KR20010106939A - Method of a Substation Plan - Google Patents

Abstract

In order to improve the accuracy of load forecasting, which is the most fundamental factor in the planning of the distribution system's loan financing system, the present invention uses a land-use determination technique to grasp the load characteristics by social factors such as power demand, economic indicators, and population composition and small management divisions. It is applied to provide more effective and reliable load prediction method. For example, it has been improved so that it is possible to extend the target area to be applied to the forecast area, which has been suggested as a problem in the conventional load forecasting method using economic indicators. In other words, first, the regional forecasting of economic indicators and electric power demand can be predicted macroscopically, and then the microscopic distribution of macroscopic forecasts is considered in consideration of the load characteristics of each management section. have.

In addition, it is possible to establish the optimal substation plan for new and expansion of substations by improving the problems caused by the lack of utilization rate calculation basis of conventional distribution substations, and to correlate with the past economic indicators and power demand. Through the relationship, the future power demand to the sub-management zone is calculated, and the utilization rate of each substation bank is calculated to improve the reliability of substation planning.

Description

Substation New & Expansion Plan {Method of a Substation Plan}

The present invention accurately predicts the load density of each region, use, and management district required for the most optimal investment plan when establishing a long-term power distribution plan in the electric power company by using the economic, population, and urban planning indicators, The purpose is to provide a method for planning the expansion and expansion of substations for distribution considering the accident.

As energy demand increases globally, energy supply and demand is the biggest concern in the world. The reason for this is that the forecast of energy demand needed to sustain economic growth in the future is very important for the country's energy supply and demand plan. Overall, energy consumption scales in proportion to economic scales (GDP, GNP, etc.), and thus, long-term electricity demand forecasting is usually made using economic indicators.

In general, load prediction in the distribution system is more important than predicting the amount of load growth. For example, even if the load growth amount is incorrectly predicted, if the load growth position is accurately predicted, the problem can be corrected by adjusting the purchase timing of the distribution equipment. It can be useless. As a result, the load prediction in the distribution system can be seen that the position is more important than the size of the load, and therefore, studies on the load prediction by region have been actively conducted.

On the other hand, in order to perform subdivided load forecasting, it is necessary to accurately pinpoint the predicted target area, so it is necessary to divide the cadastral map of the target area into a certain section. (At this time, the divided areas are called blocks or cells. In Korea and Japan, they are called "management zones.")

In the conventional load prediction technique, the first use of an electronic calculator was in the late 1950s. In the early prediction method, multiple regression analysis using extrapolation was mainly used to extend the trend of past load growth with irregular block configuration. Since then, the Land Use Method has been introduced in the United States, and the prediction technology and accuracy have been rapidly improved as the data processing speed, analysis method, and data management of electronic calculators have been strengthened.

However, the load prediction technique using the land use method has an excellent performance in analyzing the load characteristics of each region, but has a problem of separately predicting the growth characteristics of the loads. To this end, many regional load forecasting technologies have been tried in consideration of economic indicators, especially in Japan. This technology predicts long-term power demand for each region in relation to economic growth indicators. The characteristics are predicted by analyzing the correlations between social demands such as electricity demand, economic indicators and population composition. However, it is difficult to apply even sub-units in reality because power demand and economic growth indicators must be analyzed in each region. In addition, in the conventional substation plan, the load increase characteristics of each subdivision area, which are subunits, are not accurately reflected, thereby establishing a substation new and expanded, and thus, the accuracy and reliability of the substation location and capacity are poor.

The present invention was derived in order to solve the problems of the conventional load prediction method as described above, and after the macroscopic prediction of the load for each region where economic indicators and power demand can be aggregated, The rational target that the substation is not lost in the case of 1 bank accident of substation by substation bank configuration type by using the technology to reduce the load forecasting error of the small management district by allocating macroscopically predicted values By presenting the utilization rate, it is characterized in that it is possible to establish an optimal substation plan for the expansion and expansion of substations.

1 is a flow chart illustrating a load prediction method by region and usage.

2 is a flowchart illustrating a medium and long term load prediction method for each management section.

3 is a flow chart illustrating a method for establishing a substation new and expansion plan

4A is an exemplary diagram showing a target utilization rate (60 MVA x 3 banks) according to the bank configuration of a substation

4B is an exemplary diagram showing a target utilization rate (60 MVA x 2 banks) according to the bank configuration of a substation.

4C is an exemplary diagram showing a target utilization rate (60 MVA × 1 + 40 MVA × 1 bank) according to the bank configuration of the substation

4D is an exemplary diagram showing a target utilization rate (60 MVA x 1 + 400 MVA x 2 banks) according to the bank configuration of the substation.

4E is an exemplary diagram showing a target utilization rate (60 MVA x 2 + 400 MVA x 1 bank) according to the bank configuration of the substation

In the present invention, the distribution substation new, expansion planning method considering the load prediction for each management section, the load prediction step for each region, the purpose of predicting the load according to the region where the power is sold and the purpose of supply; A load density prediction step for each management zone for predicting the load of the management zone subdivided into regions again based on the load prediction results for each region and use; Based on the load density prediction result of each management section, the utilization rate for each bank of the substation is calculated and the substation new and expansion plan establishment step for reviewing the new substation and the extension is made.

Hereinafter, with reference to the accompanying drawings will be described in detail with respect to the load prediction method and the substation new, expansion planning method according to the present invention.

As shown in the flowchart of FIG. 1, for example, when targeting Seoul, which is a large city, a process of classifying regions by supply zones (branches) of a power company (KEPCO) is first performed (S11). Subsequently, each year's economic data (GDP), population, and supply demand data for each year are analyzed for 10 years (S12). Here, based on the data analyzed above, items with strong correlation among annual power sales and various coefficients in annual GDP are calculated using the Least Square Method. The relationship between the GDP per capita and the relevant GDP coefficient is set and a correlation is derived for each use (S13).

On the other hand, the maximum load prediction value for each use per person of the region is calculated according to the result calculated from the use-specific correlation (S13) and the future economic indicator (GDP) scenario (A) provided by the Ministry of Economic Affairs of the country (S14). The calculated maximum load prediction value per supply use per person S14 derives the maximum load prediction value for each use corresponding to the population prediction scenario B (S15). In the next step, it is judged by comparing the total number of regions and the number of regions where load prediction has been carried out so far (S16), and if it does not reach the total number of regions, it returns to the loop and repeats the load prediction process to the next target region When it corresponds to the total number of regions, the final load prediction value for each region and usage is calculated. (S17)

Next, in step 2, as shown in FIG. 2, the first step of classifying the entire Seoul by management district (S21) is preceded. “Management zone” is the coordinate used by each KEPCO supply area (point), and it refers to the area or block that has divided the cadastral map into a certain section by pinpointing the target area and is largely related to the large management zone (2km x 2km). It is divided into ligu (500m x 500m). Usually, the management zone is used to establish the distribution system, that is, the location of distribution lines and substations, etc. geographically and to use them for efficient distribution planning and facility maintenance.

On the other hand, if the entire area to be predicted is classified by management zone (S21), land use of each management zone is determined for each purpose of supplying electric power such as residential, public, industrial, agricultural, etc. The land area is calculated (S22). At this time, the determined land use data is databased through a computer worksheet. In addition, the load density by use is calculated by dividing the load by use by each point by the total area value by use by reflecting the load prediction result by region and use (S17) performed in the previous step (S23). Subsequently, multiply the land area for each management zone by multiplying the load density for each region and use to predict the load density for each management zone, and the load according to the urban planning scenario (C) reflecting urban planning such as housing redevelopment, apartment reconstruction, and water and sewage projects. If the final management section load density is calculated (S24). Next, it is determined by comparing the number of management zones to which the load density prediction has been carried out so far and the total management zones (S25). If the total management zones do not reach this point, the loop is returned to the next control zone. The load density prediction process is repeated, and when the number of management zones of the corresponding work corresponds to the total number of management zones, the calculation is finished to calculate the final load density prediction value for each management zone (S26).

On the other hand, new and expansion plans for distribution substations provide a way to calculate and review the operational status (utilization rates) of each bank of a substation when supplying loads predicted by management zones at the current level. Here, "bank" means the unit supply capacity of the substation. Generally, there are 2 to 4 banks in each substation, and several circuits are connected in each bank to supply power to customers. First, as shown in FIG. 3, first, the range of the proper supply zone of the current distribution substation is set for each management zone based on the load density (S26) for each management zone previously performed as shown in FIG. 3 (S31). The load density for each management zone in the supply zone range is calculated for each year, and the bank capacity of each substation is examined, and finally, the utilization rate for each bank configuration of each substation is calculated for each year (S32).

Here, the formula (*) cited is as follows.

Maximum load of the control area

Utilization = --------------------------- -------------- (*)

Substation Bank Capacity

In a subsequent step, the constant target utilization rate for each bank configuration is calculated as shown in the following example, targeting the substation bank configuration in consideration of an emergency accident.

{Case1} 60MVA × 3 banks

; Utilization Substations> 80% (see Figure 4A)

{Case2} 60MVA × 2 bank

; Utilization substation with more than 75% utilization (see Figure 4b)

{Case3} 60MVA × 1 + 40MVA × 1 bank

; Utilization substation exceeding 65% (see Figure 4c)

{Case4} 60MVA × 1 + 40MVA × 2 Bank

; Utilization substation with more than 73.3% (see Fig. 4D)

{Case5} 60MVA × 2 + 40MVA × 1 bank

; Substation with 80% utilization (see FIG. 4E)

In general, the bank configuration of the distribution substation is preferably composed of 3 banks of 3 x 60 MVA, and in the case of the three bank configuration, the target utilization rate is always 80% and the target utilization rate in case of an accident is 120%. First, in consideration of the standard capacity (60MVA), as shown in Figure 4a, when composed of three banks of capacity of 60MVA, when the utilization of all banks in normal operation at 80%, the load of 48MVA for each bank Will be hung. Here, in the event of an emergency, that is, in the case of a one-bank accident, the load is transferred to the other two banks, respectively, and banks 2 and 3 are subjected to an excessive load of 72 MVA, which is 120% of the standard capacity. However, the remaining two healthy banks usually share their loads below the maximum utilization (120-125%) of the banks, so there is no problem in substation operation during an accident, so supply reliability can be maintained without customer outages.

Figure 4b is a case consisting of two banks of the standard capacity (60MVA), if the normal use of all the banks to operate at 75% in the case of one bank accident, the remaining one bank shares the load with 125% utilization, in this case about 15MVA There is no load on the substation, and this residual load can be operated with slight overload on the distribution line, so there is no problem in the operation of the substation. Therefore, the operation target utilization rate in such a substation bank configuration can be set to 75%.

On the other hand, the form of the bank configuration for the two-capacity substation is examined differently from the form of the bank configuration of the same-capacity substation previously examined in terms of supply reliability.

First, as shown in FIG. 4C, the case of a two-capacity substation consisting of one bank of standard capacity (60 MVA) and one bank of 40 MVA, and when operating the utilization rate of all banks at a normal state of 75%, that is, 1 In the event of a bank accident, the remaining 1 bank will share the load with 125% utilization, in which case a load of about 25MVA will remain.In this case, the remaining load of 15MVA can be switched to the distribution line, but the remaining 10MVA cannot be switched, so the constant load is lowered by 10MVA. Since it is necessary to drive, the substation's constant load is driven at 65 MVA. Therefore, the operation target utilization rate in such a substation bank configuration can be set to 65%.

4d shows a case of a two-capacity substation consisting of one bank of standard capacity (60 MVA) and two banks of 40 MVA. When the utilization rate of all banks is operated at 80% under normal conditions, the remaining one bank is used at the time of one bank accident. The load is divided by%, and in this case, about 16 MVA load is left. Here, 15MVA of the remaining load can be switched to the distribution line, but the remaining 1MVA is impossible to switch, so it is necessary to operate the load lower 1MVA at all times, such a constant load of the substation is driven to 111MVA. Therefore, the operation target utilization rate in such a substation bank configuration can be set to 79.3%.

Figure 4e is a case consisting of a two-capacity substation with two banks of 60MVA capacity and one bank of 40MVA. As shown in the figure, if the utilization rate of all banks is operated at 80% in normal state, the remaining 1 bank will share the load with 120% utilization in case of emergency, and in this case, the load of about 8MVA will remain. Similarly on the line, there is no problem in substation operation because it can be operated with a slight overload. Therefore, the operation target utilization rate in such a substation bank configuration can be set to 80%.

When the target utilization rate (Fig. 4a to e) for each bank configuration type is calculated as described above (S32), the next step, the substation for the substation for exceeding the operation target rate based on the previously calculated target target utilization rate (S32) The expansion and expansion of is planned according to the following priority (S33).

부하 Load transfer (transition) to the surrounding light load substation

증 Expansion of substation bank

신 New substation

On the other hand, substations that require new or expanded banks are considered as follows.

Capacity 2 Bank: Substation with over 75% utilization

3 banks of same capacity: Substation with over 80% utilization

2 60MVA + 1 40MVA: Substation with over 80% utilization

1 60MVA + 1 40MVA: Substation with over 65% utilization (over 65MVA)

1 60MVA + 2 40MVA: Substation with utilization above 79.3% (more than 111MVA)

After the step of calculating the priority of the new substation extension (S33) is completed, the next step is to determine the number of substations and the total substations that have been in operation up to now (S34), and if it does not reach the total number of substations, loop again. The next step is to repeat the previous process to the corresponding substation, and when the number of substations of the work corresponds to the total number of substations, the calculation work is completed and the final new and expansion plan for each substation is established (S35). .

As described above, the present invention improves the accuracy of load prediction, which is the most fundamental of the distribution system plan, thereby establishing an optimized plan at the time of establishing a distribution facility investment loan including a substation plan in a power company. In other words, by improving the accuracy of the forecast load in each region and management zone, it is possible to invest in more accurate and reasonable power facilities as follows.

First, by calculating the accurate load density by regional management zones, the power company can plan the optimal power distribution facilities when establishing a power facility investment plan, thereby reducing the cost of unnecessary waste and reducing the investment cost.

Second, due to the improved accuracy of load prediction, it is possible to contribute to the improvement of management balance in the distribution field by maintaining and managing the distribution system in an optimal state.

Third, a more reliable substation plan is established by setting the substation proper supply zone range from the estimated load density of each management zone, and calculating the substation target utilization rate considering the assumed accident according to each substation bank configuration type. do.

Fourth, it is possible to accurately set the direction of supply facility expansion for the rapidly increasing power demand due to the improved accuracy of load forecasting, thereby inducing economic investment by improving the efficiency and economic efficiency of facility operation.

Fifth, distribution planners can set up scenarios according to changes in economic indicators and urban planning, and can predict loads by management zones for each scenario.

Claims (5)

In the method of establishing a distribution substation new and expansion plan, A load prediction step S17 for each region and usage for predicting the load according to the region where the electric power is sold and the intended use; A load density prediction step for each management zone for predicting the load of the management zone subdivided into regions again based on the load prediction results for each region and use (S26); Substation new, expansion planning method comprising the step of calculating the utilization of each substation of the substation based on the result of the management section, the step of establishing a new substation, expansion plan to review the future, the expansion of the substation (S35). The method of claim 1, wherein the load prediction step (S17) for each region and usage, Classifying regions by supply zones to which power is supplied (S11); Analyzing data of the population, the Gross Domestic Product (GDP), and the power demand for each use for a predetermined period of time in the classified region (S12); Deriving a correlation for each use of a corresponding region from the analyzed data (S12) (S13); Predicting the maximum load for each use per user by reflecting the GDP prediction scenario (A) of the region from the derived use-specific correlation (S13) (S14); Predicting the maximum load for each use by reflecting the population prediction scenario (B) of the region from the maximum load for each use per person (S15); Determining the number of regions up to now on which load prediction is being performed by comparing with the total number of regions (S16); The substation new, expansion planning method comprising the step (S17) of calculating the final load prediction for each region, the use is calculated as the result of the determination is the number of regions subjected to the load prediction to the total number of regions. The method of claim 1, wherein the load density prediction step for each management section (S26) Classifying the entire target area into a management zone (S21); Calculating each land use area by dividing the classified management zone (S21) for each use (S22); Predicting load densities for each use by reflecting load prediction results (S17) for each region and use based on the determined land use area (S22) for each management zone (S23); Predicting the load density for each management section by reflecting the city planning scenario (C) to the predicted load density (S23) for each use (S24); Judging the number of management zones up to now on which load prediction is being performed by comparing with the total management zones (S25); And a step (S26) of calculating the final load density prediction for each management zone by calculating the estimated number of management zones as a result of the determination. According to claim 1, Substation new, expansion planning step (S35) Setting the supply zone range of the power distribution substation for each management zone from the load density prediction result for each management zone (S31); Calculating a utilization rate of each substation by a bank configuration from the set appropriate supply area range (S31) for each substation (S32); Calculating an appropriate extension, extension time and capacity of the substation for each year from the calculated utilization rates for each bank configuration (S32) and comparing and comparing the existing plans with the existing plans to calculate priorities for substation extension and expansion (S33); Determining by comparing the number of substations and the total number of substations to which the utilization calculation operation is being performed (S34); The substation new, expansion planning method comprising the step (S35) of the final substation new, expansion plan is derived when the number of substations in which the utilization rate calculation operation has reached the total number of substations as a result of the determination. The method of claim 2, Calculation of the use-by-use correlation (S13) is a substation new, expansion planning method characterized by using the least-square method (Least Square Method) for items that have a strong correlation among annual sales power by use and various coefficients in the annual GDP.