CN-116090196-B - Method for measuring and calculating deviation between actual measurement data and simulation data of new energy station and electronic equipment

CN116090196BCN 116090196 BCN116090196 BCN 116090196BCN-116090196-B

Abstract

The invention provides a method for measuring and calculating deviation between measured data and simulation data of a new energy station and electronic equipment. The method comprises the steps of obtaining actual measurement data of a target new energy station and simulation data of a model corresponding to the new energy station, aligning the simulation data with the actual measurement data based on fault occurrence time, supplementing the simulation data according to the actual measurement data to obtain simulation supplemented data, matching the simulation supplemented data with the actual measurement data according to a plurality of preset data models to obtain an identification model, determining noise coordinates of the actual measurement data and weights of the noise data according to the identification model and a preset noise threshold, and calculating deviation of the actual measurement data and the simulation data of the target new energy station according to the weights, the actual measurement data and the simulation supplemented data. The invention can accurately measure the deviation of the measured data and the simulation data of the new energy station.

Inventors

LI ZIFAN
WANG LEI
WANG XIANGDONG
LI TIECHENG
HU XUEKAI
ZHOU HAO
ZHANG RUNTAO

Assignees

国网河北省电力有限公司电力科学研究院
国家电网有限公司
国网河北能源技术服务有限公司

Dates

Publication Date: 20260512
Application Date: 20221223
Priority Date: 20221021

Claims (8)

1. The utility model provides a new energy station actual measurement data and emulation data deviation measuring and calculating method which is characterized by comprising the following steps: Obtaining actual measurement data of a target new energy station and simulation data of a model corresponding to the new energy station; Aligning the simulation data with the actual measurement data based on the fault occurrence time, and supplementing the simulation data according to the actual measurement data to obtain simulation supplementing data; Matching with the actual measurement data according to a plurality of preset data models to obtain an identification model; according to the identification model and a preset noise threshold, determining the noise coordinates of the actual measurement data and the weight of the noise data; Calculating the deviation of the measured data and the simulation data of the target new energy station according to the weight, the measured data and the simulation complement data; the step of aligning the simulation data with the actual measurement data based on the fault occurrence time and supplementing the simulation data according to the actual measurement data to obtain simulation supplementing data comprises the following steps: preliminarily aligning the simulation data with the actual measurement data based on the fault occurrence time; aligning the transient data of the simulation data with the transient data of the actual measurement data according to the transient data in the actual measurement data, and supplementing the transient data of the simulation data to obtain simulation supplementing data; the matching with the measured data is performed according to a plurality of preset data models to obtain an identification model, which comprises the following steps: Dividing the measured data into a plurality of first data sets according to a preset time length, wherein the length of a time coordinate in the first data sets is the preset time length; Determining a plurality of second data sets corresponding to the first data sets according to the plurality of preset data models and the first data sets; the method comprises the steps of establishing a plurality of preset data models, wherein each data model in the plurality of preset data models is a model constructed by a polynomial, and a plurality of second data sets corresponding to a first data set are a plurality of data sets obtained by carrying out data fitting on the first data set according to each data model; Respectively calculating the sum of squares of differences between the data of each second data set and the data of the corresponding first data set according to the first data set and the second data set; Taking a data model corresponding to the second data set with the smallest sum of squares of the differences as a data model of the corresponding first data set; And sequentially connecting the data models of the first data sets according to the measured data to obtain the identification model.
2. The method for measuring and calculating deviation between measured data and simulation data of a new energy station according to claim 1, wherein said preliminarily aligning said simulation data with said measured data based on a time of occurrence of a fault comprises: based on the fault occurrence time, respectively determining a first fault coordinate corresponding to the simulation data and a second fault coordinate corresponding to the measured data at the fault occurrence time; detecting whether the first fault coordinates are consistent with the second fault coordinates; And if the first fault coordinates are inconsistent with the second fault coordinates, aligning the first fault coordinates with the second fault coordinates, and correspondingly supplementing the simulation data according to the measured data.
3. The method for measuring and calculating the deviation between measured data and simulation data of a new energy station according to claim 2, wherein the determining, based on the occurrence time of the fault, the first fault coordinates corresponding to the simulation data and the second fault coordinates corresponding to the measured data at the occurrence time of the fault respectively includes: initializing a time coordinate value and setting related parameters, wherein the related parameters comprise a fault occurrence judgment preset data value, a preset coordinate difference value and a preset coordinate judgment precision condition; Step two, detecting whether simulation data or corresponding measured data corresponding to the current coordinate value is smaller than a fault occurrence judgment preset data value; Step three, if the simulation data or the measured data corresponding to the current coordinate value is not smaller than the fault occurrence judgment preset data value, adding 1 to the current coordinate value, and jumping to the step two; Step four, if the simulation data or the measured data corresponding to the current coordinate value is smaller than the fault occurrence judgment preset data value, detecting whether the difference value between the current coordinate value and the expected coordinate value corresponding to the fault occurrence moment is smaller than or equal to a preset coordinate difference value; fifthly, if the difference value between the current coordinate value and the coordinate value corresponding to the fault occurrence time is larger than the preset coordinate difference value, determining the current coordinate value as an interference point, adding 1 to the current coordinate value, and jumping to the second step; step six, if the difference value between the current coordinate value and the coordinate value corresponding to the fault occurrence time is smaller than or equal to the preset coordinate difference value, detecting whether the current coordinate value meets a preset precision condition; Step seven, if the current coordinate value does not meet the preset precision condition, removing interference points in the simulation data or the actually measured data, and jumping to the step one; and step eight, if the current coordinate value meets a preset precision condition, determining the current coordinate value as a fault coordinate corresponding to the simulation data or the actually measured data at the occurrence time of the fault respectively.
4. The method for measuring and calculating the deviation between measured data and simulated data of a new energy station according to claim 1, wherein determining the noise coordinates of the measured data and the weight of the noisy data according to the identification model and a preset noise threshold value comprises: The data of each first data set is brought into a corresponding identification model, and a third data set corresponding to each first data set is calculated, wherein the third data set corresponding to the first data set is obtained by carrying out data fitting on the first data set according to the identification model corresponding to the first data set; calculating the difference value between the data of each first data set and the data of the corresponding third data set; if the difference value is larger than the preset noise threshold value, determining a coordinate corresponding to the data as a noise coordinate; and determining the weight of the noise data corresponding to the noise coordinates according to the difference value between the actually measured data corresponding to the noise coordinates and the identification model data.
5. The method for measuring and calculating the deviation between the measured data and the simulation data of the new energy station according to claim 1, wherein calculating the deviation between the measured data and the simulation data of the corresponding model of the target new energy station according to the weight, the measured data and the simulation complement data comprises: According to Calculating average deviation of actual measurement data and simulation data in a preset time length; Determining the deviation of the measured data of the target new energy station and the simulation data of the corresponding model according to the average deviation of the measured data and the simulation data in each preset time length; Wherein the method comprises the steps of For the average deviation of the measured data and the simulation data in the preset time, sim (t) is the simulation filling data, test (t) is the measured data, L is the preset time length, t represents each moment coordinate value, and w t represents the weight corresponding to the data of the moment coordinate of the measured data t.
6. The utility model provides a new energy station actual measurement data and emulation data deviation measuring and calculating device which characterized in that includes: the acquisition module is used for acquiring actual measurement data of the target new energy station and simulation data of a model of the corresponding new energy station; The alignment module is used for aligning the simulation data with the actual measurement data based on the fault occurrence time, and supplementing the simulation data according to the actual measurement data to obtain simulation supplementing data; The identification module is used for matching with the actual measurement data according to a plurality of preset data models to obtain an identification model; the determining module is used for determining the noise coordinates of the actually measured data and the weight of the noise data according to the identification model and a preset noise threshold; the calculation module is used for calculating the deviation between the measured data and the simulation data of the target new energy station according to the weight, the measured data and the simulation complement data; The alignment module is specifically configured to: preliminarily aligning the simulation data with the actual measurement data based on the fault occurrence time; aligning the transient data of the simulation data with the transient data of the actual measurement data according to the transient data in the actual measurement data, and supplementing the transient data of the simulation data to obtain simulation supplementing data; The identification module is specifically used for: Dividing the measured data into a plurality of first data sets according to a preset time length, wherein the length of a time coordinate in the first data sets is the preset time length; Determining a plurality of second data sets corresponding to the first data sets according to the plurality of preset data models and the first data sets; the method comprises the steps of establishing a plurality of preset data models, wherein each data model in the plurality of preset data models is a model constructed by a polynomial, and a plurality of second data sets corresponding to a first data set are a plurality of data sets obtained by carrying out data fitting on the first data set according to each data model; Respectively calculating the sum of squares of differences between the data of each second data set and the data of the corresponding first data set according to the first data set and the second data set; Taking a data model corresponding to the second data set with the smallest sum of squares of the differences as a data model of the corresponding first data set; And sequentially connecting the data models of the first data sets according to the measured data to obtain the identification model.
7. An electronic device comprising a memory for storing a computer program and a processor for calling and running the computer program stored in the memory, characterized in that the processor implements the steps of the method according to any of the preceding claims 1-5 when the computer program is executed.
8. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any of the preceding claims 1 to 5.

Description

Method for measuring and calculating deviation between actual measurement data and simulation data of new energy station and electronic equipment Technical Field The invention relates to the technical field of new energy power generation, in particular to a method for measuring and calculating deviation between measured data and simulation data of a new energy station and electronic equipment. Background Along with the development and utilization of a large amount of new energy sources, a large number of power grids initially form a pattern of coordinated development of traditional energy power generation and new energy power generation, centralized power generation and distributed power generation. But the power generation characteristics of the new energy unit are different from those of the traditional grid-connected power supply, and the characteristics of devices for various fault ride-through, operation condition change and sequential frequency modulation actions are more complex. In order to describe the operation characteristics of the new energy station more accurately and improve the grid-connected detection test efficiency of the station, simulation modeling needs to be carried out on the new energy station. The quality of the simulation modeling of the new energy station has the greatest influence on the construction planning, network access detection and grid-connected operation of the new energy station. Therefore, the deviation between the measured data and the simulation data of the new energy station needs to be measured so as to ensure the modeling accuracy of the new energy station. In the prior art, when measuring and calculating various indexes of a new energy station, the test data of a simulation model are usually compared with the measured data of the new energy station, but the measured data and the simulated data are directly compared and calculated under the influence of simulation measuring equipment and a computer iterative algorithm due to different characteristics of the measured data and the simulated data, so that the deviation between the measured data and the simulated data is difficult to accurately measure, and the calculation accuracy cannot be ensured. Disclosure of Invention The embodiment of the invention provides a method for measuring and calculating the deviation between measured data and simulation data of a new energy station and electronic equipment, which are used for solving the problem that the deviation between the measured data and the simulation data of the new energy station is difficult to accurately measure. In a first aspect, an embodiment of the present invention provides a method for measuring and calculating deviation between measured data and simulated data of a new energy station, including: Obtaining actual measurement data of a target new energy station and simulation data of a model corresponding to the new energy station; aligning the simulation data with the actual measurement data based on the fault occurrence time, and supplementing the simulation data according to the actual measurement data to obtain simulation supplementing data; matching with measured data according to a plurality of preset data models to obtain an identification model; According to the identification model and a preset noise threshold value, determining the noise coordinates of the actually measured data and the weight of the noise data; and calculating the deviation of the measured data and the simulation data of the target new energy station according to the weight, the measured data and the simulation filling data. In one possible implementation manner, based on the fault occurrence time, aligning the simulation data with the actual measurement data, and supplementing the simulation data according to the actual measurement data to obtain simulation supplementing data, including: based on the fault occurrence time, preliminarily aligning simulation data with measured data; According to the transient data in the actual measurement data, aligning the transient data of the simulation data with the transient data of the actual measurement data, and supplementing the transient data of the simulation data to obtain simulation supplementing data. In one possible implementation, the preliminary alignment of the simulation data with the measured data based on the moment of occurrence of the fault includes: based on the fault occurrence time, respectively determining a first fault coordinate corresponding to the simulation data of the fault occurrence time and a second fault coordinate corresponding to the measured data; Detecting whether the first fault coordinates are consistent with the second fault coordinates; and if the first fault coordinates are inconsistent with the second fault coordinates, aligning the first fault coordinates with the second fault coordinates, and correspondingly supplementing the simulation data according to the measured data. In one possible impl