JP2006101604A - System for predicting electric power quality - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To compute the degree of influence of the occurrence of instantaneous voltage drop in a power system, and to provide electric power customers with information for coping with instantaneous voltage drop. <P>SOLUTION: An electric power quality predicting system includes a means of storing past weather record information, a means of storing information on customers' equipment and information on systems to which the equipment is connected, a means of storing the status of systems, and an electric power quality predicting means. The electric power quality predicting means performs the operation that it predicts power failure and short-time power failure, with respect to each system based on the past weather record information and the system information; it computes electric power quality with respect to each system, electric power customer, or equipment based on the information on the customers' equipment, the information on the systems to which the equipment is connected, and the status of the systems; and it computes the degree of influence of electric power quality, with respect to each electric power customer or equipment. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a power quality prediction system capable of predicting power quality of a power system and providing effective countermeasure information to consumers.

Conventionally, a technique for predicting power quality and providing prediction information to a power consumer has been proposed. For example, in Patent Document 1, based on past lightning strike data, instantaneous voltage drop (instantaneous drop) data, and weather data in order to reduce the burden on grid operators and electric power consumers and make the judgment uniform, A system and method for calculating the instantaneous voltage drop probability of a power system using an inference engine such as a neural network is described.
JP 2003-90887 A

  The above-mentioned conventional technology calculates the probability of high-precision instantaneous voltage drop for the instantaneous voltage drop that is one of the power quality, and notifies the power consumer of the prediction information. The provided prediction information also depends on the past performance, and the countermeasures against the instantaneous voltage drop have been left to the electric power consumer. For this reason, when a customer selects a new installation point, information on the power quality cannot be obtained in advance and used for point selection. In addition, high accuracy could not be obtained when the past performance and the operation status of the power system differed due to new expansion of the power system or system switching. Moreover, the electric power consumer who obtained the prediction information has been able to take only limited measures such as delaying the operation of the factory equipment when the possibility of the instantaneous voltage drop is high. Moreover, countermeasure information considering a plurality of power qualities could not be obtained.

  The present invention has been made in view of such circumstances, and provides an electric power quality prediction system capable of calculating the influence degree together with electric power quality prediction of an electric power system and providing countermeasure information to electric power consumers. For the purpose.

  In order to achieve the above object, an instantaneous voltage drop prediction system according to the present invention includes means for storing weather performance information, means for storing customer facility information and system information to which the facility is connected, and system status. Predicting power outages and short-time power outages for each system based on the means to perform, weather performance information and system information, as well as system information based on customer equipment information, system information to which the equipment is connected, and system status Power quality predicting means for calculating the power quality for each power consumer or for each facility, and for calculating the degree of influence due to the power quality for each power consumer or facility.

  By calculating with the above means, it is possible to predict the state that matches the power system, and it is possible to predict the future state such as newly installed equipment, so that the accuracy of prediction is improved. For example, the consumer can determine the location of the factory by his / her selection in consideration of the power quality at the location.

  Here, the “system” means a power transmission system or a power distribution system, and is the same system if connected by a switch. Further, the degree of influence can be obtained from the degree of power quality and the facility tolerance for the power quality.

  In addition, the power quality prediction system according to the present invention further extracts facility information of customers connected to a system having power quality below a certain level, and calculates measures for each customer based on the degree of influence. A measure calculation notification means for notifying is provided.

  By managing the grid connection state of the facility of the electric power consumer, the influence level of the instantaneous drop of the facility is obtained. In addition, it is good to use the tolerance with respect to the fall of electric power quality, and tolerance time as equipment information.

  The power quality prediction system according to the present invention further includes means for associating a power quality level and a unit price of electricity charges for each system and storing them as electricity rate information, and for each power consumer with reference to the electricity rate information. And an electricity charge calculating means for calculating an electricity charge based on the connected system.

  By changing the electricity rate according to the level of power quality, the power consumer can determine the location of the factory facility by his / her choice after considering these factors. Here, the “electricity unit price” includes data that can be converted into the data, and includes, for example, a discount rate.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to provide the countermeasure information with respect to the fall of electric power quality with respect to an electric power consumer by calculating the influence degree as well as prediction of the electric power quality of an electric power system.

  Embodiments of the present invention will be described below. FIG. 1 is a functional block diagram of a power quality prediction system according to an embodiment of the present invention, a weather information providing system that communicates with this system, and a customer terminal.

  In FIG. 1, the power quality prediction system 1 is connected to a weather information providing system 3 via a dedicated line 2 and is connected to a customer terminal 5 via a communication network 4.

  Here, the power quality prediction system 1 is managed and operated by an electric power company or another service provider. In addition, the weather information providing system 3 is managed and operated by an operator that provides weather information. The customer terminal 5 is a terminal of one or more customers who desire a service provided by a service provider.

  The power quality prediction system 1 includes a transmission / reception unit 11 for transmitting / receiving data via the dedicated line 2, a transmission / reception unit 12 for transmitting / receiving data via the communication network 4, and processing of data received from the transmission / reception unit. The central processing unit 13 is configured to include a storage unit 14 for storing data, and an input unit 15 and a display unit 16 for inputting / outputting data to / from the central processing unit 13.

  Further, the central processing unit 13 is a transmission / reception processing means (function) 131 that exchanges data between the transmission / reception unit 11 and the transmission / reception unit 12, and an input / output processing means that exchanges data with the input unit 15 or the display unit 16. (Function) 132, a weather record input means (function) 133 for inputting a weather record such as a lightning strike inputted via the input unit 15, a customer information input means (function) 134 for inputting customer information, and a transmission / reception unit 11 Meteorological information input means (function) 135 for inputting weather information input via the power, power quality prediction means (function) 136 for predicting power quality degradation, and countermeasure calculation notification for notifying customers of power quality prediction and countermeasures Means (function) 137 are provided. The storage unit 14 includes a customer information database (DB) 141 that stores information related to power customers who are customers, a weather record database (DB) 142 that stores information related to weather results, and a power quality that stores information related to prediction of power quality. It has a prediction database (DB) 143 and a countermeasure file 144 for storing information regarding countermeasures against power quality degradation. The customer terminal 5 includes a transmission / reception unit 51 for transmitting / receiving data via the communication network 4, a central processing unit 53, an input unit 55, and a display unit 56.

[1. Basic data registration]
First, the service provider inputs customer information and weather results from the input unit 15. Customer information input from the input unit 15 is stored in the customer information DB 141 of the storage unit 14.

  FIG. 2 is a data configuration example of the customer information DB. In this figure, information such as a customer ID for customer identification, a customer name associated with the customer ID, and customer equipment is stored, and equipment ID for equipment identification and equipment name associated therewith as information relating to the customer equipment. Information such as a rated voltage, a rated current, an allowable value for power quality degradation, an allowable time for power quality degradation, and the transmission line ID of the transmission line to which the facility is connected is stored.

  FIG. 3 is a data configuration example of the weather record DB 142. In this figure, the lightning location, polarity, intensity, frequency, snowfall, snow cover, wind direction, wind speed, lightning line accident probability, movement pattern (probability), lightning associated with the area as aggregated weather information The individual information is stored, and the individual information includes the date of lightning, the time of lightning, the intensity, the presence or absence of sag, the time of occurrence of sag, the lightning transmission line, the line voltage information, the continuation of sag Information such as time, pre-accident voltage, and voltage drop rate is stored.

[2. Power quality prediction]
When weather information such as lightning is transmitted from the weather information providing system 2 to the power quality prediction system 1, it is received and processed by the transmission / reception unit 11 and the transmission / reception processing unit 131 of the power quality prediction system 1, and is stored by the weather information input unit 135. 14 is stored in a temporary storage area. The power quality prediction unit 136 performs power quality prediction based on the received weather information.

  FIG. 4 is an explanatory diagram of how to predict power quality. In this figure, lightning, strong wind, and snow (hereinafter referred to as lightning) are predicted for each area, and for each system (○○ line, △△ line) where an accident may occur due to lightning. The accident occurrence probability is obtained from the performance data stored in the weather performance DB 142 and the system information DB 147. Thereby, a power failure, a short time power failure, and an instantaneous voltage drop can be predicted. The prediction result is registered in the power quality prediction DB 143.

  FIG. 5 is a data configuration example for the instantaneous voltage drop in the power quality prediction DB 143. In this figure, information such as a lightning prediction area, a lightning transmission line (track) name, an affected range (customer), a connection state with a system, and an influence degree are stored.

  If the area of the lightning forecasting point is A-1, this means that the XX line is exposed to lightning, and the customer AAA with equipment connected to this power transmission line will be greatly affected. If the prediction point is area A-2, the XX line and the △△ line will be exposed to lightning, and the customer AAA with equipment connected to the XX line will be greatly affected, and the connection relationship with the △△ line. This means that a customer BBB with no equipment is subject to minor damage. The data structure is the same for power outages and short-time power outages.

  In addition, in the case of harmonics and voltage fluctuations, it does not occur due to weather conditions, but because other customers' operating conditions have a significant impact, other customer information is used as input at the time of prediction instead of weather conditions. To do.

  FIG. 6 is a data configuration example of the system information DB 147. System identification information such as lightning prediction area and transmission line name, system information associated with this, information on accident occurrence probability (real time), accident occurrence probability (long term), etc. are stored. System information is system status information such as system configuration (system information in a narrow sense), circuit breaker on / off information, and generator operation information. Accident occurrence probability related to power quality such as time outage occurrence probability, outage occurrence probability, harmonic generation probability, voltage fluctuation occurrence probability is stored. In addition, the accident occurrence probability (long-term) stores the accident occurrence probability related to long-term power quality as well as the accident occurrence probability (real-time).

Next, the operation of the power quality prediction unit 136 will be described in detail with reference to FIG.
For example, when predicting an instantaneous voltage drop, first, lightning information is received from the weather information providing system (S101). Next, the power quality prediction means 136 extracts the lightning line lightning probability at the time of lightning in the area from the weather record DB 142 (S102). The range and extent of the instantaneous voltage drop that occurs when a transmission line that is likely to receive lightning during a lightning strike is calculated from the system information by the system information DB 147 (S103). As a result of extracting the range and degree of the instantaneous voltage drop, it is determined whether or not there is a possibility of occurrence of a sag (S104). If there is no possibility of occurrence of a sag, the process ends. If there is a possibility of occurrence of a sag, A movement pattern (movement probability to another area) is extracted (S105). Then, the instantaneous drop probability for each transmission line is calculated by multiplying the lightning transmission line instantaneous drop probability and the movement pattern (movement probability to another area) (S106). Customer information connected to the power transmission line is extracted from the customer information DB 141 (S107). Next, it is determined whether a predetermined time has elapsed from the lightning information reception time (S108). If the predetermined time has not been exceeded, the movement pattern (probability) of the adjacent area is searched from the weather record DB 142, and the area with the highest lightning probability is extracted (S109). Thereafter, the area extracted in step S109 is set as the area, and the process returns to step S102 to repeat the process. If the specified time has been exceeded, the power quality is predicted using the lightning prediction area derived from the above, the lightning transmission line (line) name, the affected area (customer), the connection status with the system, the degree of influence, etc. Register in the prediction DB 143 and end (S110).

After the instantaneous drop prediction is registered in the power product measurement prediction DB 143, the countermeasure calculation notification unit 137 is activated. The countermeasure calculation notification means 137 extracts the instantaneous drop countermeasure according to the customer from the countermeasure file 144 based on the degree of influence. The instantaneous drop prediction result and the instantaneous drop countermeasure are transmitted to the customer terminal 5 by the countermeasure calculation notification means 137.
The same flow is used for power outages and short outages.

  FIG. 9 is a data configuration example of the countermeasure file 144. In this figure, the degree of influence and measures associated therewith are stored. In this figure, when the impact level of the power failure is “Large”, a measure to install a self-generated facility is stored. Similarly, when the impact level of the short-time power failure is “Large”, the uninterruptible power supply (UPS) If the impact of the voltage sag is “Large”, install a voltage sag prevention device. If the effect of voltage fluctuation is “Large”, install a voltage regulator. In the case of “Large”, a countermeasure for providing a self-excited static reactive power compensator (self-excited SVC) is stored. For example, when the effects of the voltage sag and the harmonics are “large”, a combination of a device that can deal with both the voltage sag and harmonics as a device that uses both a voltage sag prevention device and a self-excited converter. May also be stored.

The operation of the measure calculation notification means 137 will be described in detail with reference to FIG.
The customer facility information (installation ID, facility name, rated voltage, rated current, permissible value for power quality degradation, permissible time for power quality degradation, transmission line ID) extracted in step S106 of the processing of the power quality prediction unit 136 is temporarily stored. Save to the area (S201). The average value is calculated by extracting the power outage, short-time power outage, voltage sag duration and voltage drop rate of the area from the weather record DB 142 (S202). Predetermined values based on the allowable value for the power quality decrease stored in the temporary area, the allowable time for the power quality decrease and the power outage, short time power outage, average voltage drop rate and average voltage sag duration extracted in step S202 above. It is determined whether there is a decrease in power quality that exceeds the value, and the degree of influence is calculated (S203). Based on the degree of influence, countermeasure data is extracted from the countermeasure file 144 (S204). The customer can install the countermeasure device in advance by calculating the average value of the weather results for a certain period in advance and providing the countermeasure.
Further, the power quality reduction probability and the countermeasure are transmitted to the customer's mail address extracted in step S106 of the processing of the power quality prediction means 136 of FIG. 7 by real time prediction (S205).
As a result, the customer can determine whether or not the apparatus needs to be operated, and can minimize the operating cost of the apparatus.

  Further, according to the present embodiment, the accident probability (real time) is predicted by the power quality prediction means 136 based on the real time weather information emitted from the weather information system 3, and the weather stored in the weather performance DB 142 is stored. A long-term accident occurrence probability can be predicted based on the record and system information DB 147 and provided to the customer. In particular, the countermeasure can be presented to the customer according to the type of accident that is predicted to occur, in addition to presenting the countermeasure to the customer based on the degree of influence when a voltage sag occurs.

  The probability of occurrence of harmonics and voltage fluctuations is determined by letting the customer input the limit values of harmonics and voltage fluctuations based on the customer's equipment specifications in advance and storing the information in the customer information DB 141. The probability of occurrence exceeding the limit value is provided to the customer. Note that the predicted value itself such as harmonics may be provided instead of the occurrence probability.

  Furthermore, according to the present embodiment, it is possible to perform not only real-time prediction but also long-term prediction and prediction before location for each customer by system information for each lightning area. As a result, real-time countermeasures against real-time accidents include more real-time countermeasures such as reducing the operating time of uninterruptible power supplies and private facilities, reducing operating costs, and preventing product quality variations due to voltage fluctuations. As measures against long-term accidents, it is possible to provide information for determining the installation of an uninterruptible power supply or a self-generated facility.

Next, a second embodiment will be described.
In the first embodiment, the power quality is predicted and the countermeasure is notified to the customer. However, in this embodiment, the power quality is predicted and the electricity charge is discounted according to the frequency. .

  FIG. 10 is a functional block diagram of the present embodiment. The difference from FIG. 1 is that an electricity charge DB 145 for storing information related to electricity charges is added to the storage unit 14, and the electricity charge calculating means for calculating the electricity charge based on the frequency of occurrence of instantaneous drops in the central processing unit 13. (Function) 138 is added.

  FIG. 11 shows a configuration example in the case of an instantaneous voltage drop in the electricity rate DB 145. In this figure, the frequency of the instantaneous drop and the discount rate of the electricity charge associated therewith are stored. Here, if the instantaneous drop occurs twice or more in one year, the electric charge is discounted by 10% from the normal electricity charge. One time represents a 5% discount on the electricity bill.

  The electricity bill DB 145 is referred to according to the frequency at which the voltage drop occurs by the electricity bill calculating means 138, and the electricity bill is discounted. The electricity rate DB 145 may store the unit price of the electricity rate instead of the discount rate.

  According to the present embodiment, it is possible to supply electric power at an appropriate price by reducing the price of electricity for consumers according to the frequency of instantaneous voltage drop. Note that it is possible to provide performance data in which a voltage drop occurs when a customer constructs equipment in an area.

  In addition, this invention is not limited to embodiment mentioned above, In the range which does not deviate from the summary, it can implement in various deformation | transformation. For example, when an accident such as an instantaneous drop or a short-time power failure is predicted, the power quality may be maintained by charging the customer and switching the system. In this case, using long-term forecasting, a service that charges the customer by adding system equipment and a service that charges the customer by switching the system only when an instantaneous drop is predicted in real time It is possible. By taking this system measure, when selling an industrial park, etc., it is possible to increase the added value of the industrial park, etc., and at the same time, it is possible to implement more efficient measures than taking measures for each individual factory.

  Also, when separating the uninterruptible power supply from the self-generated equipment according to the degree of influence, if only a sag is expected, it should be an uninterruptible power supply. Whether or not the uninterruptible power supply can be handled is determined based on the duration and the specifications of the uninterruptible power supply, and if the uninterruptible power supply cannot handle it, the countermeasure information for the self-generated equipment may be required and the countermeasure information may be provided to the customer .

1 is a functional block diagram of a power quality prediction system according to a first embodiment of the present invention. It is a structural example of customer DB of FIG. It is a structural example of the weather performance DB of FIG. It is explanatory drawing of the method of the instantaneous drop prediction by embodiment of this invention. It is a structural example of electric power quality prediction DB of FIG. It is a structural example of the system | strain information DB of FIG. It is a flowchart which shows operation | movement of the electric power quality prediction means of FIG. It is a flowchart which shows operation | movement of the countermeasure calculation notification means of FIG. It is an example of a structure of the countermeasure file of FIG. It is a functional block diagram of the power quality prediction system concerning the 2nd Embodiment of this invention. It is an example of a structure of electricity bill DB of FIG.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Power quality prediction system 2 Dedicated line 3 Weather information provision system 4 Communication network 5 Customer terminal 11 12 51 Transmission / reception part 13 Central processing part 14 Storage part 15 55 Input part 16 56 Display part 51 Transmission / reception part 53 Central processing part 131 Transmission / reception Processing means 132 Input / output processing means 133 Weather result input means 134 Customer information input means 135 Weather information input means 136 Electric power quality prediction means 137 Countermeasure calculation notification means 138 Electricity charge calculation means 139 Electricity purchase amount calculation means 141 Customer information database 142 Weather results database 143 Power quality prediction database 144 Countermeasure file 145 Electricity rate database 147 System information database

Claims (6)

Means for storing weather performance information;
Means for storing customer equipment information and system information to which the equipment is connected;
Means for storing system status;
Power outages and short-time power outages are predicted for each system based on the actual weather information and the system information, and the system is based on the customer's equipment information, system information to which the equipment is connected, and the system status. Power quality predicting means for calculating the power quality for each power consumer or facility, and further calculating the degree of influence by the power quality for each power consumer or facility;
A power quality prediction system comprising:   It is characterized by comprising measure calculation notification means for extracting facility information of customers connected to a system having power quality of a certain level or less, calculating measures for each customer based on the degree of influence, and notifying them. The power quality prediction system according to claim 1.   The power quality prediction system according to claim 1, wherein the power quality level and the degree of influence when a facility is installed are predicted for a point in an arbitrary power system.   4. The power quality prediction system according to claim 2, wherein the facility information is a tolerance and / or a tolerance time for a power quality degradation of the facility. Means for associating and storing the power quality level and the electricity unit price for each system as electricity rate information;
An electricity rate calculating means for calculating the electricity rate based on the system to which the facility is connected for each power consumer with reference to the electricity rate information;
The power quality prediction system according to any one of claims 1 to 4, further comprising:   6. The power quality prediction system according to claim 1, wherein the power quality is obtained by quantifying any element or a plurality of elements of a power failure, a short-time power failure, an instantaneous voltage drop, a harmonic, and a voltage fluctuation. The power quality prediction system characterized by being calculated.

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