A Flexible Synchronous Coordination Optimization Method for the Frequency and Voltage of a Beam Pumping System

Abstract

The present invention provides a flexible synchronous coordination optimization method for the frequency and voltage of a beam pumping system, which relates to the technical field of oil and gas exploitation and includes the following steps: respectively taking the frequency weight coefficient and the voltage weight coefficient as optimization design variables; obtaining the preferred range of the coefficients; establishing a flexible synchronous coordination optimization model for the frequency and voltage of the beam pumping system; substituting the preferred range of the coefficients into the flexible synchronous coordination optimization model for the frequency and voltage of the beam pumping system to obtain the optimal coefficients, and adjusting the frequency and voltage of the beam pumping system according to the optimal coefficients to complete the dynamic optimization of the frequency and voltage of the beam pumping system. The present invention aims at the periodic fluctuating load of the pumping system, takes the time-varying frequency and time-varying voltage within the period as optimization variables, takes the lowest input power of the motor as the optimization goal, and uses the genetic algorithm to complete the dynamic optimization of the frequency and voltage, so as to achieve the purpose of reducing the load fluctuation of the pumping system and saving energy and reducing consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploitation, and in particular, to a flexible synchronization coordination optimization method for the frequency and voltage of a beam pumping system. Background Art

[0002] With the deepening of oil and gas exploitation and the production of crude oil, the formation supply capacity is insufficient to support the natural flow of oil wells. To improve the efficiency of oil exploitation, artificial lift equipment has been more and more widely used. At present, the artificial lift equipment mainly includes: pumping units, electrical submersible pumps, screw pumps, high-pressure gas lift and other lifting processes. The beam pumping unit occupies the main market share due to its simple structure, reliable performance and low price. The beam pumping unit mainly consists of a sucker rod pump, sucker rods, polished rod, four-bar mechanism, reduction gearbox, belt and motor. The motor drives the crank to rotate through the speed increase and torque increase effects of the belt and the reduction gearbox, and the four-bar mechanism converts the rotational motion into the linear motion of the rod string. According to the movement direction of the rod string, the operation process of the pumping unit is divided into the upstroke and the downstroke. In the upstroke, the liquid located inside the tubing and above the traveling valve is lifted, and when the standing valve opens, the liquid in the casing is sucked into the pump barrel; in the downstroke, when the traveling valve opens, the fluid in the pump barrel is discharged, and the liquid load located above the traveling valve is transferred and acts on the standing valve, and the sucker rod string is unloaded. This "up suction and down discharge" pumping method, combined with the motion characteristics of the crank-rocker mechanism and the comprehensive action of the balance weight, results in a "double-hump" type bidirectional fluctuation of the ground load of the beam pumping system. The periodic fluctuating load not only affects the balance and reliability of the mechanical system, but also increases the required rated power of the motor to meet the peak torque demand, resulting in the motor running in the low-load area for most of the time, with low motor power utilization rate and serious energy consumption waste. In particular, the negative torque generated in a local time period drags the motor to generate reverse power, reducing the energy transmission efficiency and polluting the power grid, causing unstable power supply of the power grid and energy consumption waste.

[0003] In recent years, with the reduction of the cost of automation equipment and the construction of digital oilfields, the beam pumping system based on variable frequency and voltage control technology has been widely used in oilfields. In particular, the flexible variable frequency and voltage control technology can keep the pumping speed of the pumping equipment constant while adjusting the frequency and speed in real time according to the system load fluctuation within a cycle, adjusting the voltage and magnetic flux, and reducing the system load fluctuation by redistributing the inertial load, eliminating reverse power generation, and achieving energy conservation and consumption reduction.

[0004] However, there are still deficiencies in the current flexible variable frequency and voltage control technology. Its step-by-step optimization scheme of optimizing the frequency first and then the voltage does not consider the coupling effect of flexible variable frequency and flexible voltage regulation, restricting the optimal selection range of frequency and voltage and reducing the energy-saving effect. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to propose a flexible synchronous coordination optimization method for the frequency and voltage of a beam pumping system, which expands the preferred range of frequency and voltage and improves the energy-saving effect while considering the coupling effect of flexible frequency conversion and flexible voltage regulation. It solves the problem that the prior art reduces the energy-saving effect due to the failure to consider the coupling effect of flexible frequency conversion and flexible voltage regulation.

[0006] The technical means adopted by the present invention are as follows:

[0007] A flexible synchronous coordination optimization method for the frequency and voltage of a beam pumping system, comprising the following steps:

[0008] Considering the influence of the time-varying driving frequency and time-varying driving voltage of the motor on the dynamic characteristics and energy consumption of the beam pumping system, the frequency weight coefficient and voltage weight coefficient are respectively used as optimization design variables;

[0009] The time-varying driving frequency and time-varying driving voltage of the motor in the beam pumping system within one cycle are expressed in the form of a periodic function by Fourier transform, and the Fourier transform coefficients that determine the change forms of the time-varying frequency and time-varying voltage are used as optimization design variables;

[0010] The time-varying driving frequency function and time-varying driving voltage function are expanded into Fourier series by Fourier transform to obtain the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient;

[0011] Sensitivity analysis is performed on the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient to obtain the preferred range of the coefficients;

[0012] Establish a flexible model for the frequency and voltage of the beam pumping system;

[0013] An algorithm that can optimize discrete and continuous variables simultaneously and has good global search ability is used to optimize the preferred range of the coefficients to obtain the optimized preferred range.

[0014] The optimized preferred range is substituted into the flexible synchronous coordination optimization model of the frequency and voltage of the beam pumping system to obtain the optimal coefficients, and the frequency and voltage of the beam pumping system are adjusted according to the optimal coefficients to complete the dynamic optimization of the frequency and voltage of the beam pumping system.

[0015] Furthermore, sensitivity analysis is performed on the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient to obtain the preferred range of the coefficients, which specifically includes:

[0016] Adjust the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient according to the load change of the pumping system. When the load increases, the motor driving frequency decreases, and the motor driving voltage increases; when the load decreases, the motor driving frequency increases, and the motor driving voltage decreases. Determine the frequency and voltage change ranges respectively according to the output capacity of the electric control device at the oil field site, and then determine the coefficient optimization range. The initial frequency range is 20Hz to 80Hz, and the voltage range is 0V to 220V.

[0017] Furthermore, establish a flexible model of frequency and voltage for the beam pumping system, specifically including:

[0018] Taking the frequency and voltage weight coefficients and Fourier coefficients as design variables, with the lowest system energy consumption as the optimization goal, set the production constant constraint according to the oil well inflow characteristic curve and the pump outflow characteristic curve, set the stroke rate constant constraint for the average motor speed within the period, set the frequency and voltage amplitude limit constraint according to the frequency converter adjustment ability and the motor bearing capacity, set the torque constraint for the bearing capacity of each node of the ground transmission mechanism, set the fatigue fracture constraint for the tensile strength of the sucker rod string, and set the balance degree constraint for the peak ratio of the motor input power during the up and down strokes.

[0019] Furthermore, algorithms that can optimize discrete and continuous variables simultaneously and have good global search capabilities include genetic algorithms, wolf pack algorithms, particle swarm algorithms, and bird flock algorithms.

[0020] Furthermore, the genetic algorithm specifically includes:

[0021] Within the determined coefficient optimization range, randomly generate 2N time-varying driving frequency functions as the initial population P1(0); 2 time-varying driving voltage functions as the initial population P2(0), and input the frequency weight coefficient, frequency Fourier coefficient, voltage weight coefficient, and voltage Fourier coefficient as gene variables.

[0022] Retain a group of candidate solutions in each iteration, select the better individuals from the solution group according to the index of smaller load fluctuation of the pumping system, use genetic operators to combine these individuals to generate a new generation of candidate solution groups, and repeat this process until the convergence index of the smallest load fluctuation of the pumping system is satisfied. Finally, output the population P1(n) and population P2(m) that minimize the load fluctuation of the pumping system.

[0023] Furthermore, the Fourier series expansion of the time-varying driving frequency function is:

[0024]

[0025] The Fourier series expansion of the time-varying driving voltage function is:

[0026]

[0027] Wherein: a0 is the frequency weight coefficient, c0 is the voltage weight coefficient, a j , b j , c j , d j are Fourier coefficients, and T is a period of the pumping unit system.

[0028] The present invention also provides a storage medium, which includes a stored program. When the program runs, it executes the flexible synchronous coordination optimization method for the frequency and voltage of the beam pumping unit system described in any one of the above.

[0029] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. The processor runs through the computer program to execute the flexible synchronous coordination optimization method for the frequency and voltage of the beam pumping unit system described in any one of the above.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] Based on the principles of variable frequency speed regulation and variable voltage magnetic regulation, the present invention aims at the periodic fluctuating load of the pumping unit system. At the same time, taking the time-varying frequency and time-varying voltage within the period as the optimization variables and the lowest input power of the motor as the optimization goal, comprehensively considering the bearing capacity constraints of each mechanical component of the pumping unit system and the matching relationship between the output capacity of the motor and the load, the genetic algorithm is adopted to complete the dynamic optimization of the frequency and voltage, so as to achieve the purpose of reducing the load fluctuation of the pumping unit system and saving energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 It is a flowchart of the flexible synchronous coordination optimization method for the frequency and voltage of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0035] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present invention described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily limit to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0036] As Figure 1 shown, the present invention provides a flexible synchronous coordination optimization method for the frequency and voltage of a beam pumping system, including the following steps:

[0037] Considering the influence of the time-varying driving frequency and time-varying driving voltage of the motor on the dynamic characteristics and energy consumption of the beam pumping system, the frequency weight coefficient and voltage weight coefficient are respectively used as the optimization design variables;

[0038] The time-varying driving frequency and time-varying driving voltage of the motor in a beam pumping system within one cycle are represented in the form of periodic functions by Fourier transform, and the Fourier transform coefficients that determine the change patterns of the time-varying frequency and time-varying voltage are used as the optimization design variables;

[0039] The time-varying driving frequency function and time-varying driving voltage function are expanded into Fourier series through Fourier transform to obtain the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficients and voltage Fourier coefficients;

[0040] The Fourier series expanded from the time-varying driving frequency function is:

[0041]

[0042] The Fourier series expanded from the time-varying driving voltage function is:

[0043]

[0044] Where: a0 is the frequency weight coefficient, c0 is the voltage weight coefficient, a j , b j , c j , d j are Fourier coefficients, and T is a cycle of the pumping system.

[0045] Perform sensitivity analysis on the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient to obtain the preferred range of the coefficients;

[0046] Adjust the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient according to the load change of the pumping system. That is, when the load increases, the driving frequency of the motor decreases, but the driving voltage of the motor increases. When the load decreases, the driving frequency of the motor increases, but the driving voltage of the motor decreases. Finally, determine the frequency and voltage change ranges according to the output capacity of the electric control device on the oil field site, and then determine the optimization range of the above coefficients. The initial frequency range is 20Hz to 80Hz, and the voltage range is 0V to 220V.

[0047] Establish a flexible model of the frequency and voltage of the beam pumping system;

[0048] Taking the frequency and voltage weight coefficients and Fourier coefficients as design variables, with the lowest system energy consumption as the optimization goal, set the production constant constraint according to the oil well inflow characteristic curve and the pump outflow characteristic curve, set the constant stroke constraint for the average motor speed within the period, set the frequency and voltage amplitude limit constraint according to the frequency converter adjustment ability and the motor bearing capacity, set the torque constraint according to the bearing capacity of each node of the ground transmission mechanism, set the fatigue fracture constraint according to the tensile strength of the sucker rod string, and set the balance degree constraint according to the peak ratio of the motor input power in the up and down strokes.

[0049] Optimize the preferred range of the coefficients by using an algorithm that can optimize discrete and continuous variables simultaneously and has good global search ability to obtain the optimized preferred range. The algorithms that can optimize discrete and continuous variables simultaneously and have good global search ability include genetic algorithm, wolf pack algorithm, particle swarm algorithm, and bird flock algorithm.

[0050] The specific genetic algorithm includes:

[0051] Within the determined coefficient optimization range, randomly generate 2N (N = 1, 2, 3...) time-varying driving frequency functions as the initial population P1(0); 2 time-varying driving voltage functions as the initial population P2(0), and input the frequency weight coefficient, frequency Fourier coefficient, voltage weight coefficient, and voltage Fourier coefficient as gene variables;

[0052] In each iteration, retain a group of candidate solutions, select the better individuals from the solution group according to the index of smaller load fluctuation of the pumping system, and use genetic operators (selection, crossover, and mutation) to combine these individuals to generate a new generation of candidate solution groups. Repeat this process until the convergence index of the smallest load fluctuation of the pumping system is satisfied, and finally output the population P1(n) and population P2(m) that minimize the load fluctuation of the pumping system.

[0053] Substitute the optimized preferred range into the flexible synchronous coordination optimization model of the frequency and voltage of the beam pumping system to obtain the optimal coefficients. Adjust the frequency and voltage of the beam pumping system according to the optimal coefficients. Finally, achieve "high load, low frequency, high voltage, low load, high frequency, low voltage" for the pumping system, "cut the peaks and fill the valleys" for the load torque, reduce the load fluctuation, and complete the dynamic optimization of the frequency and voltage of the beam pumping system.

[0054] The present invention also provides a storage medium, which includes a stored program. When the program runs, it executes the flexible synchronous coordination optimization method of the frequency and voltage of the beam pumping system described in any one of the above.

[0055] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and operable on the processor. The processor runs the computer program to execute the flexible synchronous coordination optimization method of the frequency and voltage of the beam pumping system described in any one of the above.

[0056] In the above embodiments of the present invention, the descriptions of the respective embodiments have their own focuses. For the parts not detailed in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0057] In several embodiments provided by the present application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the units or modules can be in electrical or other forms.

[0058] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0059] In addition, in each embodiment of the present invention, the functional units can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0060] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs.

[0061] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A flexible synchronous coordination optimization method for the frequency and voltage of a beam pumping system, characterized in that The steps are as follows: Considering the influence of the time-varying driving frequency and time-varying driving voltage of the motor on the dynamic characteristics and energy consumption of the beam pumping system, the frequency weight coefficient and voltage weight coefficient are respectively used as the optimization design variables; The time-varying driving frequency and time-varying driving voltage of the beam pumping system within one cycle are expressed as periodic function forms by Fourier transform, and the Fourier transform coefficients that determine the variation forms of the time-varying frequency and time-varying voltage are used as the optimization design variables; The time-varying driving frequency function and time-varying driving voltage function are expanded into Fourier series through Fourier transform to obtain the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient; Perform sensitivity analysis on the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient to obtain the preferred range of the coefficients; Establish a frequency and voltage flexible model for the beam pumping system; Use an algorithm that can optimize discrete and continuous variables simultaneously and has good global search ability to optimize the preferred range of the coefficients to obtain the optimized preferred range; Substitute the optimized preferred range into the frequency and voltage flexible synchronous coordination optimization model of the beam pumping system to obtain the optimal coefficients, and adjust the frequency and voltage of the beam pumping system according to the optimal coefficients to complete the dynamic optimization of the frequency and voltage of the beam pumping system.

2. The flexible synchronous coordination optimization method for the frequency and voltage of the beam pumping system according to claim 1, characterized in that, Perform sensitivity analysis on the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient to obtain the preferred range of the coefficients, specifically including: Adjust the frequency weight coefficient, voltage weight coefficient, frequency Fourier coefficient, and voltage Fourier coefficient according to the load change of the pumping system. When the load increases, the motor driving frequency decreases and the motor driving voltage increases; when the load decreases, the motor driving frequency increases and the motor driving voltage decreases; determine the frequency and voltage change ranges respectively according to the output capacity of the electric control device at the oil field site, and then determine the preferred range of the coefficients. The initial frequency range is 20Hz~80Hz, and the voltage range is 0V~220V.

3. The frequency and voltage flexible synchronization and coordination optimization method for the beam pumping system according to claim 1, characterized in that, Establish a frequency and voltage flexible model for the beam pumping system, specifically including: Taking the frequency and voltage weight coefficients and Fourier coefficients as design variables, with the lowest system energy consumption as the optimization goal, setting the production constant constraint according to the oil well inflow characteristic curve and the pump outflow characteristic curve, setting the stroke constant constraint for the average motor speed within the cycle, setting the frequency and voltage amplitude limit constraint according to the frequency converter adjustment ability and motor bearing capacity, setting the torque constraint according to the bearing capacity of each node of the ground transmission mechanism, setting the fatigue fracture constraint according to the tensile strength of the sucker rod string, and setting the balance degree constraint according to the peak ratio of the motor input power in the up and down strokes.

4. The frequency and voltage flexible synchronization and coordination optimization method for the beam pumping system according to claim 1, characterized in that, Algorithms that can optimize discrete and continuous variables simultaneously and have good global search ability include genetic algorithms, wolf pack algorithms, particle swarm algorithms, and bird flock algorithms.

5. The frequency and voltage flexible synchronization and coordination optimization method for the beam pumping system according to claim 4, characterized in that, The specific genetic algorithm includes: Within the determined coefficient optimization range, randomly generate 2N time-varying driving frequency functions as the initial population P1(0); 2 time-varying driving voltage functions as the initial population P2(0), and input the frequency weight coefficient, frequency Fourier coefficient, voltage weight coefficient, and voltage Fourier coefficient as gene variables; In each iteration, a set of candidate solutions is retained, and better individuals are selected from the solution group according to the index of less load fluctuation of the pumping system. The genetic operator is used to combine these individuals to generate a new generation of candidate solution groups. This process is repeated until the convergence index of the minimum load fluctuation of the pumping system is satisfied. Finally, the populations P1(n) and P2(m) that minimize the load fluctuation of the pumping system are outputted.

6. The frequency and voltage flexible synchronization and coordination optimization method for the beam pumping system according to claim 1, characterized in that The Fourier series expansion of the time-varying driving frequency function is as follows: The Fourier series expansion of the time-varying driving voltage function is as follows: Where: a0 is the frequency weight coefficient, c0 is the voltage weight coefficient, a j , b j , c j , d j are Fourier coefficients, and T is a period of the pumping system.

7. A storage medium, characterized in that, The storage medium includes a stored program, wherein when the program runs, it executes the flexible synchronous coordination optimization method for the frequency and voltage of the beam pumping system according to any one of claims 1 to 6.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein, The processor runs through the computer program to execute the flexible synchronous coordination optimization method for the frequency and voltage of the beam pumping system according to any one of claims 1 to 6.

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