KR102512790B1 - System and Method for estimating power demand over the long term, Computer readable storage medium - Google Patents

Abstract

A long-term power demand forecasting system capable of determining the time required for substation facilities by calculating the simultaneous maximum load for each distribution line, predicting the amount of new supply to a large load and future demand increase, and predicting long-term power demand based on this, is disclosed. . The long-term power demand forecasting system includes an input unit for receiving basic data for demand forecasting, a determination unit for determining whether it is a previously reviewed old area or a new area based on the basic data, and a result of the determination. Determining the size of the supply load being supplied, generating power demand forecasting information that predicts power demand according to the determined size of the supply load and the size of the general load, and using the power demand forecasting information to expand power facilities It is characterized in that it includes a calculation unit for generating facility expansion required time information indicating the required time.

Description

System and method for estimating power demand over the long term, computer readable storage medium storing the method {System and Method for estimating power demand over the long term, computer readable storage medium}

The present invention relates to a technology for predicting power demand, and more particularly, by calculating the simultaneous maximum load for each distribution line, predicting the actual supply amount and future demand increase, and predicting long-term power demand based on this, and determining the time when substation facilities are needed. It relates to a long-term power demand forecasting system and method for determining.

In order to supply power to the right place at the right time, there must be a supply margin in the substation facility. To do so, it is necessary to predict the load demand and establish a new/extension plan for transformers or substations in advance. Two factors are used to forecast demand.

First, the load demand is predicted by considering the load increase rate calculated by dividing the country into 52 regions based on the load performance by substation. Second, after estimating the total load demand according to the area and population for large-scale housing districts or industrial complex sites, the load demand is predicted by assuming that the load increases year by year according to the ratio according to the standard. Demand forecasting is done by adding the demand from the first method and the second method.

However, in the first method, in reality, the load increase rate differs depending on the regional characteristics such as downtown, industrial area, and rural area, but this difference is simply divided into 52 areas nationwide and the substation load belonging to the area is applied as a lump sum increase rate This causes a gap in demand forecasting.

In addition, the second method assumes that large-scale residential districts or industrial complexes supply loads at a certain rate at a certain time, but in reality, electricity demand does not increase by year as suggested above. In addition, the exact amount of load that is actually being supplied to the housing complex or industrial complex is not properly grasped. Even if the actual demand load is smaller than the initially expected load, it does not reflect these matters and considers it as an untransmitted load and calculates it as a load that must be supplied someday.

When establishing a new load supply plan, it is established using the remaining capacity after excluding the maximum load performance and untransmitted load from the supplyable capacity of the transformer. If there is insufficient supply, a new transformer or substation is built. The supply margin is calculated by subtracting the estimated demand value considering the maximum load volume, future load increase rate, and untransmitted load from the supply capacity of the transformer.

However, due to such inaccurate demand forecasting, it is not possible to construct transformers or substations, which are power supply facilities, in a timely manner. In the case of late construction, over-investment occurs because new loads must be supplied by drawing out additional distribution lines from substations in other areas that are far away from each other in order to supply new loads. ), and an opportunity to reduce financial costs is missed by delaying the construction period.

There are two reasons why this problem occurs. The first is that it is not possible to determine how much load has been supplied compared to the total demand for large-scale housing sites or industrial complexes.

1. Korean Patent Publication No. 10-2019-0051243

The present invention is proposed to solve the problems caused by the above background art, by calculating the simultaneous maximum load for each distribution line, predicting the actual supply amount and future demand increase, and predicting long-term power demand based on this, and the need for substation facilities. Its purpose is to provide a system and method for predicting long-term power demand that can determine the timing.

In addition, another object of the present invention is to provide a long-term power demand forecasting system and method capable of increasing the efficiency of facilities by increasing the accuracy of distribution load demand prediction and calculating the necessary time for new/extended power supply facilities.

In order to achieve the object presented above, the present invention calculates the simultaneous maximum load for each distribution line, predicts the actual supply amount and future demand increase, predicts long-term power demand based on this, and determines the time of need for substation facilities. Provides a long-term power demand forecasting system.

The long-term power demand prediction system,

an input unit that receives basic data for demand forecasting;

a judging unit that determines whether it is a previously reviewed old area or a new area based on the basic data; and

According to the result of the determination, the size of the supply load (Load _00-k ) is determined, and the demand for power is predicted according to the size of the load supply (Load _00-k ) and the size of the general load. It is characterized by including; a calculation unit for generating information and generating facility expansion required time information indicating a time when power facilities need to be expanded using the power demand prediction information.

At this time, the basic data is the name of a large-scale load indicating the name of a house or industrial complex to be stored in the database, the final predicted demand indicating the predicted final power demand of a new load that is preset, the name of a supply substation indicating a power plant supplying power to consumers, A transformer number indicating a transformer to which a distribution line supplying power to the customer is connected, a distribution line name indicating a distribution line supplying power to the customer, a load ratio indicating the ratio of power load supplied to a large load by a specific distribution line, and a supply date indicating when the specific distribution line was supplied with a specific load ratio.

In addition, the determining unit compares the basic data with stored data stored in the database, and acquires measured external data when the basic data does not match the stored data according to a result of the comparison.

In addition, the external data is characterized in that it includes a corrected distribution line load obtained through a Substation Operation Result Management System (SOMAS) system, and the number of transformers and transformer capacity obtained through a system protection system.

로 정의되며, 상기 해당 날짜의 부하비율은 미리 설정되는 것을 특징으로 한다.In addition, the load of the modified distribution line is Equation

It is defined as, and the load ratio of the corresponding day is characterized in that it is set in advance.

In addition, when there is a change in the capacity of the transformer, it is characterized in that it is obtained by searching for the capacity of each transformer of the transformer corresponding to the name of the supply substation.

In addition, the determining unit outputs the name of the distribution line, the last data extraction date, and the final load ratio of the distribution line among the stored data when the basic data matches the stored data according to the result of the comparison. to be

(여기서, 00은 대규모 부하명칭, k는 년도, A,B,C는 배전선로 부하 크기, a,b,c는 배전선로 부하중 에서 상기 00 부하에 공급하는 부하 부하비율(0〈a,b,c,≤100 사이의 실수), i는 k년의 연간시간(1 ~ 8760의 자연수) )로 정의되는 것을 특징으로 한다.In addition, the size of the supply load (Load _00-k ) is expressed by the equation

(Where, 00 is the name of the large-scale load, k is the year, A, B, C are the distribution line load size, a, b, c are the load supplied to the 00 load out of the distribution line load Load ratio (0 < a, b , c, a real number between ≤ 100), i is characterized in that it is defined as an annual time of k years (a natural number from 1 to 8760).

In addition, the power demand forecast information is determined when the load size (Load _00-k ) exceeds the final demand forecast value according to a comparison result between the supply load size (Load _00-k ) and a preset final demand forecast value. It is characterized in that the size of the supply load (Load _00-k ) is calculated as a final demand forecast value.

In addition, the power demand forecast information is k if the load size (Load _00-k ) is less than or equal to the final demand forecast value according to a comparison result between the supply load size (Load _00-k) and a preset final demand forecast value. After the load supplied until year is calculated as the size of the supply load (Load _00-k ), the demand forecast after year k+1 is calculated by applying the large-scale load supply ratio for each year determined according to the progress of the preset year, or It is characterized in that it is calculated by recalculating the expected load supply for each future year using the performance-based curve fitting method.

In addition, the large-scale load supply ratio by year is calculated by calculating the average value of the selected data within the upper 90% and the lower 90% or more of the performance values for the supply performance of various large-scale loads stored in the database 140 by year. It is characterized in that the ratio from the year of supply to the completion of supply is converted to 100%.

In addition, the preset large-scale load supply ratio for each year is characterized by periodically updating and managing the above-mentioned large-scale load supply ratio for each year with a recalculated value.

로 정의되며, 상기 일반 부하의 크기를 이용하여 일반 부하 증가율이 산출되는 것을 특징으로 한다.In addition, the size of the general load is expressed by the equation

It is defined as, characterized in that the general load increase rate is calculated using the size of the general load.

(여기서, a₀는 0년째의 일반 부하의 크기이고, a₃는 3년째의 일반 부하의 크기이고, a₀가 0이면

이며, len(a₃)는 a₃의 자리수이다)으로 정의되는 것을 특징으로 한다.In addition, the general load increase rate is expressed by the equation

(Where a ₀ is the size of the general load in the 0th year, a ₃ is the size of the general load in the 3rd year, and if a ₀ is 0,

, and len(a ₃ ) is the number of digits of a ₃ ).

In addition, the long-term power demand prediction system compares the power demand prediction information with the maximum capacity of the transformer of the substation, and outputs notification information indicating the time of new establishment of the substation, the time of expansion of the transformer, and the time of capacity change. It is characterized in that it includes; part.

On the other hand, another embodiment of the present invention, (a) receiving basic data for the input unit to predict demand; (b) determining, by a judging unit, whether it is a previously reviewed old area or a new area based on the basic data; (c) The calculation unit determines the size of the load being supplied (Load _00-k ) according to the result of the determination, and determines the demand for power according to the size of the determined load (Load _00-k ) and the general load. generating power demand prediction information to predict; and (d) generating, by the calculation unit, facility expansion time information indicating a time when power facilities need to be expanded by using the power demand prediction information. do.

In the step (b), the determining unit compares the basic data with the stored data stored in the database and obtains measured external data if the basic data does not match the stored data according to the result of the comparison. It is characterized in that it comprises a; step.

In addition, the external data is characterized in that it includes a corrected distribution line load obtained through a Substation Operation Result Management System (SOMAS) system, and the number of transformers and transformer capacity obtained through a system protection system.

In addition, the long-term power demand prediction method compares the power demand prediction information with the maximum capacity of the transformer, and outputs notification information indicating the time of new construction of the substation, the time of expansion of the transformer, and the time of capacity change. It is characterized in that it includes; outputting to ).

On the other hand, another embodiment of the present invention provides a computer-readable storage medium storing a program code for executing the method for predicting long-term power demand described above.

According to the present invention, by determining the pre-supply amount of a large load (residential district, industrial complex) and predicting the amount of additional power supply in the future, the amount of untransmitted load can be estimated, so that the supply margin of the transformer can be accurately known.

In addition, another effect of the present invention is that it is possible to improve the accuracy of load demand forecasting at a future point in time by calculating the load increase rate based on performance by calculating the load increase rate for each substation.

In addition, as another effect of the present invention, it is possible to stably supply power by accurately predicting the necessary timing of substation facilities through this.

1 is a block diagram of a system for predicting long-term power demand according to an embodiment of the present invention.
FIG. 2 is a conceptual diagram illustrating that the calculation unit shown in FIG. 1 uses input data and external data.
FIG. 3 is a flowchart showing a process executed in the input unit and determination unit shown in FIG. 1 .
FIG. 4 is a flowchart illustrating a process executed by an extraction unit that obtains data from an external site based on information transferred from the determination unit shown in FIG. 1 .
FIG. 5 is a flowchart illustrating a process of predicting power demand and determining an optimal power facility expansion time using information stored in a database in the calculation unit shown in FIG. 1 .
FIG. 6 is a flowchart illustrating a process of estimating the previously supplied large-scale load and distributing the untransmitted load by year shown in FIG. 5 .
FIG. 7 is a flowchart illustrating a process of calculating a large-scale load supply ratio for each year in the calculation unit shown in FIG. 1 .
FIG. 8 is a flowchart illustrating a process of calculating an increase rate of a general load shown in FIG. 5 .
FIG. 9 is a flow chart showing a process of determining the construction timing for the long-term demand forecasting and substation facilities shown in FIG. 5 .
10 is an example of an input screen according to an embodiment of the present invention.
11 is a result of extracting the supply performance of a large load according to an embodiment of the present invention into an Excel file.

Since the present invention can make various changes and have various embodiments, specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents, or substitutes included in the spirit and scope of the present invention.

In describing each figure, like reference numbers are used for like elements. Terms such as first and second may be used to describe various components, but the components should not be limited by the terms. These terms are only used for the purpose of distinguishing one component from another.

For example, a first element may be termed a second element, and similarly, a second element may be termed a first element, without departing from the scope of the present invention. The term "and/or" includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs.

Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in this application, it should not be interpreted in an ideal or excessively formal meaning. Should not be.

Hereinafter, a system and method for predicting long-term power demand according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of a long-term power demand prediction system 100 according to an embodiment of the present invention. Referring to FIG. 1 , the long-term power demand prediction system 100 includes an input unit 110, a determination unit 120, an extraction unit 130, a database 140, a calculation unit 150, an output unit 160, and the like. can be configured to include

The input unit 110 performs a function of receiving basic data for demand forecasting. Accordingly, the input unit 110 may be a keyboard, a microphone, a universal serial bus (USB), a CD-ROM drive, a DVD drive, and the like. Of course, the input unit 110 may be connected to a power grid (not shown) to receive data from a cloud server or a single server. To this end, the input unit 110 may include a communication modem, a processor, and the like.

The determination unit 120 serves to review whether it is a previously reviewed area or a new area based on input basic data.

The extraction unit 130 performs a function of extracting and bringing data from an external system when it is determined that new information is needed.

The database 140 performs a function of storing extracted new data, previously reviewed existing data, and the like. Of course, the database 140 may be configured within the system or may be configured as a separate database server.

The calculation unit 150 performs a function of generating power demand prediction information for predicting power demand according to the size of the determined load and/or facility expansion required time information indicating a time when power facilities need to be expanded. In other words, it determines the size of the existing load among large-scale loads, predicts future demand, and calculates the necessary time for facility expansion.

The output unit 160 performs a function of notifying the review result as notification information. Notification information may be a combination of text, voice, and graphics. To this end, the output unit 160 may include a sound system, a display, and the like. The display may be a liquid crystal display (LCD), a light emitting diode (LED) display, a plasma display panel (PDP), an organic LED (OLED) display, a touch screen, a cathode ray tube (CRT), a flexible display, or the like. In the case of a touch screen, it may be used as an input means.

1, the determination unit 120, the extraction unit 130, and the calculation unit 150 refer to units that process at least one function or operation, and may be implemented in software and/or hardware. In hardware implementation, ASIC (application specific integrated circuit), DSP (digital signal processing), PLD (programmable logic device), FPGA (field programmable gate array), processor, microprocessor, other It may be implemented as an electronic unit or a combination thereof.

In software implementation, software component components (elements), object-oriented software component components, class component components and task component components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, data , databases, data structures, tables, arrays, and variables. Software, data, etc. may be stored in memory and executed by a processor. The memory or processor may employ various means well known to those skilled in the art.

In particular, the memory is a flash memory type, a hard disk type, a multimedia card micro type, and a card type memory (for example, SD (Secure Digital) or XD (eXtreme) digital memory, etc.), RAM (Random Access Memory, RAM), SRAM (Static Random Access Memory), ROM (Read Only Memory, ROM), EEPROM (Electrically Erasable Programmable Read Only Memory), PROM (Programmable Read Only Memory), It may include at least one type of storage medium among a magnetic memory, a magnetic disk, and an optical disk.

Database 140 is also implemented in this memory.

FIG. 2 is a conceptual diagram showing that the calculation unit shown in FIG. 1 uses input data (ie input values) and external data. Referring to FIG. 2 , the calculation unit 150 checks the input data obtained through the input unit 110, calculates power demand prediction information, and generates facility expansion required time information based on the power demand prediction information. To this end, the input data may include a large-scale load name, a final predicted demand value set in advance, a supply substation name, a transformer number, a distribution line name, a load ratio, and a supply date. A unique identification number is given to each large-scale load name, supply substation name, transformer number, distribution line name, etc. for identification.

In general, the load ratios of housing complexes and industrial complexes are as follows. For reference, the unit is "%".

power demand 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years 9 years 10 years Over 100 MW 15 20 30 40 50 60 70 80 90 100 100 MW or less 15 25 40 50 60 80 90 100 30 ㎿ or less 20 55 80 100

power demand 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years 9 years 10 years 11 years Over 100 MW 15 25 30 35 45 55 65 75 80 90 100 100 MW or less 15 20 25 30 40 50 60 80 100

The calculation unit 150 acquires external data corresponding to newly added data among input data. In other words, the newly input input data is compared with the existing data stored in the database 140, and if not stored in the database 140, the external data 220 is requested. Acquisition of external data is performed through the SOMAS system and/or the power system protection system. The SOMAS (Substation Operation Result Management System) system is a substation operation performance management system, and the load status of the main transformer, transmission line, distribution line, etc. for each substation nationwide It is a system that collects circuit breaker status information from the power system Supervisory Control and Data System (SCADA) and provides load information and operation information of lines related to substations scattered across the country.

In particular, the load (P) of the distribution line is calculated using the current value measured by the CT (ammeter) installed on the distribution line drawn out of the transformer substation and the voltage measured by the PT (voltmeter) installed on the bus line from which the distribution line is drawn. If this is expressed as a mathematical formula, it is as follows.

Here, V is the voltage and I is the current.

Load information such as distribution line load, transformer load, and substation load is stored in the SOMAS system on an hourly basis.

The power system protection system performs functions of protecting, monitoring, and controlling generators, transformers, motors, transmission lines, busbars and distribution lines, capacitors, and the like. In the present invention, in particular, a function of obtaining information such as the number of transformers and the capacity of transformers is performed.

In the SOMAS system, the load of the distribution line desired by the reviewer is called. The process of searching and extracting loads from SOMAS every time causes excessive traffic to the SOMAS server. Therefore, in one embodiment of the present invention, when necessary information is initially input, SOMAS crawls and searches for necessary load information and stores it in the server of the prediction program. After that, the information stored in the server is used, and SOMAS is configured to crawl and retrieve information only when there is additional necessary information.

By using this method, the traffic of the external server is reduced and the data acquisition speed required for calculation is increased. In addition, as the frequency of use increases, the amount of valid data stored in the server increases, so there is an advantage that the time required for data extraction gradually decreases.

FIG. 3 is a flowchart showing processes executed by the input unit 110 and the determination unit 120 shown in FIG. 1 . Referring to FIG. 3 , when a land (industrial complex) name, which is a large-scale load name, is input among the input data input through the input unit 110, the determination unit 120 determines that the input large-scale load name is input into the database 140 and stored. It is checked whether it is a name (steps S310 and S320).

In step S320, as a result of checking, if the name is not stored in the database 140, external data is received and “DATA SCRAP1” is generated (steps S340 and S371). External data contains items of basic data. Looking at the external data:

- Housing site (industrial complex) name: large-scale load name to be stored as a new load in the database (140)

- Final predicted demand: The predicted amount of final power demand of the new load in the power supply plan

- Supply period: The year in which electricity is to be supplied to customers

- Supply substation name: Substation name that supplies electricity to customers

- Transformer number: The number of the transformer to which the distribution line that supplies electricity to consumers is connected

- Name of distribution line: distribution line that supplies electricity to consumers

- Load ratio: Since a specific distribution line can supply other nearby loads in addition to the housing district (industrial complex), the ratio supplied to the housing district (industrial complex)

- Supply date: when a specific distribution line was supplied with a specific load ratio

The dual supply date may include the year in which electricity is to begin supplying the customer.

In contrast, in step S320, as a result of the check, if the large load name is the name stored in the database 140, the stored data of the database 140 is output to check whether the data of the latest date is required (steps S330 and S350). In other words, if it has been reviewed before, the name of the distribution line stored in the database, the date of the last data extraction, and the final load ratio of the distribution line are output. As for the final load ratio of the distribution line, only the last changed information is provided because the ratio supplied by a specific distribution line may be changed in the middle. Also, the data extraction date is the last date stored in the database.

In step S350, as a result of the confirmation, if the data of the latest date is not needed, power demand prediction information for predicting power demand is generated using the stored data in the database 140, and power facilities are used using the power demand prediction information. Data calculation is performed to generate facility expansion required time information indicating the time when the expansion is required (step S351). In other words, if it can be used as it is with only the existing review data, all information of the housing district (industrial complex) to be reviewed stored in the DATABASE 140 is called and the data is passed to the calculation unit 150.

In contrast, in step S350, as a result of the confirmation, if data of the latest date is required and other information is additionally required, the process proceeds to step S340 (step S360).

In step S360, if additional information is not required, it is checked whether there is a change in capacity and expansion of transformers in the supply substation (step S370). In the case of wanting to update only the date to the latest date among the existing review data, information on the substation and distribution line and load ratio are provided to the extraction unit 130 . To do this, create "DATA SCRAP1". Substation information is also provided when the capacity of a supply substation transformer is changed or an extension of a transformer occurs. To this end, "DATA SCRAP2" is generated (step S371).

In the case of adding a new distribution line among the existing review data, the remaining information except for the name of the housing site (industrial complex), the final load expected to be supplied, and the supply start time are input as new loads and the information is passed to the extraction unit 130. Therefore, "DATA SCRAP1" is generated (step S371).

FIG. 4 is a flowchart illustrating a process executed by the extraction unit 130 acquiring data from an external site based on the information transferred from the determination unit 120 shown in FIG. 1 . Referring to FIG. 4, when "DATA SCRAP1" is generated in FIG. 3, it is checked whether the distribution line is the distribution line input by the reviewer (step S420).

As a result of the check, if it is the distribution line input by the reviewer, it is necessary to extract additional data on the load, and the name of the substation and distribution line input from the determination unit 120 is searched in the SOMAS system and divided by time period from the input date to the present. Scrap the load and get it. The load of the modified wiring line calculated in consideration of the received load and load ratio for each time period is stored in the database 140 (steps S431, S433, and S450). The modifier is defined as:

For example, in the case of distribution line A, if the load ratio is 20[%] until May 1st and 2nd and the load ratio is 50[%] until May 3rd and 4th, distribution line A is stored in the database 140. (D/L:Distribution Line) The value where the load is stored is as follows.

A
D/L 5/1 5/2 5/3 5/4 date 20 30 20 … 30 20 40 … 30 40 40 … 60 60 40 … Measured load by time period 4 6 4 … 6 4 8 … 15 20 20 30 30 20 … Modification load by time period

On the other hand, in step S420, as a result of checking, if it is not the distribution line input by the reviewer, the measured transformer load is stored in the database 140 (steps S432 and S450). " is generated, the searched transformer capacity is obtained, and whether it is the same as the existing information is checked (steps S440, S441, and S443).

In step S443, as a result of checking, if the transformer capacity is not the same as the existing information, the searched transformer capacity is stored in the database 140 (step S450). In other words, when a new load is input or when a transformer capacity is changed or expanded among existing loads, the capacity of each transformer corresponding to the input substation is searched in the system protection system. In the case of a new load, it is immediately stored in DATABASE (140), and in the case of existing data, only changed information is saved.

Data scraped from an external system (not shown) (i.e. data) and data directly input by a reviewer are stored in the database 140, and the stored information is as follows.

Data received from the input unit 110 and the extraction unit 130 Data provided by the calculation department Large Load Designation and Final Forecast Demand
supply start time
Supply substation name
transformer number
transformer capacity
Name of load supply distribution line and connected transformer number
Distribution Line Load Ratio and Period
Distribution line load and corrected distribution line load by time period
Load per transformer per time period
Last extraction date


supply start time
Load increase rate by substation
Large Load Yearly Performance
Untransmitted large loads
Substation long-term expected load

FIG. 5 is a flowchart illustrating a process of predicting power demand and determining an optimal power facility expansion time by using information stored in the database 140 in the calculation unit 150 shown in FIG. 1 . Referring to FIG. 5 , a pre-supplied large-scale load is estimated using information stored in the database 140 (step S520). In other words, in order to understand the annual supply of large-scale loads (residential districts, industrial complexes), the maximum load is obtained by adding the hourly corrected distribution line load values of all distribution lines supplying large-scale loads from March of the previous year to February of this year. . Since the winter period is considered until February, the load supplied for one year is regarded as one year from March of the previous year to February of this year. For example, the distribution lines supplying the oo area are A, B, and C, and each load If the ratios are a%, b% c%, and the loads at time i are A, B, and C, the size of the supply load supplied to the oo region by year k (Load _00-k ) is calculated as follows: It can be.

Here, 00 is the name of the large-scale load, k is the year, A, B, C are the distribution line load size, and a, b, c are the load ratios supplied to the 00 load among the distribution line loads (0 < a, b, c, real number between ≤100), i is the annual time of k years (a natural number from 1 to 8760).

Based on the size of the supplied load (Load _00-k ) calculated above, the yearly distribution of the untransmitted load is calculated, and the existing load increase rate is calculated (steps S530 and S540).

When the yearly distribution of the untransmitted load and the load increase rate are calculated, a long-term demand forecast is calculated based on this and stored in the database 140 (steps S550 and S551).

As the long-term demand forecast is calculated, the substation expansion timing is reviewed using this (step S560).

FIG. 6 is a flowchart illustrating a process of estimating previously supplied large-scale loads (step S520) and distributing untransmitted loads by year (step S530) shown in FIG. 5 . Referring to FIG. 6 , as described above, when the previously supplied large-scale load performance is calculated, the expected load for each year of the large-scale load can be obtained (step S610).

It is checked whether the size of the supply load is greater than or equal to a preset reference value (step S620). The reference value is the final demand forecast value X 5%.

As a result of the check, in step S620, if the size of the supply load is smaller than the preset reference value, assuming that it is a temporary load and that the supply has not started, the supply timing is delayed by one year from the current time, and the large-scale load supply ratio by year A long-term demand forecast value is determined by calculating the expected supply load for each year by applying (steps S640, S641, S643, and S645).

On the other hand, as a result of the confirmation, in step S620, it is assumed that load supply has started when the size of the supply load is 5% or more of the final demand forecast (step S630).

In step S650, if 3 years have not elapsed since the start of supply, the expected supply load for each year is calculated by applying the previously entered large-scale load supply ratio for each year (step S651).

In contrast, in step S650, when more than three years have elapsed since the start of large-scale load supply, the expected load supply ratio for each future year is recalculated using the performance-based curve fitting method based on the performance for the last three years (steps S652 and S653). The performance-based curve fitting method means calculating a mathematical straight line or curve representing the data using actual data.

In other words, if the supply load performance for many years is accumulated, performance curve fitting is applied using a method such as linear regression analysis based on the performance. Through this performance curve fitting, a polynomial function is created to estimate load supply for future years. Years are incremented until the size of the load supply equals the final predicted demand. The load supply at the time when the load supply becomes greater than the final demand is the final demand value.

The load demand in year n can be defined as:

7 is a flowchart illustrating a process of calculating a large-scale load supply ratio for each year in the calculation unit 150 shown in FIG. 1 . Referring to FIG. 7, data on the supply performance ratio by year of large-scale loads such as large-scale residential districts and industrial complexes stored in DATABase (140) is obtained, and the same year has elapsed since the start of supplying the large-scale load. It is classified as data, and data within the upper 90% and lower 90% or more of the performance ratio value for each year is selected (step S730). Of course, it is also possible to additionally classify and manage in detail by receiving geographical conditions and load characteristics of large-scale loads.

Thereafter, after calculating the average value of the data selected for each year above, the "large-scale load supply ratio by year" is recalculated by converting the period from the year of supply to the completion of supply to 100% (steps S740 and S750).

In the case of the initial stage where there is not much supply performance by year, use the “large-scale load supply ratio by year” according to the 『Notification of Revision Results of Load Growth Trends in Housing and Industrial Complexes』 enacted in 2013.

8 is a flowchart showing a process of calculating the increase rate of the general load shown in FIG. 5 (step S540). Referring to FIG. 8 , when the size of a pre-supplied large-scale load is determined, the long-term demand for the general load can be predicted by calculating the increase rate of the general load. The maximum value of the sum of the load performance of each transformer from March to February of the following year of the substation supplying the large-capacity customer is the maximum load performance of the substation in that year. A value obtained by subtracting the previously supplied large-scale load performance from the maximum load performance becomes the size of the general load (steps S801, S810, S820, and S830). The magnitude of the general load is expressed as follows.

Thereafter, it is checked whether the performance of 3 years ago is “0” (step S840). In step S840, if the result of three years ago is "0" as a check result, a geometric average growth rate based on the performance of the current year is calculated, and the expected general load demand for each year is calculated using the increase rate (steps S842 and S850). On the other hand, if the performance for 3 years is not "0", the geometric average growth rate is calculated using the performance of 3 years ago, and the expected general load demand for each year is calculated using the growth rate (steps S841 and S850).

Since the geometric mean is applied when calculating the average of growth rates such as inflation rate and population change rate, the average load growth rate of general loads is also calculated by applying the geometric mean. In order to calculate the load increase rate of the substation, the performance for 4 years including the current year is used. If there is no performance for 4 years due to the establishment of the substation, if the maximum load performance for the current year is one digit, the performance three years ago is 1, and if the performance is two digits 10, if it is three digits, it is calculated by assuming 100. If this is represented in a table, it is as follows.

0 years 1 year 2 years 3 years geometric mean
Size of general load [MW]
a ₀
a ₁
a ₂
a ₃

Increase (%) r ₁ r ₂ r ₃

If a ₀ ≠ 0, normal load increase rate =

If a ₀ = 0, then

, (

) Normal load increase rate =

, (

)

Here, len(a ₃ ) is the number of digits of a ₃ .

If the general load increase rate is less than 0, it is set to 0.

Since the long-term demand forecast in the system planning considers up to 15 years, the demand forecast of the general load is calculated for the next 15 years (steps S860 and S870).

On the other hand, when the increase rate is calculated, the normal load for the next year is estimated by multiplying the increase rate by the general load (step S861). If this is expressed as a mathematical formula, it is as follows.

FIG. 9 is a flow chart showing a process of determining the construction timing of the long-term demand forecasting and substation facilities shown in FIG. 5 (steps S550 and S560). Referring to FIG. 9 , the total demand is predicted by adding the untransmitted load value by year of the large load and the predicted demand value of the existing load by year (steps S901, S902, and S910). In general, long-term load demand is calculated for 15 years, so if the undelivered load is supplied before that time, the final value of the undelivered load is added from the following year to estimate the demand.

Demand values for each year predicted by the above process are classified for each substation and stored in the database 140 (step S911).

The reason for dividing the size of large-capacity load and the size of general load is to consider the natural increase rate in case of general load, and not consider the above calculated natural increase rate because it is assumed that the final demand for large-capacity load includes the natural increase rate. Because.

The transformer capacity corresponding to each substation is brought from the DATABASE 140 and the effective capacity of the substation is calculated (steps S903 and S920). In the case of a substation, four transformers can be installed, but when considering the effective capacity, one is excluded from the calculation in preparation for failure. Substation effective capacity is defined by the following equation.

For example, a transformer with a maximum capacity of 60 MVA has an effective capacity of 55.2 MW, and a transformer with a maximum capacity of 40 MVA has an effective capacity of 36.8 MW.

Thereafter, the predicted value of long-term power demand is compared with the effective capacity of the substation (step S930). As a result of the comparison, if the predicted demand value is smaller than the effective capacity of the transformer in step S930, notification information is provided to the output unit indicating that new/extended substation facilities are not required (steps S931 and S960).

On the other hand, as a result of the comparison, if the predicted acceptance value is greater than the effective capacity of the transformer in step S930, it is checked whether there is a substation bank (step S940). In other words, the expected long-term power demand value for 15 years and the effective capacity of the substation are compared to review the timing of new/extended substation facilities.

If the substation transformer has 4 banks (165.6MW), there is no spare bank, so the substation new construction time is provided to the output unit 160, and when the substation transformer has 2 to 3 banks, the transformer extension time is output. Information is provided to the unit 160, and when there is a transformer with a capacity of 40 MW in the substation, notification information of the capacity increase timing is provided to the output unit 160 (steps S941, S950, S951, S952, and S960).

If you elaborate,

- When the effective capacity of the substation is 165.6MW (there is no spare bank in the substation)

=> If substation effective capacity ≤ load demand in year i, then a new substation is established in year i

- When the effective capacity of the substation is 55.2MW or 110.4MW (there is a spare bank in the substation)

=> If substation effective capacity ≤ load demand in year i, the transformer is added in year i

- If the effective capacity of the substation is other than that (40MW transformer exists)

=> If substation effective capacity ≤ load demand in year i, increase transformer capacity in year i

Therefore, the output unit 160 provides the following data to the user.

- Yearly supply performance of large-scale residential land (industrial complex)

- Demand forecast until completion of supply of large-scale residential land (industrial complex)

- Load increase rate of general load by substation

- 15-year long-term demand forecast for each substation

- When it is necessary to construct new substations, expand transformers, and increase transformer capacity

10 is an example of an input screen according to an embodiment of the present invention. Referring to FIG. 10 , data can be added or deleted by inputting substation names, distribution line names, and load ratios by clicking an add button 1010 or a remove button 1020 . Extraction is executed by clicking the Create CSV (Comma Separated Values) button 1030 .

11 is a result of extracting the supply performance of a large load according to an embodiment of the present invention into an Excel file. Referring to FIG. 11, substation names, distribution line names, ratios, etc. are extracted in Excel.

In addition, the steps of a method or algorithm described in connection with the embodiments disclosed herein are implemented in the form of program instructions that can be executed through various computer means such as a microprocessor, processor, CPU (Central Processing Unit), etc. It can be recorded on any available medium. The computer readable medium may include program (instruction) codes, data files, data structures, etc. alone or in combination.

The program (command) code recorded on the medium may be specially designed and configured for the present invention, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs, DVDs, and Blu-rays, and ROMs and RAMs ( A semiconductor storage element specially configured to store and execute program (instruction) codes such as RAM), flash memory, or the like may be included.

Here, examples of the program (command) code include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler. The hardware devices described above may be configured to act as one or more software modules to perform the operations of the present invention, and vice versa.

*100: Long-term power demand forecasting system
110: input unit
120: judging unit
130: extraction unit
140: database
150: calculation unit
160: output unit

Claims (1)

An input unit 110 that receives basic data for demand forecasting;
a determination unit (120) for determining whether it is a previously reviewed old area or a new area based on the basic data; and
According to the result of the determination, the size of the supply load (Load _00-k ) is determined, and the demand for power is predicted according to the size of the load supply (Load _00-k ) and the size of the general load. A calculation unit 150 for generating information and generating facility expansion required time information indicating a time when power facility expansion is required using the power demand prediction information;
The basic data is the name of a large-scale load indicating the name of a house or industrial complex to be stored in the database 140, the final predicted demand indicating the predicted final power demand of a new load to be set in advance, and the name of a supply substation indicating a power plant supplying power to consumers. , Transformer number indicating the transformer to which the distribution line supplying power to the customer is connected, distribution line name indicating the distribution line supplying power to the customer, and load ratio indicating the ratio of the power load supplied to the large load by the specific distribution line. , and a supply date indicating when the specific distribution line was supplied with a specific load ratio,
The determination unit 120 compares the basic data with stored data stored in the database 140, and obtains measured external data if the basic data does not match the stored data according to a result of the comparison
The external data includes a modified distribution line load obtained by a SOMAS (Substation Operation Result Management System) system, and the number of transformers and transformer capacity obtained by a grid protection system,
The determining unit 120 outputs the name of the distribution line, the last data extraction date, and the final load ratio of the distribution line among the stored data when the basic data matches the stored data according to the result of the comparison. Long-term power demand forecasting system featuring.

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