JPWO2019003367A1 - Power system state estimation apparatus and method, power system stabilization system - Google Patents

Abstract

When the state estimation calculation does not converge or when the power flow state changes suddenly, there is a possibility that a large deviation from the current system state occurs. In order to solve the present problem, the present invention provides a power system state estimating device, a system state calculating unit that performs state estimation calculation based on a plurality of system measurement data, and a current system based on the result of the state estimation calculation. A deviation determining unit that determines a degree of deviation from a state, a correction amount distribution creating unit that creates a correction amount distribution model for state estimation based on a predetermined predicted value or a planned value, and a result of the state estimation calculation; A correction unit that corrects the result of the state estimation calculation based on the correction amount distribution model when the degree is equal to or greater than a predetermined threshold.

Description

  The present invention relates to a power system state estimation device and method, and a power system stabilization system.

  Understanding the power flow (active power P, reactive power Q, voltage V, voltage phase δ) state of the power system is effective not only for monitoring and controlling the power system, but also for constructing analysis models such as power flow calculation. Useful. By reproducing a state close to the current power system with an analysis model, it is possible to predict a power system state that may occur in the future, and to perform a stabilization measure in preparation for a power system failure in advance. In general, the state of the power system is determined by using the measured values of the electric quantities (active power P, reactive power Q, voltage V, voltage phase δ, current I) measured by the measurement sensors installed in the power system. It is grasped by the state estimation calculation performed at intervals.

  In order to grasp the state of the power system, it is important to prepare a sufficient number of measured values to solve the power equation of the power system and make it observable. Depending on the case where there is a section where the resistance component is large, the section where the reactive power flow is large, or the case where the voltage values of the adjacent measured values are largely different, for example, the state estimation calculation may not converge. When the state estimation calculation does not converge, the value calculated in the previous calculation is generally used, so a large deviation from the current system state occurs, and the reliability of the obtained estimation result (tidal current state) decreases. There is. In particular, this problem is likely to occur in areas where the monitoring function and measurement accuracy of the power system are insufficient.

  In addition, the expansion of new energy (wind power, solar power, etc.) is expected along with the decrease in conventional large-scale power sources (thermal power, hydro power, nuclear power, etc.). It is known that the output of the new energy fluctuates every moment depending on weather conditions. During the state estimation calculation interval, if the power flow state suddenly changes due to a new energy output fluctuation, a large deviation from the current system state occurs, and the reliability of the obtained estimation result decreases. In particular, this problem is likely to occur in areas where large amounts of new energy are introduced.

  In the state estimation calculation field, there is Japanese Patent Application No. 2013-213334 (Patent Document 1). This document describes that a current and a current phase angle measured by a phase measuring device are converted into a pseudo measurement value which is a pseudo measurement value, and a state estimation calculation is performed.

  In the field of correction control for absorbing system changes during the state estimation calculation interval, there is Japanese Patent Application No. 2016-25715 (Patent Document 2). This document describes a pre-computation unit that calculates a correction amount indicating an influence amount due to a fluctuation of a control target and a non-control target generator generated at each failure, and is measured from a control target generator when any failure occurs. Based on actual measurement values, a model for determining the transient stability of the power system is generated, and the post-calculation means for performing control in accordance with the control pattern after reflecting the correction amount on the generated model. It is described that suitable stabilization control of the power system can be realized by the above.

JP 2015-77034 Patent application 2016-25715

  However, in the power system state estimating device of Patent Document 1, as described in the background art, when the state estimation calculation does not converge or when the power flow state changes suddenly, there is a possibility that a large deviation from the current system state may occur. is there.

  Further, in the power system stabilization system of Patent Document 2, control is performed by performing post-calculation when the value calculated by state estimation greatly deviates from the current system state, but the calculation time after failure is reduced. Since consideration must be given, the timing of the control operation may be delayed.

  In order to solve the above-mentioned problem, the present invention provides a power system state estimating device, a system state calculating unit that performs state estimation calculation based on a plurality of system measurement data, and a current system based on a result of the state estimation calculation. A deviation determination unit that determines a degree of deviation from a state, a correction amount distribution creating unit that creates a correction amount distribution model for state estimation based on a predetermined predicted value or a planned value, and a result of the state estimation calculation; A correction unit that corrects the result of the state estimation calculation based on the correction amount distribution model when the degree is equal to or greater than a predetermined threshold.

  According to the present invention, when the power flow suddenly changes during the state estimation calculation interval, the correction amount is calculated from the degree of change in the system status (the predicted value of the demand, the predicted value of the output of the new energy, the output value of the large-scale power supply) and the result of the state estimation calculation. If a distribution model is created and the state estimation calculation result deviates from the system state estimation value, the current power flow situation can be grasped by correcting the state estimation calculation result.

FIG. 3 is an example of a software configuration diagram of a power system state estimation device. FIG. 2 is an example of a hardware configuration diagram of a power system in which a plurality of measurement data is stored in a database via a communication network, and a power system state estimation device. It is an example of the flowchart which shows the whole process of the state estimation apparatus of a power system. It is an example of the flowchart which shows the process of state estimation. FIG. 4 is an example of a software configuration diagram of a correction distribution creating unit in the state estimation device. It is an example of the flowchart which shows the process of the preparation method of a correction amount distribution model. It is an example of the electric power system diagram to which one new energy was connected. It is an example of a correction distribution model. It is an example of the software block diagram of the state estimation apparatus of the electric power system which added the missing interpolation part and the after-correction precision verification part. It is an example of the flowchart which shows the whole process of the state estimation apparatus of the electric power system which added the process of loss interpolation and the accuracy verification after correction | amendment. FIG. 4 is an example of a software configuration diagram of a power system state estimating apparatus to which a stability calculation unit, a control unit determination unit, and a control result database are added. It is an example of the flowchart which shows the whole process of the state estimation apparatus of the electric power system which added the process of the stability calculation and the control of electric power.

  Hereinafter, preferred embodiments for implementing the present invention will be described. It should be noted that the following is merely an example of the embodiment, and is not intended to limit the invention itself to the following specific contents.

  Embodiment 1 of the present invention will be described below.

  FIG. 1 is a diagram illustrating an example of a software configuration of a power system state estimating apparatus 10 to which an embodiment of the present invention is applied, and includes a demand prediction database DB1, a new energy output prediction database DB2, a large-scale power supply output database DB3, The system includes a system state measurement value database DB4, a state estimation calculation correction result database DB5, a state estimation calculation unit 11, a correction amount distribution creating unit 12, a state estimation calculation result deviation determination unit 13, and a state estimation calculation result correction unit 14.

  The demand forecast database DB1 stores a demand forecast value D1 for each area and each connection point (node).

  The new energy output prediction database DB2 stores a new energy output prediction value D2 for each region and each connection point (node).

  The large-scale power supply output database DB3 stores the output value D3 of the large-scale power supply.

  The system state measurement value database DB4 stores system state measurement values D4 measured by a system state measurement device such as SCADA or PMU.

  The state estimation calculation correction result database DB5 stores the corrected state estimation calculation result D5.

  The state estimation calculation unit 11 performs a state estimation calculation using the system state measurement value D4 as an input, and outputs a state estimation calculation result D7.

  In the correction amount distribution creating unit 12, a correction amount distribution model is created by using the state estimation calculation result D7, the demand prediction value D1, the output prediction value D2 of the new energy, and the output value D3 of the large-scale power supply as inputs, and the correction amount distribution model Outputs D6.

  The state estimation calculation result deviation determination unit 13 receives the system state measurement value D4 and the state estimation calculation result D7 as inputs, determines the degree of deviation from the current system state, and outputs whether or not the state estimation calculation result correction is necessary D8. .

  The state estimation calculation result correction unit 14 calculates a state estimation calculation result correction amount using the correction amount distribution model D6, the system state measurement value D4, and the state estimation calculation result D7 as inputs, and outputs a state estimation calculation result correction value D5.

  FIG. 2 shows a power system in which a plurality of measurement data are stored in a database via a communication network, and a hardware configuration example of a power system state estimating apparatus 10 to which an embodiment of the present invention is applied.

  The power system is a system in which a plurality of synchronous generators 130 and loads 150 are interconnected via a bus (node) 110, a transformer 120, a transmission line 140, and the like. Note that, in FIG. 2, reference numeral 160 indicates a supposed fault location in the power system. Various measuring instruments for protection, control, and monitoring of the power system are appropriately installed in the node 110, and signals detected by the measuring instruments are communicated by the power system state estimating device 10 via the communication network 300. Sent to the unit 23. In FIG. 2, the node numbers shown in the drawings are given as appropriate to the nodes 110. In the nodes having other node numbers, for example, a current transformer CT, a voltage transformer PT, and the like are installed as existing measuring instruments.

  The power system state estimating device 10 is configured by a computer system, and includes a display unit 21 such as a display device, an input unit 22 such as a keyboard and a mouse, a communication unit 23, a CPU 24, a memory 25, and various database DBs connected to a bus line 26. It is connected to the. The power system power flow monitoring device 10 includes a demand forecast database DB1, a new energy output forecast database DB2, a large-scale power output database DB3, a system state measured value database DB4, and a state estimation calculation correction result database DB5.

  The display unit 21 may be configured to use a printer device, an audio output device, or the like instead of, or together with, the display device. The input unit 22 can be configured to include, for example, at least one of a keyboard switch, a pointing device such as a mouse, a touch panel, a voice instruction device, and the like. The communication unit 23 includes a circuit and a communication protocol for connecting to the communication network 300. The CPU 24 executes a calculation program, instructs image data to be displayed, and searches for data in various databases. The CPU 24 may be configured as one or a plurality of semiconductor chips, or may be configured as a computer device such as a calculation server. The memory 25 is configured as, for example, a RAM (Random Access Memory), and stores a computer program, and stores calculation result data and image data necessary for each process. The screen data stored in the memory 25 is sent to the display unit 21 and displayed.

  FIG. 3 is a flowchart illustrating an entire processing example of the power system state estimating apparatus 10. In the first processing step S1, the state of the power system is estimated based on the system state measurement value D4 in which measurement data at a plurality of measurement points is stored.

  FIG. 4 is a processing flowchart illustrating an example of the state estimation calculation performed in the first processing step S1 of FIG. In processing step S5, from the relationship between the observed value Z, the power system state value F (X), and the power system error e expressed by the equation (1), the state value X To determine. Where Z is the observed value of active power P, reactive power Q, voltage V, etc., X is the power system state (voltage V, voltage phase δ, etc.), F (X) is the value of state quantity (connection state of circuit and impedance Is determined by the circuit equation determined from).

  In the processing step S6 in FIG. 4, the residual ε is calculated, and error data such as removing the measured value having a large residual or replacing the measured value with a substitute pseudo measured value (using past measured value data instead) is used. Perform removal. In processing step S7, the calculated residual ε is compared with a specified value. If the residual ε is equal to or smaller than the specified value, the processing flow of the state estimation calculation ends, and if it is equal to or larger than the specified value, the process returns to the processing step S5. Note that such a state estimation calculation of the power system is an established calculation method, and can be calculated using a general algorithm. The state value X for which the residual ε is determined to be equal to or smaller than the specified value is output and stored as a state estimation calculation result (state amount estimation value) D7.

  Returning to FIG. 3, in the next processing step S2, a state estimation calculation result divergence indicating the divergence between the system state measurement value D4 and the state estimation calculation result D7 is calculated. The divergence is, for example, a total value of the voltage phase differences between D4 and D7 at each system state measuring device point. In the processing step S3, if the divergence is larger than a certain threshold, the process proceeds to step S4, and if smaller than the threshold, the process flow of the power system state estimating device 10 ends. In processing step S4, the state estimation calculation correction result is calculated by inputting the system state measurement value D4 and the state estimation calculation result D7 to a correction amount distribution model D6 described below.

  FIG. 5 is an example of a software configuration diagram of the correction distribution creating unit 12 in the state estimating device, and includes a power flow calculating unit 15 and a correction distribution model unit 16.

  The power flow calculation unit 15 performs a power flow calculation using the state estimation calculation result D7, the demand prediction value D1, the output predicted value D2 of the new energy, and the output value D3 of the large-scale power supply as inputs, and outputs a power flow calculation result D9.

  The correction distribution model creating unit 16 creates a correction distribution model using the tidal current calculation result D9 as an input, and outputs a correction amount distribution model D6.

FIG. 6 is a flowchart illustrating a process of a method for creating a correction amount distribution model used in processing step S4. In processing step S8, using the demand forecast value D1, the output forecast value D2 of the new energy, the output value D3 of the large-scale power supply, the system state measurement value D4, and the state estimation calculation result D7, the system state change until the next state estimation calculation Predict the amount. The system status change amount is a change amount of the demand, the new energy output, and the large-scale power supply output during the state estimation calculation interval. In the following, using the example of the power system in FIG. 7, the processing of the method of creating the correction amount distribution model used in the processing step S4 will be described. If the maximum change predicted value (new energy output predicted value D2) until the next state estimation calculation of the new energy output connected to node 700 is α, and the current output of the new energy is P _RES (t) from the system state measured value D4, , Pres (t) is within the range of Pres (t) −α <Pres (t + 1) <Pres (t) + α.

  In the processing step S9, an input value Pres (t + 1) is given for each certain step width of the system status change amount prediction range (Pres (t) −α <Pres (t + 1) <Pres (t) + α), Perform tide calculation. The active power P, reactive power Q, and voltage V, which are required for power flow calculation, are input with a wide range of predicted values for new energy output, while other input values used for power flow calculation are the previous state estimation. It is assumed that the calculation result is D7.

  In processing step S10, of the results of the power flow calculation, a difference between the state estimation calculation result D7 for each system state measuring device point and the power flow calculation value when the new energy output predicted value is given, and a value required for the power flow calculation A certain active power P, a reactive power Q, and a voltage V are input, and a correction amount distribution model is output. For example, a correction distribution model shown in FIG. 8 is created. Here, it is represented by three axes for simplicity. In FIG. 8, the active power of transmission line 1 is Pse1, the active power of transmission line 2 is Pse2 as the state estimation calculation result, and the active power of transmission lines 1 and 2 at the system state measurement device installation point is the power flow calculation result. Ppf1 and Ppf2, and the active power of the transmission line 3 for correcting the estimated state value is Ppf3.

  When the correction amount distribution model shown in FIG. 8 is created, the correction amount distribution (Ppf3) corresponding to the Ppf distribution (Ppf1, Ppf2) is calculated, and the system state measurement values (Pobserve1, Pobserve2) are applied when the correction amount distribution model is used. The correction amount (Pse_cor3) can be obtained. That is, when the correction amount distribution model is used, in the processing step S4, the state estimation calculation results Pse1 and Pse2 and the system state measurement values Pobserve1 and Pobserve2 are input to the correction amount distribution model to obtain a state estimation calculation correction result. The active power Pse_cor3 of the transmission line 3 can be calculated.

  In processing step S4, the current data is compared with the past data, and the demand value D1, the output value D2 of the new energy, and the output value D3 of the large-scale power supply are the closest past time-series data, and the system state measurement value D4 is used. Create and select a correction distribution model showing the relationship between the state estimation calculation result D7, and calculate the state estimation correction result D5 by using the system state measurement value D4 and the state estimation calculation result D7 as inputs to the correction distribution model. Is also good. The difference from the above method is that a correction distribution model is created using past data instead of using the previous state estimation calculation result and system change predicted value. If the past data is not sufficiently prepared, a large amount of data may be created by Monte Carlo simulation.

  According to the first embodiment, when the power flow fluctuates during the state estimation interval, the degree of system status change (demand forecast value D1, new energy output forecast value D2, output value D3 of large-scale power source) and state estimation calculation result A correction amount distribution model D6 is created from D4, and when the system state measurement value D4 and the state estimation calculation result D7 deviate, the system state measurement value D4 and the state estimation calculation result D7 are input to the correction amount distribution model D6, By calculating the state estimation calculation result D5, a tidal current state close to the current state can be grasped.

  Embodiment 2 of the present invention will be described below. Note that a description overlapping with the content described in the first embodiment will be omitted.

  FIG. 9 is a diagram illustrating an example of a software configuration of the power system state estimation device according to the second embodiment. The power system state estimating apparatus according to the second embodiment illustrated in FIG. 9 is obtained by adding a loss interpolation unit 17 and a corrected accuracy verification unit 18 to the configuration of the first embodiment.

  The loss interpolation unit 17 outputs a loss interpolation value D10 when a loss occurs with the system state measurement value D4 as an input.

  The post-correction accuracy verification unit 18 performs accuracy verification based on the system state measurement value D4, which is a state quantity having a measurement value. Of the state estimation calculation result D7 before correction and the state estimation calculation result D5 after correction, the value closer to the system status is output to the state estimation calculation correction result database DB5 based on the system state measurement value D4. The system status is, for example, the total value of the active power P of the transmission line at the installation point of the system status measuring device.

  FIG. 10 is a flowchart illustrating an entire processing example of the power system state estimating apparatus according to the second embodiment, in which a loss interpolation processing step S11 and a corrected accuracy verification processing step S12 are added to the flowchart of FIG. It is. In a processing step S11 which is a difference from the first embodiment, when a loss occurs in the system state measurement value D4, a loss interpolation value D10 is calculated. Note that such loss interpolation is an established calculation method, and can be calculated using a general algorithm. In the processing step S5 which is a difference from the first embodiment, the state estimation calculation result D7 before correction and the state estimation calculation result D5 after correction are compared with the system state measurement value D4, and the system state measurement value D4 is set to a true value. In this case, a value closer to the state estimation calculation result D7 before correction and the state estimation calculation result D5 after correction is used as the final state estimation result.

  According to the second embodiment, the accuracy of the state estimation calculation result can be improved by the missing interpolation. In addition, the post-correction accuracy verification verifies the validity of the post-correction state estimation calculation result, and selects a high-precision state estimation calculation result. As described above, if the accuracy of the corrected state estimation calculation result is low, an accurate power flow state can be grasped by using the estimated value of another state quantity for selection.

  Embodiment 3 of the present invention will be described below. Note that a description overlapping with the content described in the first embodiment will be omitted.

  State estimation is widely used as an input value of a monitoring system and a stabilization system in a power system. Here, as an example of the above, a method of applying state estimation to a system stabilization system of synchronization stability (transient stability) will be described.

  FIG. 11 is a diagram illustrating an example of a software configuration of the power system state estimation device according to the third embodiment. The power system state estimating apparatus according to the third embodiment shown in FIG. 11 is obtained by adding a control result database DB6, a stability calculation unit 17, and a control unit determining unit 18 to the configuration of the first embodiment.

  In the electrical machine result database DB6, an electrical appliance determination result D12 described later is stored.

  The stability calculation unit 17 receives the corrected state estimation calculation result D5 as input, performs a stability calculation for analyzing the out-of-synchronization phenomenon of the generator caused by a fault such as a lightning strike, and calculates the internal phase angle for each generator. The stability calculation result D11 of the series data or the like is output.

  The power control determining unit 18 receives the stability calculation result D11 as an input, determines a generator (electric power control) that disconnects the generator that has lost synchronization from the system in order to prevent the spread of a fault, and determines the power control. The result D12 is output.

  FIG. 12 is a flowchart illustrating the entire processing example of the power system state estimating apparatus according to the third embodiment, and a processing step S13 for stability calculation and a processing step S14 for determining an electrical control are added to the flowchart in FIG. It is an example. In processing step S13, which is a difference from the first embodiment, stability calculation is performed for each assumed failure case, and time series data and the like of the internal phase angle of each generator at each failure point are calculated. In the present processing step S14, which is the difference from the first embodiment, the generator in which the out-of-synchronization has occurred for each failure case is determined as the controlled generator.

  According to the third embodiment, when the power flow fluctuates during the state estimation interval, the number of corrected power-suppressed vehicles is corrected in advance by the correction of the result of the state-estimation calculation, thereby preventing excess and underpower-suppression.

10 Power system state estimation device
11 Correction amount distribution creation unit
12 State estimation calculator
13 State estimation calculation result deviation judgment unit
14 State estimation calculation result correction unit
15 Power flow calculation section
16 Correction distribution model generator
17 Loss interpolation unit
18 Accuracy verification unit after correction
19 Stability calculator
20 Electrical control unit
100 Power system stability monitoring device
21 Display
22 Input section
23 Communication section
24 CPU
25 memory
26 bus lines
110 nodes
120 transformer
130 Synchronous generator
140 Transmission line
150 load
160 wind generator
300 communication network
DB1 demand forecast database
DB2 new energy output forecast database
DB3 large power output database
DB4 system status measurement value database
DB5 State estimation calculation correction result database
DB6 Electric Machine Result Database

Claims (15)

A system state calculation unit that performs state estimation calculation based on a plurality of system measurement data,
A deviation determination unit that determines the degree of deviation from the current system state based on the result of the state estimation calculation,
A predetermined predicted value or planned value, and a correction amount distribution creating unit that creates a correction amount distribution model for state estimation based on the result of the state estimation calculation,
And a correction unit that corrects the result of the state estimation calculation based on the correction amount distribution model when the degree of divergence is equal to or larger than a predetermined threshold. The state estimation device for a power system according to claim 1,
The power system state estimating device, wherein the predetermined predicted value or planned value includes a demand predicted value, a predicted output value of new energy, or an output value of a large-scale power supply. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising a demand forecast database storing a demand forecast value for each area or each connection point. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising a large-scale power supply output database for storing output values of a large-scale power supply. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising a system state measurement value database storing system measurement data including SCADA or PMU. The state estimation device for a power system according to claim 1,
A state estimation device for a power system, further comprising a state estimation calculation correction result database that stores a state estimation calculation result after correction obtained by the correction unit. The state estimation device for a power system according to claim 1,
The said predetermined threshold value is determined based on the magnitude | size of the difference of system measurement data and a state estimation calculation result, The state estimation apparatus of the electric power system characterized by the above-mentioned. The state estimation device for a power system according to claim 1,
The state estimation device for a power system, wherein the correction amount distribution creating unit estimates a change amount in which the predicted value or the planned value changes from the state estimation calculation to the next state estimation calculation. The state estimation device for a power system according to claim 8,
The state estimating apparatus for a power system, wherein the correction amount distribution creating unit performs a power flow calculation based on the predicted change amount to create the correction amount distribution model. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising a loss interpolator that performs interpolation of the loss when the loss occurs in the system measurement data. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising a loss interpolator that performs interpolation of the loss when the loss occurs in the system measurement data. The state estimation device for a power system according to claim 1,
An apparatus for estimating a state of a power system, further comprising an accuracy verification unit that verifies the accuracy of the state estimation calculation based on the system measurement data. The state estimation device for a power system according to claim 12,
The accuracy estimating unit compares a result of the state estimation calculation before correction with a result of the state estimation calculation after correction, and outputs a result close to the system measurement data. A power system stabilization system that performs system stabilization calculation based on an output value of the power system state estimation device according to claim 1,
Based on the output value of the state estimation device, a stability calculation unit that performs stability calculation for each generator,
A power system stabilization system, comprising: a power control unit that determines a power control unit that disconnects a predetermined power generator from a power supply system based on a result of the stability calculation. Perform state estimation calculation based on multiple system measurement data,
Determine the degree of deviation from the current system state based on the result of the state estimation calculation,
Predicted or planned values, and a correction amount distribution model for state estimation based on the result of the state estimation calculation,
When the degree of divergence is equal to or greater than a predetermined threshold, the result of the state estimation calculation is corrected based on the correction amount distribution model.

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