Method for improving load calibration accuracy of substation during full stop and full rotation
Technical Field
The invention relates to the field of load verification, in particular to a method for improving the accuracy of full-stop and full-rotation load verification of a substation.
Background
With the rapid development of economy, the requirements on the power supply reliability of residents and enterprises are higher and higher, the requirements on a power grid are higher and higher, meanwhile, the arrangement of the power grid operation mode is more and more complex, and the safety risk is increased. In addition, in cooperation with equipment troubleshooting, a dispatching department is also required to perform load transferring work, but whether the load can be transferred needs to consider a plurality of factors, and in order to complete the dispatching work more quickly and safely, the accuracy rate of the full-stop and full-rotation load verification of the transformer substation needs to be improved, so that the rapid transfer analysis is performed, an accident handling scheme is obtained rapidly, and the safe and stable operation of a power grid is ensured.
In the prior art, for example, the invention of publication number CN106099917A discloses a method for quickly determining a load transfer scheme of a transformer substation, which includes: setting an initial load transfer scheme according to the type of the transformer substation; aiming at a 220kV transformer substation, acquiring a 110kV loss load rate and a 35kV loss load rate under the highest load rate; aiming at a 110kV transformer substation, obtaining a 10kV loss load rate under the highest load rate; aiming at a 220kV transformer substation, adjusting an initial load transfer scheme of the 220kV transformer substation according to the loss load rate under the highest load rate; and aiming at the 110kV transformer substation, adjusting an initial load transfer scheme of the 110kV transformer substation according to the transfer load rate under the highest load rate. The invention mainly adjusts the transfer scheme through the load loss rate.
However, in the prior art, only the factors of the substation are considered, the factors such as the electricity utilization condition in the area are not considered too much, and a corresponding prediction means is also lacked, so that the accuracy of the load calibration of the substation during full-stop and full-rotation is generally difficult to guarantee.
Disclosure of Invention
The invention provides a method for improving the accuracy of the load calibration of a substation in full stop and full rotation aiming at the problem that the accuracy of the load calibration of the substation in full stop and full rotation is low due to lack of prediction of the electricity consumption in an area in the prior art.
The technical scheme of the invention is as follows.
A method for improving the accuracy of the load calibration of the full stop and the full rotation of a substation comprises the following steps: carrying out plot classification and population classification in a region range, and carrying out type classification on a date; historical data records, wherein the population and the date type of each plot are recorded by taking time as a unit, and the load capacity transfer phenomenon are recorded; calculating population load carrying rates of each type of population in different plots in a specified time period according to load transfer; inputting a target plot, date and time, predicting load according to population flow data and population load carrying rate, and comparing the predicted value of the load with the maximum load of a power substation in the district to obtain a transfer expected result.
Since the load in the area is changed in a very complex way, and the limit load which can be carried by the substation is relatively fixed, but the way of comparing the maximum load in the area with the limit load of the substation is rather stiff and not beneficial to allocation, so that in order to obtain more accurate and reference value substation full stop and full turn load verification data, the load in the range must be predicted. According to the method, the land parcel and the population are classified, the population is used as a main factor influencing the load, the load carrying rate of the population is calculated, the load in the area can be predicted according to the population mobility data, and the accuracy rate is high.
Preferably, the parcel classification comprises: residential, industrial, commercial and other areas.
Preferably, the demographic categories include: the population is divided into weakly affected and strongly affected populations according to age. Wherein the weak influence population is mainly the low age population and the high age population, the middle age layer is the strong influence population, the specific boundary can be divided by self, the age is generally 16 years old and 53 years old as a boundary, and the specific boundary can be adjusted according to the regional conditions; the weak influence population is mainly characterized by less daily migration and less generated load, and the represented load characteristic is relatively stable, while the strong influence population generally has daily migration and generally shows obvious load migration characteristic, and has obvious influence on the load in the region.
Preferably, the triggering condition of the load transfer phenomenon record comprises; in a specified time period, the load quantity of any land block deviates in a single direction to reach a specified value, and in a specified time interval, the load quantity of other land blocks deviates in a reverse direction and reaches the specified value, and then the load quantity transfer is recorded once. That is, the above condition is triggered as long as the absolute value of the deviation occurring within the time period reaches the requirement, regardless of whether the load amount becomes high or low.
Preferably, the population load carrying rate is represented by Xn (a, b, c, d) and Yn (a, b, c, d), where X represents a weakly-affected population, Y represents a strongly-affected population, n is a timestamp label, a represents the load carrying rate of the corresponding classified population in the residential area, b represents the load carrying rate of the corresponding classified population in the industrial area, c represents the load carrying rate of the corresponding classified population in the commercial area, and d represents the load carrying rate of the corresponding classified population in another area.
Preferably, the calculation process of the load carrying rate with strong influence on the population comprises the following steps: xn (a, b, c, d) = Q1/M1, where Q1 is the difference in load amount of any parcel at the beginning and end of the corresponding time period, and M1 is the corresponding population number; the calculation process of the load carrying rate of the weak influence population comprises the following steps: yn (a, b, c, d) = Q2/M2, where Q2 is the bottom load amount of an arbitrary parcel over the corresponding time period and M2 is the corresponding population number. That is, the load carrying rate of the weak influence population is mainly related to the lowest load in the region, while the load carrying rate of the strong influence population is mainly related to the fluctuation value of the load in the region, and the load carrying rate and the fluctuation value of the load in the region affect the load in the region together.
Preferably, the process of predicting the load amount includes: q = m1 Xn + m2 Yn, where m1 is the number of strong influence population for the time period corresponding to the parcel and m2 is the number of weak influence population for the time period corresponding to the parcel.
The substantial effects of the invention include: the influence of the population type and the plot type on the load capacity in the historical data is analyzed to obtain the corresponding population load carrying rate, the load capacity, the plot and the population are bundled on the data, the future load capacity is accurately predicted, the method can be used for improving the load checking accuracy rate of the full stop and the full transfer of the substation, and helps to optimize the transfer scheme.
Detailed Description
The technical solution of the present application will be described with reference to the following examples. In addition, numerous specific details are set forth below in order to provide a better understanding of the present invention. It will be understood by those skilled in the art that the present invention may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present invention.
Example (b):
a method for improving the accuracy of the load calibration of the full stop and the full rotation of a substation comprises the following steps: carrying out plot classification and population classification in a region range, and carrying out type classification on a date; historical data records, wherein the population and the date type of each plot are recorded by taking time as a unit, and the load capacity transfer phenomenon are recorded; calculating population load carrying rates of each type of population in different plots in a specified time period according to load transfer; inputting a target plot, date and time, predicting load according to population flow data and population load carrying rate, and comparing the predicted value of the load with the maximum load of a power substation in the district to obtain a transfer expected result.
Since the load in the area is changed in a very complex way, and the limit load which can be carried by the substation is relatively fixed, but the way of comparing the maximum load in the area with the limit load of the substation is rather stiff and not beneficial to allocation, so that in order to obtain more accurate and reference value substation full stop and full turn load verification data, the load in the range must be predicted. In the embodiment, the land parcel and the population are classified, the population is used as a main factor influencing the load, and the load carrying rate of the population is calculated, so that the load in the area can be predicted according to the population mobility data, and the accuracy is high.
Wherein the parcel classification comprises: residential, industrial, commercial and other areas.
Wherein the demographic categories include: the population is divided into weakly affected and strongly affected populations according to age. The weak influence population mainly comprises a low age population and an old age population, the middle age layer is a strong influence population, the specific boundary can be divided by self, the age of the middle age layer is 16 years and 53 years, and the specific boundary can be adjusted according to the regional conditions; the weak influence population is mainly characterized by less daily migration and less generated load, and the represented load characteristic is relatively stable, while the strong influence population generally has daily migration and generally shows obvious load migration characteristic, and has obvious influence on the load in the region.
The triggering conditions of the load transfer phenomenon record comprise; in a specified time period, the load quantity of any land block deviates in a single direction to reach a specified value, and in a specified time interval, the load quantity of other land blocks deviates in a reverse direction and reaches the specified value, and then the load quantity transfer is recorded once. That is, the above condition is triggered as long as the absolute value of the deviation occurring within the time period reaches the requirement, regardless of whether the load amount becomes high or low.
The population load carrying rates are represented as Xn (a, b, c, d) and Yn (a, b, c, d), wherein X represents the weakly-affected population, Y represents the strongly-affected population, n is a timestamp label, a represents the load carrying rate of the corresponding classified population in the residential area, b represents the load carrying rate of the corresponding classified population in the industrial area, c represents the load carrying rate of the corresponding classified population in the commercial area, and d represents the load carrying rate of the corresponding classified population in other areas.
The calculation process of the load carrying rate which strongly influences the population comprises the following steps: xn (a, b, c, d) = Q1/M1, where Q1 is the difference in load amount of any parcel at the beginning and end of the corresponding time period, and M1 is the corresponding population number; the calculation process of the load carrying rate of the weak influence population comprises the following steps: yn (a, b, c, d) = Q2/M2, where Q2 is the bottom load amount of an arbitrary parcel over the corresponding time period and M2 is the corresponding population number. That is, the load carrying rate of the weak influence population is mainly related to the lowest load in the region, while the load carrying rate of the strong influence population is mainly related to the fluctuation value of the load in the region, and the load carrying rate and the fluctuation value of the load in the region affect the load in the region together.
The process of predicting the load amount includes: q = m1 Xn + m2 Yn, where m1 is the number of strong influence population for the time period corresponding to the parcel and m2 is the number of weak influence population for the time period corresponding to the parcel.
The substantial effects of the present embodiment include: the influence of the population type and the plot type on the load capacity in the historical data is analyzed to obtain the corresponding population load carrying rate, the load capacity, the plot and the population are bundled on the data, the future load capacity is accurately predicted, the method can be used for improving the load checking accuracy rate of the full stop and the full transfer of the substation, and helps to optimize the transfer scheme.
The technical solution of the embodiments of the present application may be essentially or partially contributed to the prior art, or all or part of the technical solution may be embodied in the form of a software product, where the software product is stored in a storage medium, and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.