Field of the Invention [0002] The invention relates to metrology, and in particular, to increasing the accuracy of measurements during the operation of equipment in energy, information, and other systems.

Related Background Art [0003] A known method of determining the parameters of a system by measuring the parameters of a network and storing the measurement data is described in Patent RF No 212746,9/20/2003.

[0004] The principal disadvantage of this known method is the inability to ensure that the measurements are accurate. As a result, inaccurate assessments of the system's operating parameters can cause errors in the operation and control of the system. A need exists, therefore, to provide a method for reducing measurement errors that does not suffer from the foregoing disadvantage.

SUMMARY OF THE INVENTION [0005] It is an object of the invention is to provide an apparatus, system, method and program that provide a high degree of accuracy in the determination of a distributed system's parameters during system operation.

[0006] It is another object of the invention to provide to provide an apparatus, system, method and program that provide a high degree of accuracy in the real-time measurement of parameters of any preset elements of a system and synchronizing the readings from all sensors in the system, thereby reducing or substantially preventing malfunctions during the operation of the system.

[0007] According to an aspect of the present invention, when determining predetermined parameters of a distributed network including switching elements, sensing stations are used to measure the parameters of the system at its separate points, and an array of sequential measurements is produced for each of the sensing stations. Each measurement in the array indicates the time of measurement and determines the status of the system's preset switching elements. An array of the status of each of the switching elements is produced, indicating, for example, the time at which the status is checked and/or the time of a change in the status of each switching element. At least one selected sensing station is assigned a conversion function that determines whether a measurement is consistent with the"true" value of the parameter, as determined by a set of coefficients corresponding to that function. Each measurement given by a sensing station is compared to a control value for the measurement of that parameter determined by at least one other sensing station and in accordance with a network diagram determined by the status of the switching elements at the time of the measurement. Coefficients are determined based on the measurements by the sensing stations and the control values, such that if the true value of a measured parameter corresponds substantially equally to the control value of that parameter, the measured value of the parameter that corresponds to the true value is deemed equal to the measured value, and the true value of the parameter is used as the value of the network parameter as determined at the site of the corresponding sensing station.

[0008] When a network parameter must be determined by at least one sensing station, the measurements from a single sensing station are used. In addition, when the coefficients that determine the precise conversion function of at least one sensing station change based on the results of the measurements, the coefficients determining the precise conversion function of other sensing stations are adjusted by recalculating the prior measurements for those sensing stations.

[0009] To avoid recording clearly inaccurate measurements, a limit is imposed on the deviation of measurement of at least one sensing station, relative to the control value. If this deviation exceeds the limit, the sensing station provides an error signal.

[0010] Also, to avoid recording clearly inaccurate measurements, at least one sensing station has a limit on the extent to which the control values may deviate from each other. If this deviation exceeds the limit, an error signal is provided.

[0011] The method may be used to determine the parameters of, for example, hydraulic, electrical, and heating networks, mechanical energy distribution networks, or information networks, including data transfer networks. In the latter case, the method may be used to determine, for example, the volume of traffic in the communication nodes or lines of a network.

[0012] The method may also be used to detect inconsistencies among sensing stations in a network. The method permits a comparison of the measurements of at least two linked sensing stations. In the event of a disparity in the measurements of these sensing stations that exceeds the permissible disparity for linked sensing stations, a signal is given indicating the disparity.

BRIEF DESCRIPTION OF THE DRAWINGS [0013] Fig. 1 is a block diagram of a distributed electrical network in the form of a power grid that is suitable for practicing the present invention.

[0014] Fig. la depicts a computing device used in the network of Fig. 1.

[0015] Fig. lb represents first and second sensing stations included in the network of Fig.

1.

[0016] Fig. 2 represents two heterogeneous sets of measurement results employed in the present invention.

[0017] Fig. 3, consisting of Figs. 3A and 3B, depicts a flow diagram of a method performed according to the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT [0018] A preferred embodiment of the present invention will be described in detail below with reference to the accompanying drawings. It is noted that although the following description is described primarily in the context of an electrical power grid system, the invention is not limited for use only in such a system. Indeed, it is within the scope of this invention to increase the accuracy of measurements during the operation of equipment used in any other suitable types of energy, information, or other like distributed systems.

[0019] During the operation of a power grid, malfunctions can occur as a result of, for example, leakage of current to ground, damage to inter-phase insulation, unauthorized connections, and the like, which can either cause failures in or otherwise detrimentally affect the operation of the power grid, or exceed predetermined acceptable tolerance limits for the power grid. The preferred embodiment of the present invention is designed to detect such malfunctions as well as to increase the accuracy in the measuring of parameters of the network so as to enhance the stability and reliability of the system during normal operations and emergencies.

[0020] The ability to increase the accuracy is supported by the following mathematical theory. The effect of ambiguousness, which is the basis of the technical result produced by this invention, is illustrated in diagram 2.

[0021] The principal problem in increasing the accuracy of processing technical measurements on the basis of mathematical methods of processing the results of measurements is eliminating systematic constituent errors in the measurements, which generally account for more than 90% of total errors in measurement. Traditional mathematical methods of processing data examine a set of measurement results as a homogenous aggregation Q, and therefore they do not allow for the reduction of systematic constituent errors without conducting additional highly precise measurements. The invention, on the other hand, provides a method for obtaining virtual reference measurements based on the use of two (or more) heterogeneous sets of measurement results (Ql Q2 in Fig. 2), and on that basis, reduces systematic constituent errors in measurements as well as incidental errors.

[0022] If measurements are represented as a function of unknown incidental and systematic constituent errors in measurement, then an equation that is a function of only a single set of measurement results will be unsolvable. However, by examining the results of the measurements as two heterogeneous sets, a system can be obtained that is made up of two equations that are a function of two unknowns, namely, incidental and systematic constituent errors of measurement. Such a system is solvable, and can take into account known measurement results and computational errors to evaluate the true value of a measured parameter. For example, the coefficients of a functional dependency that is a function of unknown incidental and systematic constituent errors of measurement are determined on the basis of multiple measurements with a consistently changing (decreasing or increasing) determining parameter.

[0023] By example, as the two heterogeneous sets of measurement results (Q1 Q2 in Fig.

2) the following can be used, respectively: a set of results of multiple measurements, obtained as the measured parameter changes (decreases or increases) consistently, and a set of a priori information representing the measured parameter at each moment of time of the measurement.

[0024] The method of processing measurements depends on the use of reliable a priori information representing the measured parameter at each moment of time of measurement.

Generally, such a priori information is very frequently present in the process of measurement, and if the necessary a priori information about the measured parameter is absent, it can be obtained on the basis of additional measurements that need not be extremely precise. The fact that the accuracy of measurement is elevated to the reference level as a result ensures that a very significant effect is achieved in this case as well.

[0025] It follows that the discovery of ambiguity in the relationship between the true value of a measured parameter and the results of measurements allows the formulation and solution of the system indicated above from two mutually independent equations, and on that basis ensures reference-level precision in the measurements, taking into account the incidental as well as the systematic errors.

[0026] The physical origin of this effect of ambiguity in whether the true value of a parameter is consistent with the results of the measurements will now be examined. The interaction of the measured parameter and the means of measurement (MM) occurs on the potential field of the measured parameter, which generally is accompanied by a transformation of the potential energy between two points with different potentials into different forms of energy in the method of measurement. During measuring, the measuring instrument or gauge can disturb the object of measurement and introduce an error in the result of measurement.

[0027] A principal idea of a measurement procedure is the transformation of a closed mutually exclusive (isomorphic, as known in abstract algebra) system, "object of measurement-MM", into a unidirectional (homomorphous) system. This ideal condition with unidirectional (homomorphous) connections, "object of measurement-MM", corresponds to the true value of the measured parameter. The actual value of the measured parameter differs from the true value by the size of the measurement error.

[0028] Fig. 1 depicts a distributed network in the form of an electrical power grid system that is but one example of a type of network that is suitable for practicing this invention.

The power grid comprises at least one energy source, such as power source (1), at least one downstream distribution station, such as power station (2), which locally distributes electricity to predetermined consumers, and transmission lines (3) that interconnect the elements (1) and (2). Pre-set switching elements (4) that are employed to selectively connect or disconnect network components, such as elements (1) and (2), from each other through, for example, line (3), also are included at predetermined points in the network depending on applicable network design criteria. The switching elements (4) are preset, using a calibration function, discussed later, according to the structure of the network. The coefficients of the calibration function may be expressed in a tabular form and used for calculating a measurement value of the sensing stations (5) (only one sensing station, power source, and power station are shown in Fig. 1 for convenience; however, it should be understood that more of these components may be connected in the network). The switching elements (4) can be controlled by a network management control system, which may be, for example, the computing device (6) or a separate management system (not shown) in communication therewith and connected in the network.

[0029] Sensing stations (5) measure predetermined parameters or phenomena at predetermined points in the grid, such as in, for example, transmission lines (3) or elsewhere. The sensing stations (5) each measure/detect a predetermined physical parameter or phenomenon of the power grid, such as (electrical energy) current voltage, potential, capacity, power, and/or any other predetermined measurable physical (electrical) quantity, and transmit the measured parameters (i. e. , detected levels of the parameters) to a computing device (6), such as, for example a data processing unit, server, a PC, laptop or other remote personal computer, although in other embodiments other suitable types of information processing apparatuses also may be employed.

[0030] Referring to Fig. la, the computing device (6) preferably comprises a controller (7), and an associated data storage device (8), an output-user interface, such as a display (9), a user-input interface (10), and an electronic interface (6'), all of which are electronically coupled to the controller (7). The controller (7) controls the overall operation of the computing device (6), and includes, for example, one or more microprocessors and/or logic arrays for performing arithmetic and/or logical operations required for program execution.

[0031] The electronic interface (6') is employed by the controller (7) for communicating bidirectionally with other, external components of the network.

[0032] The data storage device (8) represents one or more associated memories (e. g., disk drives, read-only memories, and/or random access memories), and stores temporary data and instructions, as well as various routines and operating programs that are used by the controller (7) for controlling the overall operation of the computer device (6). Preferably, at least one of the programs stored in the device (8) includes instructions for performing a method in accordance with this invention, to be described below. The data storage device (8) preferably also can store various other information obtained during performance of the method of the invention to be described below.

[0033] The user-input interface (10) may include, for example, a keyboard, mouse, a trackball, touch screen, and/or any other suitable type of user-operable input device (s), and the output-user interface may include, for example, a video display, a liquid crystal or other flat panel display, a speaker, a printer, and/or any other suitable type of output device for enabling a user to perceive outputted information, although for convenience, only the display (9) is shown in Figure 1 a.

[0034] The sensing stations (5) are networked in a system via data transfer channels (not shown). The sensing stations (5) preferably are disposed at predetermined points in the network, as mentioned above. Each sensing station (5) is responsive to detecting a predetermined parameter being measured by outputting a corresponding output signal, representing the detected level of the predetermined parameter. The signal is forwarded to the computing device (6) via dedicated communication paths such as communication channels, high-frequency communication lines, or other suitable communications paths.

The communication paths may include, for example, telephone, cable, or wireless technologies, and may communicate through a network such as the Internet (not shown) and/or some other communication network, local or otherwise. The number and variety of computing devices (6) that may be employed can vary widely, as can the number of sensing stations (5) and components (1), (2) and (4) that are employed, depending upon applicable operating criteria. It should be noted that the sensing stations (5) can be included elsewhere in the system than the locations shown in the Fig. 1 and described above, as can the switching elements (4), and also that the elements (1) and (2) may represent any other node within a distribution system besides a power source and power station. In general, the teaching of this invention may be employed in conjunction with any suitable type of computing device or information processing apparatus that is capable of

receiving information from other components of a distribution network, such as, by example only, sensing stations within the distribution network.

[0035] A more detailed depiction of two sensing stations, identified further herein as a first sensing station (4') and a second sensing station (5'), is shown in Fig. 1B. The first sensing station (5') (also referred to as a control station) includes a sensor (51) and an indirect measurement module (52), and the second sensing station (4') includes a sensor (61) and an approximate measurement module (62). The components (52) and (62) may each represent a separate physical component that undesirably introduces some error quantity into the measurements made by the sensors (51) and (61), respectively. By example only, in an embodiment where the sensors (51) and (61) are analog devices, the modules (52) and (62) may be A/D converters that introduce an error quantity into the measurements, wherein the error quantity depends on a characteristic error inherent in the respective modules (52) and (62). In another embodiment, the modules (52) and (62) may be voltage- frequency converters with a counter, although it should be noted that the modules (52) and (62) are not limited only to A/D or voltage-frequency converting devices. Preferably, as known by the computing device (6) based on predefined criteria information identifying the stations (4') and (5'), the relative error rate (i. e. , characteristic error) inherent in the indirect measurement module (52) is less than that of the approximate measurement module (62).

The computing device (6) can deliberately select to monitor those stations for the purpose of performing a method of the invention to be described below, for increasing the accuracy of station (4') measurements and network measurements in general, based on the more accurate station (5') measurements. The selection can be based on predetermined criteria for evaluating the network, may depend on load requirements at particular times, or the like, and may occur periodically or as deemed necessary. Such criteria also can determine the precise locations of the sensing stations that are to be evaluated as the first and second sensing stations.

[0036] By virtue of the characteristic error inherent in the modules (62) and (52), their output signals represent the original measurements made by the sensors (61) and (51), respectively, but varied by (plus or minus) an error value corresponding to the characteristic error inherent in the respective modules (62) and (52). For convenience, these output signals are hereinafter referred to as uncompensated parameter measurement signals, and may include random and systematic errors (described below). The measurements may vary over time owing to, for example, error fluctuations. Also,

although in the illustrated embodiment the modules (62) and (52) are depicted as being physically separate from the sensors (61) and (51), respectively, in other embodiments the modules (62) and (52) and sensors (61) and (51), respectively, may be integrally formed.

[0037] The parameters measured by the selected sensing stations (5') and (4') are provided to the computing device (6) wherein they are stored in the data storage device (8). The sensing stations (5) generally measure the predetermined parameters automatically at predetermined time intervals. The different sensing stations (5) may output signals over a same (or different) time period, and the computing device (6) is able to recognize that those signals originate from particular ones of the sensing stations as opposed to from other sensing stations. Preferably, at least some of the sensing stations transmit output signals at different time intervals. For example, the interval between measurements taken by one of the sensing stations (5), such as the first sensing station (5') (also referred to as a control sensing station), preferably is greater than the interval between measurements taken by another sensing station (5), such as the second sensing station (4'), as known to the computing device (6).

[0038] An array of the results is produced that includes the measured parameters, and the time of each measurement, for example, the current time at the end or the beginning of the measurement process. Substantially simultaneously with the measurements made by the sensing stations (5), at least one system, for example a telemetry system (not shown) in communication with the computing device (6), determines the status of the preset switching elements (4) of the power grid, and transmits"status"data to the computing device (6) which then creates an array representing the status of each switching element (4) and the time at which the status of the switching element (4) was taken and/or the time when the status changed (for example, the time when switching began or ended). The telemetry system, which may be electrically connected to the sensing stations (5), determines the"open"or"closed"status of the switching elements (4). The telemetry system makes the"status"determination using any suitable, known technique. For example, the telemetry system may operate according to the technique (s) described in the article entitled"Telemetry"by Albert Lozano-Nieto (CRC Press LLC, copyright 2000 http ://www. engnetbase. com), which is incorporated by reference herein in its entirety, as if fully set forth herein.

[0039] At least one selected sensing station (5) is assigned a conversion function (also referred to as a transformation function) that determines whether the measurement made

thereby is consistent with the"true"value of the parameter, as determined by a set of coefficients corresponding to that function. In one embodiment, the conversion function may be given in the form of an exponential or trigonometric series or other series in which the coefficients of the series must be collated in order to determine their precise relationship. In other embodiments, the function may be given as a piecewise linear approximation or as a function whose values are expressed in tabular form. In the latter case, the coefficients of the function will be the possible values of an argument and function values corresponding to them. For example, a tabular form of the calibration function may describe three types of linear coefficients of three different voltage ranges (less than 50 volts, 50-100 volts, and greater than 100 volts). If the voltage value is 73 volts, a calculation according to the calibration function of u = 0.05 (V) + 1. 101*73 (V) is performed. Considering that the precision of the representation of the results of measurement is always limited by the quantity of significant digits, the last type of representation of a function whose values are expressed in tabular form is preferred for use in practice.

[0040] The calibration function may be connected with an input resistance connected to the network. The network is based on a particular configuration of the power grid determined by the connected ("closed") switching elements.

[0041] The coefficients of the function are collated (calculated) by the computing device (6) determining, for each measurement by a sensing station (5) (e. g. , sensing station (4')), at least one"control"value corresponding to the measurement of the corresponding parameter according to the network parameters, as measured by a different sensing station (5) (e. g. , sensing station (5') ) and in accordance with the network determined by the status of the switching elements at the time of the measurement. (The determination of the coefficients is described in detail later on. ) For example, the current in a specific transmission line, as measured by a current sensing station (5) connected to that transmission line, can also be determined in an indirect way by a process of computing and determining the current in all of the other transmission lines that are switchably connected to a predetermined one of the nodes in the grid to which the transmission line to be measured is connected. The current in the transmission line, determined by this indirect method, typically is not simply the sum of the currents in the power grid, because the determined value may be adjusted, if deemed necessary, to account for possible errors inherent in the sensing stations, depending on how accurately these errors can be detected.

Calculating or measuring the fall in voltage in the line under the known full resistance of the line can also determine the current.

[0042] Accordingly, coefficients of the dependency function are determined for a given sensing station based on the measurements by the sensing station (5) and the control values measured by a different sensing station, such that if the true value of a measured parameter corresponds substantially to the control value of that parameter, then the corresponding measured value of that parameter substantially corresponds to the true value. The resulting true value of the parameter is used as the value of the network parameter as determined at the location of the corresponding sensing station (5).

[0043] It should be noted that the term"true value"is used herein to indicate the value (quantity) of a parameter as determined with the maximum possible accuracy (i. e. , a substantial, approximation of the actual quantity), because in practice the actual true value cannot be determined with absolute precision. (However, for convenience, the phrase"true value"is used herein). This is due not only to limitations in the precision of determining error, but also to the limitations in the precision in representations of the measurement, determined, for example, with the maximum quantity of significant digits in the numbers that can be processed by a computer system, such as device (6). For convenience, the terms"true value"and"substantial approximation of the true (or actual) value"are used interchangeably herein.

[0044] In a simple case, the measurement by a single sensing station (5) can be used when a network parameter must be determined by at least one sensing station (5). However, in order to ensure the maximum possible precision of the measurement, the parameters of a sensing station (5), as adjusted based on a computation of the appropriate functional dependencies, can be used as the network parameter.

[0045] A method according to a preferred embodiment of this invention will now be described in detail, with reference to FIGS. 3A and 3B. The method operates in accordance with instructions of a program stored in the data storage device (8), and the controller (7), among other components, operates in accordance therewith.

[0046] At block 20 detections made in the above-described manner by at least two different sensing stations (5), such as the first sensing station (5') and the second sensing station (4'), are processed at block 22. As mentioned above, the modules (52) and (62), which may include, for example, analog-to-digital converters, can introduce an undesired

error into the sensor (51) and (61) outputs, depending on the characteristic error inherent in the modules (52) and (62).

[0047] Uncompensated parameter measurement signals outputted by the sensing stations (4') and (5') are provided to computing device (6). The controller (7) responds to receiving the initial signals by, for example, identifying the first and second sensing stations from which the received signals originated (by recognizing, for example, a predetermined unique identification code included in the signals), and also recognizing the types and number of the sensing stations and the type of parameter (s) detected thereby. These identification and recognition functions may be performed in accordance with any suitable, known identification and recognition technique (s), and will not be described in further detail herein.

[0048] A high-precision error compensation procedure according to the present invention then is performed. During the procedure, which, for example, may be initiated either automatically, or at predetermined time intervals, or in response to a user entering a predetermined command into the computing device (6), first values Y1 representative of the uncompensated parameter measurement signals outputted by the first sensing station (5') (over the predetermined time period) and provided to the computing device (6), are stored in data storage device (8) in a first array of such values (block 24). Second values Y2 representative of the uncompensated parameter measurement signals outputted from the second sensing station (4') (over the predetermined time period) also are provided to the computing device (6) and stored in the data storage device (8), but in a second array that includes such values, at the block 24.

[0049] Next, at block 26 the computing device (6) performs a number of procedures.

First, an arithmetic mean of the measurement results is determined. As an example, the array of first values Y1 and the array of second values Y2 are each subdivided into a first subset and a second subset thereof, wherein, the each subset includes a predetermined number (e. g. , five) of the respective first or second values. The first values of the first subset of first values are summed in the equation (Fl 11) and the first values of the second subset of first values are summed in equation (Fla), and each sum is divided by n/2 :

where: n represents the number of first values ; yil represents a first value (originally outputted by module (52) ) ; Fll represents an average of the first subset of first values; and Y2l represents an average of the second subset of first values.

[0050] The second values of the first subset of second values are summed in the equation (F2l) and the second values of the second subset of second values are summed in equation (F22), and each sum is divided by n/2 : where: n represents the number of second values; yi2 represents a second value (originating from module (62) ) ; Y12 represents an average of the first subset of second values; and Y22 represents an average of the second subset of second values.

[0051] A transpose of Yll and Y21can be represented by (F3) below, and a transpose and 2 can be represented by (F4) below: [0052] A ratio ko represents a first general approximation of a multiply-systematic effect in the error in the indirect measurement module as a proportion (ko-1), and essentially is a difference between the averages of the second and first subsets of second values to a difference between the averages of the second and first subsets of first values. The ratio ko is determined using the following equation (F5) (preferably the middle portion is employed in the calculation), based on the averages determined above.

[0053] A linear operator T representing the second sensing station (4') can be represented in matrix form (F6) below, and, based thereon, another form of the above formula (F5) can be obtained, as represented by formula (F7) below. where E"is a unit vector as follows: [0054] In the process of real technical measurements, elements such as a module (62) of a sensing station (5), such as station (4'), can introduce a multiply-systematic error effect (factor), and thus disturbances in the linear operator T occur, where the influence of disturbance can be represented by the following expression: T (,-) = T + X-T where: X represents a disturbance value caused by external influencing factors. e. g. , at least part, if not all, of the disturbance % may be caused by the multiply-systematic effect of the module (62).

[0055] It is known that linear operators of the type T (Z) are characterized by their own ambiguous functions with two branches. For example, in a publication by Kato T. , entitled "Theory of Disturbance of Linear Operators", pp. 62-67, M: Mir (1972) (hereinafter"the Kato publication"), a description is given of an example analysis resulting from research, of the disturbance (perturbation) of individual characteristic values (eigenvalues) of a disturbed operator of the following type :

[0056] Thus, a"perturbed"form of formula (F7) can be represented as shown in the following expression (10).

[0057] Based on the definition of eigenvectors, two eigenvalues of linear operator T are #1,2(#) and thus eigenvectors UI, 2 of T'can be obtained through the following equations (all) and (F112), which generally relate to a matrix of eigenvectors: <BR> <BR> <BR> <BR> T'#u1,2(#)=#1,2(#)#u1,2(#) (F111)<BR> <BR> <BR> <BR> <BR> <BR> <BR> <BR> <BR> (T'-#1,2(#)#E)#u1,2(#)=0 (F112) where: E is a unit vector and u is a vector representing a single matrix (with one diagonal).

[0058] According to the definition of eigenvectors, and based on the form of formulas (F5) and (F10), values kl and k2 are obtained by the computing device (6) based on formula (F14) : where: kl represents one possible value of the approximation of the multiply-systematic effect in the error in the module (52) as a proportion (kl-1) ; and k2 represents another possible value of the approximation of the multiply-systematic effect in the error in the module (52) as a proportion (k2-1).

[0059] Based on the above expression (F14), a multi-valued function (F15), defining the equation of a straight line (disposed at an angle), can be represented by:

yi2=k1,2#yi1+a0 (F15) [0060] After block 26, control passes to block 28 where data obtained based on at least some of the foregoing formulas is stored in the data storage device (8). Thereafter, control passes through connector A to block 30 of FIG. 3B. At block 30, a determination is made as to whether kl or ka should be selected as being closest to ko, using a target function formed using min-max criteria. For example, according to a preferred embodiment of the invention, this procedure first includes assignment of the required type of function, using expression (F18) : where: xi represents ideally the"true"value of the measurement (i. e. , a substantial approximation thereof) ; vy is a transformation function representing the first sensing station (5'); yil represents measurement values taken by the first sensing station (5') and stored in device (8); and ao is a value representing a common (systematic) effect expressed as an additive correction. Generally, value ao is near zero, and is less than the multiplicative systematic error.

[0061] Also, a constraint zone is formed based on the following formula (F19) : ; (F19) where: yil represents a first value, influenced by kl and k2 (through formulas (F14) and (F15)) (i. e. , a signal from module (52) and stored in device (8)) ; ys2 represents the second value (i. e. , a signal from the module (62) and stored in device (8) ) ; and ai represents a predetermined error constraint value defining the limit of acceptable ys2 values. The predetermined error constraint value preferably is substantially equal to a predetermined characteristic error inherent in the first sensing station, although in other embodiments other values may be employed instead, such as, for example, a characteristic error inherent in the second sensing station.

[0062] Thereafter, the criterion function H is formed as represented in formula (F20) (block 30).

[0063] The formula (F20) employs only those values that are determined to satisfy the formula (F19), and determines essentially a difference between (ko-kl) and (ko-k2). The lesser difference is then selected, as is the corresponding value kl or k2.

[0064] Thereafter, control passes to block 32, where the computing device (6) calculates a value for xi based on formula (F 18) above, using values determined to satisfy formula (F19) as well as the result of formula F (20). The resulting calculated value xi is stored in the data storage device (8) and may be provided to a predetermined external destination, such as an information processing/exchange apparatus, server, or the like, either directly or through a communication network (not shown) (block 34). Thereafter, at block 36 the computing device (6) uses the result from formula (F 18) and a second valuer (originating from the second sensing station (4')) in performing formula (F21) below, to calculate a corresponding error A, that includes both random and systematic components: , Yi = yi,-xi (F21) [0065] It should be noted that in formula (F21) second value (s) yi2 (originating from the second sensing station (4') ) preferably are employed rather than first value (s) (originating from the first sensing station (5')). Those second values may be ones received in real time, or, in another embodiment, they may be previously received and/or stored second values, depending on predetermined operating criteria. In other embodiments of the invention, values from the first sensing station (5') may be used in formula (F21) instead, depending on the application of interest.

[0066] The random component (of the above error), which also is referred to as a random effect, is then calculated by computing device (6) using equation (F22) (block 36): A rand = VD-A. (F22) where: A,, d represents the random component ; and Dx represents a known mathematical dispersion.

[0067] Moreover, according to an aspect of this invention, the systematic component (also referred to as a systematic effect) is calculated by the computing device (6) using equation (F23) : <BR> <BR> <BR> <BR> <BR> <BR> #syst=trend(#x)<BR> (F23) where: A, yst represents the systematic component (also referred to as the systematic effect) of the second sensing station (4') (particularly module (62) ), in the exemplary embodiment described herein; and trend (Ax) represents a trend function.

[0068] The error coefficients determined in the foregoing manner in formulas (F21) to (F23) are then stored in the data storage device (8) at block 40.

[0069] Thus, when uncompensated parameter measurement signals are received by the computing device (6) from the second sensing station (4') (after the value xi has been obtained by computing device (6) ), random and systematic errors that may be included in the signals are substantially compensated for by the computing device (6), based on a random error value A,. ana and systematic error value Asyst calculated using formulas (F22) and (F23), respectively. As a result, the computing device (6) generates corresponding compensated signals that are substantially close in value (or at least closer than the corresponding value outputted from the second sensing station (4') ) to the actual or'true" value of the corresponding parameter (phenomenon) subjected to measurement by the second sensing station (4') (block 42). Information outputted from the computing device (6) represents the compensated signal (s) (as well as a reference magnitude of the measured parameter) and is displayed on display (9), which responds to receiving the information by presenting it to the user (block 44). That same information also can be forwarded to the predetermined external destination and/or the network management control system through the interface (6'). In the foregoing manner, the measurements originating from the second sensing station (4') are corrected to improve their accuracy.

[0070] As discussed previously, an aspect of the invention is the ability to correct errors not only in ongoing measurements, but also in earlier measurements, to ensure necessary precision of the earlier measurements, and for use in future calculations. The output of the computing device (6) allows a user and/or the network management control system to

monitor the network parameters, and make necessary adjustments such as effecting appropriate switching control in the network, etc. For example, the information obtained from the computing device (6) by virtue of the above method can be used in conjunction with obtained switching element status information and network architecture information, to close or open selected ones of the switching elements (4) to selectively connect or disconnect a load and/or power station to/from the network, to isolate faults identified based on the information, to redistribute loads within the network to accommodate for daily load requirement variations, and the like.

[0071] In some cases, the decision of whether to connect or disconnect a power source or load may not require the adjustment of previous measurements, although they may be so adjusted if deemed necessary. However, in determining the amount of a consumed load for a calendar month, for example, or to account for the difference in tariffs for various times of day, adjustments to previous measurements can have a significant effect on the result and thus significantly change the amount of payments by energy consumers, for example.

The adjustments may be for, by example, every hour, per week or month, or per another time period.

[0072] When necessary to adjust previous measurements in the event that, based on the results of measurements, changes are made in the coefficients that determine the conversion function of at least one sensing station (5), the coefficients that determine the conversion function of the other sensing stations are adjusted by recalculating the previous measurements for those sensing stations. Thus, based on results obtained by the computing device (6) in the above-described manner, more accurate assessments can be obtained of the network's load consumption and associated expenses over predetermined time periods.

Even if original load consumption and expense determinations have already been made without the benefit of employing the above method of this invention, the sensing station outputs (data) that were used to make such original determinations can be recorded for subsequent insertion into the above formulas (Fig. 3) to obtain more accurate measurement readings, or they can be adjusted (weighted) based on other sensor measurements made more accurate by the above method, using a predetermined relationship relating those sensor outputs (according to the network configuration), or based on a predetermined result from the formulas (e. g. , (F21), (F22), and/or (F23) ). The results then can be used to adjust the original determinations to obtain more accurate determinations. Such procedures can be performed, for example, automatically at the computing device (6).

[0073] According to another aspect of the invention, when the coefficients that determine the precise conversion function of at least one sensor change based on the results of the measurements, the coefficients determining the precise conversion function of other sensors are adjusted by recalculating the prior measurements for those sensors. Such recalculating can be performed based on the relationship between the parameters detected by those sensors and/or the network configuration. As but one example, the recalculating can be performed according to formula (F23) above. Also, the result obtained from formula (F23) can be used to adjust measurements taken by other sensors based on the result of the formula obtained for one sensor.

[0074] To increase the stability and reliability of the system, at least one sensing station (5), such as for example station (4'), has a limit on the extent to which the measurement of a parameter may deviate from the control value of the parameter of another station (e. g., station (5') ). If the measurement exceeds a predetermined deviation limit, an error signal indicating the deviation by the sensing station (5) is generated in the computing device (6) as a result of it recognizing the situation. The deviation may be a result of, for example, a break in connections of the sensing station (5) measuring circuit or some other disruption or fault in the operation of the sensing station (5), and the error signal can be presented through the user-output interface and/or forwarded to another destination by device (6).

When an error signal is provided, the measured parameters of the sensing station (5) in error are not counted or employed in the determination of the functional dependency in the above formulas. The defective sensing station (5) can be isolated (by, e. g. , ignoring its outputs, effecting appropriate switching, or the like, upon recognition of the error signal), and can be fixed or replaced in time, and a determination of the modes of operation of that sensing station (5) maintains the operability and stability of the network.

[0075] In a similar manner, errors in the operation of the overall grid system can be detected and a user and/or the network management control system alerted. Examples of such errors include, without limitation, an excessive increase in the diversion of the capacity for the system's own needs or an unauthorized connection of a consumer/power station. In order to detect such errors, at least one sensing station (5) is given a limit on the extent to which the control values of a parameter may deviate from each other. If the control values of the parameter exceed the deviation limit, a signal indicates an error in the operation of the grid system. Appropriate network control can then be effected to isolate related equipment.

[0076] The function of this embodiment also ensures that a predetermined disparity among linked sensing stations can be detected by comparing in device (6) the measurements of at least two linked sensing stations (5). If the predetermined disparity in the measurements of these sensing stations (5) exceeds a predetermined value for linked sensing stations, a signal is provided as above, indicating the disparity and its magnitude.

[0077] Upon recognizing a signal indicating either a disparity or an exceeding of an acceptable measured value, appropriate switching arrangements/control can be effected under the control of the network management control system to remove and/or isolate part (s) of the network deemed to be suffering from a fault condition, shift loads, etc. , as deemed necessary.

[0078] It should be noted that, in the context of the invention, additional procedures/calculations also may be performed in the computing device (6) to standardize the value (s) from the first and second sensing stations to ensure that they are processed in a same workable format that depends on the application of interest. For example, in a case where it is expected that a voltage detected by the first sensing station differs by a predetermined factor from a voltage detected by the second sensing station because of the sensing stations'given locations within the distribution network, voltage values obtained from one or both sensing stations can be weighted as deemed necessary to account for the factor, and the output value from the computing device (6) can be modified to account for any such weighting. Also, in embodiments where the first and second sensing stations measure different types of parameters (e. g. , current and voltage), the calculations preferably also account for this difference as well by converting values derived from a predetermined one of the sensing stations from one format (i. e. , current) to another selected format (e. g. , voltage), based on the predetermined relationship through which the parameter types are related, so that values of the same type are obtained for each first and second sensing station for use in the formulas. These calculations may me performed in accordance with any suitable known techniques, and may account for the network configuration etc.

[0079] Also, in accordance with a preferred embodiment of this invention, calculations by the computing device (6) according to Fig. 3 are performed only after a signal is applied to the computing device (6) from the first sensing station (5'). The outputs of computing device (6) are maintained the same until a next signal received from the first sensing station (5') is applied to and processed by the computing device (6) (or the computing device (6)

processes a next subset of values received from the first sensing station (5'), depending on the embodiment employed).

[0080] Also, it should be noted that, according to one embodiment of the invention, the signals that are subjected to compensation in Fig. 3 are the same signals for which the error is determined. However, in other embodiments the signals that are subjected to compensation may be ones that are received at computing device (6) after the error is determined based on earlier received and stored signals (i. e. , based on values stored in storage device (8) ), or based on, for example, the eigenvalues andlor values ko, kl, and k2 calculated based on earlier measurements.

[0081] Also, according to an embodiment of this invention, values calculated by formulas (F18), (F21), (F22), and/or (F23) are outputted from the controller (7) to the predetermined destination external to the device (6), through the interface (6'). Such outputting may be performed upon each value or selected group of values being calculated, or at some time later after the value (s) have been stored in storage device (8), and may occur either automatically or in response to a predetermined event occurring, such as a predetermined time being reached or a predetermined command being inputted through the input-user interface (10). Additionally, those values may be outputted from device (6') either together with, or separately from, the corresponding first and second values that originally were received from the sensing stations (5') and (4') and used to generate the values from the mentioned formulas.

[0082] According to another aspect of the invention, the controller (7) preferably excludes clearly erroneous values (e. g. , values falling outside a predetermined range) of parameters from those already saved, and the storage device (8) stores information identifying values of parameters determined to be erroneous. Preferably, the controller (7) produces an alarm signal when one of the parameters exceeds predetermined, or permissible, limits. The alarm signal may be outputted to the output-user interface and/or provided to the predetermined external destination through the interface (6'). Formula (F19) is but one example of a manner for determining such erroneous values.

[0083] According to another embodiment of the invention, after the interface (6') receives and forwards to the controller (7) the output signals of the sensing stations (5') and (4'), the controller (7) determines whether there is a predetermined disparity between the output signals of the sensing stations (5') and (4'), and if there is a predetermined disparity (unbalance), the procedure depicted in Fig. 3 is then performed based on those signals. The

controller (7) also can generate a signal indicating the size of the disparity, if any, to the display (9) and/or through the interface (6') to a predetermined external destination, although this step can be performed without the further implementation of the method of Fig. 3.

[0084] The computing device (6) is able to further increase the precision of measurements due to the fact that the controller (7) can determine the limits of permissible values of input parameters and delete from the storage area (8) the values of input parameters that, after comparison to a predetermined permissible range of values, are determined to exceed limits of the range.

[0085] As noted above, it should also be noted that, although the present invention is described in the context of measurements of the electrical parameters described above, broadly construed, the invention is not limited for use only in conjunction with electrical measurements. Indeed, the present invention can perform mathematical processing of measurement results to increase the precision of any suitable type of physical measurements, whether electrical or not. For example, in other embodiments, the present invention can measure, in aggregate or separately, a system's active, reactive or full capacity, losses in insulation, consumption of power for the system's own needs (auxiliary power consumption), the currents and voltages in the system, the full, active, or reactive resistances in the circuits, as well as other parameters. With a qualitative analysis of the status of the circuits, it is possible to prevent common failures in the modes of operation.

[0086] When used in information networks, the present invention allows the determination of bandwidth and attenuation coefficients of separate communication channels, making it possible not only to control individual branches of the circuit, but also to decide whether to connect reserve communication channels and to make preventive repairs. In a simple application, the present invention allows the determination of the status and the measurement of the volumes of network traffic in telephone and data transfer systems. In each case, for example, the sensing stations detect a corresponding bandwith or communication traffic level being monitored, and the method proceeds in a similar manner as described above using that detected information (e. g., Fig. 3).

[0087] In mechanical systems, the present invention allows for the determination of force, moments, and transmitted capacity, heat energy, fluid flow, and the like (i. e. , the sensing stations detect those types of parameters, and the method proceeds in a similar manner as described above (e. g., Fig. 3) ). When applied, for example in automobiles with automatic

transmissions, the reliability of the automatic transmission and anti-locking systems can be increased. Forces, moments, and transmitted power, which may find application of four- wheel drive vehicles with automatic transmission, for example, can be determined, thereby enhancing the reliability in the operation of automatic gear boxes and anti-lock systems.

[0088] The present invention can also be used in hydraulic and pneumatic systems with characteristics similar to those of electrical networks (i. e. , the sensing stations detect predetermined hydraulic or pneumatic parameters in such systems, and the method proceeds in a similar manner as described above (e. g., Fig. 3)).

[0089] A principal advantage of the described invention is that, during its use, it does not require the use of references to make reference measurements, because the functional dependencies, assuming precise determination of the corresponding coefficients, allow the determination of a substantial approximation of the true or actual values of parameters subjected to measurement, with any required level of precision.

[0090] Knowing the parameters of a system that are obtained using this method makes it possible to manage the efficiency of a system purposefully and consistently, using known methods and means (regulation, management of modes, etc. ) to reduce losses of energy in the systems and increasing the operational reliability and efficiency of systems.

[0091] While the invention has been particularly shown and described with respect to preferred embodiments thereof, it will be understood by those skilled in the art that changes in form and details may be made therein without departing from the scope and spirit of the invention.