WO2019150738A1 - Power system monitoring device - Google Patents

Abstract

The purpose of the present invention is to implement a power system monitoring device through which an operator can more rapidly determine a stability decision result of a power system. In order to address this issue, the power system monitoring device is provided with: a stress index calculation unit which calculates stress indices of two or more assumed faults in the power system by using facility information on the power system and measurement information obtained periodically; a prior fault selection unit which divides the assumed faults into two or more groups of different priorities by using a pre-calculated reference value and the stress indices; a stability decision unit which decides, in order, the stability from the assumed faults belonging to a group of higher priority among the assumed faults by using the facility information and the measurement information; and a reference changing unit which changes the reference value by using the facility information and the measurement information.

Description

Power system monitoring device

The present invention relates to a system monitoring device that determines whether or not stable power system operation is possible.

As background technology in this technical field, there is "Analysis and operation technology that supports the use of electric power system" IEEJ Technical Report No. 1100, 2007. Here, an assumed failure analysis is described as an on-line security analysis technique for a power system. One of the elemental technologies is screening that eliminates failures that do not affect stability from a large number of failures (page 85).

In addition, as a background technology of this technology, “Bonneville Power Administration Technical Operations System Operating Limit Methodology Horizon Operations Horizon Version 3” (Non-patent Document 3). According to this operation rule, as a method of selecting a failure to be calculated, a failure having a small influence with an OTDF of less than 3.0% is not targeted. OTDF (Outage Transfer Distribution Factor) is one of the power transmission fluctuation indicators due to power system failure, and its definition is “the MW change in a branch flow for 1 MW exchange bewethew twoway”.

Also, Japanese Patent Laid-Open No. 7-298498 is a background art of this technology. According to this publicity, “based on online data from the electric power system, the severity of each failure is determined by the phase angle of the generator for a plurality of assumed failure cases, and the failure case selection means 112 exceeds the threshold. “Select an assumed failure case”.

Japanese Patent Laid-Open No. 7-298498

In the future, due to the progress in the liberalization of the electricity market or the increase in fluctuations due to the increase in the introduction of renewable energy, there is a possibility that the uncertainty of the power system will increase and the need for power system monitoring by online security analysis may increase.

On the other hand, failures that should be assumed in online security analysis become more complex due to the complexity of the power system represented by wide area interconnection and the progress of liberalization of the power market. In addition to the conventional N-1 failure, Nx failure, which is a simultaneous failure of multiple facilities, and N-x1-x2 -... failure where additional failure occurs after failure occurs. The total number of will increase. Therefore, higher accuracy is required for screening.

The system stabilization device described in Patent Document 1 calculates a failure in which the phase angle or phase angle change of the generator in each of the assumed failure cases exceeds a predetermined threshold as a severe failure case. In the method for setting a power transmission limit described in Non-Patent Document 2, only a failure in which the power transmission amount fluctuation index OTDF due to a failure is a predetermined value or more is regarded as a failure that affects the power transmission limit. Neither method nor apparatus takes into account the fact that the number of severe cases exceeding a predetermined threshold increases when the system becomes severe due to the use of a fixed threshold, and the calculation time increases. Moreover, since these do not consider that the control amount of a control apparatus changes dynamically when a system | strain becomes severe, it is not considered about calculating the fault which is not severe by control.

If one of the typical things of this invention is shown, the severeness which is a parameter | index of the system stability deterioration of two or more contingency faults in the said electric power system using the power system equipment information and the measurement information obtained periodically A severe index calculation unit that calculates an index, a priority fault selection unit that divides the assumed fault into two or more groups having different priorities whose stability is determined based on a reference value calculated in advance and the severe index, and the facility information And the measurement information, a stability determination unit that determines stability in order from an assumed failure belonging to a group having a high priority among the assumed failures, and the reference value using the facility information and the measurement information A reference changing unit to be changed.

According to the present invention, it is possible for an operator to realize a power system monitoring apparatus that can quickly determine the stability determination result of the power system.

It is an example of the whole block diagram of an electric power system monitoring apparatus. It is an example of the hardware configuration of an electric power system monitoring apparatus, and the whole electric power system block diagram. It is an example of the block diagram which shows the content of the program data of an electric power grid | system monitoring apparatus. It is a figure explaining an example of the assumption failure database of an electric power grid monitoring device. It is a figure explaining an example of the control amount versus reference database of an electric power system monitoring device. It is a figure explaining an example of the standard history database of an electric power system monitoring device. It is an example of the flowchart which shows the whole process of an electric power grid | system monitoring apparatus. It is a figure explaining calculation of the generator phase difference angle fluctuation which is an example of severe index calculation. It is an example of the flowchart explaining the process of a reference | standard change. It is a figure explaining the method which shows the result of stability determination of assumption failure. It is a figure explaining the method which shows a reference | standard history. It is an example of the whole block diagram of the electric power system monitoring apparatus which does not require a control amount vs. reference database. It is a figure which shows an example of the control amount data which is an output of a stability determination result. It is an example of the flowchart which shows the reference | standard change process in which a control amount versus reference | standard database is unnecessary. It is a figure explaining the P-delta curve regarding a reference change.

Hereinafter, examples will be described with reference to the drawings.

In the present embodiment, an overall configuration of the power system monitoring apparatus that outputs a priority fault selection result and a stability determination result of the assumed fault from the system model data and the assumed fault data will be described with reference to FIG. 2 will be used to explain the hardware configuration of the power system and the power system monitoring device.

FIG. 1 is an example of the overall configuration diagram of the power system monitoring apparatus 100 of the present embodiment. The system model data D1 held by the system model database, the assumed failure data D2 held by the assumed failure database, and the control amount vs. reference database are shown in FIG. Control amount to be stored vs. reference data D7, reference change unit 111, severe index calculation unit 110, reference data D3, severe index data D4, priority failure selection unit 112, priority failure data D5, non-priority failure data D6, and stability determination It is the figure which showed the structure of the electric power system monitoring apparatus which consists of the part 113, the reference | standard history display part 114, and the stability display part 115.

The input data of the power system monitoring apparatus 100 is composed of system model data D1, assumed fault data D2, and control amount versus reference data D7. The reference changing unit 111 of the power system monitoring apparatus 100 performs stability analysis and statistical processing using the system model data D1 and the control amount versus reference data D7, outputs the reference data D3, and outputs the reference data D3 to the reference history display unit 114. Send. The severe index calculation unit 110 of the power system monitoring apparatus 100 performs stability analysis using the system model data D1 and the assumed failure data D2, and calculates a severe index that is an index of the deterioration of the system stability of the assumed failure from the result. Then, the severe index data D4 is output. The priority fault selection unit 112 of the power system monitoring apparatus 100 uses the reference data D3 and the severe index data D4 to select a priority fault whose stability is determined in advance of the assumed fault, and the priority fault data D5 and the non-priority Fault data D6 is output. The stability determination unit 113 of the power system monitoring apparatus 100 receives the priority failure data D5, the non-priority failure data D6, and the system model data D1, performs stability analysis on the priority failure and the non-priority failure, and can stabilize the failure. The result is output as determination result data and transmitted to the stability display unit 115.

FIG. 2 is an example of the hardware configuration of the power system monitoring device 100 and the overall configuration diagram of the power system. The power system 1, the power system monitoring device 100, the measuring device 10, the power source 3 (for example, a generator), the load, and the bus 2 It is the figure which showed the example of the hardware constitutions of the power transmission line 4 and the transformer 9. The electric power system 1 is connected via a branch (line) 4 and a node (bus line) 2, respectively, a power source 3, a transformer 9, a measuring device 10, a load, and other measuring devices and controllable although not shown in the figure. It is composed of one or a plurality of devices (battery, chargeable / dischargeable secondary battery, EV storage battery, flywheel, etc.).

Here, examples of the power source 3 include a distributed power source such as a solar power generator and a wind power generator in addition to a large power source such as a thermal power generator, a hydroelectric power generator, and a nuclear power generator.

Here, the example of the measuring device 10 is a device (VT, PT, or CT) that measures any one or more of the node voltage V, the branch current I, the power factor Φ, the active power P, and the reactive power Q. And a function of transmitting data including a data measurement location identification ID and a built-in time stamp of the measurement device (such as a telemeter (TM)). Note that a device that measures power information (voltage phasor information) with absolute time using GPS, a phase measurement device (PMU: Phaser Measurement Units), or other measurement devices may be used. Although the measurement device 10 is written to be in the power system 1, the measurement device 10 may be installed on a power source 3, a transformer 9, and a bus or power transmission line connected to the measurement device 10.

Here, the measurement data is the data measured by the measurement device 10 and is received by the power system monitoring device 100 via the communication network 900. The measurement data may include a unique number for identifying the data and a time stamp.

The configuration of the power system monitoring apparatus 100 will be described. A CPU (Central Processing Unit) 102, a memory 103, an input unit 104 such as a keyboard and a mouse, a display unit 105 such as a display device, a communication unit 106, and various databases (for example, a computer device and a calculation server) A program database 130, a system model database 131, a contingency database 132, a control amount versus reference database 133, and a reference history database 134) are connected.

The display unit 105 may be configured to use a printer device, an audio output device, or the like instead of the display device or together with the display device. For example, the input unit 104 can be configured to include 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 106 includes a circuit and a communication protocol for connecting to the communication network 900. The CPU 102 reads a predetermined computer program from the program database 130 and executes it. The CPU 102 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 103 is configured as, for example, a RAM (Random Access Memory), and stores a computer program read from the program database 130, and stores calculation result data and image data necessary for each process. The screen data stored in the memory 103 is sent to the display unit 105 and displayed. An example of the displayed screen will be described later.

Here, the stored contents of the program database 130 will be described with reference to FIG. Note that programs characteristic to the invention are described, and programs for reading data and programs necessary for communication are omitted. FIG. 3 is an example of a configuration diagram showing the contents of the program data of the system monitoring device. In the program database 130, for example, a state estimation calculation program P1, a reference change program P2, a severe index calculation program P3, a priority failure selection program P4, and a stability determination program P5 are stored.

Returning to FIG. 2, the CPU 102 reads out the calculation programs (state estimation calculation program P1, reference change program P2, severe index calculation program P3, priority failure selection program P4, and stability determination program P5 read from the program database 130 into the memory 103. ) To perform a plausible system state calculation, reference data change, severe index calculation, priority fault selection, stability determination, data search in various databases, and the like. A memory 103 is a memory for temporarily storing temporary calculation data and calculation result data such as display image data, reference data, severe index data, and stability determination result data. The CPU 102 generates necessary image data and displays it. 105 (for example, a display screen).

The electric power system monitoring apparatus 100 stores five databases roughly divided. Excluding the program database 130, the system model database 131, the contingency database 132, the control amount vs. reference database 133, and the reference history database 134 will be described.

The system model database 131 includes system configuration, line impedance, ground capacitance, active power, reactive power, voltage, voltage phase angle, current, power factor, data necessary for system configuration and state estimation (such as threshold value of bat data) ), Generator data, and other data necessary for tidal current calculation and state estimation. Data with time stamp or PMU data may be used. The result of estimating and calculating the active power, reactive power, voltage, voltage phase angle, current, and power factor of each node, branch, generator, load, and control device of the plausible system is also stored as system measurement data. In addition, when inputting manually, it inputs and memorize | stores manually by the input part 104. FIG. When inputting, necessary image data is generated by the CPU 102 and displayed on the display unit 105. At the time of input, it may be semi-manual so that a large amount of data can be set by using a complementary function.

The assumed failure database 132 includes a list that is stored using the input unit 104 and that combines failure locations and failure aspects as possible failure cases in the power system. Other elements include failure removal timing and the like in the list. FIG. 4 is an image of the contingency database.
The control amount vs. reference database 133 stores data in which an arbitrary control amount and reference correspond one-to-one. FIG. 5 is an image of the control amount versus the reference database. A plurality of data sets may be provided and switched using the input unit 104.

The reference history database 134 stores the reference data calculated by the reference change program P2, the severe index of each contingency, and the control amount necessary for stabilizing each contingency calculated by the stability determination along with the time. Has been. An image of the reference history data is shown in FIG. Thereby, the operator can confirm the operation of the power system monitoring device and determine whether or not the reference changing unit 111 and the severe index calculating unit 110 need to be corrected.

Next, calculation processing contents of the power system monitoring apparatus 100 will be described with reference to FIG. FIG. 7 is an example of a flowchart showing the entire processing of the power system monitoring apparatus. First, the flow will be briefly described. The system model data D1, the assumed failure data D2, and the control amount versus reference data D7 are read from the system model database. Next, severe index data D4 is calculated using the system model data D1 and the assumed failure data D2. Next, the reference data D3 is changed using the system model data D1 and the control amount versus reference data D7, sent to the display unit, and stored in the reference history database. Next, priority failure data D5 and non-priority failure D6 are determined using severe index data D4 and reference data D3. Next, the stability calculation is performed using the system model data D1 and the priority failure data D5 to determine the stability, and the control amount is sent to the reference history database and sent to the display unit. Finally, the stability is calculated by using the system data and the non-priority fault to determine the stability, and the result is stored in the reference history database and sent to the display unit. The above processing flow will be described step by step.

First, in step S1, the system model data D1 and the assumed failure data D2 are read from the system model database 131 and the assumed failure database 132. Here, the data may be corrected using the input unit 104 and the display unit 105.

In step S2, the severe index calculation program P3 is read from the program database 130 into the memory and executed, and the severe index is calculated for each assumed failure using the system model data D1 and the assumed failure data D2. For example, the maximum value of the phase difference angle δ of the generator after a certain time after the failure is taken as a severe index. For example, a method described in JP-A-7-298498 “Method and apparatus for stabilizing a power system”, H. W. It is performed in accordance with the calculation method described in Dommel “Fast Transient Stability Solutions”. These methods have an effect that can be performed in a shorter time than the stability analysis described in step S5 by linear approximation of a non-linear calculation formula or by ignoring the stabilization control logic.

FIG. 8 shows an image when the fluctuation of the phase difference angle δ of the generator is calculated as a severe index in step S2. The horizontal axis in FIG. 8 is time, and the vertical axis is the phase difference angle of the generator. As an example, the figure shows the results of phase difference angle fluctuation calculation of three generators G1, G2, G3. Times t (0), t (1), and t (2) are a simulation start time, a disturbance occurrence time, and a severe index calculation time, respectively. δ (G1, t), δ (G2, t), and δ (G3, t) are the phase difference angles of G1, G2, and G3 at time t, respectively. When a disturbance such as the failure shown in FIG. 4 occurs at t (1), the phase difference angle of each generator starts to fluctuate. If the phase difference angle of the generator is significantly separated from other generators as a result of shaking, the generator will step out and the power system may become unstable. In general, the more unstable the grid state, the shorter the time until step-out. Therefore, the phase difference angle of each generator, δ (G1, t (2)), δ (G2, The maximum value of t (2)) and δ (G3, t (2)) can be used as a severe index of failure. In the figure, δ (G3, t (2)) is a severe index of this failure. As another severe index using the phase difference angle δ, for example, a change from the initial state, δ (G1, t (2)) − δ (G1, t (0)), δ (G2, t (2)) − The maximum value of δ (G2, t (0)), δ (G3, t (2)) − δ (G3, t (0)) may be used as a severe index. Instead of the maximum value, an average value or a weighted average based on the capacity of the generator may be used.

Returning to FIG. 7, in step S3, the reference change program P2 is read from the program database 130 into the memory and executed, the reference data D3 is calculated using the system model data D1, and stored in the reference history database 134. Here, by changing the reference data D3 based on the system model, it is possible to adjust the number and nature of the priority faults selected in step S5. The flow of changing the reference data will be described with reference to FIG. FIG. 9 is an example of a flowchart illustrating the reference data change process. FIG. 9 shows a method of reading the control amount vs. reference data D7, changing the reference data D3, and storing it in the reference history database 134 through steps S7 to S10. In step S7, the control amount versus reference data D7 is read from the control amount versus reference database 133. In step S8, the control amount of the generator of each contingency that can be stabilized in the previous stability determination steps S5 and S6 is read and the sum is calculated. In step S9, a reference for the control amount sum obtained in step S8 in the control amount versus reference database 133 is read. In step S10, the reference data D3 obtained in step S9 is transmitted to the priority failure selection unit 112 and stored in the reference history database 134.

Here, in FIG. 7, S2 is executed first for S2 and S3, but S3 may be executed first, or S2 and S3 may be executed in parallel.

Returning to FIG. 7, in step S4, priority failure is selected using the severe failure severity index data D4 obtained in step S2 and the reference data D3 obtained in step S3, and priority failure data D5 and non-priority are selected. Output as failure data D6. As a method, for example, a severe index of an assumed failure and a reference are numerically compared, an assumed failure exceeding the reference is output as priority failure data, and an assumed failure below the reference is output as non-priority failure data. For example, as shown in FIG. 8, when the maximum value of the phase difference angle δ of the generator after a certain time after the failure is taken as a severe index, the threshold θth and δ (G3, t (2)) are compared. In FIG. 8, since the phase difference angle δ (G3, t (2)) of the generator G3 at time t (2) is larger than the threshold value θth, this failure is added to the priority failure data.

In step S5, the priority fault stability is determined using the system model data D1 read in step S1 and the priority fault data D5 output in step S4, and the priority fault stability determination result is output. As a method for determining the stability of an assumed failure, see, for example, Yuji Sekine “Power System Transient Analysis” pp. This is performed in accordance with a calculation method called transient calculation described in 377-392. At this time, for example, if there is a power system stabilization device or a power system stabilization system that operates when an accident occurs in the power system as described in JP2011-19361, the transient calculation is performed in consideration of the control. Do. If the power system becomes stable after the failure, it is determined that the failure can be stabilized. If the power system becomes unstable after the failure, it is determined that the failure cannot be stabilized. At this time, the control amount such as the generator is stored in the reference history database 134.

In step S6, the system model data D1 read in step S1 and the non-priority fault data D6 output in step S4 are used to determine the stability of the non-priority fault and output the non-priority fault stability determination result. The stability determination method is the same as that in step S5. At this time, if there is control of the generator or the like, the control amount is stored in the reference history database 134.

Here, refer to FIG. FIG. 10 is a diagram illustrating an example of a screen that displays a power system stability determination result. The first line is a heading of the contingency, and the name and outline of the contingency are displayed in each column. The second line indicates whether or not a priority failure has occurred. A round mark indicates a priority failure, and a cross indicates a non-priority failure. From the third line, the results of various stability determinations are displayed. If it is stable, “stable” is displayed. If it is unstable, “unstable” is displayed together with an outline of the unstable portion. As shown in FIG. 10, by indicating whether or not the assumed failure and the priority failure of each assumed failure and the stability determination result of each assumed failure, it is possible to determine at a glance whether there is a failure that cannot be stabilized and the instability tendency. The progress of the stability determination can be determined by indicating the stability determination result in a blank for a failure for which the stability determination has not ended. If all priority faults have been determined and there are no unstable faults, the operator can focus on other tasks during the non-priority fault stability determination.

Here, refer to FIG. FIG. 11 is a diagram illustrating an example of a screen that displays a history of reference data. The horizontal axis is time, and the vertical axis is a reference value. As shown in FIG. 11, the change of the reference data is shown on the screen of the power system monitoring device 100, so that when the reference is inappropriately changed due to a measurement error or the like, the operator can easily detect and correct the abnormality. There is. Not only the reference value but also the value related to the reference change may be displayed as the second vertical axis. As a value related to the reference change, for example, in Example 1, there is a control amount sum at the time of the previous stability determination.

The control amount vs. reference data D7 is created by the operator with reference to the history data. For example, first, a severe index is arranged for each control amount, and a standard is selected so that the top 10% is statistically selected. Next, the standard is corrected so as to have an arbitrary margin based on the experience of the operator.

In the embodiments so far, priority faults and non-priority faults are divided into two stages, but a plurality of criteria may be set and priority may be set in multiple stages. For example, set two criteria, divide high priority failure, medium priority failure, low priority failure and failure into three stages, judge stability from failure with high priority, and display the judgment result You can do it.

As described above, in the invention of Example 1, the number of failures extracted by screening can be dynamically adjusted. As a result, the number of severe failures selected when the system is severe can be reduced, and the power system monitoring device can be realized in which the operator can quickly determine the stability determination result of the power system.

In the present embodiment, a method for changing the reference without using the control amount vs. reference database of the first embodiment will be described. Note that descriptions overlapping with the contents described in FIGS. 1 to 11 are omitted.

FIG. 12 is an example of an overall configuration diagram of the power system monitoring apparatus 100 according to the second embodiment, and control amount data D8 is added instead of the control amount versus reference data D7. In the power system monitoring apparatus 100 of FIG. 12, the description of the components having the same functions as those already described with reference to FIG. 1 is omitted. Input data of the power system monitoring apparatus 100 includes system model data D1, assumed failure data D2, and control amount data D8. An example of the control amount data D8 is shown in FIG. The minimum control amount that can be stabilized for each contingency obtained by the stability analysis is stored in the memory. FIG. 14 shows an example of processing of the reference changing unit 111 of the power system monitoring apparatus that does not use the control amount versus reference database 133 of the second embodiment. For convenience, t is the current time and t−T is the time when the stability of the previous power system was determined. In step S11, a representative value is calculated from the control amount of the generator of each contingency at the time of stability determination at time t−T. For example, the median value of the control amount is taken. In step S12, the output of each generator after the failure at time t is obtained. For example, the frequency fluctuation is calculated from the gain and load characteristics of the governor of the generator using [Equation 1], and the generator output fluctuation is calculated from the frequency fluctuation using [Equation 2].

In [Equation 1] and [Equation 2], GC indicates an index of a generator that continues system connection after a failure. K _GC is the output variation rate with respect to the frequency variation of the generator to continue grid connection after a failure, K _L is the output variation rate with respect to the frequency fluctuation of the power system load. P _CONTROLLED is a representative value of the control amount of the generator obtained in step S11. ΔF is a frequency variation. ΔP _GC is the output fluctuation of each generator, and the output of each generator in step S12 is obtained using this value. In step S13, a P-δ curve is created for each generator. As a method for creating a P-δ curve, for example, Y.C. There is a method described in “A SIMPLE DIRECT METHOD FOR FAST TRANSIENT STABILITY ASESSMENT OF LARGE POWER SYSTEMS” by Xue et al. In step S14, the fluctuation of the generator phase difference angle before and after the failure at time t is obtained using the P-δ curve. The P-δ curve has the shape shown in FIG. 15, and there are two phase difference angles corresponding to the output of the generator. Since a large value is an unstable point, a small value is a corresponding phase difference angle. The phase difference angle δ1 (t) corresponding to the generator output before the failure obtained from the system model and the phase difference angle δ2 (t) corresponding to the generator output after the failure obtained in step S12 are obtained, and the difference Δδ ( t). In step S15, a representative value of phase difference angle fluctuation before and after the failure is obtained from Δδ (t) of each generator. For example, the third quartile of Δδ (t) is obtained and set as Δδq (t). In step S16, the reference is changed using the representative value Δδq (t) of the phase difference fluctuation before and after the failure obtained in step S15. For example, a difference from the previous Δδq (t−T) is added as a reference.

If the system becomes severe, the amount of control increases and Δδ (t) of each generator increases. In the present embodiment, a typical Δδ (t) variation of each assumed failure is calculated, and the failure is selected as a priority failure by biasing a severe index that increases as the system becomes severe by changing the standard. Can be narrowed down to more severe ones. Further, it is not necessary to create the control amount vs. reference database of the first embodiment, and it can be easily implemented as compared with the first embodiment.

1: Power system 2: Busbar 3: Power supply 4: Transmission line 7: Circuit breaker (relay)
9: Transformer 10: Measuring device 100: Power system monitoring device 101: Communication bus line 102: CPU (Central Processing Unit)
103: memory 104: input unit 105: display unit 106: communication unit 110: severe index calculation unit 111: reference change unit 112: priority failure selection unit 113: stability determination unit 114: reference history display unit 115: stability display unit 130: Program database 131: System model database 132: Contingency failure database 133: Control amount vs. reference database 134: Reference history database 900: Communication network

Claims (10)

1. A severe index calculation unit for calculating a severe index representing an influence of deterioration in stability of each power system of two or more contingencies in the power system using facility information of the power system and periodically obtained measurement information; ,
   A priority fault selection unit that divides the contingency into two or more groups having different priorities for which stability determination is calculated based on a pre-calculated reference value and the severe index;
   A stability determination unit that performs stability determination by sequentially determining stability from an assumed failure belonging to a group having a high priority among the assumed failures using the facility information and the measurement information;
   A power system monitoring apparatus comprising: a reference changing unit that changes the reference value using the facility information and the measurement information.
2. The power system monitoring device according to claim 1,
   A power system monitoring apparatus comprising: a stability determination result display unit that displays a group to which the assumed failure belongs and a result of the stability determination.
3. The power system monitoring device according to claim 1,
   A power system monitoring apparatus characterized in that the severe index is a phase difference angle or phase angle change of a generator.
4. The power system monitoring device according to claim 3,
   The power system monitoring apparatus, wherein the reference value is changed by using the control amount of the generator as a result of the stability determination in the reference changing unit.
5. The power system monitoring device according to claim 4,
   A power system monitoring apparatus comprising a control amount vs. reference database for storing the control amount vs. reference data, using the control amount vs. reference data that associates the control amount with the reference value.
6. The power system monitoring device according to claim 3,
   Calculating a phase difference angle fluctuation before and after an assumed failure using the P-δ curve of the generator and a control amount of the generator in the reference changing unit, and changing the reference value using the phase difference angle fluctuation; A power system monitoring device characterized.
7. The power system monitoring device according to claim 1,
   The power system monitoring apparatus characterized in that frequency fluctuation or frequency fluctuation speed in the assumed failure is used as the severe index.
8. The power system monitoring device according to claim 6,
   The power system monitoring apparatus, wherein the reference change unit changes the reference value using inertia of the generator.
9. The power system monitoring device according to claim 1,
   A power system monitoring apparatus having a reference history database for storing a history of the reference value.
10. The power system monitoring device according to claim 1,
    An electric power system monitoring apparatus having a reference display unit indicating a history of the reference value.

Images