KR-20260065879-A - Method for determining load parameters

Abstract

A computer-implemented method (100) for determining load parameter values of a load model of an electrical load comprises: receiving a synchronized data pair from a data acquisition means, which is active power and voltage amplitude, reactive power and voltage amplitude, active power and frequency, or reactive power and frequency; continuously generating a first data set and a second data set from the collected data pairs, wherein the first data set represents samples of active power or reactive power and the second data set represents samples of voltage or frequency; continuously calculating variations of each of the first data set and the second data set; detecting a discontinuity by continuously comparing the variation of the first data set with a discontinuity limit (102); detecting a disturbance by continuously comparing the variation of the second data set with a disturbance variation detection limit (101); and calculating load parameter values using a mathematical method (103).

Inventors

• 마에바, 쿠르셀르
• 드 카르네, 지오반니
• 타오, 큐센

Assignees

• 칼스루헤 인스티투트 퓌어 테흐놀로기

Dates

Publication Date

20260511

Application Date

20240829

Priority Date

20230905

Claims (5)

1. A computer implementation method (301) for determining at least one load parameter value (100) of at least one load parameter defined by a load model (1031) of at least one electric load connected to an electric grid, having the same sampling rate from a data acquisition means, Active power and voltage amplitude, Reactive power and voltage amplitude, Active power and frequency, or Reactive power and frequency A step of receiving at least one of the synchronized data pairs, Step of continuously generating a first data set and a second data set from data pairs collected during a specified time range - The first data set and the second data set include at least two samples, and The above first data set is, Active power sample, or Represents a reactive power sample, The second dataset is, Voltage amplitude sample, or Represents frequency samples, The length of the above specified time range depends on the sampling rate of the data pair - , A step of continuously calculating the variation of each of the first data set and the second data set, Step (102) of continuously comparing the variation of the first data set with a specified discontinuity limit - It is considered discontinuous when the variation of the first data set exceeds the specified discontinuity limit - , Step (101) of continuously comparing the variation of the second data set with the specified disturbance variation detection limit (202) - When the variation in the second data set exceeds the designated disturbance variation detection limit (203), it is considered a disturbance, and The disturbance ends when the variation in the second data set is less than the designated disturbance variation detection limit (203) - , Step (103) of calculating at least one load parameter value of a load parameter using a mathematical method (1032) - Calculation starts when considered a disturbance, and The calculation is interrupted when the disturbance ends or is considered discontinuous, and The disturbance time window is set as the duration between the start and stop of the first calculation - , A step of generating a third data set and a fourth data set over a disturbance time window when the calculation of at least one load parameter value is interrupted - The third data set includes at least two samples, and The above third data set is, Active power sample during the disturbance time window, or Represents a sample of reactive power during the disturbance time window, The fourth data set is, Indicates at least one load parameter calculated during the disturbance time window - , Step of generating the fifth dataset over the pre-disturbance time window - The time window prior to disturbance is set by a specified prior to disturbance duration ending at the start of a first calculation of at least one load parameter value, and The above fifth data set is, Active power sample during the time window before disturbance, or Represents reactive power samples during the time window prior to disturbance - , A step of calculating the variation of the third data set and the fifth data set, Step (104) of comparing the variation of the third data set with the variation of the fifth data set - It is considered a trust case when the variation in the third data set exceeds the variation in the fifth data set - , Step (105) of calculating the average load parameter given as the average value of the fourth data set when considered as a confidence case A computer-implemented method including
2. A data acquisition means configured to execute the steps of the computer implementation method of claim 1, The above data acquisition means is coupled to at least one output means of a sensor assembly comprising at least a first sensor and a second sensor, wherein the first sensor is configured to measure the voltage of at least one electrical load in an electric grid and the second sensor is configured to measure the current of at least one electrical load in an electric grid, and The above data acquisition means is From voltage and current, Voltage amplitude, Current amplitude, Phase difference between voltage and current, and Optionally, frequency It is configured to calculate, From the above voltage amplitude, the above current amplitude, and the phase difference, Active power, or Reactive power It is configured to calculate, The above data acquisition means is Active power and voltage amplitude, Reactive power and voltage amplitude, Active power and frequency, or Reactive power and frequency Data acquisition means comprising an output means configured to transmit at least one of a pair of data.
3. In paragraph 2, a data acquisition means configured to resample a data pair so that the data pair is synchronized when the data pair has different sampling rates.
4. A computer program comprising a command that causes the computer to perform the method of claim 1 when the computer program is executed by the computer.
5. A computer-readable medium on which the computer program of paragraph 4 is stored.

Description

Method for determining load parameters The technical field of the present invention addresses the requirement to calculate highly accurate load parameters even under minor disturbances compared to existing solutions. Additionally, the identification of load parameters is provided in real time. Prior art for this invention is a method disclosed in publication [1], which provides real-time load sensitivity identification based on disturbance events. This method is also disclosed in [2], where the synchronization of the calculation window and the disturbance window is achieved through communication with an actuator. Furthermore, as disclosed in publications [3, 4], a comparison of voltage values targeting the disturbance window is disclosed, as opposed to calculating load parameters using disturbance events. Additionally, publication [5] discloses an additional method of using the acquired disturbance window in calculations by comparing the voltage value with a voltage threshold and checking the common direction of fluctuations in voltage and power. However, the aforementioned methods are not suitable for detecting small disturbances; identifying load parameters using small disturbances of 0.01% to 5% of the nominal voltage is more suitable for electrical grids and can also be implemented through smart devices. While existing solutions utilized larger disturbances, there are limitations to methods that use thresholds or minimum fluctuation percentages for disturbance detection. Furthermore, existing non-integrated systems require additional synchronization. Further details and features of the present invention are derived from the description of the following preferred embodiments, particularly with respect to the dependent claims. Each function may be implemented alone or in combination with one another. The present invention is not limited to embodiments or forms. Examples or forms of embodiments are schematically illustrated in the following drawings. Herein, identical reference numerals in the drawings indicate identical or functionally identical elements or functionally corresponding elements. For the sake of illustrative purposes only, and not limited thereto, additional features and advantages of the present invention are derived from the description of the accompanying drawings. FIG. 1 is a flowchart of a load sensitivity identification process including disturbance detection according to claim 1. Figure 2 is a schematic diagram for disturbance detection using an estimator. FIG. 3 is a schematic diagram of the application of the method according to claim 1. FIG. 1 shows a flowchart (100) of a load sensitivity identification process including disturbance detection according to claim 1. The first step (101) corresponds to disturbance detection, where the variation of the second data set is compared with the disturbance variation detection limit. If the variation of the second data set exceeds the disturbance variation detection limit, the process continues, otherwise, the variation of the second data set is continuously compared with the disturbance variation detection limit. The variation in the second data set is a variable It is represented as and explained by the following mathematical formula (4): (4) Here ε is the calculated standard deviation of the signal for N points, V₀ is the rated value of the disturbance, and α dist/% is the percentage of the amplitude change of the disturbance relative to the rated value of the disturbance. Here, the rated value of the disturbance amount corresponds to the average value of the corresponding amount prior to the occurrence of the disturbance, and the disturbance amount represents the physical quantity of the second data set, which is voltage or frequency. Here, the variable N is the standard deviation. It affects. - Here, N is the standard deviation of the disturbance period T dist (e.g., 1 for non-periodic disturbances) and the measurement sampling time t s. Consequently, the second dataset without affecting It is selected so as not to affect the fluctuation of. - Here, α represents the ratio of the size of the specified time window to the number of measurement samples during one cycle of disturbance and is defined by the following mathematical formula (5): (5) Here, N represents the size of the specified time window, and N pt/cycle represents the number of measurement samples during one cycle of the disturbance. Here, N pt/period is defined by the following mathematical formula (6): (6) Here, α can be selected in the range of 0.8 to 1.0, and in this range, the effect on detection accuracy will be negligible. Here, the detection variation detection limit is set to 0.2 to 0.5, that is, the estimator If it exceeds this limit, it is considered a disturbance. In the second step (102), power fluctuations are analyzed, where the fluctuations in the first data set are compared to discontinuity limits. If discontinuity is detected, the process is stopped and returns