An optimization control method of a petroleum drilling rig hybrid power system

Abstract

This application discloses an optimized control method for a hybrid power system of an oil drilling rig, relating to the field of oil drilling rig technology. The method includes: acquiring high-frequency impact power data; calculating the overdraft-equivalent fuel quantity and energy margin ratio based on the high-frequency impact power data and the current available energy of the supercapacitor; extracting charging and discharging characteristic data from the high-frequency impact power data, and processing the charging and discharging characteristic data using the energy margin ratio to obtain the battery's heat-equivalent fuel quantity; acquiring the transient power difference within the current preset control cycle, and constructing allocation weights based on the overdraft-equivalent fuel quantity and the heat-equivalent fuel quantity; and allocating energy supply based on the allocation weights to the transient power difference, generating a first power command for the battery and a second power command for the supercapacitor to adjust the energy supply ratio between the battery and the supercapacitor. This application achieves the technical effect of avoiding generator stalling caused by supercapacitor overdraft.

Description

Technical Field

[0001] This application relates to the field of oil drilling rig technology, and specifically to an optimized control method for a hybrid power system of an oil drilling rig. Background Technology

[0002] During the tripping and jacking operations of oil drilling rigs, diesel generator sets are typically connected in parallel with batteries, supercapacitors, and other equipment to form a hybrid power system, providing continuous and stable basic power. Oil drilling rig tripping and jacking operations are highly repetitive, with long lifting cycles for a single drill pipe.

[0003] Existing hybrid power systems generally use fixed filter distribution to cope with long-cycle heavy loads and high-frequency jamming impacts during the lifting process. However, during the lifting operation that lasts for tens of seconds, the supercapacitor is very likely to be completely depleted in the first half. Once the supercapacitor is depleted, the subsequent high-frequency impacts will be forced to be transferred to the diesel generator set, causing the generator set to suddenly be subjected to a large transient load, that is, the engine stalls, resulting in a surge in fuel consumption and a sharp deterioration in emissions. Summary of the Invention

[0004] To address the technical problem in related technologies where fixed filter allocation leads to sudden surges in generator loads, resulting in a sharp increase in fuel consumption and a drastic deterioration in emissions, this application provides an optimized control method for a hybrid power system of an oil drilling rig.

[0005] The specific technical solution adopted is as follows: Obtain the high-frequency impact power data of the previous drill pipe lifting cycle; Based on high-frequency impact power data and the current available energy of the supercapacitor, the fuel consumption and energy margin ratio of the supercapacitor overdraft are calculated. Charge and discharge characteristic data are extracted from high-frequency impact power data. The charge and discharge characteristic data are then calculated and processed using the energy margin ratio to obtain the fuel consumption equivalent to the heat generated by the battery. Obtain the transient power difference within the current preset control cycle, and construct allocation weights based on the fuel quantity calculated from overdraft and the fuel quantity calculated from heat generation; Based on the allocation weights, the power supply is allocated according to the transient power difference, generating a first power command for the battery and a second power command for the supercapacitor, so as to adjust the power supply ratio between the battery and the supercapacitor based on the first power command and the second power command.

[0006] In one possible implementation of this application, based on high-frequency impact power data and the current available energy of the supercapacitor, the overdraft-equivalent fuel quantity and energy margin ratio of the supercapacitor are calculated, including: The expected high-frequency impact energy is calculated based on the integral value of the high-frequency impact power data during the drill pipe hoisting cycle. Based on the expected high-frequency impact energy and the current available energy of the supercapacitor, the fuel consumption equivalent to the overdraft of the supercapacitor is calculated. The energy margin ratio of the supercapacitor is determined based on the ratio between available energy and expected high-frequency impact energy.

[0007] In one possible implementation of this application, the expected high-frequency impact energy is calculated based on the integral value of high-frequency impact power data during the drill pipe hoisting cycle, including: Extract multiple power points with values ​​greater than zero from the high-frequency impact power data during the drill pipe lifting cycle; The expected high-frequency impact energy is obtained by integrating and accumulating the data at each power point.

[0008] In one possible implementation of this application, the overdraft-equivalent fuel consumption of the supercapacitor is calculated based on the expected high-frequency impact energy and the current available energy of the supercapacitor, including: Obtain the current terminal voltage of the supercapacitor; Based on the terminal voltage and the preset energy constant, the available energy that the supercapacitor can currently release is calculated. Based on the difference between the expected high-frequency impact energy and the available energy, the available energy gap is calculated. If the available energy gap is positive, the overdraft equivalent fuel consumption of the supercapacitor is calculated based on the available energy gap and the preset transient fuel consumption rate.

[0009] In one possible embodiment of this application, the charge / discharge characteristic data includes the single-cycle power alternation amplitude and cycle frequency. The charge / discharge characteristic data is then calculated using an energy margin ratio to obtain the fuel consumption equivalent to the battery's heat generation, including: The net alternating amplitude value that actually penetrates to the battery is obtained by calculating the proportional attenuation of the single power alternating amplitude value through the energy margin ratio. The amount of fuel equivalent to the heat generated by the battery is calculated based on the net alternation amplitude and cycle frequency.

[0010] In one possible implementation of this application, the fuel consumption equivalent to the heat generated by the battery is calculated based on the net alternation amplitude and cycle frequency, including: Calculate the first ratio between the net alternating amplitude value and the preset bus rated voltage; The internal heat increment is calculated based on the product of the first ratio and the cycle frequency. The internal heat increment is mapped to the fuel consumption calculated based on the battery's heat output.

[0011] In one possible implementation of this application, an allocation weight is constructed based on the fuel consumption calculated from overdraft and the fuel consumption calculated from heat generation, including: The total weight base is calculated based on the sum of the fuel consumption calculated from overdraft and the fuel consumption calculated from heat. The first weight of the battery is determined based on the ratio between the overdraft-calculated fuel amount and the total weight base. The second weight of the supercapacitor is determined based on the ratio between the fuel consumption calculated from heat generation and the total weight base. The weights are determined based on the first and second weights.

[0012] In one possible implementation of this application, power supply is allocated based on the transient power difference according to the allocation weight, generating a first power command for the battery and a second power command for the supercapacitor, including: Multiply the first weight by the transient power difference to obtain the first power command of the battery; Multiplying the second weight by the transient power difference yields the second power command of the supercapacitor.

[0013] In one possible implementation of this application, before acquiring the high-frequency impact power data of the previous drill pipe hoisting cycle, the method further includes: Obtain historical power data from the previous drill pipe hoisting cycle; Low-pass filtering is applied to historical power data to obtain low-frequency reference power data; The high-frequency impulse power data is obtained by subtracting the historical power data from the low-frequency reference power data.

[0014] In one possible implementation of this application, extracting charge-discharge characteristic data from high-frequency impulse power data includes: By using the raindrop counting algorithm, multiple local extreme points in the high-frequency impact power data are processed to obtain a discrete set of sequential extreme points; Determine the amplitude difference that constitutes the charge-discharge closed-loop data in the set of extreme points of the sequence; The amplitude difference is taken as the amplitude of a single power alternation, and the number of times the amplitude of a single power alternation occurs in the set of extreme points of the sequence is counted as the cycle frequency. By pairing and mapping the cycle frequency with the single power alternation amplitude, charge and discharge characteristic data are obtained.

[0015] This application has, but is not limited to, the following technical effects: In this application, high-frequency impact power data from the previous drill pipe lifting cycle is acquired. This data is then analyzed to obtain the fuel consumption equivalent to the overdraft of the supercapacitor and the fuel consumption equivalent to the heat generated by the battery. Based on these fuel consumption values, a weighting system for the supercapacitor and battery is established. Then, according to the transient power difference within the current preset control cycle and the weighting system, a first power command for the battery and a second power command for the supercapacitor are generated. Finally, the energy supply ratio between the battery and supercapacitor is adjusted based on these commands. This achieves adaptive deflection of micro-commands according to the health status of the energy storage device. Without increasing hardware costs, this adaptive adjustment of the energy supply operation between the battery and supercapacitor effectively avoids generator stalling caused by supercapacitor overdraft, reducing the surge in fuel consumption and the sharp deterioration in emissions. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the first embodiment of the optimized control method for the hybrid power system of an oil drilling rig according to this application. Figure 2 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application. Detailed Implementation

[0017] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0018] This application provides an optimized control method for a hybrid power system of an oil drilling rig. In the first embodiment of this optimized control method for an oil drilling rig hybrid power system, refer to... Figure 1 This system, hereinafter referred to as the system, is applied to the hybrid power system of oil drilling rigs. The hybrid power system for oil drilling rigs includes supercapacitors and batteries, and comprises: Step S10: Obtain the high-frequency impact power data of the previous drill pipe lifting cycle.

[0019] As an example, before elaborating on the specific steps of this application, it is necessary to first clarify the control feedforward prediction mechanism of this application. Since the tripping and tripping operations of oil drilling rigs exhibit highly repetitive characteristics of identical drill pipe weight and fixed wellbore trajectory, two adjacent macroscopic tripping cycles have a strong temporal correlation in terms of basic mechanical load and friction jamming probability. Based on this engineering implementation premise, the method of this invention uses the historical macroscopic electrical data of the previous tripping cycle as the feedforward prediction benchmark for the current tripping cycle, thereby coordinating the power distribution within the microscopic control cycle.

[0020] Since the subsequent cost assessment of this method strictly depends on the historical power sequence of the previous complete drill pipe hoisting cycle, the historical feature buffer in the controller memory is empty during the cold start phase when the system is first powered on. If the empty buffer is read directly for closed-loop calculation, the control program will crash due to reading empty values.

[0021] During the cold start phase described above, the system performs the following initialization operations: First, the system allocates a fixed-length storage space in the controller's memory. After allocating the storage space, the system marks it as a historical feature buffer. After marking the historical feature buffer, the system reads a set of factory-calibrated standard lifting power sequences pre-stored in read-only memory (ROM). After reading the standard lifting power sequence, the system writes the entire sequence into the historical feature buffer. After writing, the system uses this factory-calibrated data as the initial input reference for the first control cycle and allows the drilling rig system to enter normal mechanical lifting operation, thus completely avoiding the risk of calculation stagnation during the initial stage of system startup.

[0022] As an example, the drill pipe hoisting cycle can be the time cycle of a single hoisting action in actual drilling operations, which can be 30 to 60 seconds.

[0023] Specifically, after the drilling rig enters normal mechanical lifting operation mode, the system is based on the drill pipe lifting cycle (defined as the time axis). The system performs real-time rolling data updates as follows: A speed encoder installed on the winch monitors the mechanical speed of the winch drum in real time. After monitoring this speed, the system identifies the complete motion process of the winch drum speed increasing from zero and then decreasing back to zero. The system defines this complete motion process as one drill pipe hoisting cycle.

[0024] As an example, the lifting process of an oil drilling rig involves both a gradual and continuous high-power basic mechanical load from the weight of the drill pipe itself, and a high-frequency abrupt load generated by friction and jamming of the drill string within the wellbore. These two types of loads have completely different consumption mechanisms for supercapacitors and batteries, necessitating frequency domain separation.

[0025] Among them, the high-frequency impact power data is obtained by separating and processing the historical active power data on the common DC bus. The high-frequency impact power data is data that characterizes the high-frequency and severe load fluctuations caused by abnormal frictional resistance of the drill bit.

[0026] Before step S10, the following are included: Obtain historical power data from the previous drill pipe hoisting cycle; As an example, historical power data can be composed of instantaneous active power data at various time points during the previous drill pipe hoisting cycle, specifically: During the identified drill pipe hoisting cycle, the system collects instantaneous active power data on the common DC bus in real time at a preset high sampling frequency (e.g., 500 Hz). After collecting the instantaneous active power data, the system concatenates these discrete data points in chronological order to form a discrete time series data. At the end of the current macroscopic hoisting cycle, the system writes this discrete time series data into the aforementioned historical feature buffer to replace the old data. After the full overwrite, the system extracts the latest sequence from the buffer and records it as historical power data. This historical power data This will serve as the initial input data for subsequently separating different types of electrical loads.

[0027] Low-pass filtering is applied to historical power data to obtain low-frequency reference power data.

[0028] As an example, the system receives the historical power data extracted above. Receive the sequence Then, the system calls the preset digital low-pass filter module. After calling the digital low-pass filter module, the system sets the cutoff frequency of the filter. In order to accurately separate the smooth power caused by the weight of the drill bit, the system sets the cutoff frequency to a specific extremely low frequency constant range (for example, set to the range of 0.1 Hz to 0.5 Hz, preferably 0.2 Hz in this embodiment).

[0029] As an example, after setting the cutoff frequency, the system uses this digital low-pass filter to process the aforementioned historical power data. After performing a low-pass filter, the system removes all high-frequency alternating components with frequencies higher than 0.2 Hz from the sequence. After filtering out these high-frequency alternating components, the system outputs a smooth data sequence, which is defined as the low-frequency reference power data characterizing the continuous lifting of the hook by the winch and the weight of the heavy drilling tool. .

[0030] The high-frequency impulse power data is obtained by subtracting the historical power data from the low-frequency reference power data.

[0031] As an example, output low-frequency reference power data Then, the system will generate the original historical power data. Subtract low-frequency reference power data By performing this simple time-corresponding subtraction operation, the system extracts the residual data. The system defines this residual data as high-frequency impact power data. This high-frequency impact power data It characterizes the high-frequency, severe load fluctuations caused by abnormal frictional resistance of the drill bit.

[0032] Step S20: Based on the high-frequency impact power data and the current available energy of the supercapacitor, calculate the overdraft equivalent fuel quantity and energy margin ratio of the supercapacitor.

[0033] As an example, the current available energy of a supercapacitor can be the actual available energy that can be released at the moment, representing the electrical energy reserves that the supercapacitor can use to mitigate subsequent shocks at this time.

[0034] As an example, the overdraft equivalent fuel quantity is used to characterize the relative deterioration of the generator's sudden load increase after the capacitor is depleted, and the energy margin ratio is used to characterize the physical absorption / suppression capability of the current remaining energy of the capacitor for subsequent high-frequency impacts.

[0035] Step S20 further includes steps S21 to S23: Step S21: Calculate the expected high-frequency impact energy based on the integral value of the high-frequency impact power data during the drill pipe lifting cycle.

[0036] As an example, the expected high-frequency impact energy represents the total increase in work that the hybrid energy storage system is expected to do if a jamming friction of the same intensity as the previous drill pipe lifting cycle occurs.

[0037] Step S21 includes: Extract multiple power points with values ​​greater than zero from the high-frequency impact power data during the drill pipe lifting cycle.

[0038] The expected high-frequency impact energy is obtained by integrating and accumulating the data at each power point.

[0039] As an example, the system targets the received high-frequency impulse power data. The system extracts power point data with values ​​greater than zero (i.e., the load portion representing the energy drawn by the busbar). After extracting the power point data with values ​​greater than zero, the system calculates the corresponding values ​​of this power point data over the entire time length of the current drill pipe hoisting cycle (e.g., time interval). The system performs an integral accumulation operation in the time domain. After performing this operation, the system obtains the expected high-frequency impact energy within that period. .

[0040] Step S22: Based on the expected high-frequency impact energy and the current available energy of the supercapacitor, calculate the overdraft equivalent fuel quantity of the supercapacitor.

[0041] As an example, the available energy gap is determined based on the difference between the expected high-frequency impact energy and the current available energy of the supercapacitor. Then, based on the available energy gap and the fuel consumption rate constant, the final fuel consumption equivalent of the supercapacitor overdraft is calculated.

[0042] Step S22 includes: Obtain the current terminal voltage of the supercapacitor.

[0043] Based on the terminal voltage and a preset energy constant, the available energy that the supercapacitor can currently release is calculated.

[0044] Specifically, the system uses voltage sensors installed across the capacitor assembly to collect the current terminal voltage of the supercapacitor in real time. After collecting the current terminal voltage, the system retrieves the nominal farad capacitance constant and the safety lower limit voltage constant of the supercapacitor, which are pre-written into the read-only memory. To prevent hardware sampling errors from causing negative square roots or other errors in the subsequent energy calculation formula, the system compares the current terminal voltage with the safety lower limit voltage. If the current terminal voltage is lower than the safety lower limit voltage, the system forcibly assigns the value of the safety lower limit voltage to the current terminal voltage. After determining the terminal voltage, the system performs the following energy calculation formula: .in, The nominal farad capacity constant is retrieved. Given the current terminal voltage as determined above, This is the safety lower limit voltage constant. Through the above exponentiation and multiplication operations, the system accurately calculates the actual usable energy that the supercapacitor can currently release. Among them, available energy The parameter is calculated using absolute values ​​and is always greater than or equal to 0.

[0045] The available energy gap is calculated based on the difference between the expected high-frequency impact energy and the available energy.

[0046] As an example, the system will use the expected high-frequency impact energy Subtract the above available energy After performing the subtraction operation, the system calculates the available energy gap. Calculate the available energy gap. Then, the system determines the magnitude of the gap to determine the subsequent compensation calculation logic: In particular, to prevent meaningless boundary collapses in integration operations due to extremely stable operating conditions, the system implements a boundary fault protection mechanism: If the expected high-frequency impact energy calculated within the current cycle Equal to zero, or the calculated available energy gap A value less than or equal to zero indicates that the capacitor currently has sufficient remaining energy and no destructive impact has occurred. At this point, the system directly assigns a pre-set, positive-zero baseline depletion constant (characterizing the steady-state standby equivalent fuel consumption of the energy storage device; a value of 0.1-0.5 ml / cycle is recommended) to the supercapacitor's overdraft-equivalent fuel consumption. This basic loss constant represents the bottom-line penalty weight of the system in a steady state, ensuring subsequent performance based on... When constructing an inverse proportional weight allocation, the control logic will not crash due to division by zero or negative numbers.

[0047] If the available energy gap is positive, the overdraft equivalent fuel consumption of the supercapacitor is calculated based on the available energy gap and the preset transient fuel consumption rate.

[0048] As an example, regarding the determination of an available energy gap If the value is greater than zero, the system will fill the gap. Multiply by a preset transient fuel consumption rate constant (e.g., based on offline bench calibration, set to a value per kilojoule). (equivalent fuel cost per milliliter). After performing the multiplication operation, the system adds the aforementioned basic loss constant to the product result to calculate the equivalent fuel consumption of the amplified supercapacitor. After the calculation is completed, the system will convert the overdraft into fuel consumption. Saved to the controller's memory register.

[0049] As an example, the available energy gap The larger the value, the more severe the energy overdraft of the supercapacitor. The final calculated overdraft of the supercapacitor is equivalent to the amount of fuel consumed. The value also increases accordingly. This value does not represent the actual physical fuel consumption, but rather serves as the dimensionless penalty base in the cost function, participating in subsequent microscopic power allocation calculations.

[0050] Step S23: Determine the supercapacitor energy margin ratio based on the ratio between available energy and expected high-frequency impact energy.

[0051] As an example, the system retrieves a preset minimum normal value from the controller. (For example, the value is) This constant is specifically designed to prevent hardware-level crashes caused by a zero denominator during division operations.

[0052] retrieve the smallest positive number Subsequently, the system anticipates high-frequency impact energy. Add this minimal normal number This yields a sum. After obtaining this sum, the available energy... Divide by the sum of the above values.

[0053] After performing the above division calculation, the system calculates the energy margin ratio of the supercapacitor. Calculate the energy margin ratio. Then, the system forcibly limits the ratio to a certain value. To the numerical value Within the closed interval (i.e., if the calculated value is greater than 1, the forced limit is 1). In this definition, the energy margin ratio of the supercapacitor. The closer to the value This indicates that the more charge a supercapacitor has remaining, the stronger its ability to physically absorb and suppress subsequent high-frequency pulses.

[0054] Step S30: Extract charge and discharge characteristic data from the high-frequency impact power data, and calculate the charge and discharge characteristic data using the energy margin ratio to obtain the fuel consumption equivalent to the heat generated by the battery.

[0055] As an example, charge / discharge characteristic data includes the amplitude of a single power alternation. Its corresponding cycle frequency The data set is used to reflect the impact characteristics of the battery. The charge and discharge characteristic data completely eliminates the harmless shallow high-frequency ripples and retains only the deep charge and discharge cycle information that is most heat-generating and destructive.

[0056] As an example, the heat-induced fuel consumption calculation is based on the equivalent energy minimization strategy (ECMS), which maps the increase in internal polarization heat generated by the battery due to high-frequency current impact to a dimensionless penalty fuel base through a preset heat-induced fuel consumption calculation constant.

[0057] As an example, in the parallel DC bus architecture of a hybrid power system, the supercapacitor has extremely low hardware impedance and a much faster response speed than the battery, naturally absorbing high-frequency fluctuations preferentially. Therefore, the actual pulse damage experienced by the battery is strictly limited by the current remaining energy of the supercapacitor. A cross-proportional attenuation calculation must be performed on the supercapacitor's energy state and the extracted alternating characteristic set to filter out pulse signals that have been smoothed by the supercapacitor, in order to accurately calculate the true remaining heat energy acting on the battery.

[0058] The step S30, which involves extracting charge-discharge characteristic data from the high-frequency impact power data, includes: By using the raindrop counting algorithm, multiple local extreme points in the high-frequency impact power data are processed to obtain a discrete set of sequential extreme points.

[0059] As an example, the raindrop counting algorithm is used to transform complex and irregular alternating loads into complete closed loops. It is often used in the field of mechanical fatigue to extract the deep drop amplitude and the number of cycles that constitute a complete closed charge-discharge cycle by filtering out clutter.

[0060] As an example, the set of sequence extrema includes a discrete data set with multiple local extrema, specifically: First, iterate through the received high-frequency impulse power data. The system scans and extracts all local maxima (representing discharge spikes) and local minima (representing feedback charging spikes) that change over time in the high-frequency impulse power data. After extracting these extreme points, the system connects them sequentially according to their occurrence time to construct a discrete piecewise linear data set. This set is denoted as the sequence extreme point set. .

[0061] Determine the amplitude difference that constitutes the charge-discharge closed loop data in the set of extreme points of the sequence.

[0062] As an example, construct the set of extreme points of this sequence. Then, the system sets a sliding read cursor in the controller's memory. After setting the read cursor, the system starts from the set of extreme points in the sequence. Starting with the first data point, four consecutive adjacent extreme points are read sequentially. To clearly illustrate the algorithm's decision-making logic, the system labels these four extreme points as point 1, point 2, point 3, and point 4, respectively.

[0063] After reading four consecutive extreme points, the system enters the core step of determining a four-point closed loop: The system calculates the absolute difference in power values ​​between point 1 and point 2, and records it as the first amplitude difference; it calculates the absolute difference between point 2 and point 3, and records it as the second amplitude difference; it calculates the absolute difference between point 3 and point 4, and records it as the third amplitude difference. After calculating the above three consecutive absolute amplitude differences, the system compares the magnitude of the second amplitude difference with the first amplitude difference and the third amplitude difference, respectively.

[0064] When the value of the second amplitude difference is simultaneously greater than or equal to the values ​​of the first and third amplitude differences, it indicates that the deep power drop trough or peak in the middle completely encloses the adjacent peaks or troughs. Based on this, the system determines that a complete deep charge-discharge closed loop is formed between points 2 and 3.

[0065] The amplitude difference is taken as the amplitude of a single power alternation, and the number of times the amplitude of a single power alternation occurs in the set of extreme points of the sequence is counted as the cycle frequency.

[0066] As an example, for cases where a closed loop is determined to exist, taking the second amplitude difference mentioned above as an example, the system extracts the specific value of the second amplitude difference and records it as the amplitude of a single power alternation. Among them, subscripts As a sequence number, it represents the currently extracted number. A pulse cycle exhibiting closed-loop characteristics. Record the amplitude of a single power alternation. Then, the system accumulates the number of times the specific amplitude occurs in memory and records this number as the cycle frequency. .

[0067] As an example, in order to extract all single power alternation amplitudes from the set of sequence extrema, and to ignore this already processed high-frequency oscillation feature in subsequent traversals, the system removes points 2 and 3 from the set of sequence extrema. The data is completely deleted from the set, and points 1 and 4 are reconnected to generate a new, reduced set. If the value of the second amplitude difference is less than either the first or third amplitude difference, this indicates that points 2 and 3 are merely an unclosed shallow clutter segment. The system then slides the cursor backward by one extreme point, rereading points 2, 3, 4, and 5 as the four new comparison points. The system continues to repeat the steps of calculating the absolute difference, comparison size, extracting alternating amplitude and frequency, sliding the cursor, and generating a new set until the set of sequence extreme points is reached. If the number of remaining extreme points is less than four, it indicates that the entire sequence has been extracted.

[0068] By pairing and mapping the cycle frequency with the single power alternation amplitude, charge and discharge characteristic data are obtained.

[0069] As an example, after the traversal is complete, the system will retrieve all successfully extracted single-power alternating amplitude values. Its corresponding cycle frequency After pairwise mapping and pairing, the system outputs this set of two-dimensional data to generate charge and discharge characteristic data reflecting the impact characteristics of the battery. This charge / discharge characteristic data The harmless shallow high-frequency ripples have been completely eliminated, and only the deep charge and discharge cycle information, which is most heat-generating and destructive, has been retained.

[0070] Among them, step S30, which calculates the charge and discharge characteristic data based on the energy margin ratio to obtain the fuel consumption equivalent to the heat generated by the battery, includes steps S31 to S32: Step S31: Calculate the proportional attenuation of the single power alternation amplitude using the energy margin ratio to obtain the actual net alternation amplitude that penetrates to the battery.

[0071] As an example, consider the energy margin ratio of supercapacitors. As an attenuation operator, dynamic multiplication reduces the single alternating amplitude value extracted by the rainflow counting algorithm. This cross-device characteristic-level cross-attenuation calculation accurately reflects the true damping effect of capacitors on high-frequency pulses in parallel circuits, overcoming the shortcomings of existing technologies that cannot quantify internal cumulative damage.

[0072] As an example, for each set of single power alternation amplitude values The system will display the values. Subtract the energy margin ratio of the supercapacitor mentioned above After performing the subtraction operation, the system obtains the remaining penetration ratio; after obtaining the remaining penetration ratio, the system compares it with the single power alternation amplitude value currently being traversed. After performing the multiplication operation, the system obtains the remaining net alternating amplitude value acting on the battery.

[0073] Step S32: Calculate the fuel consumption equivalent to the heat generated by the battery based on the net alternating amplitude and cycle frequency.

[0074] As an example, the net alternating amplitude value is first converted into an equivalent thermal damage cost, which is the internal heat increment, and then the internal heat increment is mapped to the fuel consumption equivalent to the heat of the battery.

[0075] Step S32 includes: Calculate the first ratio between the net alternating amplitude and the preset bus rated voltage.

[0076] The internal heat increment is calculated based on the product of the first ratio and the cycle frequency.

[0077] As an example, to convert the aforementioned net alternating amplitude into an equivalent thermal damage cost, the system needs to perform an integral accumulation calculation in conjunction with the battery's own electrical parameters. Specifically, because the rainflow counting algorithm only retains the amplitude and frequency when extracting features, omitting the pulse duration information in the time dimension, it cannot be calculated directly using Joule's law. Therefore, the system pre-calibrates a fixed empirical parameter by extracting the average duration of high-frequency jamming pulses from historical bench tests, denoted as the reference action time constant for a single cycle. (In actual engineering implementation, this constant may take the value of, for example, ) Instant A fixed value within a second interval, preferably... (seconds). This reference action time constant. Used to equivalently reconstruct the thermal accumulation time of alternating pulses in rainflow characteristics without temporal information.

[0078] As an example, internal heat increment The calculation method is as follows: Among them: subscript Indicates the traversal index. This represents the total number of characteristic pulse pairs extracted from the set.

[0079] Indicates the amplitude of a single power alternation. This indicates the energy margin ratio of a supercapacitor.

[0080] This represents the net alternating amplitude value that actually penetrates to the battery after being absorbed and smoothed by the supercapacitor.

[0081] The preset bus rated voltage, or the average of the bus voltage sequence of the previous period.

[0082] This indicates that the above net alternating power amplitude is converted into the net alternating current amplitude acting on the battery, which is also the first ratio.

[0083] This is the nominal internal resistance constant of the battery. The reference action time constant for a single cycle, as specified above. This represents the frequency of cycles in which this characteristic amplitude occurs.

[0084] This demonstrates the physical property that heat is proportional to the square of the electric current in Joule heating.

[0085] This formula shows that if the energy margin ratio The larger the value, the smaller the penetration ratio of the inner brackets. After square magnification, the final calculated value is... The shrinkage is exponential. This objectively reflects the strong protective effect of sufficient capacitance on the battery. It needs to be clarified that the calculated... It is not the total physical heat generation of the battery, but rather the equivalent of the internal polarization heat generation caused solely by deep charge and discharge fluctuations, in addition to the stable heating at the reference DC.

[0086] The internal heat increment is mapped to the fuel consumption calculated based on the battery's heat output.

[0087] As an example, by performing an equivalent cost mapping, the system calculates the equivalent of the internal polarization heating increment. Multiply by the thermal fuel consumption conversion constant pre-written in the read-only memory (calibrated based on the equivalent relationship between battery purchase cost, cycle life, and fuel unit price; a recommended value is 0.1-0.3 ml per kilojoule of polarization heat). After performing the multiplication operation, the system adds a preset, positive-to-zero battery baseline depreciation constant to the product. After performing the addition operation, the system finally calculates the fuel consumption equivalent to the battery's thermal load. .

[0088] Step S40: Obtain the transient power difference within the current preset control cycle, and construct the allocation weight based on the fuel quantity calculated from overdraft and the fuel quantity calculated from heat generation.

[0089] As an example, the preset control period can be a time period of 2 milliseconds to 5 milliseconds, defined as the time axis. During this preset control cycle, the system no longer performs complex feature extraction and historical integration calculations. Instead, it directly obtains the current transient gap through a high-frequency sensor, which serves as the absolute reference value for triggering the hybrid energy storage unit to perform energy compensation.

[0090] Because the mechanical fuel speed regulation system of the diesel generator set has significant physical lag, its output capacity remains relatively constant when dealing with millisecond-level sudden load changes, and it cannot keep up with the rapid peak changes of the total bus load in real time. Therefore, the system must accurately calculate the transient power gap that cannot be covered by relying solely on generator power supply.

[0091] Specifically, the system uses a power sensor module installed on the inverter side of the drilling rig to collect in real time the total transient power consumed by the entire inverter load on the bus at the current moment. Collect the total transient power consumption of this bus. Subsequently, the system synchronously reads the current steady-state output power of the generator from the engine control unit (ECU) of the diesel generator set via the on-site controller area network (CAN bus) communication interface. Read the generator's steady-state output power. Then, the system will obtain the total transient power consumption of the bus as described above. Subtract the generator's steady-state output power After performing the subtraction operation, the system calculates the transient power difference that must be provided by both the battery and the supercapacitor. Calculate the transient power difference. The system then saves this data for subsequent power cutting and allocation.

[0092] As an example, an allocation weight is constructed based on the fuel consumption calculated from overdraft and the fuel consumption calculated from heat generation. The allocation weight includes a first weight for the battery and a second weight for the supercapacitor. After determining the allocation weights of the two, a corresponding power command is generated, and a power allocation operation is performed on the supercapacitor and the battery.

[0093] Step S40 includes: The total weight base is calculated based on the sum of the fuel consumption calculated from overdraft and the fuel consumption calculated from heat generation.

[0094] As an example, the overdraft amount of the supercapacitor stored in the controller's memory register is extracted and converted into fuel quantity. Fuel consumption calculated based on battery heat generation After extracting the two penalty constants mentioned above, the system will... Plus After performing the addition operation, the system obtains a total weight base for overall allocation.

[0095] The first weight of the battery is determined based on the ratio between the overdraft-calculated fuel amount and the total weight base.

[0096] As an example, the system performs a cross-weighting operation, whereby, for the battery allocation link, the system discounts the overdraft representing the capacitor state. Divide by the total weight base mentioned above to obtain the first weight on the battery side.

[0097] The second weight of the supercapacitor is determined based on the ratio between the fuel consumption calculated from heat generation and the total weight base.

[0098] The weights are determined based on the first and second weights.

[0099] As an example, for a supercapacitor distribution link, the system translates the heat generated, representing the battery state, into fuel consumption. Divide by the total weight base mentioned above to obtain the second weight on the supercapacitor side.

[0100] Step S50: Based on the allocation weight, power supply is allocated according to the transient power difference, and a first power command for the battery and a second power command for the supercapacitor are generated, so as to adjust the power supply ratio between the battery and the supercapacitor based on the first power command and the second power command.

[0101] As an example, the system will measure the bus transient power difference. Multiply by the corresponding allocation weights to calculate the first power command of the battery. With the second power command of the supercapacitor Then, through these two power commands, the power supply ratio between the battery and the supercapacitor is adjusted.

[0102] Step S50 includes: Multiplying the first weight by the transient power difference yields the first power command for the battery.

[0103] As an example, the first power command The calculation method can be: in, Indicates the transient power difference. This indicates the first weight.

[0104] Multiplying the second weight by the transient power difference yields the second power command of the supercapacitor.

[0105] As an example, the second power command The calculation method can be: in, Indicates the transient power difference. This indicates the second weight.

[0106] Specifically, in the above cross division operation, if the overdraft is converted into fuel quantity... The value is significantly greater than the fuel consumption calculated based on calorific value. (This indicates that the supercapacitor is about to be completely depleted during the current lifting operation), and the formula calculation will cause the battery-side allocation weight to approach a value of 1. This inverse proportional cross-calculation forces the battery to actively bear the vast majority of the load within the current micro-millisecond. This allows the supercapacitor to retain its baseline energy, successfully achieving adaptive deflection intervention of macroscopic historical states on microscopic transient commands.

[0107] As an example, after generating the first power command and the second power command, they are converted into underlying current reference values ​​and issued for execution. Specifically: Due to the strict physical hardware limitations of the underlying bidirectional DC / DC converter in practical engineering, the single-sided target power command calculated based on inverse proportions may be excessive in extreme cases, leading to overcurrent damage to components. Therefore, strict limiting protection logic must be executed before issuing the command. The specific operation is as follows: The system retrieves the pre-calibrated rated maximum allowable power of the battery bidirectional DC-DC converter. and the rated maximum allowable power of the supercapacitor bidirectional DC-DC converter. After retrieving the maximum allowable power, the system compares it with the battery's first power command. With its rated maximum allowable power .like Greater than The system will The forced limit is the rated maximum allowable power. The value. After forced limiting, the system will reduce the power difference exceeding the limit (i.e., the original value). minus (Part of) superimposed on the second power command of the supercapacitor This is to ensure that the total power shortfall of the busbar is compensated. Similarly, the system compares the second power command of the supercapacitor. With its rated maximum allowable power If an over-limit occurs, a forced limiting operation will also be performed. Specifically, when the supercapacitor's command also exceeds its rated maximum allowable power, the remaining power difference after the second over-limit will be directly borne by the diesel generator set, or the torque / speed reduction protection command of the drilling rig's frequency converter will be triggered to forcibly reduce the total load demand of the bus and the power flow of the closed-loop system.

[0108] After completing the limiting protection operation, the system enters the current conversion stage. Because the underlying bidirectional DC-DC converter is limited by the active current source drive mode, the power command must be converted into an electrically readable specific current reference value. The system obtains the actual terminal voltages of the battery and supercapacitor at the current moment. After obtaining the actual terminal voltages, the system divides the limited target power command for the battery by the actual terminal voltage of the battery to obtain a current quotient, which is used as the underlying current reference value on the battery side. Simultaneously, the system divides the limited target power command for the supercapacitor by the actual terminal voltage of the supercapacitor to obtain the underlying current reference value on the supercapacitor side.

[0109] After generating the underlying current reference values, the system sends these two reference values ​​to the proportional-integral (PI) regulators inside the bidirectional DC-DC converters connected to the battery and the supercapacitor, respectively. Upon receiving the reference values, the PI regulator calculates the current deviation signal between the received current reference values ​​and the feedback current actually collected by the sensors. Based on this deviation signal, the PI regulator outputs a corresponding pulse-width modulation (PWM) duty cycle using known drive logic. After outputting the duty cycle, the PWM signal directly drives the insulated-gate bipolar transistors inside the bidirectional DC-DC converter to perform high-frequency switching operations. By performing the above-mentioned current regulation closed-loop operation within a micro-cycle, the converter, as an active current source, takes over the transient power distribution of the parallel bus, forcing the battery and supercapacitor to actively inject energy into the common DC bus strictly according to the power ratio calculated at the macro-cost. This ultimately completes the hybrid power optimization distribution closed loop within this millisecond-level control cycle.

[0110] This application provides an optimized control method for a hybrid power system of an oil drilling rig. In this method, high-frequency impact power data from the previous drill pipe lifting cycle is acquired. This data is analyzed to obtain the fuel consumption equivalent to the overdraft of the supercapacitor and the fuel consumption equivalent to the heat generated by the battery. Based on these fuel consumption values, a weighting system is constructed for the supercapacitor and battery. Then, according to the transient power difference within the current preset control cycle and the weighting system, a first power command for the battery and a second power command for the supercapacitor are generated. Finally, the energy supply ratio between the battery and the supercapacitor is adjusted based on these commands. This achieves adaptive deflection of micro-commands according to the health status of the energy storage equipment. Without increasing hardware costs, the method adaptively adjusts the energy supply operation between the battery and the supercapacitor, effectively avoiding generator stalling caused by supercapacitor overdraft and reducing the surge in fuel consumption and the sharp deterioration in emissions.

[0111] Reference Figure 2 , Figure 2 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of this application.

[0112] like Figure 2 As shown, the optimized control device for the hybrid power system of the oil drilling rig may include: a processor 1001, a memory 1003, and a communication bus 1002. The communication bus 1002 is used to realize the connection and communication between the processor 1001 and the memory 1003.

[0113] Optionally, the optimized control equipment for the hybrid power system of the oil drilling rig may also include a user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, a WiFi module, etc. The user interface may include a display screen and an input submodule such as a keyboard; optional user interfaces may also include standard wired or wireless interfaces. The network interface may include standard wired or wireless interfaces (such as a Wi-Fi interface).

[0114] Those skilled in the art will understand that Figure 2 The optimized control equipment structure of the oil drilling rig hybrid power system shown in the figure does not constitute a limitation on the optimized control equipment of the oil drilling rig hybrid power system. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0115] like Figure 2As shown, the memory 1003, serving as a storage medium, may include an operating system, a network communication module, and an optimization control program for the oil drilling rig hybrid power system. The operating system is a program that manages and controls the hardware and software resources of the optimization control equipment for the oil drilling rig hybrid power system, supporting the operation of the optimization control program and other software and / or programs. The network communication module is used to enable communication between the various components within the memory 1003, as well as communication with other hardware and software in the optimization control system of the oil drilling rig hybrid power system.

[0116] exist Figure 2 In the optimized control device for the oil drilling rig hybrid power system shown, the processor 1001 is used to execute the optimized control program for the oil drilling rig hybrid power system stored in the memory 1003, and to implement the steps of the optimized control method for the oil drilling rig hybrid power system described above.

[0117] The specific implementation of the optimized control device for the hybrid power system of the oil drilling rig in this application is basically the same as the embodiments of the optimized control method for the hybrid power system of the oil drilling rig described above, and will not be repeated here.

[0118] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0119] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0120] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0121] The above are merely preferred embodiments of this application and do not limit the scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the scope of protection of this application.

[0122] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0123] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An optimized control method for a hybrid power system of an oil drilling rig, characterized in that, The method, applied to a hybrid power system for an oil drilling rig, the oil drilling rig hybrid power system including a supercapacitor and a battery, comprises: Obtain the high-frequency impact power data of the previous drill pipe lifting cycle; Based on the high-frequency impact power data and the current available energy of the supercapacitor, the overdraft equivalent fuel consumption and energy margin ratio of the supercapacitor are calculated. Charge and discharge characteristic data are extracted from the high-frequency impact power data, and the charge and discharge characteristic data are calculated and processed using the energy margin ratio to obtain the fuel consumption equivalent to the heat generated by the battery. Obtain the transient power difference within the current preset control cycle, and construct allocation weights based on the overdraft-equivalent fuel quantity and the heat-equivalent fuel quantity; Based on the allocation weight, the transient power difference is used to allocate power, and a first power command for the battery and a second power command for the supercapacitor are generated, so as to adjust the power supply ratio between the battery and the supercapacitor based on the first power command and the second power command.

2. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 1, characterized in that, The calculation of the overdraft-equivalent fuel consumption and energy margin ratio of the supercapacitor based on the high-frequency impact power data and the current available energy of the supercapacitor includes: Based on the integral value of the high-frequency impact power data during the drill pipe lifting cycle, the expected high-frequency impact energy is calculated. Based on the expected high-frequency impact energy and the current available energy of the supercapacitor, the overdraft equivalent fuel consumption of the supercapacitor is calculated. The energy margin ratio of the supercapacitor is determined based on the ratio between the available energy and the expected high-frequency impact energy.

3. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 2, characterized in that, The calculation of the expected high-frequency impact energy based on the integral value of the high-frequency impact power data during the drill pipe hoisting cycle includes: Extract multiple power points with values ​​greater than zero from the high-frequency impact power data during the drill pipe lifting cycle; The expected high-frequency impact energy is obtained by integrating and accumulating the power point data.

4. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 2, characterized in that, The calculation of the overdraft-equivalent fuel consumption of the supercapacitor based on the expected high-frequency impact energy and the current available energy of the supercapacitor includes: Obtain the current terminal voltage of the supercapacitor; Based on the terminal voltage and the preset energy constant, the available energy that the supercapacitor can currently release is calculated. Based on the difference between the expected high-frequency impact energy and the available energy, the available energy gap is calculated; If the available energy gap is positive, the overdraft equivalent fuel consumption of the supercapacitor is calculated based on the available energy gap and the preset transient fuel consumption rate.

5. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 1, characterized in that, The charge / discharge characteristic data includes the single-cycle power alternation amplitude and cycle frequency. The calculation and processing of the charge / discharge characteristic data using the energy margin ratio to obtain the fuel consumption equivalent to the battery's heat generation includes: The net alternating amplitude value that actually penetrates to the battery is obtained by proportionally attenuating the single power alternating amplitude value by using the energy margin ratio. Based on the net alternation amplitude and the cycle frequency, the fuel consumption equivalent to the heat generated by the battery is calculated.

6. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 5, characterized in that, The calculation of the fuel consumption equivalent to the heat generated by the battery based on the net alternating amplitude and the cycle frequency includes: Calculate the first ratio between the net alternating amplitude value and the preset bus rated voltage; The internal heat increment is calculated based on the product of the first ratio and the cycle frequency. The internal heat increment is mapped to the fuel consumption calculated based on the heat generated by the battery.

7. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 1, characterized in that, The process of constructing allocation weights based on the overdraft-converted fuel quantity and the heat-converted fuel quantity includes: The total weight base is calculated based on the sum of the overdraft equivalent fuel quantity and the heat equivalent fuel quantity; The first weight of the battery is determined based on the ratio between the overdraft-converted fuel amount and the total weight base. The second weight of the supercapacitor is determined based on the ratio between the fuel consumption calculated from the heat generation and the total weight base. The allocation weights are determined based on the first weight and the second weight.

8. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 7, characterized in that, The step of allocating power based on the allocation weights to the transient power difference, and generating a first power command for the battery and a second power command for the supercapacitor, includes: Multiply the first weight by the transient power difference to obtain the first power command of the battery; Multiplying the second weight by the transient power difference yields the second power command of the supercapacitor.

9. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 1, characterized in that, Before acquiring the high-frequency impact power data of the previous drill pipe hoisting cycle, the method further includes: Obtain historical power data from the previous drill pipe hoisting cycle; The historical power data is low-pass filtered to obtain low-frequency reference power data; The high-frequency impact power data is obtained by subtracting the historical power data from the low-frequency reference power data.

10. The optimized control method for a hybrid power system of an oil drilling rig as described in claim 1, characterized in that, The extraction of charge-discharge characteristic data from the high-frequency impact power data includes: The raindrop counting algorithm is used to process multiple local extreme points in the high-frequency impact power data to obtain a discrete set of sequential extreme points. Determine the amplitude difference that constitutes the charge-discharge closed-loop data in the set of extreme points of the sequence; The amplitude difference is taken as the amplitude of a single power alternation, and the number of times the amplitude of a single power alternation occurs in the set of extreme points of the sequence is counted as the cycle frequency. The cycle frequency and the single power alternation amplitude are paired and mapped to obtain charge and discharge characteristic data.

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