WO2019003367A1

WO2019003367A1 - Power system state estimation device and method, and power system stabilization system

Info

Publication number: WO2019003367A1
Application number: PCT/JP2017/023861
Authority: WO
Inventors: 佑樹辻井; 顕エドワード川喜田; 正俊熊谷; 渡辺　雅浩; 輝菊池
Original assignee: 株式会社日立製作所
Priority date: 2017-06-29
Filing date: 2017-06-29
Publication date: 2019-01-03
Also published as: JPWO2019003367A1; JP7012720B2

Abstract

The present invention addresses the problem of the possible occurrence of a large deviation from a current system state when a state estimation calculation does not converge or when a power flow state has abruptly changed. In order to solve this problem, a power system state estimation device according to the present invention is provided with: a system state calculation unit for performing a state estimation calculation on the basis of a plurality of system measurement data; a deviation determination unit for determining the degree of deviation from a current system state on the basis of the result of the state estimation calculation; a correction amount distribution creation unit for creating a correction amount distribution model for state estimation on the basis of a predetermined predicted value or planned value and the result of the state estimation calculation; and a correction unit for, when the degree of deviation is a predetermined threshold value or more, correcting the result of the state estimation calculation on the basis of the correction amount distribution model.

Description

Power system state estimation device and method, power system stabilization system

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

Understanding the status of power flow (active power P, reactive power Q, voltage V, voltage phase δ) in the power system is effective for monitoring and controlling the power system, and is also for constructing analytical models such as power flow calculation. It is useful. By reproducing a state close to the current power system using an analysis model, it is possible to predict a possible power system state in the future, and to perform stabilization measures in preparation for a power system failure in advance. In general, the state of the power system is constant using the measured values of the electric quantity (active power P, reactive power Q, voltage V, voltage phase δ, current I) measured by the measurement sensor installed in the power system. It is grasped by state estimation calculation performed at intervals.

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

Along with the decrease in conventional large-scale power sources (thermal power generation, hydroelectric power generation, nuclear power generation, etc.), expansion of new energy (wind power generation, solar power generation, etc.) is expected. It is known that new energy fluctuates with time depending on weather conditions. During the state estimation calculation interval, when the power flow state suddenly changes due to the new energy output fluctuation, a large deviation from the current system state occurs, and the reliability of the obtained estimation result is reduced. In particular, this problem is considered to occur in areas where a large amount of new energy is introduced.

There is Japanese Patent Application No. 2013-213334 (Patent Document 1) in the field of state estimation calculation. In this document, it is described that the current and the current phase angle measured by the phase measuring device are converted into pseudo measured values which are pseudo measured values, and state estimation calculation is performed.

Japanese Patent Application No. 2016-25715 (Patent Document 2) is in the field of correction control for absorbing systematic changes during a state estimation calculation interval. In this document, pre-calculation means for calculating the correction amount indicating the influence amount of the control target generator and the control target generator generated in each failure is measured from the generator to be controlled when any failure occurs. While generating a model for determining the transient stability of the power system based on the actual measurement value, reflecting the correction amount on the generated model, and fusing the post calculation means for performing control according to the control pattern It is stated that appropriate power system stabilization control can be realized.

JP 2015-77034 Japanese Patent Application No. 2016-25715

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

Further, in the power system stabilization system of Patent Document 2, although the value calculated in the state estimation causes a large deviation from the current system state, control is performed by performing post operation, but the operation time after failure is Because it must be taken into consideration, the timing of the control operation may be delayed.

In order to solve the above problems, the present invention relates to a system state calculation unit for performing state estimation calculation based on a plurality of system measurement data in a power system state estimation device, and a current system based on the result of the state estimation calculation. A deviation determination unit that determines a degree of deviation from a state; a correction amount distribution generation unit that generates a correction amount distribution model of state estimation based on a predetermined predicted value or plan value and a 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 is equal to or more than a predetermined threshold value.

According to the present invention, when the power flow suddenly changes during the state estimation calculation interval, the correction amount from the system state change degree (the demand forecast value, the output prediction value of new energy, the output value of the large scale power source) and the state estimation calculation result If a distribution model is created and the estimated state calculation result and the estimated system state value diverge, the current flow condition can be grasped by correcting the estimated state calculation result.

It is an example of the software block diagram of the state estimation apparatus of an electric power grid | system. It is an example of the electric power system by which several measurement data are stored in a database via a communication network, and the hardware block diagram of the state estimation apparatus of an electric power system. It is an example of the flowchart which shows the whole process of the state estimation apparatus of an electric power grid | system. It is an example of the flowchart which shows the process of state estimation. It is an example of the software block diagram of the correction distribution creation part in state estimating 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 defect | deletion interpolation part and the precision verification part after correction | amendment. 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 a defect interpolation and the precision verification after correction | amendment. It is an example of the software block diagram of the state estimation apparatus of the electric power system which added the stability calculation part, the electric controller determination part, and the electric controller result database. 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 stability calculation and the electric controller determination.

Hereinafter, preferred embodiments for carrying out the present invention will be described. The following is merely an example of the embodiment, and the invention itself is not intended to be limited to the following specific contents.

The first embodiment of the present invention will be described below.

FIG. 1 is a diagram showing an example of the software configuration of a power system state estimation apparatus 10 to which an embodiment of the present invention is applied, a demand forecast database DB1, a new energy output forecast database DB2, a large scale power output database DB3, 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 creation unit 12, a state estimation calculation result deviation determination unit 13, and a state estimation calculation result correction unit 14 are provided.

In the demand forecasting database DB1, the demand forecast value D1 in the area unit or connection point (node) unit is stored.

In the new energy output prediction database DB2, the output predicted value D2 of the new energy in units of regions and connection points (nodes) is stored.

In the large scale power supply output database DB3, the output value D3 of the large scale power supply is stored.

In the system condition measurement value database DB4, a system condition measurement value D4 measured by a system condition measurement device such as SCADA or PMU is stored.

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

State estimation calculation unit 11 performs state estimation calculation with system state measurement value D4 as an input, and outputs state estimation calculation result D7.

In the correction amount distribution creating unit 12, a correction amount distribution model is created with the state estimation calculation result D7, the demand forecast value D1, the output forecast value D2 of new energy and the output value D3 of the large-scale power source as input, and the correction amount distribution model Output D6.

State estimation calculation result divergence determination unit 13 receives system state measurement value D4 and state estimation calculation result D7 as input to determine the degree of divergence between the current system state, and outputs necessity necessity D8 of state estimation calculation result correction. .

State estimation calculation result correction unit 14 receives correction amount distribution model D6, system state measurement value D4 and state estimation calculation result D7 to calculate a state estimation calculation result correction amount, and outputs state estimation calculation result correction value D5.

FIG. 2 shows an example of a hardware configuration of a power system in which a plurality of measurement data are stored in a database via a communication network, and a power system state estimation device 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 with one another via a bus (node) 110, a transformer 120, a transmission line 140, and the like. In FIG. 2, reference numeral 160 exemplifies an assumed failure point in the power system. In the node 110, various measuring instruments for the purpose of protection, control and monitoring of the electric power system are appropriately installed, and the signal detected by the measuring instrument is communicated by the state estimating device 10 of the electric power system via the communication network 300. It is sent to the part 23. In FIG. 2, node numbers shown in the figure are appropriately assigned to the nodes 110. For example, a current transformer CT, a voltage transformer PT, and the like are installed as existing measuring instruments at nodes of other node numbers.

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

Among them, the display unit 21 may use, for example, a printer device or an audio output device in place of or in addition to the display device. The input unit 22 can include, for example, at least one of a keyboard switch, a pointing device such as a mouse, a touch panel, and a voice instruction device. 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 to instruct image data to be displayed, search data in various databases, and the like. The CPU 24 may be configured as one or more 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, image data, and the like necessary for each process. The screen data stored in the memory 25 is sent to the display unit 21 and displayed.

FIG. 3 shows a flowchart showing the entire processing example of the power system state estimation device 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 are stored.

FIG. 4 shows a processing flowchart showing an example of the state estimation calculation performed in the first processing step S1 of FIG. At processing step S5, from the relationship between the observed value Z represented by the equation (1), the power system state value F (X), and the power system error e, the state value X is set such that the relational expression of the equation (2) Decide. 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.), and F (X) is the state value (circuit connection state and impedance) It is determined by the circuit equation determined from

In the processing step S6 of FIG. 4, the residual ε is calculated, and the measurement value having a large residual is removed or is replaced with an alternative pseudo measurement value (instead of using the past measurement value data), error data Do the removal. In processing step S7, the calculated residual ε is compared with a specified value. If the residual ε is equal to or less than the specified value, the process flow of the state estimation calculation is ended, and if it is equal to or more than the specified value, the process returns to the processing step S5. Note that such power system state estimation calculation is an established calculation method, and can be calculated using a general algorithm. The state value X determined that the residual ε is equal to or less than the specified value is output and stored as a state estimation calculation result (state amount estimated value) D7.

Returning to FIG. 3, in the next processing step S2, a state estimation calculation result divergence degree indicating the degree of divergence between the system state measurement value D4 and the state estimation calculation result D7 is calculated. The degree of deviation is, for example, the total value of the voltage phase difference between D4 and D7 at each system condition measuring device point. In processing step S3, if the said deviation degree is larger than a fixed threshold value, it will progress to step S4, and if smaller than the said threshold value, the processing flow of the state estimation apparatus 10 of an electric power system will be complete | finished. In processing step S4, a 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 later.

FIG. 5 is an example of a software configuration diagram of the correction distribution creation unit 12 in the state estimation device, and includes a tidal current calculation unit 15 and a correction distribution model unit 16.

The tidal current calculation unit 15 performs tidal current calculation with the state estimation calculation result D7, the demand forecast value D1, the output predicted value D2 of new energy and the output value D3 of the large-scale power source as input, and outputs the tidal current calculation result D9.

The correction distribution model generation unit 16 receives the tidal current calculation result D9 as an input, generates a correction distribution model, and outputs a correction amount distribution model D6.

FIG. 6 shows a flowchart showing processing of a method of creating a correction amount distribution model used in processing step S4. At processing step S8, the system situation change up to the next state estimation calculation using demand forecast value D1, output prediction value D2 of new energy, output value D3 of large scale power source, system state measurement value D4 and state estimation calculation result D7 Predict the quantity. The system status change amount is the change amount of the demand, the new energy output, and the large-scale power source output during the state estimation calculation interval. Below, the process of the preparation method of the correction amount distribution model used by process step S4 is shown using the electric power system example of FIG. Let α be the maximum change forecast value (new energy output forecast value D2) up to the next state estimation calculation of new energy output connected to node 700, and _let the current output of new energy be P _RES (t) from the system status measurement value D4. The amount of change in the system status based on Pres (t) is in the range of Pres (t) −α <Pres (t + 1) <Pres (t) + α.

In processing step S9, an input value Pres (t + 1) is given for each fixed step width of the system condition change amount prediction range (Pres (t) -α <Pres (t + 1) <Pres (t) + α), Perform tidal current calculation. Active power P, reactive power Q, and voltage V, which are values necessary for power flow calculation, take an estimated value with a width for new energy output as input, while other input values used for power flow calculation are previous state estimation The calculation result is D7.

At processing step S10, among the results of the tidal current calculation, the difference between the tidal current calculation value at the time of giving the new energy output predicted value and the state estimation calculation result D7 for each system state measuring device point, and the value necessary for tidal current calculation A certain effective power P, reactive power Q, and voltage V are input, and a correction amount distribution model is output. For example, the correction distribution model of FIG. 8 is created. Here, three axes are shown for simplicity. In FIG. 8, the active power of the transmission line 1 is Pse1 and the active power of the transmission line 2 is Pse2 as the state estimation calculation result, and the active powers of the

transmission lines

1 and 2 at the system condition measuring device installation point are calculated as the power flow calculation result. It is assumed that Ppf1 and Ppf2 and the effective power of the transmission line 3 whose state estimated value is to be corrected is Ppf3.

It is appropriate to calculate the correction amount distribution (Ppf3) corresponding to Ppf distribution (Ppf1, Ppf2) when creating the correction amount distribution model of FIG. 8 and apply the system state measurement values (Pobserve1, Pobserve 2) when using the correction amount distribution model. The correction amount (Pse_cor3) can be obtained. That is, when using the correction amount distribution model, 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, current data is compared with past data, and system state measurement value D4 in past time series data in which demand value D1, output value D2 of new energy, and output value D3 of large-scale power source are closest. A correction distribution model indicating the relationship between the state estimation calculation result D7 is created and selected, and the system state measurement value D4 and the state estimation calculation result D7 are input to the correction distribution model to calculate the state estimation correction result D5. It is also good. The difference with the above method is that the correction distribution model is created using past data, not using the previous state estimation calculation result and the systematic change prediction value. If the past data is not complete enough, a large amount of data may be generated by Monte Carlo simulation.

According to the first embodiment, when the power flow fluctuates during the state estimation interval, the system state change degree (the demand forecast value D1, the output prediction value D2 of new energy, the output value D3 of the large scale power source) and the state estimation calculation result If the correction amount distribution model D6 is created from D4 and the system state measurement value D4 and the state estimation calculation result D7 diverge, 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, it is possible to grasp the tidal current state close to the current situation.

The second embodiment of the present invention will be described below. The description overlapping with the contents described in the first embodiment is 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 state estimation device for a power system according to the second embodiment shown in FIG. 9 is obtained by adding the loss interpolation unit 17 and the post-correction 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 on the basis of 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 state is output to the state estimation calculation correction result database DB5 by 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 system status measurement device installation point.

FIG. 10 is a flowchart showing the entire processing example of the power system state estimation apparatus according to the second embodiment. An example in which processing step S11 of loss interpolation and processing step S12 of accuracy verification after correction are added to the flowchart of FIG. It is. In processing step S11 which is a difference from the first embodiment, a loss interpolation value D10 is calculated when a loss occurs in the system state measurement value D4. Note that such loss interpolation is an established calculation method and can be calculated using a general algorithm. In processing step S5 which is a difference with Example 1, state estimation calculation result D7 before amendment and state estimation calculation result D5 after amendment are compared with system state measurement value D4, and system state measurement value D4 is made into a true value. In this case, the closer value of the state estimation calculation result D7 before correction and the state estimation calculation result D5 after correction is taken as a final state estimation result.

According to the second embodiment, the accuracy of the state estimation calculation result can be improved by the lossy interpolation. In addition, it is possible to verify the validity of the state estimation calculation result after correction by accuracy verification after correction and to select the state estimation calculation result with high accuracy. As described above, if the accuracy of the state estimation calculation result after correction is poor, it is possible to grasp an accurate tidal flow state by using it for selecting estimated values of other state quantities.

The third embodiment of the present invention will be described below. The description overlapping with the contents described in the first embodiment is omitted.

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

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

A controller result D12 described later is stored in the controller result database DB6.

Stability calculation unit 17 performs stability calculation to analyze out-of-synchronization of the generator caused by a fault such as lightning with the state estimation calculation result D5 after correction as an input, and the internal phase angle for each generator is calculated. The stability calculation result D11 such as series data is output.

The power control determination unit 18 receives the stability calculation result D11, determines a generator (power control) to disconnect the generator where the synchronization has occurred from the grid to prevent the spread of the failure, and determines the power control. Output the result D12.

FIG. 12 is a flowchart showing the entire processing example of the power system state estimation device according to the third embodiment, where processing step S13 of stability calculation and processing step S14 of electric controller determination are added to the flowchart of FIG. It is an example. In processing step S13 which is a difference with the first embodiment, stability calculation for each contingency case is performed, and time-series data etc. of the internal phase angle of each generator for each failure point are calculated. In step S14, which is a difference from the first embodiment, the generator in which the out-of-synchronization has occurred for each failure case is determined as the electronically controlled generator.

According to the third embodiment, when the power flow fluctuates during the state estimation interval, it is possible to prevent the excess and the excess power control by correcting the corrected number of controlled devices in advance by the state estimation calculation result correction.

10 State estimation device for power system
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 tidal current calculation part
16 Correction distribution model creation unit
17 Missing interpolation unit
18 Accuracy verification unit after correction
19 Stability Calculator
20 Power control decision department
100 Power system stability monitoring equipment
21 Display
22 Input section
23 Communication unit
24 CPU
25 memory
26 bus lines
110 nodes
120 transformers
130 synchronous generator
140 transmission line
150 load
160 wind generator
300 communication network
DB1 Demand Forecast Database
DB2 New Energy Output Forecasting Database
DB3 large scale power output database
DB4 system condition measurement value database
DB5 state estimation calculation correction result database
DB6 Electric result database

Claims

A system state calculation unit that performs state estimation calculation based on a plurality of system measurement data;
A divergence determining unit that determines the degree of divergence from the current system state based on the result of the state estimation calculation;
A correction amount distribution creation unit that creates a correction amount distribution model of state estimation based on a predetermined predicted value or plan value and the 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 deviation degree is equal to or more than a predetermined threshold value.
In the power system state estimation device according to claim 1,
A power system state estimation device, wherein the predetermined forecast value or the planned value includes a demand forecast value, an output forecast value of new energy, or an output value of a large-scale power source.
The power system state estimation device according to claim 1,
An apparatus for estimating a state of an electric power system, further comprising a demand forecasting database storing demand forecast values in units of regions or connection points.
The power system state estimation device according to claim 1,
An apparatus for estimating a state of a power system, further comprising: a large-scale power output database that stores output values of a large-scale power source.
The power system state estimation device according to claim 1,
An apparatus for estimating a state of an electric power system, further comprising a system state measurement value database storing system measurement data including SCADA or PMU.
The power system state estimation device according to claim 1,
A state estimation device for an electric power system, further comprising a state estimation calculation correction result database storing the state estimation calculation result after correction determined by the correction unit.
In the power system state estimation device according to claim 1,
A power system state estimation device characterized in that the predetermined threshold is determined based on a difference between system measurement data and a state estimation calculation result.
In the power system state estimation device according to claim 1,
The power system state estimation device, wherein the correction amount distribution creation unit predicts a change amount in which the predicted value or the plan value changes between the state estimation calculation and the next state estimation calculation.
In the power system state estimation device according to claim 8,
The correction amount distribution creation unit performs power flow calculation based on the predicted change amount, and creates the correction amount distribution model.
The power system state estimation device according to claim 1,
A power system state estimation device, further comprising a loss interpolation unit that interpolates the loss when a loss occurs in the system measurement data.
The power system state estimation device according to claim 1,
A power system state estimation device, further comprising a loss interpolation unit that interpolates the loss when a loss occurs in the system measurement data.
The power system state estimation device according to claim 1,
A power system state estimation device, further comprising: an accuracy verification unit that verifies the accuracy of the state estimation calculation based on the system measurement data.
In the power system state estimation device according to claim 12,
The accuracy verification unit compares a result of a state estimation calculation before correction with a result of a state estimation calculation after correction, and outputs a result close to the system measurement data.
In a power system stabilization system, the system stabilization calculation is performed based on the output value of the power system state estimation device according to claim 1.
A stability calculation unit that performs stability calculation for each generator based on the output value of the state estimation device;
And a controller determination unit configured to determine a controller that disconnects a predetermined generator from a grid based on the result of the stability calculation.
Perform state estimation calculation based on multiple system measurement data,
Determining the degree of deviation from the current system state based on the result of the state estimation calculation;
Create a correction amount distribution model of state estimation based on a predetermined predicted value or plan value and the result of the state estimation calculation,
And correcting the result of the state estimation calculation based on the correction amount distribution model when the deviation degree is equal to or more than a predetermined threshold value.