JP2010166702A - Power supply risk evaluation system of power facility - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To assist facility design and facility maintenance by evaluating a power supply risk of a power facility and a power supply system to optimize the relationship between the risk and facility economy. <P>SOLUTION: The power supply risk evaluation system of a power facility is provided with: a unit risk evaluation part 21 which estimates a risk model of individual power facility, and according to the estimated risk models, evaluates the power supply risk of the corresponding power facility; a system risk evaluation part 22 which generates a power supply system with such a connection configuration combining individual power facilities, and evaluates the power supply risk of the generated power supply system; and a scenario risk evaluation part 23 which generates a power supply system having such a connection configuration for each scenario corresponding to an operation mode, a maintenance work mode, and the like, and evaluates the power supply risk of the power supply system generated for each scenario. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

The present invention provides a plurality of power supply facilities such as an uninterruptible UPS (UPS).
Power system), emergency private power generation facilities, power distribution facilities, etc. to evaluate the power supply risks such as power supply reliability and power quality, and to support sound operation, maintenance, and facility renewal of power supply facilities The present invention relates to a power supply risk evaluation system for facilities.

  Important facilities such as various buildings, airports and public facilities such as airports, communication facilities, and data centers are responsible for the risk of economic damage and the provision of social services. Sound operation is essential.

  As means for ensuring the sound operation of the power supply facilities as described above, backup power sources such as uninterruptible devices and emergency diesel generators are installed as well as general power distribution facilities. These backup power supply facilities, together with other power distribution facilities, increase the risk of power supply (risks such as power outages and instantaneous voltage drops) as they age and change over time.

  Therefore, in order to ensure the sound operation of power supply facilities over a long period of time, maintenance, maintenance, and daily inspection of power supply facilities are very important. There is a problem that it is difficult to detect signs of deterioration, and preventive maintenance is difficult to implement.

  As a result, for example, in data centers, a method to increase the reliability of power supply by adopting sufficient preventive measures for the power supply equipment itself, such as duplicating uninterruptible devices and installing spare units, is adopted. ing.

  With conventional power supply facilities, it is difficult to carry out preventive maintenance of electrical facilities, so preventive measures can be taken only when there are too few facilities due to cases where excessive equipment measures are taken more than necessary for important loads and due to equipment cost constraints. Capital investment has often been made in which the trade-off between power supply risk and equipment economy is not appropriate, such as cases that are not taken.

  By the way, in recent years, a technique of an economic evaluation method for return on investment for facilities has been proposed (Patent Document 1).

  This method of evaluating the economic value of return on investment for a facility generates a maintenance scenario by inputting a strategy and a scenario for the occurrence of a failure, which are triggered by a decision to update the machinery and equipment when a future failure occurs. The timing of equipment renewal is determined for each scenario. Then, the cost for updating the machine equipment, the loss when a failure occurs, the cost for updating the machine equipment, and the updated cost are arranged in the scenario, and the cash flow for each scenario is calculated.

  Next, based on the failure establishment of machinery and equipment, calculate the establishment probability of each scenario, and finally calculate the strategic value of maintenance investment by taking the sum of the product of the cost of each scenario and the establishment of scenario establishment. Is the method.

  Conventionally, another evaluation system related to economic evaluation for facilities has also been proposed (Patent Document 2).

  This evaluation system evaluates the effects of introducing harmonic countermeasure equipment from the viewpoints of economy and risk avoidance, and supports the decision making of optimal capital investment.

JP-A-2005-202585 JP 2007-282427 A

  However, the technique of Patent Document 1 is an evaluation method for mechanical equipment, and does not target an evaluation method for electrical equipment in which it is difficult to grasp the future failure or deterioration status. In addition, there is no mention of specific risk assessments such as performance degradation and failure risk of each facility. In addition, the technology of Patent Document 1 is mainly intended to support maintenance plans that aim to rationalize maintenance, and evaluates equipment reliability and power supply risk at the design stage to support optimal equipment design. It is not what you do.

  The technology of Patent Document 2 evaluates the introduction effect when the harmonic countermeasure facility is introduced into the power system, and evaluates the power supply risk due to the failure or deterioration of the power supply facility itself as the source. Not.

  Therefore, conventionally, as shown in FIG. 9, an evaluation system for a power supply facility in consideration of a power supply risk is used. This power supply facility evaluation system includes a demand prediction database 101 that stores and manages data necessary for predicting power demand in consideration of past power demand data and future predetermined periods and seasons. An operation plan database 102 for storing future operation plan data, an equipment cost database 103 for storing data on operation and maintenance / inspection costs of each power supply facility, and an equipment evaluation system 104, The facility demand prediction function 104a retrieves data necessary for predicting power demand from the demand prediction database 101, creates a power demand prediction from the present time to the target year, and then executes the facility operation / maintenance evaluation function 104b. The facility operation / maintenance evaluation function 104b executes operation / maintenance evaluation based on the power demand prediction data and the future operation plan data of the power facility equipment stored in the operation plan database 102. Furthermore, the facility operation / maintenance cost evaluation function 104c evaluates the cost of facility operation / maintenance using data related to the operation and maintenance / inspection costs of each power supply facility based on the operation plan data. The economic evaluation result 105 is obtained in consideration of the cost based on the operation and maintenance / inspection for the future period (time) based on the operation plan data.

  In addition, by changing the operation and maintenance scenarios, the life cycle economy (value index such as the present value of the power supply equipment) is evaluated, and the optimum operation and maintenance plan is obtained.

  However, the power supply facility evaluation system as described above is evaluated from the viewpoint of economic efficiency, and does not evaluate the power supply risk of each power supply facility. It is difficult to implement. That is, when maintenance or inspection of individual power supply facilities is neglected or a failure occurs, the entire system is affected, and it is difficult to ensure sound operation for important load facilities.

  The present invention has been made in view of the above circumstances, for evaluating the power supply risk of power supply facilities, optimizing the trade-off between the power supply risk and facility economics, and ensuring the sound operation of power supply facilities. The purpose is to provide a power supply risk assessment system for power supply equipment that supports equipment design and maintenance.

(1) In order to solve the above-described problem, the present invention provides a power supply risk evaluation system for a power supply facility that evaluates at least the power supply reliability and risk of a power supply system including a plurality of power supply facilities. A unit risk evaluation unit that estimates a risk model of each power supply facility and evaluates a power supply risk of the corresponding power supply facility from each estimated risk model, and a connection configuration combining the individual power supply facilities A system risk evaluation unit that evaluates the power supply risk of the created power supply system, and a power supply system with a connection configuration for each scenario according to the operation mode, maintenance work mode, etc. And a scenario risk evaluation unit that evaluates the power supply risk of the created power supply system for each scenario. Is a Bei power supply risk assessment system.

(2) A power supply risk evaluation system for a power supply facility according to another invention is based on system configuration data set in advance as a system risk evaluation unit which is one of the components of the item (1). A system connection configuration display / editing means for creating and displaying a power supply system having a connection configuration combining facilities and executing correction processing as necessary, and a risk of the power supply facility that is a component of the created power supply system A system risk calculating means for calculating the risk of the power supply system using a predetermined failure probability calculation formula based on the predicted value is provided.

  The system risk calculation means uses unit risk data set in advance to evaluate the risk of failure of each power supply facility, and compares the risk evaluation result of each power supply facility with a preset risk requirement level. A bottleneck risk factor detection means for detecting a risk factor that becomes a bottleneck, and an improvement for calculating the economic effect of reducing the investment against risk for the equipment improvement to avoid the risk factor for the detected bottleneck risk factor An investment effect evaluation means is provided.

  According to the present invention, the power supply risk of a power supply facility can be evaluated, and the trade-off between the power supply risk and the facility economy can be optimized, and the facility design for ensuring the sound operation of the power supply facility A power supply risk assessment system for power supply equipment that can support equipment maintenance can be provided.

The basic block diagram which shows one Embodiment of the power supply risk evaluation system of the power supply equipment which concerns on this invention. The figure explaining an example which estimates a risk model using the risk model estimation means of a power supply facility (unit). The stem block diagram as a specific example for performing a system risk calculation means. A system configuration diagram created by a scenario-specific system connection configuration display / editing means. The figure which shows another structural example of the system risk-evaluation part of the electric power supply system shown in FIG. The figure explaining the improvement scenario of an electric power supply system. An example diagram visualizing and displaying the effects of equipment improvement. Another example figure which visualized and displayed the effect accompanying equipment improvement. The block diagram explaining the conventional power supply equipment evaluation system.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
(First embodiment: corresponding to claims 1 to 4)
FIG. 1 is a block diagram showing a first embodiment of a power supply risk evaluation system for a power supply facility according to the present invention.

  The power supply risk assessment system for power supply facilities is a risk assessment composed of an input unit 1 such as a keyboard or mouse pointing device for inputting data necessary for risk assessment or a control instruction, and a CPU. The processing unit 2, the display unit 3 for displaying each risk evaluation result, and the database 4 are configured.

  Functionally, the risk evaluation processing unit 2 is functionally connected to the unit risk evaluation unit 21 that evaluates the reliability or risk of individual power supply of each power supply facility (unit), and the parallel redundancy formed by combining the individual power supply facilities. A system risk evaluation unit 22 that evaluates the power supply reliability of a power supply system of a single-line connection diagram including a backup power source, a private power generation facility, etc. or a risk of a power failure, and the operation mode of the power supply system and a failure that may occur in the future Scenario risk evaluation unit that evaluates the power supply reliability or risk for each case (scenario) according to the connection status of equipment according to the expected maintenance / inspection work mode, connection status of power supply / load circuit, and supply status of external power 23. Note that the individual power supply equipment described above includes parts or a single device constituting all or part of the power supply equipment.

  The database 4 includes an operation history data storage unit 41 that stores at least data related to the operation history of the power supply equipment (for example, part manufacture date or part installation date), and maintenance such as replacement date of each part constituting each power supply equipment. Maintenance history data storage unit 42 for storing history data, failure history data storage unit 43 for storing failure history data such as the failure occurrence date including the life of each component constituting each power supply facility, and various combinations of power supply facilities A system configuration data storage unit 44 for storing configuration data of the power supply system of the single-line diagram and an operation / maintenance scenario data storage unit 45 for storing each scenario data in consideration of operation, maintenance and inspection of the power supply system are formed. Yes.

  The unit risk evaluation unit 21 includes a risk model estimation unit 21a and a risk evaluation prediction unit 21b.

  The risk model estimation means 21a has a function of estimating a risk prediction model of a power supply facility including parts from data such as past accidents / failure histories / part replacement histories. The risk evaluation prediction unit 21b has a function of calculating the survival probability of each power supply facility using the risk prediction model estimated by the risk model estimation unit 21a and displaying it on the display unit 3.

  The system risk evaluation unit 22 includes a system connection configuration display / editing means 22a for creating a power supply system of a single-line connection diagram formed by combining the power supply facilities evaluated by the unit risk evaluation unit 21, and a power supply system of the single-line connection diagram. System risk calculation means 22b for evaluating the power failure / failure risk.

  The scenario risk evaluation unit 23 includes, for example, a scenario-specific system connection configuration display / editing unit 23a that generates a scenario-specific power supply system based on a mode that considers a plurality of operations, maintenance, inspections, and the like, and a scenario-specific power supply system. It comprises scenario risk calculation means 23b for evaluating system risk.

  Next, the operation of the power supply risk evaluation system for the power supply equipment configured as described above will be described.

  First, the unit risk evaluation unit 21 executes the risk model estimation unit 21a based on the unit risk evaluation instruction from the input unit 1 and the name of the power supply equipment including the parts.

  Risk model estimation means 21a is already known literature (book title: life time analysis that can be read immediately-Kaplan-Meier method / logistic regression analysis / Cox's proportional hazard model is well known, Shin Takahashi, February 2007, Tokyo Book) The risk model can be estimated using, for example, the Kaplan-Meier method.

  This risk model estimation means 21a relates to the parts A, B, C,... From each data storage unit 41 to 43 based on, for example, each part name A, B, C,. Take out data such as installation date (operation history data), replacement date (maintenance history data) of components that make up each power supply facility, and date of failure (failure history data), as shown in FIG. Time series events for operation / part replacement and failure occurrence status from the present to the present are output and displayed on the display unit 3 as shown in the left diagram of FIG. 2 as necessary. That is, the display unit 3 displays time-series event data related to operation / maintenance / failure history of the power supply equipment.

  Then, the risk model estimating means 21a is based on the data such as the installation date, the part replacement date, the failure occurrence date, etc., relating to the parts A, B, C,. The survival probability of each part with respect to the elapsed time as shown in FIG.

  The right diagram of FIG. 2 is a diagram showing a survival model by the Kaplan-Meier method, where the horizontal axis represents a time axis (for example, a maximum of 100,000 hours), the vertical axis represents the survival probability, and the vertical axis represents the survival probability “1”. Means 100%. According to Kaplan Meier, the survival probability shown in the figure (b) is a true answer, but when considering the ambiguity of the data, it is within the range of + 95% upper limit (b) and -95% lower limit (c) If there is a confidence interval, it is determined. Therefore, by using the Kaplan-Meier method, it is possible to easily estimate the risk model of each component A, B, C,.

  Subsequently, the unit risk evaluation unit 21 executes the risk evaluation prediction means 21b. Based on the risk prediction model of each part estimated by the risk model estimation unit 21a, the risk evaluation prediction unit 21b takes out operation history data from the past to the present stored in the operation history data storage unit 41, and presents or specifies Future survival probability (for example, five years later) or failure establishment (= 1.0-survival probability), that is, a risk evaluation is calculated.

  Specifically, as described in the frame of the unit risk evaluation unit 21 of FIG. 1, the horizontal axis indicates the cumulative usage time of each component, the vertical axis indicates the survival probability (reliability), and the survival probability is “1”. A risk evaluation representing the change probability of the survival probability at the present time t and the survival probability until a specific year in the future is displayed on the display unit 3.

  Therefore, based on the risk evaluation displayed on the display unit 3 and the survival time model based on the Kaplan-Meier method described above, it is possible to predict how much future each component can maintain sufficient reliability.

  The power supply risk evaluation system executes the system connection configuration display / editing means 22a of the system risk evaluation unit 22 after performing the risk evaluation of the survival probability at the current time t of each component and the survival probability until a specific year in the future.

  The system risk evaluation unit 22 may be activated on condition that a system risk evaluation instruction is input from the input unit 1.

  The system connection configuration display / editing means 22a of the system risk evaluation unit 22 uses a drawing editing program including CAD, and uses one of the configuration data of several power supply systems stored in the system configuration data storage unit 44. The configuration data of the power supply system is read out, the parts subjected to risk assessment by the unit risk assessment unit 21 are imported, and the single-line diagram is edited and drawn. At this time, the characteristic parameters of each part necessary for the power supply system drawn in the single-line diagram are taken from the system configuration data storage unit 44. Further, after drawing the power supply system of the single-line diagram, one desired power system is created while repeating correction processing as necessary.

  In addition to the normal power distribution system, the power system includes various system configurations such as a parallel redundant configuration, a backup configuration, and a configuration of a power supply system incorporating a private generator. In any case, after drawing one power supply system, it may be stored in the system configuration data storage unit 44, which is an appropriate storage means, and then the configuration of the next power supply system may be drawn. After the configuration data of one completed power supply system is stored in the system configuration data storage unit 44, the processing may be continued by the system risk calculation unit 22b.

  The system risk calculation unit 22b calculates the power supply risk of the entire drawn power supply system.

  Regarding the calculation of the power supply risk, for example, as shown in FIG. 3, consider a case where a plurality of uninterruptible power supplies UPS1 to UPS3 have a parallel redundant configuration, that is, an UPS configuration with 1 line n + 1 redundancy. At this time, it is assumed that the failure rate with respect to the time lapse t of the i-th UPS is Pi (t). In addition, the maximum power capacity required by the important load can be covered by n UPSs.

  Therefore, in the UPS configuration with one line n + 1 redundancy, even if at least one UPS fails, the remaining n UPS can cover the important load. Therefore, the power supply risk is a problem of the probability that two or more UPSs will fail at the same time, and can be calculated by the following known formula.

That is, the probability P that two or more UPSs fail simultaneously is

  Therefore, as the system risk calculation means 22b, the failure probability of each power supply system is calculated based on the risk evaluation predicted value of each component that is a component of each power supply system, using the above-described failure probability calculation formula, for example. Assess a risk. Then, the failure probability obtained by the system risk calculation unit 22b is superimposed on a predetermined region of the power supply system image that is the created single connection diagram, and is displayed on the display unit 3.

  Further, after the processing by the system risk evaluation unit 22 is completed, the scenario risk evaluation unit 23 is activated automatically or upon receiving a scenario risk evaluation instruction from the input unit 1.

  The scenario-based system connection configuration display / editing means 23a of the scenario risk evaluation unit 23 extracts data relating to the configuration of the power supply system and the characteristic parameters of each part from the operation / maintenance scenario data storage unit 45 of the database 4, and draws a drawing including CAD. Using an editing program, as shown in Fig. 4, the power supply of a single connection diagram for each operation / maintenance state (scenario) such as normal operation mode, commercial power failure operation mode, transformer maintenance operation mode, etc. A system configuration is created and displayed on the display unit 3.

  That is, a number of scenario configurations of the power supply system can be created for each operation / maintenance state. For example, as shown in FIG. 4, a normal operation mode, a commercial system power failure operation mode, a transformer maintenance operation mode, and the like are examples.

  In the normal operation mode, two emergency generators are disconnected from the on-site system. In the operation mode at the time of power failure of the commercial system, the power line transformers from the two commercial systems are disconnected from the commercial system and the in-house system, and the two emergency generators are connected to the in-house system, and power is supplied by private power generation. Is called. In the transformer maintenance operation mode, one transformer is disconnected from the commercial system and the in-house system for maintenance.

  Subsequently, the scenario risk evaluation unit 23 executes the scenario risk calculation means 23b. The scenario risk calculation means 23b determines the risk of the power supply system of each scenario for each component that is a component of the power supply system for each scenario in the same manner as the system risk calculation means 22b of the system risk evaluation unit 22 described above. Based on the risk evaluation predicted value, the risk that is the failure probability of the power supply system for each scenario is evaluated and displayed on the display unit 3.

  Therefore, according to the first embodiment as described above, the unit risk evaluation unit 21 for each power supply facility, the system risk evaluation unit 22 of the power supply system formed by combining these power supply facilities, each operation mode, and maintenance By providing the evaluation unit 23 that evaluates the scenario risk according to the work mode, etc., the risk factor at each stage can be accurately estimated, and as a result, the risk of the entire power supply system can be accurately evaluated and estimated. Is possible.

  In addition, by using this evaluation system at the stage of power supply facility design, risk assessment and connection relationships for each power supply facility and each power supply system are visualized and displayed on the display unit 3, so that each power supply system is connected to each power supply facility. The configuration and risk evaluation can be easily confirmed, and whether or not a desired risk standard is satisfied can be confirmed.

(Second embodiment: corresponding to claim 5)
Since the power supply risk evaluation system of the power supply facility according to the second embodiment has the same configuration as that of FIG. 1 describing the first embodiment described above, the description thereof is omitted here.

  In the second embodiment, the difference is that the system risk calculation means 22b ′ constituting the system risk evaluation unit 22 is improved as shown in FIG. The system risk calculation means 22b ′ detects a bottleneck risk factor detection means 22ba that detects a risk factor that becomes a bottleneck from the risk evaluation of each system and its required level, and this bottleneck risk factor detection means 22ba detects the risk factor. The improved investment effect evaluation means 22bb which calculates the economic effect by the risk reduction against the investment for the equipment improvement for avoiding the bottleneck risk factor.

  In this embodiment, the database 4 newly includes a unit risk data storage unit 46 for storing risk assessment result data of each power supply facility obtained by the risk assessment prediction means 21b, risk request level data allowed in advance. And a facility improvement measure data storage portion 48 for specifying facility improvement measure data corresponding to a presumed bottleneck risk factor.

  Next, the operation of the system risk calculation unit 22b ′ in the system risk evaluation unit 22 shown in FIG. 5 will be described.

  When the system risk calculation unit 22b ′ inputs the bottleneck factor detection instruction from the input unit 1 after the system connection configuration display / editing unit 22a is executed, or when the bottleneck factor detection flag is set in advance, Instead of the system risk calculation means 22b shown in FIG. 1, the bottleneck risk factor detection means 22ba of the system risk calculation means 22b ′ of FIG. 5 is executed.

  The bottleneck risk factor detection means 22ba uses the unit risk data already stored in the execution stage of the unit risk evaluation unit 21 in the unit risk data storage unit 46 of the database 4 and the individual power supply equipment (unit) fails. Calculate the power supply risk sensitivity of the entire power supply system.

For example, in the upper diagram of FIG. 6, it is assumed that a power supply system including one line with one transformer and a UPS with n + 1 redundancy is assumed. At this time, even if one j-th UPS fails, the probability P that the remaining n UPSs further fail is:

And generally very low.

  However, if one transformer TR fails, the entire power supply system is in a power failure state, and there is a risk that the power supply will be stopped for a long time. Therefore, in the case of the connection configuration of this power supply system, the transformer TR becomes a bottleneck risk factor.

  Actually, the risk sensitivity calculation of each device as in the above example is compared with the risk level data or the required level data stored in the risk required level data storage unit 47 to detect the most critical risk factor, It passes to improvement investment effect evaluation means 22bb.

  The improvement investment effect evaluation means 22bb reads out the equipment improvement measure data stored in the equipment improvement measure data storage unit 48 for the bottleneck risk factor detected by the bottleneck risk factor detection means 22ba, and stores the equipment improvement measure data. After selecting equipment improvement plan data to avoid risk factors from the inside, compare the capital investment cost with the cost of the risk reduction or the effect of power outage avoidance that is improved with the addition of the equipment investment cost. Calculate the economic effect of the reduction.

  Specifically, for example, in response to the failure of the transformer TR in the upper diagram of FIG. 6, as shown in the lower diagram of FIG. At this time, the capital investment cost associated with the addition of the transformer TR2 and the bus and the cost of the risk reduction improved due to the addition or the cost associated with the power failure avoidance are compared, and the economic effect of reducing the investment versus risk is calculated. .

  Therefore, according to the second embodiment as described above, the risk factor that becomes the bottleneck is detected, and the investment cost and the risk reduction economy due to the capital investment that is the optimum improvement measure against the detected risk factor. Since the effect is calculated, it is possible to present an effective equipment improvement measure and to make a decision quickly and quantitatively.

(Third embodiment: corresponding to claims 6-8)
Since the power supply risk evaluation system of the power supply facility according to the third embodiment is the same as the configuration of FIG. 5, the description thereof is omitted here.

  In the third embodiment, the difference is that the improvement scenario display means related to the facility improvement measure calculated in the second embodiment is devised, referring to FIG. 7 and FIG. explain.

  The improvement investment effect evaluation means 22bb in the second embodiment selects an equipment improvement measure for avoiding the detected risk factor, and then calculates the investment cost and risk reduction economic effect of the equipment investment as the improvement measure. Although calculated, in the third embodiment, improvement scenario display means is provided for visualizing and displaying the relationship between the investment cost and the risk based on the facility improvement measure.

  In the third embodiment, the equipment improvement measure data stored in the equipment improvement measure data storage unit 48 for the bottleneck risk factor detected by the bottleneck risk factor detection means 22ba by the improvement investment effect evaluation means 22bb. And select a plurality of facility improvement measures in order to avoid risk factors from the facility improvement measure data.

  In addition, the equipment investment cost of each equipment improvement measure (for example, transformer equipment expansion, etc.), the reliability recovery degree and the risk reduction degree for each equipment improvement measure are calculated, and the relationship between the return on investment is visualized by the improvement scenario display means. indicate.

  As the improvement scenario display means, as shown in FIG. 7A, the horizontal axis represents the capital investment cost, and the vertical axis represents the relationship between the improvement degree of power supply reliability (reliability recovery degree). In this graph, in addition to the maximum investment efficiency line with respect to capital investment cost (the line indicating that the ratio of the most improvement effect to investment is the highest), the marginal investment efficiency curve (this is an envelope for judging the quality of investment efficiency) In the case of a facility improvement measure close to a curve, the investment efficiency is considered to be good), and the graph is visualized and displayed on the display unit 3.

  The marginal investment efficiency curve is obtained by complementing a capital investment plan with good investment efficiency with a spline complement or a Bezier curve.

  After the graph is displayed on the display unit 3 as described above, an envelope of the marginal investment efficiency curve is plotted by plotting with x marks at the locations corresponding to the equipment investment cost calculated for each equipment improvement measure and the improvement degree of power supply reliability. It is possible to visually verify whether or not the power supply reliability has been improved in line with the installation of equipment, etc.

  Moreover, as an improvement scenario display means, as shown in FIG.7 (b), it is set as the graph which shows the relationship between capital investment cost on a horizontal axis, and a risk reduction degree on a vertical axis | shaft. In this graph, a maximum investment efficiency line with respect to the capital investment cost and a marginal investment efficiency curve for judging whether the investment efficiency is good or not are set in advance, and the graph is visualized and displayed on the display unit 3. After that, plot the points corresponding to the capital investment cost and risk reduction degree calculated for each equipment improvement measure with x mark, and the risk reduction degree that is near the envelope of the marginal investment efficiency curve or suitable for equipment expansion etc. It is possible to visually verify whether or not.

  Further, as the improvement scenario display means, for example, as shown in FIGS. 8A and 8B, the capital investment cost when the investment effect for the individual equipment improvement is combined and the investment result are improved. This is an example in which the relationship between the improvement degree of power supply reliability (reliability recovery degree) and the risk reduction degree is displayed on the display unit 3 so as to be visualized by a graph.

  Furthermore, instead of the improvement scenario display means, improvement effect quantification means may be provided, and the relationship between the investment efficiency and priority of each capital investment may be determined quantitatively.

  Usually, since the priority order of each capital investment is determined according to the investment efficiency, it is displayed as text data in descending order of priority order, or a numerical value indicating the priority order in the vicinity of each x mark as shown in FIG. Visualize the display, for example.

  In other words, the improvement effect quantification means quantitatively and automatically determines the priority of each capital investment based on the following investment efficiency index, and visualizes and displays the investment effect.

(1) Distance from the marginal investment efficiency curve (the smaller the distance, the higher the priority).
(2) Investment efficiency (priority is given to the slope of the line connecting the origin to each capital investment plan, with a steep slope).
(3) Among the capital investment proposals within a certain threshold distance from the marginal investment efficiency curve, priority is given in order from the lowest investment cost.
(4) Among capital investment plans within a certain threshold distance from the marginal investment efficiency curve, priority is given in descending order of the improvement effect.

  These indicators are appropriately selected by the capital investment decision-maker. For example, when (2) investment efficiency is used as a priority index, the priority order is determined in order from the equipment improvement plan with a large inclination.

  When these are displayed in a composite manner, the display is performed by the improvement scenario display means for improving the composite equipment as shown in FIG. This is an evaluation result of the improvement of the complex equipment plotted with the arrow indicating the investment efficiency superimposed in order from the steep one.

  Therefore, according to the third embodiment, it is possible to compare and examine the scenario for equipment improvement by visualizing the economic effect of reducing the risk for investment for each equipment investment plan. It is also possible to predict the effects of complex equipment improvements and evaluate them by visualization. Furthermore, it becomes easy to determine the priority order of the capital investment, and the reliability for the equipment installer can be improved.

  In addition, the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the scope of the invention.

  DESCRIPTION OF SYMBOLS 1 ... Input part, 2 ... Risk evaluation process part, 3 ... Display part, 4 ... Database, 21 ... Unit risk evaluation part, 22 ... System risk evaluation part, 23 ... Scenario risk evaluation part, 21a ... Risk model estimation means, 21b ... risk evaluation prediction means, 22a ... system connection configuration display / editing means, 22b, 22b '... system risk calculation means, 22ba ... bottleneck risk factor detection means, 22bb ... improvement investment effect evaluation means, 23a ... system connection configuration by scenario Display / editing means, scenario risk calculating means, 41 to 48, storage unit.

Claims (8)

Among the power supply reliability and risk of the power supply system composed of a plurality of power supply facilities, at least in the power supply risk evaluation system of the power supply facility that evaluates the risk,
A unit risk evaluation unit that estimates the risk model of each power supply facility and evaluates the power supply risk of the corresponding power supply facility from each estimated risk model;
A system risk evaluation unit that creates a power supply system having a connection configuration combining the individual power supply facilities, and evaluates the power supply risk of the generated power supply system;
A scenario risk evaluation unit that creates a power supply system with a connection configuration for each scenario according to the operation mode, maintenance work mode, etc., and evaluates the power supply risk of the created power supply system for each scenario. A power supply risk evaluation system for power supply facilities. In the power supply risk evaluation system of the power supply facility according to claim 1,
The unit risk evaluation unit uses risk model estimation means for estimating a risk model according to a predetermined risk prediction model estimation method using data on past accidents, failure histories, component replacement histories, etc. of the target power supply facility, A risk evaluation predicting means for predicting a power supply risk from the present to a specific future year using the past operation history data for the power equipment risk model estimated by the risk model estimating means. Power supply risk assessment system for power supply facilities. In the power supply risk evaluation system for the power supply facility according to claim 1 or claim 2,
The system risk evaluation unit creates and displays a power supply system having a connection configuration in which the power supply facilities are combined based on preset system configuration data, and executes a correction process as necessary. System connection configuration display / edit And a system risk calculation means for calculating a risk of the power supply system using a predetermined failure probability calculation formula based on the risk prediction value of the power supply equipment as a component of the created power supply system A power supply risk evaluation system for power supply facilities, characterized in that In the power supply risk evaluation system for the power supply facility according to claim 1 or 2,
The scenario risk assessment unit creates and displays a power supply system for each scenario of the connection configuration that incorporates the system connection status and power supply / load circuit status according to various operation modes and maintenance modes, and performs correction processing as necessary. Based on the scenario-specific system connection configuration display / editing means and the risk prediction value of the power supply facility that is a component of the created scenario-specific power supply system, using a predetermined failure probability calculation formula, A power supply risk evaluation system for a power supply facility, comprising scenario risk calculation means for calculating a risk of each power supply system. In the power supply risk evaluation system for the power supply facility according to claim 3,
As the system risk calculation means of the system risk evaluation unit, the risk due to failure of each power supply facility is evaluated using unit risk data set in advance, the risk evaluation result of each power supply facility and a preset risk requirement level The bottleneck risk factor detection means for detecting the risk factor that becomes the bottleneck from the comparison with the economic effect of reducing the investment versus risk for the equipment improvement to avoid the risk factor against the detected bottleneck risk factor A power supply risk evaluation system, further comprising an improvement investment effect evaluation means for calculating In the power supply risk evaluation system of the power supply facility according to claim 5,
At least a marginal investment efficiency curve is set on a graph representing the relationship between the capital investment cost and reliability recovery degree and risk reduction degree in advance, and the equipment of the corresponding power supply equipment is provided for each of the equipment improvements for the bottleneck risk factor. A power supply risk evaluation system for a power supply facility, characterized by providing an improved scenario display means for plotting the investment cost and the degree of risk reduction and visualizing and comparing them. In the power supply risk evaluation system of the power supply facility according to claim 5,
At least a marginal investment efficiency curve is set on a graph representing the relationship between the capital investment cost, reliability recovery degree, and risk reduction degree in advance. A power supply risk assessment system for a power supply facility, characterized by providing an improved scenario display means for plotting the capital investment cost and the degree of risk reduction and visualizing and displaying a composite effect. In the power supply risk evaluation system for the power supply facility according to claim 6,
A power supply risk assessment system for a power supply facility, characterized in that an improvement effect quantification means for visualizing and displaying a priority order for each improvement facility is provided according to a predetermined criterion, and a priority order is assigned to each improvement facility. .

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