off and uses those in obtaining mathematically equivalent ratios as the relevant classification values).

Figure 5 shows the power profiles for two further appliances which have the same nominal (steady state) power and cooling rates, but still have different profiles.

These two appliances could not be distinguished on the basis of steady state power consumption or fractional change in resistance because those values are the same.

The difference between these appliances is the thermal mass of the heating element and any other parts of the appliance that are being heated. For example, the effective thermal mass of an electric iron which has a large heating plate heating element is much greater than that of, for example, a toaster, which has a small heating element.

Again, looking at it physically, the heat energy added to a system is related to the change in temperature of that system as follows: Q = cinzT Equation (2) where Q is the net heat energy added to the system, c is the specific heat capacity of that system, m is the mass of the material heated, and iTis the change in temperature of the system.

In the case of an electrical appliance, the net heat energy added, Q, is equal to the integral with respect to time of the power supplied minus the heat lost through all cooling mechanisms. Although the electrical energy supplied can be obtained by integrating the electrical power from the electrical measurements, and LT can be approximated from Equation (1) from the resistance ratio and by assuming a value for c from known material properties (most heating elements are nichrome), the product c.m cannot be solved because the heat losses from the appliance are unknown and would generally be difficult to model because of their dependence on complex processes and their variation as a function of temperature.

However, according to a further embodiment of the invention, a classification value that is related to the thermal mass (c.m) and serves as a suitable classification value with which to discriminate between appliances has been found. This can be used both to identify the type of appliance (e.g. whether it is a toaster or a kettle) and to act as a further classification value to detect every time that particular appliance is turned on. Referring to Figure 6, this shows the electrical power drawn by an appliance from the time of switch on to to the time t1 at which a steady state is reached, this total time being Although plotted in terms of number of cycles, the physical time in seconds is directly proportional to the number of cycles of the alternating supply. The dark-shaded, approximately triangular area at the top of the graph is the area of interest according to this embodiment of the invention. This area provides a signature or classification value that can conveniently be used to distinguish between appliances, even when their steady-state power consumption P1 is substantially the same. Crudely speaking, the dark-shaded area is related to the excess energy that must be supplied to the appliance over and above the energy required to maintain a steady state when the appliance is at its operating temperature.

This area is related to the energy required to heat up the appliance, which in turn is related to the thermal mass of the system (product of the physical mass and the specific heat capacity).

One way to calculate this area is as follows: following the detection of an "on event" for a resistive appliance by the transient detector, the processor 26 starts to integrate the power with respect to time. When the power has stabilised (reached a steady state at which its gradient is below a threshold value), integration is stopped.

The integral value obtained gives the total area under the curve. The lower rectangular area is calculated by multiplying the final steady-state power P1 by the integration time (t3) and this is then subtracted from the total integral value to obtain the dark-shaded area of interest. This area is then used as a classification value along with some or all of the other values and coefficients defined above to determine which appliance was switched on and ultimately to calculate the energy consumed by that appliance.

The above example is simply one way of calculating the area to obtain a classification value. Other methods could equally be used, for example by approximating the shape as a triangle and calculating the area as: Iç(i, -i) or by other methods that seek to approximate the shape of the transient by fitting an approximate curve, and then integrating that, or other numerical integration techniques.

Furthermore, although in the above description the integration to find the area as a classification value is carried out on the real power, it could alternatively be carried out on the power in the first harmonic, or the power where the voltage is assumed to be constant (so the power is just related to the current, and would be equivalent to integrating the RMS current), or other derivations, such as equivalent areas on the resistance or impedance curves which are mathematically equivalent and related to the electrical energy supplied to the appliance in excess of that required to maintain the steady state.

Another classification value that can be used in the inference by the processor 26 is the time t until steady state is reached, and also the steady state power itself.

These, together with the other appliance characteristics such as time of day of use, duration of use, frequency of use and so on enable appliances with resistive loads to be uniquely identified.

It is not necessary to calculate the full set of classification values or appliance signatures every time that the appliance turns on, and indeed this may not always be possible if a further appliance is turned on while the first appliance is still warming up, such that the two transients overlap. However, the switch on power (P0) and the steady state power (P1 or equivalently the power at switch-off) can be measured in a single cycle of the alternating electricity supply independently of the base load or other appliance transients. Therefore, in these circumstances, these power levels can be assigned as belonging to "appliance A". In future, once the full transient information has been measured and the appliance has been classified, then a search through the local database will show that appliance A is in fact, for example, a kettle, and the energy consumption information can be updated accordingly. This inference can be reliable because in a typical house there are only a relatively small number of appliances of any particular type, and the set of appliances in the house does not change frequently. Therefore, once it has been established that a particular appliance is present, then it would be very unlikely that there is another appliance in the house that has exactly the same switch on power and steady state power levels.

A further enhancement is to take into account the cooling down of a resistive appliance after it turns off (either as a result of the natural end of its cycle of use, or as part of a thermostatic control). As it cools, its resistance will decrease. Then if it turns on again, before it has completely cooled down to ambient temperature, the measured resistance will be somewhere between the normal operating resistance R1 and the cold resistance R0. By monitoring appliances over time, the processor 26 will be able to deduce the rate of cooling and thus, when a switch on transient event is detected, be able to determine whether this is a new appliance switching on, or whether it is the previous warm appliance switching on again, based on the time since that appliance last switched off.

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 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 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 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 (RF) 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 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 andlor printer, or can be a dedicated device. Although the 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 meter is the analysis stage as already described to identify which appliances are being used at any particular time and bow 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.

A further use of the apparatus is to change the way billing is done, by acting as a smart meter". The data from the 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 reducing the quantity of energy 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 communities 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.

In the embodiments of the invention described above, only electrical energy is measured and discussed. However, the meter could be concerned with two or more utilities, for example additionally measuring water andlor gas consumption to improve inference of which appliances are in use at a particular time; in general the meter may aggregate information about multiple utilities to improve confidence in the inferred usage (for example by particular appliances) of each one of the utilities.

Claims (19)

1. CLAIMS1. Apparatus for metering the use of electricity supplied to a plurality of appliances, the apparatus comprising: an input section arranged to receive values representative of the total supply of electrical power as a function of time; a transient detector arranged to detect the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; an analysis section arranged to analyse the received values and to determine: (i) a first value related to the resistance of said appliance at the time of being switched on detected by said transient detector; and (ii) a second value related to the resistance of said appliance when operating in a steady state; and a processing section arranged to identify said appliance based on at least said first and second values, and to determine the electrical energy consumed by said appliance.
2. 2. Apparatus according to claim 1, wherein the received values are measurements of current or measurements of current and voltage of the electricity supply.
3. 3. Apparatus according to claim 1 or 2, wherein each said value related to the resistance is one of: the current; the reciprocal of the current; the voltage divided by the current; the voltage multiplied by the current, arid wherein said current values represent the current supplied to said appliance given by the total supply current minus the supply current before the switch on of said appliance detected by the transient detector.
4. 4. Apparatus according to claim 1, 2 or 3, wherein the processing section is arranged to calculate a classification value given by: the difference between the second value and the first value, divided by the first value.
5. 5. Apparatus according to any one of the preceding claims wherein the analysis section is further arranged to determine the time duration from when the appliance is switched on until the electrical power being used by the appliance has reached a steady state; and the identification of said appliance by said processing section is further based on said time duration.
6. 6. Apparatus according to claim 5, wherein the analysis section is arranged to determine a further classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and the identification of said appliance by said processing section is further based on said further classification value.
7. 7. Apparatus for metering the use of electricity supplied to a plurality of appliances, the apparatus comprising: an input section arranged to receive values representative of the total supply of electrical power as a function of time; a transient detector arranged to detect the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; an analysis section arranged to analyse the received values and to determine: (i) the time when the electrical power being used by the appliance has reached a steady state; and (ii) a classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; a processing section arranged to identify said appliance based on at least said classification value, and to determine the total electrical energy consumed by said appliance.
8. 8. Apparatus according to any one of the preceding claims, wherein electricity is supplied to a plurality of appliances and said processor is arranged to determine information on the electricity usage by individual ones of said appliances.
9. 9. Method for metering the use of electricity supplied to a plurality of appliances, the method comprising: receiving values representative of the total supply of electrical power as a function of time; detecting the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; analysing the received values and determining: (i) a first value related to the resistance of said appliance at the time of being switched on; and (ii) a second value related to the resistance of said appliance when operating in a steady state; and identifying said appliance based on at least said first and second values, and determining the electric energy consumed by said appliance.
10. 10. Method according to claim 9, wherein the received values are measurements of current or measurements of current and voltage of the electricity supply.
11. 11. Method according to claim 9 or 10, wherein each said value related to the resistance is one of: the current; the reciprocal of the current; the voltage divided by the current; the voltage multiplied by the current, and wherein said current values represent the current supplied to said appliance given by the total supply current minus the supply current before the switch on of said appliance.
12. 12. Method according to claim 9, 10 or 11, further comprising calculating a classification value given by: the difference between the second value and the first value, divided by the first value.
13. 13. Method according to any one of claims 9 to 12, further comprising determining the time duration from when the appliance is switched on until the electrical power being used by the appliance has reached a steady state; and wherein the identification of said appliance is further based on said time duration.
14. 14. Method according to claim 13, comprising determining a further classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and wherein the identification of said appliance is further based on said further classification value.
15. 15. Method for metering the use of electricity supplied to a plurality of appliances, the method comprising: receiving values representative of the total supply of electrical power as a function of time; detecting the time at which an appliance is switched on from a change in the received values due to an increase in the electric power being supplied at that time; analysing the received values and determining: (i) the time when the electrical power being used by the appliance has reached a steady state; and (ii) a classification value related to: the total electrical energy supplied to the appliance from the time of switch on until the time steady state is reached, minus the product of the steady state power and the time from switch on until steady state is reached; and identifying said appliance based on at least said classification value, and determining the total electrical energy consumed by said appliance.
16. 16. Method according to any one of claims 9 to 15, wherein electricity is supplied to a plurality of appliances and said method is arranged to determine information on the electricity usage by individual ones of said appliances.
17. 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. 18. A computer-readable medium storing a computer program according to claim 17.
19. 19. A computer program product comprising a signal comprising a computer program according to claim 17.