JP3450188B2 - Power equipment operation and maintenance support system - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a power equipment operation / maintenance support system that predicts the temperature of a portion of a power equipment that contributes to deterioration and supports high-efficiency operation and maintenance of the equipment.

[0002]

2. Description of the Related Art In recent years, technological development for highly efficient operation (high-load operation) of electric power equipment has been underway for the purpose of suppressing capital investment. There are demands for operation and maintenance support systems such as equipment monitoring and abnormality prediction systems for highly reliable operation. As a conventional technique to meet such a demand, for example, in an oil-filled transformer or the like, the following device life diagnosis device and control device have been proposed. For example, Japanese Patent Laid-Open No. 3-2
The oil-filled transformer residual life diagnosing device disclosed in Japanese Patent No. 74473 calculates the winding maximum temperature of the transformer from the oil temperature and the ambient temperature or the secondary load current and the ambient temperature, and based on that, The remaining life of the transformer is calculated. This remaining life is obtained by subtracting a value obtained by converting the loss life obtained by actual measurement into a 100% load from the normal life when a 100% load operation is given in advance, and presents the remaining life when the 100% load continues. However, it does not support driving in consideration of the load that changes from moment to moment.

Further, a transformer operation control method described in, for example, Japanese Patent Laid-Open No. 57-48209 is based on each information of an operating state of a transformer cooling device, a cooling medium temperature and a secondary winding current. To estimate the temperature rise rate of the transformer winding,
This is a control device that calculates the operable time (margin time) in each load operation by estimating the time until the maximum temperature is reached. This is to calculate the operable time as the load continues when overload operation occurs, and does not consider temporal load variation and temperature change. Further, for example, a transformer overload protection relay system disclosed in Japanese Patent Laid-Open No. 63-314130 approximates to a winding temperature curve of the transformer in advance when an overload is detected for an arbitrary overload. The time (overload allowable time) from the overload occurrence time to the winding maximum temperature reaching the settling value is estimated according to the winding temperature determination curve set as above. In this case, too, the allowable overload time is estimated assuming that the state at the time of overload continues, and the cooling effect will be reduced when the cooler fails, the ambient temperature will change at midsummer, and it will change from moment to moment. It is not possible to deal with load fluctuations over time.

[0004]

In the conventional equipment life diagnosis device and control device as described above, the remaining life and the allowable overload time are calculated as if the load continues at the time of occurrence of the overload, and in the future. Since it does not consider the temporal load changes and ambient temperature changes that may occur, and the energy-saving operation control conditions of the coolers used by electric power companies, etc.
The state of the equipment could not be predicted accurately, and it was difficult to perform highly efficient operation to effectively operate the equipment to the limit. In addition, since it is impossible to deal with an unexpected situation such as a partial or complete failure of the cooling device, there is a problem that the burden on the operator and the maintenance staff increases.

The present invention has been made in order to solve the above problems, and an object thereof is to predict a temperature change with time of a portion that contributes to deterioration of a power device with respect to a load change and to provide a margin to a limit. (EN) A power equipment operation and maintenance support system capable of highly accurately predicting a time and an allowable operation time when a failure occurs and presenting it to an operator and a maintenance staff.

[0006]

In a power equipment operation and maintenance support system according to the present invention, a means for detecting an operating state of a power equipment that changes with time, a detected operating state and a control condition for a cooler are used. And a means for simulating a temperature change with time of a portion contributing to the deterioration of the power equipment by a thermal equivalent model, and a means for outputting deterioration prediction information of the power equipment based on a result of the simulation. .

In addition, as an operating state of the electric power equipment, an electric current (load) to the electric power equipment and a cooling medium temperature of the cooler are detected.

Further, at least one of the applied voltage to the power equipment, the cooler operating status, and the ambient temperature is detected as the operating status of the power equipment.

Further, the temperature of the part contributing to the deterioration of the electric power equipment obtained by the simulation from a predetermined time before to the current time is set as the temperature at the current time, and the simulation is performed after the current time with the temperature as an initial value. According to the above, deterioration of the electric power equipment is predicted.

Further, the simulation up to the present time is
This is performed from a time before the time constant equal to or higher than the time constant of winding temperature rise from the current time.

In the simulation after the current time, the predicted load fluctuation and the predicted cooler control condition are input.

Further, as a result of the simulation, if the predicted temperature of the part contributing to the deterioration of the electric power equipment exceeds a preset limit value, it is judged as abnormal and the judgment result is output.

Further, as a result of the simulation, the degree of deterioration of the part concerned is calculated based on the predicted temperature of the part contributing to the deterioration of the electric power equipment, and the calculation result is output.

Also, obtained by simulation,
It is a graph for displaying a temperature change over time of a part that contributes to deterioration of electric power equipment.

When it is determined as abnormal as a result of the simulation, the deterioration state of the main insulator of the electric power equipment is detected.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiment 1. FIG. 1 is a configuration diagram when the system of the present invention is applied to a three-winding oil-filled transformer with a forced cooler as a power device. In the figure, 1
Is an oil-filled transformer body, 2 is a cooler (oil-air heat exchanger) that releases the loss (heat amount) generated in the transformer 1 to the atmosphere
Then, the oil pump 3 guides the insulating oil, which is the cooling medium of the transformer 1, to the cooler 2 through the oil pipe 4, and the cooled insulating oil is forcibly returned to the transformer 1. A fan for improving the cooling capacity is attached to the cooler 2 and has a structure for forcibly blowing the atmosphere, and is operated in conjunction with the oil pump 3. In the case of a large-capacity transformer, a plurality of the coolers 2 and the oil pump 3 are attached, and the cooler control panel 5 has a load of the transformer main body 1 for the purpose of saving the power supplied to the oil pump 3. The number of operating oil pumps 3 may be controlled in accordance with the above. FIG. 2 is a graph showing an example of the relationship between the load of the transformer 1 and the number of cooling operation units. Reference numeral 6 is a cable for supplying power from the cooler control panel 5 to the oil pump 3 and the fan.

A power equipment operation and maintenance support system according to the present invention detects, with a sensor or the like, an operating state of a transformer having the above-mentioned structure, which changes with time, and based on the detection signal. The simulation is performed by a thermal equivalent model in the host computer, and the part that contributes to the device deterioration, especially the change in the winding temperature with time is predicted. In FIG. 1, 7 is a current transformer (CT) that detects the load of the transformer body 1, 8 is an oil temperature sensor such as a resistance temperature detector that detects the oil temperature, and 9 is the application of the transformer body 1. A voltage transformer (PT) 11 for detecting voltage is tapped from the tap changer operating mechanism 10 of a tap changer (not shown) for controlling the voltage on the transformer load side (secondary and tertiary output). A tap position detector 12 for detecting a position is a peripheral temperature sensor such as a thermocouple for inputting a peripheral temperature (atmospheric temperature) via a local signal processing board 13, and converts the input signal into a predetermined physical quantity. . That is, the signal from each detector such as the oil temperature sensor 8 is converted into a physical quantity by the signal processing unit 15 via the measurement interface unit 14, and a higher-level computer 17 such as an engineering workstation is used.
(Hereinafter referred to as EWS) through the transmission interface 16. 18 is a local signal processing board 13 and EWS1
7 is a transmission cable.

In the EWS 17, the temperature of the winding at the present time is obtained by a thermal equivalent model described later based on the measurement state information (operating state information), and the predicted variable load or Based on the predicted cooler control conditions,
It is intended to simulate future temperature changes of each part. FIG. 3 shows the device configuration shown in FIG. 1 by a thermal equivalent model with transient characteristics that also considers transient phenomena, and can be expressed by the following differential equation. C _1c (dθ _1c (t) / dt) + H _1c (Q _p (t)) ・ (θ _1c (t) −θ _o (t)) = ((W _1rn (θ _1c (t)) + W _1en (θ _{1c (t))) P 1} 2 (t)) k ··· (1) C 2c (dθ 2c (t) / dt) + H 2c (Q p (t)) · (θ 2c (t) -θ o (t)) = ((W _2rn (θ _2c (t)) + W _2en (θ _2c (t))) P ₂ ² (t)) ^k・ ・ ・ (2) C _3c (dθ _3c (t) / dt ) + H _3c (Q _p (t)) ・ (θ _3c (t) −θ _o (t)) = ((W _3rn (θ _3c (t)) + W _3en (θ _3c (t))) P ₃ ² ( t)) ^k・ ・ ・ (3) C _o (dθ _o (t) / dt) + H _o (Q _p (t), Q _f (t)) ・ (θ _o (t) −θ _a (t)) _{= ΣH ic (Q p (t} )) · (θ ic (t) -θ o (t)) + W i (t) ··· (4) However, C _ic, C _o: of winding heat capacity, cooling medium , The heat capacity of the iron core and the tank H _ic : Heat dissipation coefficient between the winding and the cooling medium (insulating oil) R _ic = 1 / H _ic (R _ic is the thermal resistance during the period, shown in FIG. 3) H _o : Cooling medium ( Insulation oil) -Air heat dissipation The number _{R o = 1 / H o (} R is the thermal resistance, there shown in FIG. 3) W _IRN: winding resistance loss W at the rated load _ien: stray loss at rated load winding W _i: No Load loss (determined by applied voltage and tap position) I _i = (W _irn (θ _ic (t)) + W _ien (θ _ic (t))) P _i ² I _o = W _i (t) (I _i is Winding loss, I _o is other loss, I _o
Both _i and I _o are shown in Fig. 3) θ _ic , θ _o : Average temperature of winding, temperature of cooling medium (insulating oil) θ _a : Ambient temperature (atmospheric temperature) Q _p : Flow rate of cooling medium (insulating oil) Q _f : Cooling medium (air) flow rate P _i : Winding load factor i: Winding number (= 1, ..., N; n is the number of windings) (i = 1, 1 in this embodiment) 2 and 3.) k: constant t: time elapsed from time or reference time Since the above expressions (1) to (4) are non-linear, for example, Runge-
A solution can be easily obtained in a short time by using the Kutta method or the like.

Next, the calculation processing of the simulation by the above differential equation, which is performed in the EWS 17, will be described with reference to the flowchart of FIG. First, load pattern, ambient temperature, cooler control condition, equipment constant, limit winding maximum temperature, etc. are input (S1). Here, the load pattern is a predicted load corresponding to time, and indicates a daily load pattern determined for each day of the week, for example. The ambient temperature may be the temperature at each time according to the season or weather forecast. The cooler control condition is, for example, as shown in FIG. 2, the number of operating coolers with respect to the load of the transformer. The device constants are constants of the above differential equation such as resistance loss, stray loss, and no-load loss at rated load, and are expressed in the form of numbers and functions based on product test results, design values, or actual measured values during operation. Set. Next, the generated loss is obtained from the measured load factor, the system voltage (applied voltage), and the tap position from the time n times before the calculation time step Δt from the current time T, and the generated loss, the number of operating coolers, and the measured cooling medium. Based on the temperature, the temperature of each part up to the current time T is simulated by the differential equations (1) to (3) (S2). It should be noted that although the winding temperature rise is most involved in the deterioration of the equipment, it is very difficult to measure the temperature rise by a sensor or the like because the winding portion is a power-applying portion. Therefore, it is of utmost importance to accurately predict the change in winding temperature over time, and the calculation time n
Δt is preferably equal to or greater than the time constant of the temperature rise of the winding in order to improve the estimation accuracy. Further, the calculation process in S2 is repeated until the winding temperature and the loss therefor converge because the resistance loss and the stray loss vary depending on the winding temperature (S
If N in 3) and converge (Y in S3),
Time is initialized (current time T, elapsed time t = 0) (S
4) As the temperature of each part at the current time T, the final value of the simulation is set.

Then, based on the predicted values of the load pattern, ambient temperature, cooler control conditions, etc. input in S1,
The respective values at the time T are set (S5), and the time T to the time (T
+ Δt) or the average generation loss of each part during the elapsed time (t + Δt) is calculated, and the temperature distribution calculation at the time (T + Δt) or the elapsed time (t + Δt) is performed until the result converges ( S6 to S8). If the calculation result converges in the processing of S8, the winding highest temperature θ _iT (t) is obtained from the winding average temperature θ _ic (t) at that time by the following equation (5) (S9). θ _iT (t) = θ _ic (t) + α (Q _p (t)) · _{Δθ iTn} · P _i (t) β ・ ・ ・ (5) where α (Q _p ): Cooling medium flow rate Q _{p Specified} coefficient _{Δθ iTn} : Maximum point temperature difference from average winding temperature at rated load and rated flow rate P _i : Load factor of winding i β: Constant The determined maximum winding temperature is stored in a memory device Store (S1
0), the time (T + Δt) does not exceed the time that is set in advance to predict the temporal change of the winding temperature,
Alternatively, if the elapsed time (t + Δt) does not exceed the similarly defined time (when N in S11), the current time T is further increased by + Δt or the elapsed time t is further increased by + Δt,
The processes of S5 to S10 are repeated based on the predicted value such as the predicted load at that time.

After the winding highest point temperature is calculated up to a predetermined time (for a predetermined time) (when Y in S11), the winding highest point temperature and a predetermined limit winding temperature are calculated. By comparison, if the winding maximum temperature exceeds the limit winding temperature,
Judge as abnormal. Also, from the winding maximum temperature, the following equation (6)
According to, the life loss calculation is performed (S12). The following equation (6) is
For example, the formula is developed from the oil-immersed transformer operation guideline shown in Technical Report (Part I) No. 143 of the Institute of Electrical Engineers of Japan. This is an expression for obtaining the life loss V (degree of deterioration with respect to the normal life Y ₀ ) during the time Δt when the normal life at that time is Y ₀ . V = (1 / Y ₀ ) ・ Σ (e ^{b (} θ ^T-95)・ △ t) ・ ・ ・ (6) However, b: constant (when the temperature difference is 6 ° C and the life is halved, b = 0.
1155) θ _T : Temperature of the highest winding point Finally, from the current time T to a predetermined time (for a predetermined time)
The calculation result, the margin time until the occurrence of an abnormality, the life loss, etc. are displayed (S13). FIG. 5 shows an example of the display. The time from the current time T1 to the time T2 at which the temperature change with time of the winding maximum temperature reaches the limit winding temperature is the margin time until the abnormality occurs. Further, as the calculation result, the temporal changes of the winding maximum temperature, the cooling medium temperature, the ambient temperature, the load factor, etc. are simultaneously displayed, so that a more detailed state of the device can be predicted.

To continue the calculation (Y in S14)
If there is an input from each sensor (when Y in S15), the process returns to S2 and the simulation is performed based on the device state at the new time. From the above, the equipment is represented by a thermal equivalent model, and moreover, the winding temperature at the current time is calculated with high accuracy based on the detected value from each sensor, and that value is used as the initial value for the lapse of time after the current time. Since the temperature change is calculated, it is possible to accurately predict the margin time until the occurrence of a device abnormality. In addition, since it is possible to calculate the life loss up to the point of abnormality occurrence, it is possible to easily understand the risk of continued operation, which allows the equipment to operate at its marginal limits and, in terms of maintenance, the It is possible to carry out easy maintenance or make a facility renewal plan. Also, in the case where some or all of the coolers are stopped, if the number of stopped coolers and the cooling capacity of the coolers are input as the cooler control conditions in the process S1 of FIG. Temperature change can be calculated. From this result as well, it is possible to predict the operation margin time until the occurrence of an abnormality, and therefore the operator can also carry out a planned equipment stop.

In the above description, the case where the system of the present invention is applied to the forced cooling oil-filled transformer provided with the load control type cooler for controlling the number of operating transformers according to the load of the transformer has been described. In the oil-filled transformer,
Similar simulations can be performed even with an inverter control type cooler that has been adopted for energy saving in electric power companies in recent years. That is, by setting the condition of the cooling medium flow rate for the load or the operating frequency for the load (since the operating frequency of the pump or fan is proportional to the cooling medium flow rate) as the cooler control condition of the simulation,
The same effect as the control of the operating number can be obtained. The same applies to the oil temperature control method in which the number of operating coolers is increased or decreased depending on the oil temperature. Further, in the above description, a simulation using a thermal equivalent model was performed in the EWS as the host computer 17. However, due to the progress of the microcomputer in recent years, the arithmetic processing unit 15 in the on-site processing board 13 in FIG. It is also possible to perform the above simulation here using a computer. In this case, since the processing load on the host computer 17 is reduced, one host computer 17 can process a plurality of electric power devices.

Embodiment 2. In the first embodiment, the voltage applied to the equipment is measured, but when the system voltage of the power equipment is almost constant, voltage measurement is omitted and only the presence or absence of voltage application is detected. Then
The voltage may be applied to cause a typical no-load loss. In this case, the prediction accuracy will drop slightly,
As shown in FIG. 6, compared with the configuration of the first embodiment shown in FIG. 1, the instrument transformer 9 and the tap position detector 11 can be omitted, and the device configuration becomes simple.

Embodiment 3. Embodiments 1 and 2 above
In the above, the case where the present system is applied to the transformer with the forced cooler is shown. However, when it is applied to the self-cooling type transformer as shown in FIG. 7, the simulation can be performed by the similar thermal equivalent model. . In this case, the operating condition of the cooler is obtained by inputting the equivalent flow rate characteristic that is a function of the temperature difference between the oil temperature and the ambient temperature. Therefore, in the calculation by the above-mentioned differential equations (1) to (4), the cooling medium flow rate and the cooling medium-atmosphere heat dissipation coefficient are given as a function of the temperature difference between the cooling medium temperature and the ambient temperature. Further, as shown in the flowchart of FIG. 8, the temperature calculation by the differential equation (S2 or S6 to S7) is performed until the result converges, the cooling medium flow rate and the cooling medium-atmosphere heat dissipation coefficient are calculated for each temperature calculation result. It is calculated again from (T1 or T2). In this way, it is possible to give the temperature as a function of the temperature difference between the cooling medium temperature and the ambient temperature without detecting the operating state of the cooler.

Fourth Embodiment In the first embodiment, the predicted value of the change over time of the winding temperature is displayed in a graph, the time when the maximum temperature reaches the limit winding is determined to be abnormal, and the deterioration degree at that time is determined. However, if it is determined to be abnormal, device monitoring will be further strengthened, and a function of monitoring the operating state up to the device limit will be added. FIG. 9 shows the system configuration shown in FIG.
Activation interface 19 and gas-in-oil monitoring device 20
In the case where an abnormality is determined from the simulation result, the EWS 17 is connected to the on-site signal processing panel 13 via the transmission cable 18 and the above-mentioned oil-in-gas monitoring device 20 is added.
The start command of is output. As a result, the in-oil gas monitoring device 20 is activated from the activation interface 19 in a short cycle. The in-oil gas monitoring device 20 collects insulating oil from the transformer main body 1, detects a combustible gas (gas component concentration) dissolved in the insulating oil, and transmits it to the EWS 17. EWS17
Then, it is possible to detect the abnormality and deterioration state of the transformer body 1 in more detail from the information on the gas in oil that is periodically transmitted. As described above, since not only the prediction of the device deterioration but also the details of the deterioration state can be detected, highly reliable operation of the device can be realized.

Embodiment 5. Embodiments 1 to 4 above
In all of the above, the target equipment was described as an oil-filled transformer, but for other power equipment as well, the temperature inside the equipment at the current time was similarly obtained based on equipment operating state information, and this value was used as the initial value. It goes without saying that the thermal equivalent model can predict the temperature change over time after the current time. Even if the cooling medium is a gas such as SF ₆ , the same effect can be obtained.

[0028]

Since the present invention is constructed as described above, it has the following effects.

Since the operating state of the electric power equipment, which changes with time, is detected, and the temperature change with time of the portion contributing to the equipment deterioration is calculated by the thermal equivalent model based on the operating state and the cooling condition of the cooler. Since it is possible to accurately predict the deterioration of the electric power equipment and the margin time until the occurrence of an abnormality, it is possible to effectively support the operator.

Further, since the electric current (load) to the electric power equipment and the cooling medium temperature of the cooler are detected as the operating state of the electric power equipment, the simulation suitable for the actual operating state can be performed.

Further, since any one of the applied voltage to the power equipment, the operating state of the cooler, and the ambient temperature is detected as the operating status of the power equipment, more accurate simulation can be performed.

Further, a simulation from a predetermined time before to the current time is performed based on the operating state of the electric power equipment which changes with time, and the temperature of each part obtained by the simulation is used as an initial value to obtain the temperature after the current time. Since simulation is performed, highly accurate prediction can be performed.

Further, since the simulation is performed from the present time onward before the time constant equal to or more than the time constant of the winding temperature rise, the winding temperature can be accurately estimated.

In addition, in the simulation after the current time, since the load fluctuation affecting the deterioration of the electric power equipment and the predicted cooler control condition are input, the simulation accuracy is improved and the limit of the electric power equipment can be accurately estimated. ,
Highly efficient operation of electric power equipment becomes possible.

Further, as a result of the simulation, if the predicted temperature of the part contributing to the deterioration of the electric power equipment exceeds a preset limit value, it is judged to be abnormal, and the judgment result is output to the operator or maintenance staff. On the other hand, effective support becomes possible.

Further, since the degree of deterioration of the part that contributes to the deterioration of the electric power equipment is calculated and displayed, the operator or maintenance staff can easily grasp the risk of continued operation, and timely. It is possible to carry out various maintenance or plan equipment renewal.

Also, obtained by simulation,
Since the temperature change over time of the part that contributes to the deterioration of the power equipment is displayed in a graph, the operating margin of the power equipment can be seen at a glance.

In addition, when it is determined that the power equipment is abnormal, the deterioration state of the main insulator of the power equipment is detected, so that highly reliable operation of the power equipment can be realized.

[Brief description of drawings]

FIG. 1 is a configuration diagram when an electric power equipment operation and maintenance support system according to Embodiment 1 of the present invention is applied to an oil-filled transformer with a forced cooler.

FIG. 2 is a graph showing the relationship between the load and the number of operating units in a load control type cooler.

FIG. 3 is a diagram showing a thermal equivalent model of a power device.

FIG. 4 is a flowchart showing a flow of a simulation process based on the thermal equivalent model of FIG.

FIG. 5 is a diagram showing a display example of a simulation calculation result.

[Fig. 6] Fig. 6 is a configuration diagram in the case where the power device operation and maintenance support system according to the second embodiment of the present invention is applied to an oil-filled transformer with a forced cooler.

FIG. 7 is a configuration diagram of a power equipment operation and maintenance support system according to a third embodiment of the present invention applied to a self-cooling oil-filled transformer.

FIG. 8 is a flowchart showing a flow of a simulation process based on a thermal equivalent model for the electric power device of FIG.

[Fig. 9] Fig. 9 is a configuration diagram in the case where the power device operation maintenance support system according to the fourth embodiment of the present invention is applied to an oil-filled transformer.

[Explanation of symbols]

1 transformer body, 2 cooler, 3 oil pump, 4 oil pipe, 5 cooler control panel, 6 power supply cable, 7 current transformer (CT), 8 oil temperature sensor, 9 instrument transformer (P
T), 10 tap changer operating mechanism, 11 tap position detector, 12 ambient temperature sensor, 13 field signal processing board, 1
4 measurement interface, 15 signal processor, 16
Transmission interface, 17 Host computer, 18
Transmission cable, 19 In-oil gas monitoring device activation interface, 20 In-oil gas monitoring device.

Claims (10)

(57) [Claims] 1. A driving / maintenance support system for a power device, comprising a cooler for cooling loss (heat quantity) generated inside, a means for detecting a time-dependent change of the operating condition of the power device, and a detected operating condition. And a means for simulating a time-dependent temperature change of a part that contributes to the deterioration of the power equipment by a thermal equivalent model based on the control condition of the cooler, and a deterioration prediction of the power equipment based on the result of the simulation. A power equipment operation and maintenance support system comprising means for outputting information. 2. The electric power equipment operation and maintenance support system according to claim 1, wherein the electric current (load) to the electric power equipment and the cooling medium temperature of the cooler are detected as the operating state of the electric power equipment. 3. The electric power equipment operation according to claim 1, wherein at least one of a voltage applied to the electric power equipment, a cooler operating state, and an ambient temperature is detected as an operating state of the electric power equipment. Maintenance support system. 4. The temperature of a portion that contributes to power equipment deterioration obtained by a simulation from a predetermined time before to the current time is set as the relevant temperature at the current time, and the simulation is performed after the current time with the temperature as an initial value. The power equipment operation and maintenance support system according to any one of claims 1 to 3, wherein deterioration of the power equipment is predicted according to. 5. The power equipment operation and maintenance support system according to claim 4, wherein the predetermined time is set to be equal to or longer than a time constant of temperature rise of the winding. 6. The power device according to claim 1, wherein the predicted load fluctuation of the power device and the predicted cooler control condition are input in the simulation after the current time. Operation and maintenance support system. 7. As a result of the simulation, when the predicted temperature of the part contributing to the deterioration of the electric power equipment exceeds a preset limit value, it is determined to be abnormal, and the determination result is output. The power equipment operation and maintenance support system according to any one of claims 1 to 6. 8. The result of the simulation, based on the predicted temperature of the part contributing to the deterioration of the electric power equipment, the degree of deterioration of the part is calculated, and the calculation result is output. 8. A power equipment operation and maintenance support system according to any one of 1 to 7. 9. The electric power equipment operation according to claim 1, wherein a temporal change in temperature of a portion contributing to deterioration of the electric power equipment obtained by simulation is displayed in a graph. Maintenance support system. 10. The power equipment operation and maintenance support system according to claim 7, wherein if the result of the simulation is abnormal, the deterioration state of the main insulator of the power equipment is detected. .