Electric drilling rig grid-connected control method and system

Abstract

The present invention discloses a method and system for controlling the connection to the grid of an electric drilling rig, and relates to the technical field of electric drilling rig control. The method and system construct and classify historical load change curves, extract a mark load change curve, analyze and determine driving power data according to drilling records of electric drilling rigs of the same specification, and construct a reference depth power corresponding curve. After obtaining the driving power and depth data of the electric drilling rig in real time, the real-time depth power corresponding curve is constructed, and a template for correcting power is selected; the real-time load change curve is constructed and compared with the mark load change curve to determine the reference load change curve; the power and load changes within a preset time period in the future are predicted by combining the template for correcting power and the reference load change curve, and the time length of the power change is adjusted accordingly. The above technical scheme of the present invention realizes the high efficiency and optimization of the connection to the grid of the electric drilling rig, and ensures the stable progress of the drilling operation and the safe operation of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of electric drilling rig control, and in particular to a grid-connected control method and system for an electric drilling rig. Background Art

[0002] In oil exploration and development operations, electric drilling rigs are key equipment, and the selection and optimization of their energy supply methods are of great significance for improving drilling efficiency, reducing costs and ensuring operational safety. Traditionally, electric drilling rigs rely on self-provided diesel generator sets as power sources, but with the transformation of energy structure and the improvement of environmental protection requirements, obtaining electricity directly from the power grid has become a new trend in the energy supply of electric drilling rigs. This shift not only helps to reduce carbon emissions and reduce operating costs, but also puts forward higher requirements for improving the automation and intelligence level of drilling operations. However, during the operation of electric drilling rigs, due to changes in drilling depth, geological conditions and process requirements, their power demand also fluctuates frequently. If this power change is not optimized and controlled, it may have adverse effects on the power grid, such as causing voltage fluctuations, frequency offsets and even harmonic pollution, which not only affects the stable operation of the electric drilling rig, but also may interfere with the normal power consumption of other users in the power grid. Therefore, the optimized control of the power change of electric drilling rigs has become one of the key technologies to ensure the stability of the power grid and the smooth progress of drilling operations. Summary of the invention

[0003] The object of the present invention is to provide a control method and system capable of optimizing the power drive during the grid connection process of an electric drilling rig.

[0004] The invention discloses a grid-connected control method for an electric drilling rig, comprising:

[0005] Obtain historical load change data of power grid lines, analyze the historical load change data of power grid lines, construct several historical load change curves, classify the several historical load change curves by similarity, obtain several historical load change curve groups, extract features of the historical load change curves in the historical load change curve groups, and form a sign load change curve;

[0006] Obtain drilling records of electric drilling rigs of the same specifications, analyze each drilling record, determine a number of driving power data, and construct a reference depth power corresponding curve based on the driving power data, wherein the horizontal axis of the depth power corresponding curve is the depth and the vertical axis is the driving power, and perform feature label configuration on a number of reference depth power corresponding curves;

[0007] The real-time driving power and real-time depth of the electric drill are obtained, and based on the real-time driving power and the real-time depth, a real-time depth power corresponding curve is constructed, and a feature label is determined for the real-time depth power corresponding curve, and the feature label and several corresponding reference depth power corresponding curves are used to compare the reference depth power corresponding curve and the real-time depth power corresponding curve to determine a first equivalent index of the two, and if the first equivalent index is greater than or equal to a preset value, the corresponding reference depth power corresponding curve is selected as a template for correcting power;

[0008] Acquire real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different sign load change curves, and determine a second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, determine the corresponding sign load change curve as a reference load change curve;

[0009] Based on the modified power template, the power change in the future preset time period is determined, and based on the reference load change curve, the load change of the power grid line in the future preset time period is determined. Based on the load change of the power grid line in the future preset time period, the time length of the power change is adjusted.

[0010] In some embodiments disclosed in the present invention, a method for similarity classification of several historical load change curves includes:

[0011] According to the relative method of equal time, several historical load change curves are aligned, and the high-load sections and low-load sections of all historical load change curves on the time line are analyzed, wherein the method of determining the high-load section includes that the load cumulative value is greater than or equal to the preset value in a continuous preset time period, and the method of determining the low-load section includes that the load cumulative value is less than or equal to the preset value in a continuous preset time period;

[0012] Based on the distribution consistency of the high-load section and the low-load section of each historical load change curve, the historical load change curves are classified by similarity for the first time;

[0013] Calculate the load average values ​​in the high load section and the low load section in the historical load change curve, and perform a second similarity classification on the historical load change curve of the first similarity classification based on the consistency of the load average values;

[0014] The historical load change curves that have undergone the second similarity classification are subjected to curve change similarity analysis. The method for curve change similarity analysis includes calculating the average value of the historical load change curves after classification to obtain the category average load change curve, overlapping the category average load change curve with other historical load change curves after classification, and analyzing the curve intersection area change characteristics between the two, including analyzing the area change rate of the curve intersection area as the horizontal axis advances, and the cumulative value of the curve intersection area. Based on the consistency of the area change rate and the cumulative value of the curve intersection area, the historical load change curves that have undergone the second similarity classification are subjected to a third similarity classification to obtain several historical load change curve groups.

[0015] In some embodiments disclosed in the present invention, a method for extracting features of a historical load change curve in a historical load change curve group and forming a marked load change curve includes:

[0016] A section mapping template is set for each historical load change curve in the historical load change curve group, and the section mapping template includes a plurality of interconnected mapping time sections, and each mapping time section includes a plurality of mapping time points;

[0017] Mapping the historical load change curve to the section mapping template, and comparing the trend consistency of the load change curve segments belonging to the same mapping time segment, wherein the method for comparing the trend consistency of the load change curve segments includes analyzing the curve curvature of each load change curve segment corresponding to the mapping time point, and marking the corresponding curve node of the load change curve segment, if the curve curvature of the curve nodes greater than or equal to the preset value between the load change curve segments is consistent, then it is determined that the load change curve segment trend is consistent;

[0018] Extract the load change curve segments that belong to the same mapping time segment and have the same trend, and calculate their average value to obtain the marked load change curve segment;

[0019] The segments of the sign load change curve in the section mapping template are spliced ​​with each other, and smooth transition is performed at the splicing locations to obtain the sign load change curve.

[0020] In some embodiments disclosed in the present invention, a method for configuring feature labels for a plurality of reference depth power corresponding curves is as follows:

[0021] Scan and analyze the reference depth power corresponding curve, mark the curve nodes whose curve curvature is greater than or equal to a preset value as power change nodes, map the power change nodes to the horizontal axis of the reference depth corresponding curve, and identify the distribution of the power change nodes mapped on the horizontal axis as the first feature label;

[0022] The average driving power of the preset sections before and after the power change node corresponding to the reference depth corresponding curve is determined, and the average driving power corresponding to each power change node is identified as a second feature label.

[0023] In some embodiments disclosed in the present invention, a method for comparing a reference depth power corresponding curve with a real-time depth power corresponding curve to determine a first equivalent index of the two includes:

[0024] Continuously compare the relative power change nodes in the reference depth power corresponding curve and the real-time depth power corresponding curve to determine the depth difference between the two. If the depth difference between the two is less than or equal to a preset value, it is determined that the two are worth comparing;

[0025] Based on the depth difference of the power change nodes with continuous comparison value and the trend consistency of the preset sections before and after the power change nodes, the first equivalent index of the reference depth power corresponding curve and the real-time depth power corresponding curve is determined.

[0026] In some embodiments disclosed in the present invention, the expression for calculating the first equivalent index is:

[0027] ;

[0028] in, is the first equivalent indicator, is a comparison value judgment function. If the depth difference between the power change nodes is less than or equal to the preset value, then Output 1, otherwise output 0. is a trend matching degree calculation function, used to calculate the trend matching degree of the preset sections before and after the power change node, and n is the number of power change nodes to be compared continuously;

[0029] ;

[0030] in, is the trend judgment function of the xth trend comparison node in the preset section before and after the power change node. If the trend corresponding to the xth trend comparison node matches, it outputs 1, otherwise it outputs 0. is the trend matching impact multiplier adjustment coefficient, b is the trend matching impact adjustment constant, The number of trend comparison nodes for the preset sections before and after the power change node.

[0031] In some embodiments disclosed in the present invention, the method of comparing the real-time load change curve with the load change curves of different signs to determine the second equivalent index includes:

[0032] Based on the time proximity correspondence principle, determine the translation interval of the sign load change curve relative to the real-time load change curve, and based on the determined translation interval, translate the sign load change curve relative to the real-time load change curve several times, and calculate the intersection area between the sign load change curve and the real-time load change curve after each translation, and calculate the average of several intersection areas to obtain the average intersection area;

[0033] The average cross-sectional area was determined as a second equivalent index.

[0034] In some embodiments disclosed in the present invention, based on the load change of the power grid line in a future preset time period, the method for adjusting the time length of the power change includes:

[0035] Several levels of load mapping intervals are set, and a standard intervention power change rate and a standard intervention power are set for each load mapping interval;

[0036] Based on the load mapping interval changes mapped to the reference load change curve within the future preset time period, determine the standard intervention power and standard intervention power change rate to be called at different time nodes in the future;

[0037] Determine the predicted driving power and predicted power change rate of the modified power template at different time nodes in the future, judge whether the predicted driving power is greater than the standard intervention power, and if so, correct the predicted power change rate in combination with the standard intervention power and the standard intervention power change rate at the corresponding time node to obtain the corrected power change rate;

[0038] Based on the corrected power change rates corresponding to different future time nodes, the time length of the power change at the corresponding time nodes is adjusted.

[0039] In some embodiments disclosed in the present invention, the expression for calculating the corrected power change rate is:

[0040] ;

[0041] in, is the corrected power change rate, is the standard intervention power change rate, To predict the driving power, is the standard intervention power, is the power difference impact adjustment coefficient, c is the power difference impact adjustment constant, To correct the power change rate conversion factor.

[0042] In some embodiments disclosed in the present invention, there is also disclosed an electric drilling rig grid-connected control system, comprising:

[0043] The first module is used to obtain historical load change data of power grid lines, analyze the historical load change data of power grid lines, construct several historical load change curves, classify the several historical load change curves by similarity, obtain several historical load change curve groups, extract features of the historical load change curves in the historical load change curve groups, and form a sign load change curve;

[0044] The second module is used to obtain drilling records of electric drilling rigs of the same specifications, analyze each drilling record, determine a number of driving power data, and construct a reference depth power corresponding curve based on the driving power data. The horizontal axis of the depth power corresponding curve is the depth, and the vertical axis is the driving power. Feature labels are configured for a number of reference depth power corresponding curves;

[0045] The third module is used to obtain the real-time driving power and real-time depth of the electric drill, and based on the real-time driving power and real-time depth, construct a real-time depth power corresponding curve, and determine the feature label of the real-time depth power corresponding curve, and use the feature label and several corresponding reference depth power corresponding curves to compare the reference depth power corresponding curve with the real-time depth power corresponding curve to determine the first equivalent index of the two. If the first equivalent index is greater than or equal to a preset value, the corresponding reference depth power corresponding curve is selected as a template for correcting power;

[0046] The fourth module is used to obtain the real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different sign load change curves, and determine the second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, the corresponding sign load change curve is determined as the reference load change curve;

[0047] The fifth module is used to determine the power change within a future preset time period based on the modified power template, and to determine the load change of the power grid line within the future preset time period based on the reference load change curve, and to adjust the time length of the power change based on the load change of the power grid line within the future preset time period.

[0048] The present invention discloses a method and system for controlling the connection to the grid of an electric drilling rig, and relates to the technical field of electric drilling rig control. The method and system construct and classify historical load change curves, extract a mark load change curve, analyze and determine driving power data according to drilling records of electric drilling rigs of the same specification, and construct a reference depth power corresponding curve. After obtaining the driving power and depth data of the electric drilling rig in real time, the real-time depth power corresponding curve is constructed, and a template for correcting power is selected; the real-time load change curve is constructed and compared with the mark load change curve to determine the reference load change curve; the power and load changes within a preset time period in the future are predicted by combining the template for correcting power and the reference load change curve, and the time length of the power change is adjusted accordingly. The above technical scheme of the present invention realizes the high efficiency and optimization of the connection to the grid of the electric drilling rig, and ensures the stable progress of the drilling operation and the safe operation of the power grid.

[0049] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A method step diagram of a method for controlling a grid-connected electric drilling rig disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0052] The following will be combined with the accompanying drawings and specific embodiments to clearly and completely describe the technical solution of the present invention. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art in this field can make some non-essential improvements and adjustments based on the content of the present invention described below. In the present invention, unless otherwise clearly specified and limited, the technical terms used in the present invention should be the common meanings understood by the technical personnel described in the present invention.

[0053] Example:

[0054] The object of the present invention is to provide a control method and system capable of optimizing the power drive during the grid connection process of an electric drilling rig.

[0055] The present invention discloses a method for controlling an electric drilling rig to be connected to a grid. Figure 1 ,include:

[0056] Step S100, obtaining historical load change data of the power grid line, analyzing the historical load change data of the power grid line, constructing a number of historical load change curves, classifying the several historical load change curves by similarity, obtaining a number of historical load change curve groups, extracting features of the historical load change curves in the historical load change curve groups, and forming a landmark load change curve.

[0057] The core principle of this step is to fully understand the long-term trend, periodic changes and possible abnormal fluctuations of the power grid load by collecting and deeply analyzing the historical load change data of the power grid lines. By constructing multiple historical load change curves and classifying these curves by similarity, the main change patterns and characteristics of the power grid load can be identified. Furthermore, through feature extraction, the signature load change curves are formed. These curves serve as important benchmarks for subsequent load prediction and control, which helps to more accurately grasp the changing laws of the power grid load.

[0058] In some embodiments disclosed in the present invention, a method for similarity classification of several historical load change curves includes:

[0059] Step S101, aligning several historical load change curves in a relative manner according to equivalent time, and analyzing the high-load sections and low-load sections of all historical load change curves on the timeline, wherein the method for judging the high-load section includes that the accumulated load value is greater than or equal to the preset value within a continuous preset time period, and the method for judging the low-load section includes that the accumulated load value is less than or equal to the preset value within a continuous preset time period.

[0060] The principle of this step is to first align all historical load change curves on the timeline by equating them to relative time, ensuring that they have the same time start and end points. Then, analyze the high-load section and low-load section of each curve on the timeline. The way to judge the high-load section is that the accumulated load value is greater than or equal to the preset value in a continuous preset time period; and the way to judge the low-load section is that the accumulated load value is less than or equal to the preset value in a continuous preset time period. The purpose of this step is to preliminarily identify the main load change characteristics of each curve and provide a basis for subsequent similarity classification.

[0061] Step S102 , based on the distribution consistency of the high load section and the low load section of each historical load change curve, the historical load change curves are classified for the first time based on similarity.

[0062] Based on the distribution consistency of the high-load section and the low-load section obtained in step S101, the historical load change curve is classified by the first similarity. The principle of this step is that if the two curves have high similarity in the distribution of the high-load section and the low-load section, then they may belong to the same type of load change mode. Through the first similarity classification, the historical load change curve can be preliminarily divided into several major categories.

[0063] Step S103, calculating the load average values ​​in the high load section and the low load section in the historical load change curve, and performing a second similarity classification on the historical load change curve classified by the first similarity according to the consistency of the load average values.

[0064] On the basis of the first similarity classification, the load average values ​​in the high-load section and the low-load section of each curve are further calculated. Then, based on the consistency of the load average values, the historical load change curves classified in the first similarity classification are classified in the second similarity classification. The principle of this step is that even if two curves are similar in section distribution, if there is a large difference in their load average values, they may still belong to different load change patterns. Through the second similarity classification, the classification of historical load change curves can be further refined.

[0065] Step S104, performing curve change similarity analysis on the historical load change curves that have undergone the second similarity classification. The method for performing curve change similarity analysis includes calculating the average value of the classified historical load change curves to obtain the category average load change curve, overlapping the category average load change curve with other classified historical load change curves, and analyzing the curve intersection area change characteristics between the two, including analyzing the area change rate of the curve intersection area as the horizontal axis advances, and the cumulative value of the curve intersection area. Based on the consistency of the area change rate and the cumulative value of the curve intersection area, the historical load change curves that have undergone the second similarity classification are subjected to a third similarity classification to obtain a number of historical load change curve groups.

[0066] After the historical load change curves have undergone the second similarity classification, the curve change similarity analysis is then performed. The principle of this step is to first calculate the average value of the classified historical load change curves to obtain the category average load change curve. Then, the category average load change curve is overlapped with other historical load change curves after classification, and the curve intersection area change characteristics between the two are analyzed. These characteristics include the area change rate of the curve intersection area as the horizontal axis advances, and the cumulative value of the curve intersection area. Based on the consistency of these characteristics, the historical load change curves classified by the second similarity classification are classified for the third time, and finally several historical load change curve groups are obtained. The purpose of this step is to ensure that the curves in each curve group have a high similarity in both overall change trends and detailed changes, so as to provide an accurate reference for subsequent load forecasting and control.

[0067] In some embodiments disclosed in the present invention, a method for extracting features of a historical load change curve in a historical load change curve group and forming a marked load change curve includes:

[0068] Step S105: a section mapping template is set for each historical load change curve in the historical load change curve group. The section mapping template includes a plurality of interconnected mapping time sections, and each mapping time section includes a plurality of mapping time points.

[0069] The principle of this step is that in order to conduct a more refined analysis of the historical load change curve, a segment mapping template needs to be set for each historical load change curve. This template divides the entire curve into several interconnected mapping time segments, and each segment contains several mapping time points. Such division is helpful for subsequent segment analysis and feature extraction of the curve.

[0070] Step S106, mapping the historical load change curve to the segment mapping template, and comparing the trend consistency of the load change curve segments belonging to the same mapping time segment, wherein the method for comparing the trend consistency of the load change curve segments includes analyzing the curve curvature of each load change curve segment corresponding to the mapping time point, and marking the corresponding curve nodes of the load change curve segment, if there is a curve curvature consistency of a number of curve nodes greater than or equal to a preset value between the load change curve segments, then it is determined that the load change curve segments have a consistent trend.

[0071] After setting the segment mapping template, map the historical load change curve onto the template. Then, compare the trend consistency of the load change curve segments belonging to the same mapping time segment. The principle of this step is that by analyzing the curve curvature of each load change curve segment at the mapping time point, the change trend of the curve at that time point can be understood. If the curve curvatures of two curves at the same time point are consistent, and the number of such consistent nodes is greater than or equal to the preset value, then it can be considered that the trends of the two curves in this time segment are consistent.

[0072] Step S107, extracting load change curve segments that belong to the same mapping time segment and have the same trend, and calculating their average values ​​to obtain a marked load change curve segment.

[0073] Based on the comparison result of step S106, the load change curve segments that belong to the same mapping time segment and have the same trend are extracted. Then, the average value of these curve segments is calculated to obtain the representative load change curve segment. The principle of this step is that by calculating the average value, the main characteristics and trends of the load change in the time segment can be extracted, thereby forming a representative representative load change curve segment.

[0074] Step S108, based on the segment-based load change curve segments in the segment mapping template, the segments are spliced ​​together, and smooth transition is performed at the splicing locations to obtain a marker load change curve.

[0075] Finally, the segments of the sign load change curve in the segment mapping template are spliced ​​together, and smooth transition is performed at the splicing to obtain a complete sign load change curve. The principle of this step is that by seamlessly connecting the sign load change curve segments of each time segment, the sign change pattern of the entire curve can be constructed. The smooth transition process is to ensure that the curve remains smooth and continuous at the splicing point to avoid abrupt turning points or breakpoints.

[0076] In summary, by performing segment mapping, trend consistency comparison, extraction and calculation of average values, splicing and smooth transition on the curves in the historical load change curve group, the characteristics of the curves can be extracted and a representative load change curve can be formed. Such a curve helps to more accurately grasp the law and trend of load changes and provide strong support for subsequent load forecasting and control.

[0077] Step S200, obtain the drilling records of the electric drilling rig of the same specification, analyze each drilling record, determine a number of driving power data, and construct a reference depth power correspondence curve based on the driving power data, wherein the horizontal axis of the depth power correspondence curve is the depth and the vertical axis is the driving power, and feature labels are configured for the reference depth power correspondence curves.

[0078] The principle of this step is to construct reference depth power corresponding curves by collecting and analyzing historical drilling records of electric drills of the same specifications, especially their drive power data. These curves reflect the drive power required by the electric drill at different drilling depths and are an important reference for subsequent real-time power control. By configuring feature tags for these reference curves, they can be easily compared and analyzed with real-time data, so as to more accurately grasp the power requirements of the electric drill.

[0079] In some embodiments disclosed in the present invention, a method for configuring feature labels for a plurality of reference depth power corresponding curves is as follows:

[0080] Step S201, scan and analyze the reference depth power corresponding curve, mark the curve nodes whose curve curvature is greater than or equal to a preset value as power change nodes, map the power change nodes to the horizontal axis of the reference depth corresponding curve, and identify the distribution of the power change nodes mapped on the horizontal axis as the first feature label.

[0081] Step S202 , determining the average driving power of a preset section before and after the power change node corresponding to the reference depth corresponding curve, and identifying the average driving power corresponding to each power change node as a second feature label.

[0082] Step S300, obtain the real-time driving power and real-time depth of the electric drill, and based on the real-time driving power and the real-time depth, construct a real-time depth power corresponding curve, and determine the feature label of the real-time depth power corresponding curve, and use the feature label and several corresponding reference depth power corresponding curves to compare the reference depth power corresponding curve with the real-time depth power corresponding curve to determine the first equivalent index of the two. If the first equivalent index is greater than or equal to a preset value, the corresponding reference depth power corresponding curve is selected as a template for correcting the power.

[0083] The principle of this step is to obtain the driving power and depth data of the electric drill in real time to construct a real-time depth power corresponding curve. Then, by using feature tags and comparison algorithms, the real-time curve is compared with the reference curve to find the reference curve that is most similar to the real-time curve. If the similarity between the real-time curve and a reference curve is greater than or equal to a preset value, the reference curve is selected as the template for power correction. The purpose of this step is to use similar patterns in historical data to predict and control current power changes, thereby improving the accuracy and efficiency of control.

[0084] In some embodiments disclosed in the present invention, a method for comparing a reference depth power corresponding curve with a real-time depth power corresponding curve to determine a first equivalent index of the two includes:

[0085] Step S301, continuously compare the relative power change nodes in the reference depth power corresponding curve and the real-time depth power corresponding curve to determine the depth difference between the two. If the depth difference between the two is less than or equal to a preset value, it is determined that there is a comparison value between the two.

[0086] Step S302, based on the depth difference of the power change nodes with continuous comparison value and the trend consistency of the preset sections before and after the power change nodes, determine the first equivalent index of the reference depth power corresponding curve and the real-time depth power corresponding curve.

[0087] In some embodiments disclosed in the present invention, the expression for calculating the first equivalent index is:

[0088] .

[0089] in, is the first equivalent indicator, is a comparison value judgment function. If the depth difference between the power change nodes is less than or equal to the preset value, then Output 1, otherwise output 0. is a trend matching degree calculation function, used to calculate the trend matching degree of the preset sections before and after the power change node, and n is the number of power change nodes to be compared continuously;

[0090] .

[0091] in, is the trend judgment function of the xth trend comparison node in the preset section before and after the power change node. If the trend corresponding to the xth trend comparison node matches, it outputs 1, otherwise it outputs 0. is the trend matching impact multiplier adjustment coefficient, b is the trend matching impact adjustment constant, The number of trend comparison nodes for the preset sections before and after the power change node.

[0092] Step S400, obtain the real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different marker load change curves, and determine a second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, determine the corresponding marker load change curve as the reference load change curve.

[0093] The principle of this step is to obtain the load change data of the power grid line in real time and construct a real-time load change curve. Then, the real-time load change curve is compared with the marker load change curve formed in step S100 to determine which historical load change patterns are most similar to the current power grid load. If the similarity between the real-time curve and a marker load change curve is greater than or equal to a preset value, the marker curve is determined to be the reference load change curve. The purpose of this step is to use the historical load change pattern to predict the future load trend of the power grid, thereby providing important reference information for the power control of the electric drilling rig.

[0094] In some embodiments disclosed in the present invention, the method of comparing the real-time load change curve with the load change curves of different signs to determine the second equivalent index includes:

[0095] Step S401, based on the principle of time proximity correspondence, determine the translation interval of the marker load change curve relative to the real-time load change curve, and based on the determined translation interval, translate the marker load change curve relative to the real-time load change curve several times, and calculate the intersection area between the marker load change curve and the real-time load change curve after each translation, and calculate the average of several intersection areas to obtain the average intersection area.

[0096] Step S402: identifying the average cross-area as a second equivalent index.

[0097] Step S500, based on the modified power template, determine the power change in the future preset time period, and based on the reference load change curve, determine the load change of the power grid line in the future preset time period, and adjust the time length of the power change based on the load change of the power grid line in the future preset time period.

[0098] The principle of this step is to predict the power change of the electric drill and the grid load change in the future preset time period based on the selected modified power template and the reference load change curve. By analyzing the possible impact of grid load changes on the power demand of the electric drill, the power change time length of the electric drill is adjusted. The purpose of this step is to ensure that the power change of the electric drill is coordinated with the grid load change to reduce the impact and interference on the grid, while ensuring the normal operation of the electric drill and the stable operation of the grid. Through the implementation of this step, the high efficiency and optimization of the grid-connected control of the electric drill can be achieved.

[0099] In some embodiments disclosed in the present invention, based on the load change of the power grid line in a future preset time period, the method for adjusting the time length of the power change includes:

[0100] In step S501, a plurality of load mapping intervals are set, and a standard intervention power change rate and a standard intervention power are set for each load mapping interval.

[0101] Step S502, based on the load mapping interval changes mapped to the reference load change curve within the future preset time period, determine the standard intervention power and the standard intervention power change rate to be called at different time nodes in the future.

[0102] Step S503, determine the predicted driving power and predicted power change rate of the modified power template at different time nodes in the future, and judge whether the predicted driving power is greater than the standard intervention power. If so, correct the predicted power change rate in combination with the standard intervention power and the standard intervention power change rate at the corresponding time node to obtain the corrected power change rate.

[0103] Step S504, based on the corrected power change rates corresponding to different future time nodes, the time length of the power change at the corresponding time nodes is adjusted.

[0104] In some embodiments disclosed in the present invention, the expression for calculating the corrected power change rate is:

[0105] .

[0106] in, is the corrected power change rate, is the standard intervention power change rate, To predict the driving power, is the standard intervention power, is the power difference impact adjustment coefficient, c is the power difference impact adjustment constant, To correct the power change rate conversion factor.

[0107] In some embodiments disclosed in the present invention, there is also disclosed an electric drilling rig grid-connected control system, comprising:

[0108] The first module is used to obtain the historical load change data of the power grid line, analyze the historical load change data of the power grid line, construct a number of historical load change curves, classify the several historical load change curves by similarity, obtain a number of historical load change curve groups, extract features of the historical load change curves in the historical load change curve groups, and form a landmark load change curve.

[0109] The second module is used to obtain the drilling records of electric drilling rigs of the same specifications, analyze each drilling record, determine a number of driving power data, and construct a reference depth power correspondence curve based on the driving power data. The horizontal axis of the depth power correspondence curve is the depth, and the vertical axis is the driving power. Feature labels are configured for a number of reference depth power correspondence curves.

[0110] The third module is used to obtain the real-time driving power and real-time depth of the electric drill, and based on the real-time driving power and real-time depth, construct a real-time depth power corresponding curve, and determine the feature label of the real-time depth power corresponding curve, and use the feature label and several corresponding reference depth power corresponding curves to compare the reference depth power corresponding curve with the real-time depth power corresponding curve to determine the first equivalent index of the two. If the first equivalent index is greater than or equal to the preset value, the corresponding reference depth power corresponding curve is selected as the template for correcting the power.

[0111] The fourth module is used to obtain the real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different sign load change curves, and determine the second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, the corresponding sign load change curve is determined as the reference load change curve;

[0112] The fifth module is used to determine the power change within a future preset time period based on the modified power template, and to determine the load change of the power grid line within the future preset time period based on the reference load change curve, and to adjust the time length of the power change based on the load change of the power grid line within the future preset time period.

[0113] The present invention discloses a method and system for controlling the connection to the grid of an electric drilling rig, and relates to the technical field of electric drilling rig control. The method and system construct and classify historical load change curves, extract a mark load change curve, analyze and determine driving power data according to drilling records of electric drilling rigs of the same specification, and construct a reference depth power corresponding curve. After obtaining the driving power and depth data of the electric drilling rig in real time, the real-time depth power corresponding curve is constructed, and a template for correcting power is selected; the real-time load change curve is constructed and compared with the mark load change curve to determine the reference load change curve; the power and load changes within a preset time period in the future are predicted by combining the template for correcting power and the reference load change curve, and the time length of the power change is adjusted accordingly. The above technical scheme of the present invention realizes the high efficiency and optimization of the connection to the grid of the electric drilling rig, and ensures the stable progress of the drilling operation and the safe operation of the power grid.

[0114] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for controlling an electric drilling rig in grid connection, characterized in that: include: Obtain historical load change data of power grid lines, analyze the historical load change data of power grid lines, construct several historical load change curves, classify the several historical load change curves by similarity, obtain several historical load change curve groups, extract features of the historical load change curves in the historical load change curve groups, and form a sign load change curve; Obtain drilling records of electric drilling rigs of the same specifications, analyze each drilling record, determine a number of driving power data, and construct a reference depth power corresponding curve based on the driving power data, wherein the horizontal axis of the depth power corresponding curve is the depth and the vertical axis is the driving power, and perform feature label configuration on a number of reference depth power corresponding curves; The real-time driving power and real-time depth of the electric drill are obtained, and based on the real-time driving power and the real-time depth, a real-time depth power corresponding curve is constructed, and a feature label is determined for the real-time depth power corresponding curve, and the feature label and several corresponding reference depth power corresponding curves are used to compare the reference depth power corresponding curve and the real-time depth power corresponding curve to determine a first equivalent index of the two, and if the first equivalent index is greater than or equal to a preset value, the corresponding reference depth power corresponding curve is selected as a template for correcting power; Acquire real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different sign load change curves, and determine a second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, determine the corresponding sign load change curve as a reference load change curve; Based on the modified power template, determine the power change in the future preset time period, and based on the reference load change curve, determine the load change of the power grid line in the future preset time period, and adjust the time length of the power change based on the load change of the power grid line in the future preset time period; The method for extracting features of the historical load change curves in the historical load change curve group and forming a marked load change curve includes: A section mapping template is set for each historical load change curve in the historical load change curve group, and the section mapping template includes a plurality of interconnected mapping time sections, and each mapping time section includes a plurality of mapping time points; Mapping the historical load change curve to the section mapping template, and comparing the trend consistency of the load change curve segments belonging to the same mapping time segment, wherein the method for comparing the trend consistency of the load change curve segments includes analyzing the curve curvature of each load change curve segment corresponding to the mapping time point, and marking the corresponding curve node of the load change curve segment, if the curve curvature of the curve nodes greater than or equal to the preset value between the load change curve segments is consistent, then it is determined that the load change curve segment trend is consistent; Extract the load change curve segments that belong to the same mapping time segment and have the same trend, and calculate their average value to obtain the marked load change curve segment; The segments of the sign load change curve in the section mapping template are spliced ​​with each other, and smooth transition is performed at the splicing locations to obtain the sign load change curve.

2. A motor grid-connected control method according to claim 1, characterized in that: The methods for similarity classification of several historical load change curves include: According to the relative method of equal time, several historical load change curves are aligned, and the high-load sections and low-load sections of all historical load change curves on the time line are analyzed, wherein the method of determining the high-load section includes that the load cumulative value is greater than or equal to the preset value in a continuous preset time period, and the method of determining the low-load section includes that the load cumulative value is less than or equal to the preset value in a continuous preset time period; Based on the distribution consistency of the high-load section and the low-load section of each historical load change curve, the historical load change curves are classified by similarity for the first time; Calculate the load average values ​​in the high load section and the low load section in the historical load change curve, and perform a second similarity classification on the historical load change curve of the first similarity classification based on the consistency of the load average values; The historical load change curves that have undergone the second similarity classification are subjected to curve change similarity analysis. The method for curve change similarity analysis includes calculating the average value of the historical load change curves after classification to obtain the category average load change curve, overlapping the category average load change curve with other historical load change curves after classification, and analyzing the curve intersection area change characteristics between the two, including analyzing the area change rate of the curve intersection area as the horizontal axis advances, and the cumulative value of the curve intersection area. Based on the consistency of the area change rate and the cumulative value of the curve intersection area, the historical load change curves that have undergone the second similarity classification are subjected to a third similarity classification to obtain several historical load change curve groups.

3. The electric drilling rig grid connection control method according to claim 1, characterized in that: Method for configuring feature labels for several reference depth power corresponding curves: Scan and analyze the reference depth power corresponding curve, mark the curve nodes whose curve curvature is greater than or equal to a preset value as power change nodes, map the power change nodes to the horizontal axis of the reference depth corresponding curve, and identify the distribution of the power change nodes mapped on the horizontal axis as the first feature label; The average driving power of the preset sections before and after the power change node corresponding to the reference depth corresponding curve is determined, and the average driving power corresponding to each power change node is identified as a second feature label.

4. The electric drilling rig grid connection control method according to claim 3, characterized in that: The method of comparing the reference depth power corresponding curve and the real-time depth power corresponding curve to determine the first equivalent index of the two includes: Continuously compare the relative power change nodes in the reference depth power corresponding curve and the real-time depth power corresponding curve to determine the depth difference between the two. If the depth difference between the two is less than or equal to a preset value, it is determined that the two are worth comparing; Based on the depth difference of the power change nodes with continuous comparison value and the trend consistency of the preset sections before and after the power change nodes, the first equivalent index of the reference depth power corresponding curve and the real-time depth power corresponding curve is determined.

5. The method for controlling the electric drilling rig to be connected to the grid according to claim 4, characterized in that: The expression for calculating the first equivalent index is: ； in, is the first equivalent indicator, is a comparison value judgment function. If the depth difference between the power change nodes is less than or equal to the preset value, then Output 1, otherwise output 0. is a trend matching degree calculation function, used to calculate the trend matching degree of the preset sections before and after the power change node, and n is the number of power change nodes to be compared continuously; ； in, is the trend judgment function of the xth trend comparison node in the preset section before and after the power change node. If the trend corresponding to the xth trend comparison node matches, it outputs 1, otherwise it outputs 0. is the trend matching impact multiplier adjustment coefficient, b is the trend matching impact adjustment constant, The number of trend comparison nodes for the preset sections before and after the power change node.

6. The electric drilling rig grid connection control method according to claim 1, characterized in that: The method of comparing the real-time load change curve with the load change curves of different signs to determine the second equivalent index includes: Based on the time proximity corresponding principle, determine the translation interval of the sign load change curve relative to the real-time load change curve, and based on the determined translation interval, translate the sign load change curve relative to the real-time load change curve several times, and calculate the intersection area between the sign load change curve and the real-time load change curve after each translation, and calculate the average of several intersection areas to obtain the average intersection area; The average cross-sectional area was determined as a second equivalent index.

7. The method for controlling the electric drilling rig to be connected to the grid according to claim 1, characterized in that: Based on the load change of the power grid line in the future preset time period, the method for adjusting the time length of the power change includes: Several levels of load mapping intervals are set, and a standard intervention power change rate and a standard intervention power are set for each load mapping interval; Based on the load mapping interval changes mapped to the reference load change curve within the future preset time period, determine the standard intervention power and standard intervention power change rate to be called at different time nodes in the future; Determine the predicted driving power and predicted power change rate of the modified power template at different time nodes in the future, judge whether the predicted driving power is greater than the standard intervention power, and if so, correct the predicted power change rate in combination with the standard intervention power and the standard intervention power change rate at the corresponding time node to obtain the corrected power change rate; Based on the corrected power change rates corresponding to different future time nodes, the time length of the power change at the corresponding time nodes is adjusted.

8. The electric drilling rig grid-connected control method according to claim 7, characterized in that: The expression for calculating the corrected power change rate is: ； in, is the corrected power change rate, is the standard intervention power change rate, To predict the driving power, is the standard intervention power, is the power difference impact adjustment coefficient, c is the power difference impact adjustment constant, To correct the power change rate conversion factor.

9. An electric drilling grid-connected control system, used to execute the electric drilling grid-connected control method according to any one of claims 1 to 8, characterized in that: include: The first module is used to obtain the historical load change data of the power grid line, analyze the historical load change data of the power grid line, construct a number of historical load change curves, classify the historical load change curves by similarity, obtain a number of historical load change curve groups, extract the characteristics of the historical load change curves in the historical load change curve groups, and form a symbol load change curve; The second module is used to obtain drilling records of electric drilling rigs of the same specifications, analyze each drilling record, determine a number of driving power data, and construct a reference depth power corresponding curve based on the driving power data. The horizontal axis of the depth power corresponding curve is the depth, and the vertical axis is the driving power. Feature labels are configured for a number of reference depth power corresponding curves; The third module is used to obtain the real-time driving power and real-time depth of the electric drill, and based on the real-time driving power and real-time depth, construct a real-time depth power corresponding curve, and determine the feature label of the real-time depth power corresponding curve, and use the feature label and several corresponding reference depth power corresponding curves to compare the reference depth power corresponding curve with the real-time depth power corresponding curve to determine the first equivalent index of the two. If the first equivalent index is greater than or equal to a preset value, the corresponding reference depth power corresponding curve is selected as a template for correcting power; The fourth module is used to obtain the real-time load change data of the power grid line, and construct a real-time load change curve based on the real-time load change data, compare the real-time load change curve with different sign load change curves, and determine the second equivalent index based on the comparison result. If the second equivalent index is greater than or equal to a preset value, the corresponding sign load change curve is determined as the reference load change curve; The fifth module is used to determine the power change within a future preset time period based on the modified power template, and to determine the load change of the power grid line within the future preset time period based on the reference load change curve, and to adjust the time length of the power change based on the load change of the power grid line within the future preset time period.

Images