Grid-connected operation coordination optimization control method and system for multi-machine common tail water system of hydropower station

Abstract

The invention relates to the technical field of power system automation and intelligent control, and discloses a hydropower station multi-machine common tail water system grid-connected operation coordination optimization control method and system, and the method comprises the steps: building a hydropower station multi-machine common tail water surge chamber and tail water tunnel grid-connected operation regulation system mathematical model; adopting a Hopf bifurcation theory to solve a stability domain of control parameters of each unit speed regulator of the system; establishing a multi-objective optimization function, and selecting a disturbance load proportion of each unit and a speed regulator control parameter as optimized decision variables; the decision variables are optimized through MOPSO; all the control schemes are evaluated and analyzed by using a fuzzy satisfaction evaluation method, and the scheme with the highest standardized satisfaction is selected; and verifying the effectiveness of the multi-target coordination control strategy through simulation comparative analysis. According to the method, coordinated distribution of the load among the units is considered, the dynamic regulation performance of the units, the surge chamber and the power grid frequency is integrally improved, and technical support is provided for safe and stable operation of the hydroelectric generating set and the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation and intelligent control, and in particular to a method and system for coordinated optimization control of grid-connected operation of a multi-machine common tailwater system in a hydropower station. Background Art

[0002] As a clean and renewable energy source, hydropower mainly plays the role of peak regulation, frequency regulation and phase regulation in the power grid. As a regulator and stabilizer of the power grid, its capacity accounts for an increasing proportion in the power system and has become an important pillar of the global dual carbon goals. Hydropower units are the core of hydropower production in the hydropower energy system. They play important roles such as peak regulation, frequency regulation, phase regulation and base load in my country's new power system and are stabilizers and regulators of the power system.

[0003] The stable operation of the water transmission and power generation system of a hydropower station is an important prerequisite for ensuring the safety and reliability of the power grid. During the construction process of a hydropower station, affected by multiple factors, a multi-machine shared hydraulic unit design is often adopted. However, this design will cause hydraulic interference between the units, reducing the stability of the unit operation. In addition, when the unit is connected to the grid, due to the mutual coupling characteristics of the unit's hydraulic system, mechanical system, and electrical system, the electrical interference of the power grid and each unit will be transmitted to the hydraulic and mechanical systems of each unit, greatly reducing the safety, stability, and regulation quality of the unit.

[0004] At present, domestic and foreign scholars have established a water-machine-electric coupling system model for hydropower units in response to the complex water delivery system of hydropower stations, explored the stability and dynamic characteristics of the units, and proposed a multi-objective optimization strategy for the control parameters of the hydropower unit speed governor. However, the stability and dynamic characteristics of the coupled system of the multi-unit shared tailwater system of the hydropower station have not been analyzed, especially the mutual influence between the units, the surge chamber and the power grid has not been revealed. In addition, the current optimization strategy mainly targets a single unit, ignoring the coordination of the regulation performance of the characteristic quantities between the power grid, the surge chamber, and the units. The above defects seriously restrict the high-quality regulation of the multi-unit shared tailwater system of the hydropower station. Summary of the invention

[0005] In view of the fact that in the actual regulation and control of existing units, multiple units in a hydropower station share a tailwater system and are connected to the grid, which causes the dynamic performance of each unit to interfere with each other during the regulation process, the present invention is proposed to suppress the disturbance characteristics between the units and improve the regulation quality of multiple units.

[0006] Therefore, the problem to be solved by the present invention is how to establish a model of a hydropower station multi-machine shared tailwater system grid-connected operation regulation system to achieve coordinated optimization control of the operation safety and regulation performance of each unit. In order to solve the above technical problems, the present invention provides the following technical solutions, a method for coordinated optimization control of a hydropower station multi-machine shared tailwater system grid-connected operation, including: establishing a mathematical model of a regulation system for the grid-connected operation of a hydropower station multi-machine shared tailwater surge chamber and tailwater tunnel; using the Hopf bifurcation theory to solve the stability domain of the governor control parameters of each unit of the hydropower station multi-machine shared tailwater surge chamber and tailwater tunnel grid-connected operation regulation system; establishing a multi-objective optimization function that simultaneously considers the dynamic regulation performance of the frequency of each unit, the dynamic regulation performance of the power grid and the surge chamber water level, and selecting the disturbance load proportion and governor control parameters of each unit as the optimization decision variables; using MOPSO to optimize the decision variables and obtain a control scheme; using the fuzzy satisfaction evaluation method to evaluate and analyze all control schemes, and selecting the scheme with the highest standardized satisfaction as the final coordinated optimization control scheme.

[0007] As a preferred solution of the coordinated optimization control method for the grid-connected operation of the tailwater system of a hydropower station with multiple machines shared, the invention provides: the establishment of a mathematical model of a regulation system for the grid-connected operation of a tailwater surge chamber and a tailwater tunnel shared by multiple machines in a hydropower station includes establishing a subsystem mathematical model including pressure pipeline equations of each unit, turbine torque flow equations of each unit, generator equations of each unit, governor equations of each unit, grid equivalent equations, surge chamber continuity equations, and tailwater tunnel head-flow equations; Combining the physical relationships and operational characteristics of each subsystem, the mathematical models of all subsystems are integrated to construct a mathematical model of the overall regulation system for the grid-connected operation of a multi-machine shared tailwater system in a hydropower station.

[0008] As a preferred solution of the coordinated optimization control method for the grid-connected operation of the tailwater system of a hydropower station described in the present invention, wherein: the stability domain of solving the control parameters of the speed governors of each unit of the grid-connected operation regulation system of the tailwater surge chamber and tailwater tunnel of the hydropower station includes converting the mathematical model of the grid-connected operation regulation system of the tailwater surge chamber and tailwater tunnel of the hydropower station into a matrix form according to the Hopf bifurcation principle , is the state vector, is the bifurcation parameter, let , find the equilibrium point of the system.

[0009] As a preferred solution of the coordinated optimization control method for the grid-connected operation of the tailwater system of a hydropower station described in the present invention, the stable domain of the speed governor control parameters of each unit of the tailwater surge chamber and tailwater tunnel grid-connected operation regulation system of the hydropower station multi-machine shared by the tailwater surge chamber and tailwater tunnel also includes determining the existence and type of Hopf bifurcation of the speed regulation system of the grid-connected hydropower unit, according to the Jacobian matrix The corresponding characteristic equation is Solving for the Jacobian matrix for the bifurcation parameter The solution of the corresponding characteristic equation is , obtain the stable domain corresponding to the control parameters of each unit speed governor.

[0010] As a preferred solution of the coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station described in the present invention, the multi-objective optimization function includes taking the integral of the square of the error and the time as the minimum overshoot and the shortest adjustment time performance evaluation of the dynamic response output of each system, and the specific formula is as follows: , Wherein, t represents time; The specific formula is as follows: , in, represents the controller proportional gain of unit i, represents the controller integral gain of unit i, It represents the integral of the square of frequency error of each unit and time, Indicates the proportion of disturbance load distribution of each unit, represents the dynamic response optimization target of each unit, and i represents the unit number.

[0011] A multi-objective optimization function is established with the goal of minimizing the overshoot of the power grid and the surge chamber water level and minimizing the regulation time. The specific formula is as follows: , in, represents the optimization target of the power grid and voltage regulating room, represents the integral of the square of the grid frequency error and time, It represents the square of the water level error in the surge chamber and the time integral.

[0012] As a preferred solution of the coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station described in the present invention, wherein: the optimization of decision variables using MOPSO includes setting MOPSO parameters, inputting multiple optimization objective functions and the value range of the load proportion of each unit, and determining the value range of the speed governor control parameter of each unit according to the stability domain of the speed governor control parameter of each unit; Set the particle swarm size, boundary conditions, and initialize particle speed and position; Calculate the objective function value of each particle, determine the optimal position of the individual particle, and store the non-inferior solution in the external particle swarm; The external particle is selected as the global optimal position using the roulette method; Update the speed and position of the particles and calculate the fitness value of each particle; Use the dominance relationship to select the optimal position of the individual and update the optimal position of the individual; Update the external particle swarm until the maximum number of iterations is met.

[0013] As a preferred solution of the coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station described in the present invention, the fuzzy satisfaction evaluation method includes selecting a fuzzy membership function according to each target fitness value and calculating the fuzzy satisfaction; The standardized satisfaction of each scheme is calculated according to the fuzzy satisfaction rate, and all control schemes are sorted according to their standardized satisfaction rates, and the control scheme with the largest standardized satisfaction rate is selected.

[0014] Another object of the present invention is to provide a coordinated optimization control system for the grid-connected operation of a multi-machine tailwater system in a hydropower station, which can achieve multi-objective coordinated optimization and improve the operating stability of hydropower units and power grids.

[0015] As a preferred solution of the coordinated optimization control system for the grid-connected operation of the multi-machine tailwater system of the hydropower station described in the present invention, it includes: a mathematical model establishment module, a stability domain solution module, a multi-objective optimization function establishment module, an optimization algorithm execution module, and a fuzzy satisfaction evaluation module; The mathematical model building module constructs a mathematical model of a regulation system for a hydropower station with multiple machines sharing a tailwater surge chamber and a tailwater tunnel and grid-connected operation, including mathematical models of each subsystem; The stability domain solving module uses the Hopf bifurcation theory to solve the stability domain of the speed governor control parameters of each unit to ensure the stability of the system under parameter changes; The multi-objective optimization function establishment module establishes a multi-objective optimization function that takes into account the dynamic regulation performance of the unit frequency, the dynamic regulation performance of the power grid and the surge chamber water level, and selects decision variables; The optimization algorithm execution module executes a multi-objective particle swarm optimization algorithm to optimize the decision variables to obtain multiple control schemes; The fuzzy satisfaction evaluation module uses a fuzzy satisfaction evaluation method to evaluate all control schemes, calculates the standardized satisfaction of each scheme, and selects the scheme with the highest satisfaction.

[0016] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of a coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station are implemented.

[0017] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station are implemented.

[0018] Beneficial effects of the invention: The invention lays a model and theoretical foundation for the safe, stable regulation and optimized operation of the multi-machine shared tailwater system of a hydropower station by establishing a mathematical model for the grid-connected operation of the multi-machine shared tailwater system of a hydropower station. The multi-objective coordinated control optimization method for the grid-connected operation of the multi-machine shared tailwater system of a hydropower station proposed in the invention takes into account the coordinated distribution of loads among the units, improves the overall dynamic regulation performance of the units, surge tanks and power grid frequency, and provides technical support for the safe and stable operation of hydropower units and power grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them: Figure 1 A multi-objective coordinated control optimization analysis flow chart of a coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station provided by an embodiment of the present invention.

[0020] Figure 2 A schematic diagram of the grid-connected operation layout of a shared tailwater system of a hydropower station with multiple machines provided in accordance with a method for coordinated optimization control of the grid-connected operation of the shared tailwater system in an embodiment of the present invention.

[0021] Figure 3 A schematic diagram of a module of a coordinated optimization control system for grid-connected operation of a multi-machine tailwater system of a hydropower station provided by an embodiment of the present invention.

[0022] Figure 4 A stable domain of control parameters of speed regulators of grid-connected operation units of a multi-machine common tailwater system of a hydropower station provided in an embodiment of the present invention is disclosed.

[0023] Figure 5 A Pareto frontier of multi-objective coordinated optimization control results of a shared tailwater system for grid-connected operation of a hydropower station multi-machine shared tailwater system provided by an embodiment of the present invention.

[0024] Figure 6 A standardized satisfaction level of a multi-objective optimization scheme of a multi-objective coordinated optimization control method for grid-connected operation of a tailwater system of multiple machines in a hydropower station provided by an embodiment of the present invention.

[0025] Figure 7A time domain diagram of the dynamic response of the surge chamber water level of a shared tailwater system of a hydropower station with multiple machines provided in an embodiment of the present invention, and a multi-objective coordinated optimization control method for grid-connected operation of the shared tailwater system.

[0026] Figure 8 A time domain diagram of the dynamic response of the power grid frequency of a shared tailwater system of a hydropower station with multiple machines provided in an embodiment of the present invention, and a multi-objective coordinated optimization control method for grid-connected operation of the shared tailwater system.

[0027] Fig. 9 A time domain diagram of the frequency dynamic response of unit 1 of a multi-objective coordinated optimization control method for grid-connected operation of a tailwater system of a hydropower station provided by an embodiment of the present invention.

[0028] Fig.10 A time domain diagram of the dynamic response of the frequency of unit 2 of a multi-objective coordinated optimization control method for grid-connected operation of a tailwater system of a hydropower station provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0030] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0031] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0032] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0033] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0034] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a coordinated optimization control method for the grid-connected operation of a tailwater system of a hydropower station with multiple machines sharing the same tailwater, including: S1: establishing a mathematical model of the regulation system for the grid-connected operation of a tailwater surge chamber and tailwater tunnel of a hydropower station with multiple machines sharing the same tailwater.

[0036] Furthermore, a mathematical model of the subsystem is established, including the pressure pipe equations of each unit, the turbine torque-flow equations of each unit, the generator equations of each unit, the speed governor equations of each unit, the grid equivalent equations, the surge chamber continuity equations, and the tailwater tunnel head-flow equations.

[0037] Specifically, the specific formulas of the pressure pipeline equations of each unit are as follows: , in, is the inertia time constant of water flow in the pressure pipe of unit i, , are the relative deviation values ​​of flow rate and head of pressure pipeline of unit i, It is the relative value of water level deviation in surge chamber. The subscript “0” indicates the initial value. is the rated water head of unit i, is the water head loss of the water diversion pipe of unit i.

[0038] Preferably, the specific formula of the turbine torque flow equation of each unit is as follows: , in, , and They represent the torque transfer coefficient of turbine i, , and They represent the flow transfer coefficient, Indicates the relative value of the speed deviation of unit i, Indicates the water head deviation of each unit. Indicates the relative value of the guide vane opening deviation of unit i, Indicates the relative value of the branch pipe flow deviation of each unit. It indicates the relative value of the torque deviation of the turbine of unit i.

[0039] Furthermore, the specific formulas of the generator equations of each unit are as follows: , Where i represents the unit number, represents the inertia time constant of the hydropower unit, Indicates the relative value of the unit speed deviation. Indicates the relative value of grid frequency deviation, It represents the load self-regulation coefficient. represents the equivalent damping coefficient of unit number i, Indicates the generator voltage phase difference, Indicates the relative value of the torque deviation of the turbine of unit i, Represents the output electromagnetic power.

[0040] Furthermore, the specific formulas of the speed governor equations of each unit are as follows: , in, represents the guide vane opening of unit i, , denote the proportional and integral gains respectively, Indicates the relative value of the unit speed deviation.

[0041] Preferably, the specific formula of the power grid equivalent equation is as follows: , in, represents the equivalent inertia time constant of the power grid, Indicates the relative value of grid frequency deviation, Indicates the proportion of hydropower unit power in the power grid, represents the equivalent relay time constant of the power grid, It represents the equivalent permanent slip coefficient of the power grid, Indicates the grid load, Indicates the relative value of the grid disturbance load, Indicates that the intermediate variable has no specific meaning.

[0042] in, .

[0043] Furthermore, the continuity equation of the downstream surge tank is as follows: , in, , are the relative deviation values ​​of the surge chamber water level and tailwater tunnel, respectively. The subscript “0” indicates the initial value. is the surge chamber time constant.

[0044] Preferably, the tailwater tunnel dynamic equation is as follows: , in, , They are the relative values ​​of surge chamber water level and tailwater tunnel deviation, respectively. The subscript “0” indicates the initial value. is the head loss in the tailrace tunnel, is the inertia time constant of the tailrace tunnel flow.

[0045] Furthermore, by combining the basic equations of the above hydropower station subsystem mathematical models, the mathematical model of the hydropower station multi-machine shared tailwater system grid-connected operation regulation system is obtained. The specific formula is as follows: , in, , , , are the relative deviation values ​​of pressure pipe flow, speed, guide vane opening, and water head of unit i, respectively. , , , They are the relative deviation values ​​of surge chamber water level, tailwater tunnel, grid frequency and disturbance load, respectively. The subscript “0” indicates the initial value. is the rated water head of unit i, is the head loss of the water diversion pipe of unit i, is the head loss in the tailrace tunnel, is the inertia time constant of water flow in the pressure pipe of unit i, , , is the flow transfer coefficient of unit i, , , is the torque transfer coefficient of turbine i, is the load self-regulation coefficient of the generator of unit i, is the surge chamber time constant, is the inertia time constant of the tailrace tunnel flow, is the equivalent synchronization coefficient of generator i, is the equivalent damping coefficient of generator i, Inertia time constant of unit i, , are the proportion and integral gain of unit i respectively, B is the proportion of hydropower unit power in the power grid, is the equivalent inertia time constant of the power grid, is the self-regulation coefficient of equivalent load of power grid, is the grid equivalent relay time constant, is the equivalent permanent slip coefficient of the power grid, Grid load disturbance.

[0046] S2: The Hopf bifurcation theory is used to solve the stability domain of the speed governor control parameters of each unit in the tailwater surge tank and tailwater tunnel grid-connected operation regulation system of a hydropower station with multiple units sharing the same tailwater surge tank.

[0047] Specifically: Step 1: Calculate the balance point of the speed control system of the grid-connected hydropower unit According to the Hopf bifurcation principle, the mathematical model of the multi-machine shared tailwater surge chamber and tailwater tunnel grid-connected operation regulation system of the hydropower station is converted into a matrix form , is the state vector, is the bifurcation parameter. , find the system equilibrium point, the result is as follows: , Step 2: Determine the existence and type of Hopf bifurcation in the speed control system of the grid-connected hydropower unit Grid-connected operation system for tailwater system shared by multiple units in hydropower station At the balance point The Jacobian matrix at is .make , we can get the Jacobian matrix The corresponding characteristic equation is as follows: , in, for The characteristic value of are the characteristic polynomial coefficients. is the characteristic value, is the characteristic equation coefficient, and n is the system order.

[0048] Step 3: According to the Jacobian matrix The corresponding characteristic equation is Solving for the Jacobian matrix for the bifurcation parameter The solution of the corresponding characteristic equation is , obtain the stability domain corresponding to each unit.

[0049] S3: Establish a multi-objective coordinated optimization function that takes into account the frequency regulation performance of each unit in the system, the dynamic regulation performance of the surge chamber and the dynamic regulation performance of the power grid frequency, and select the disturbance load distribution coefficient of each unit and the speed regulator control parameters as the decision variables of the multi-objective optimization.

[0050] Specifically, the integral of the square of the error and time is used as the performance evaluation of the minimum overshoot and the shortest adjustment time of the dynamic response output of each system. The specific formula is as follows: , Wherein, t represents time; A multi-objective optimization function is established with the goal of minimizing the frequency response overshoot of each unit and minimizing the adjustment time. The specific formula is as follows: , in, represents the controller proportional gain of unit i, represents the controller integral gain of unit i, It represents the integral of the square of frequency error of each unit and time, Indicates the proportion of disturbance load distribution of each unit, represents the dynamic response optimization target of each unit, and i represents the unit number.

[0051] It should be noted that in the present invention, , , Indicates the order of magnitude, .

[0052] A multi-objective optimization function is established with the goal of minimizing the overshoot of the power grid and the surge chamber water level and minimizing the regulation time. The specific formula is as follows: , in, represents the optimization target of the power grid and voltage regulating room, represents the integral of the square of the grid frequency error and time, It represents the square of the water level error in the surge chamber and the time integral.

[0053] S4: Use the MOPSO multi-objective optimization algorithm to optimize the decision variables to obtain multiple Pareto optimal control schemes that meet the requirements.

[0054] Specifically, according to the mathematical model of the multi-machine tailwater system of the hydropower station, the established multi-objectives are optimized and multiple control schemes are obtained, which specifically include the following steps: determining the boundaries of the decision variables; determining the optimization population size to be 40 and the number of iterations to be 200; according to the MOPSO algorithm process, Control scheme optimization is performed by programming in the environment.

[0055] Preferably, MOPSO parameters are set, multiple optimization objective functions and the value range of the load proportion of each unit are input, and the value range of the speed governor control parameter of each unit is determined according to the stability domain of the speed governor control parameter of each unit; Set the particle swarm size, boundary conditions, and initialize particle speed and position; Calculate the objective function value of each particle, determine the optimal position of the individual particle, and store the non-inferior solution in the external particle swarm; The external particle is selected as the global optimal position using the roulette method; Update the speed and position of the particles and calculate the fitness value of each particle; Use the dominance relationship to select the optimal position of the individual and update the optimal position of the individual; Update the external particle swarm until the maximum number of iterations is met.

[0056] S5: Use the fuzzy satisfaction evaluation method to evaluate and analyze all control schemes, and select the scheme with the highest standardized satisfaction as the final coordinated optimization control strategy.

[0057] Example 2, reference Figure 1-Figure 10 , which is the second embodiment of the present invention, and this embodiment provides an intelligent Internet of Things gateway system that supports edge computing deployment. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0058] Specifically, according to Figure 2 The mathematical model paradigm of the grid-connected operation of the tailwater system shared by multiple units in a hydropower station is established. At the same time, the grid-connected operation units with two units sharing the tailwater surge tank and tailwater tunnel are selected as cases for verification.

[0059] Preferably, the Hopf bifurcation theory is used to solve the stability domain of the speed governor control parameters of each unit in the tailwater surge tank and tailwater tunnel grid-connected operation regulation system of the hydropower station, such as Figure 4 shown. Figure 4 In the figure, the area enclosed by the curve S1 and the coordinate axis is the stable domain of the control parameters of unit 1; the area enclosed by the curve S2 and the coordinate axis is the stable domain of the control parameters of unit 2.

[0060] Furthermore, the objective optimization function is established to consider the minimum overshoot and the shortest adjustment time of each unit frequency dynamic response: , , in, represents the controller proportional gain of unit i, represents the controller integral gain of unit i, Indicates the load proportion of each 1# unit, Indicates the load proportion of each 2# unit.

[0061] At the same time, an optimization objective function is established that takes into account the minimum overshoot of the water level in the power grid and the surge chamber and the shortest adjustment time: , in, represents the controller proportional gain of unit i, represents the controller integral gain of unit i, represents the integral of the square of the grid frequency error and time, It represents the square of the water level error in the surge chamber and the time integral, Indicates the load proportion of each unit.

[0062] According to the stability domain range of each unit, the value range of each decision variable in the optimization objective function is as follows: , , , , , .

[0063] Furthermore, the MOPSO population number is set to 40 and the iteration number is set to 200. According to the mathematical model paradigm of the hydropower station dual-unit shared tailwater surge chamber and tailwater tunnel grid-connected operation, the multi-objective optimization function and its decision variables, and the MOPSO multi-objective optimization algorithm process, 40 optimization control schemes are optimized in Matlab according to the parameters of the units in Table 1, as shown in Figure 1. Figure 5 shown.

[0064] Table 1 Hydropower station unit parameters , Furthermore, according to the fuzzy satisfaction decision method, the standardized satisfaction of each solution is calculated, such as Figure 6 shown.

[0065] Furthermore, the two control schemes with the highest and lowest standardized satisfaction were selected according to the standardized satisfaction evaluation results (see Table 2). The load disturbance dynamic characteristics of the two control schemes were simulated and analyzed in Matlab based on the mathematical model of the grid-connected operation of the tailwater system of the hydropower station with two units sharing the same tailwater system. The results are shown in Table 2. Figure 7-10 As shown, it can be seen that the dynamic response performance of the surge chamber water level, grid frequency, 1# unit frequency, and 2# unit frequency of Scheme 22 is significantly better than that of Scheme 27. The results show that the proposed control model and method are effective and can effectively improve the quality of unit regulation control.

[0066] Table 2 Typical control scheme , It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0067] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that: If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0068] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0069] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0070] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0071] Example 4, reference Figure 3 , which is an embodiment of the present invention, provides a coordinated optimization control system for the grid-connected operation of a multi-machine common tailwater system of a hydropower station, characterized by: comprising a mathematical model building module 100, a stability domain solving module 200, a multi-objective optimization function building module 300, an optimization algorithm execution module 400, and a fuzzy satisfaction evaluation module 500; The mathematical model building module 100 builds a mathematical model of a regulation system for a hydropower station with multiple machines sharing a tailwater surge chamber and a tailwater tunnel and connecting the tailwater to the grid, including mathematical models of each subsystem; The stability domain solving module 200 uses the Hopf bifurcation theory to solve the stability domain of the speed governor control parameters of each unit to ensure the stability of the system under parameter changes; A multi-objective optimization function establishment module 300 is used to establish a multi-objective optimization function that takes into account the dynamic regulation performance of the unit frequency, the dynamic regulation performance of the power grid and the surge chamber water level, and select decision variables; The optimization algorithm execution module 400 executes a multi-objective particle swarm optimization algorithm to optimize the decision variables to obtain multiple control schemes; The fuzzy satisfaction evaluation module 500 uses the fuzzy satisfaction evaluation method to evaluate all control schemes, calculate the standardized satisfaction of each scheme, and select the scheme with the highest satisfaction.

[0072] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A coordinated optimization control method for grid-connected operation of a multi-machine tailwater system in a hydropower station, characterized by: include, Establish a mathematical model of the regulation system for the multi-machine shared tailwater surge chamber and tailwater tunnel of a hydropower station in grid-connected operation; The Hopf bifurcation theory is used to solve the stability domain of the speed governor control parameters of each unit in the tailwater surge tank and tailwater tunnel grid-connected operation regulation system of a hydropower station with multiple units sharing the same tailwater surge tank. A multi-objective optimization function is established that takes into account the dynamic regulation performance of the frequency of each unit, the dynamic regulation performance of the power grid and the water level in the surge tank, and the proportion of the disturbance load and the speed governor control parameters of each unit are selected as the decision variables for optimization. Use MOPSO to optimize decision variables and obtain multiple control schemes; The fuzzy satisfaction evaluation method is used to evaluate and analyze all control schemes, and the scheme with the highest standardized satisfaction is selected as the optimal coordinated optimization control scheme.

2. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system in a hydropower station according to claim 1, characterized in that: The mathematical model of the regulation system for the multi-machine shared tailwater surge chamber and tailwater tunnel of the hydropower station for grid-connected operation includes establishing a subsystem mathematical model including pressure pipeline equations of each unit, turbine torque flow equations of each unit, generator equations of each unit, governor equations of each unit, grid equivalent equations, surge chamber continuity equations, and tailwater tunnel head-flow equations; Combining the physical relationships and operational characteristics of each subsystem and integrating the mathematical equations of all subsystems, a mathematical model of the overall regulation system for the grid-connected operation of a multi-machine shared tailwater system in a hydropower station is constructed.

3. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system of a hydropower station according to claim 2, characterized in that: The stable domain of solving the speed governor control parameters of each unit of the hydropower station multi-machine shared tailwater surge chamber and tailwater tunnel grid-connected operation regulation system includes converting the mathematical model of the hydropower station multi-machine shared tailwater surge chamber and tailwater tunnel grid-connected operation regulation system into a matrix form according to the Hopf bifurcation principle. , is the state vector, is the bifurcation parameter, let , find the equilibrium point of the system.

4. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system in a hydropower station according to claim 3, characterized in that: The method for solving the stability domain of the speed governor control parameters of each unit of the multi-machine shared tailwater surge chamber and tailwater tunnel grid-connected operation regulation system of the hydropower station also includes determining the existence and type of Hopf bifurcation of the grid-connected hydropower unit speed regulation system, and according to the Jacobian matrix The corresponding characteristic equation is Solving for the Jacobian matrix for the bifurcation parameter The solution of the corresponding characteristic equation is , obtain the stable domain corresponding to the control parameters of each unit speed governor.

5. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system in a hydropower station according to claim 4, characterized in that: The multi-objective optimization function includes taking the integral of the square of the error and the time as the minimum overshoot and the shortest adjustment time performance evaluation of the dynamic response output of each system; Establish a multi-objective optimization function with the goal of minimizing the frequency response overshoot and the shortest adjustment time of each unit; A multi-objective optimization function is established with the goal of minimizing the overshoot and the shortest regulation time of the power grid and the surge chamber water level.

6. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system in a hydropower station according to claim 5, characterized in that: The optimization of decision variables by using MOPSO includes setting MOPSO parameters, inputting multiple optimization objective functions and the value range of the load proportion of each unit, and determining the value range of the speed governor control parameter of each unit according to the stability domain of the speed governor control parameter of each unit; Set the particle swarm size, boundary conditions, and initialize particle speed and position; Calculate the objective function value of each particle, determine the optimal position of the individual particle, and store the non-inferior solution in the external particle swarm; The external particle is selected as the global optimal position using the roulette method; Update the speed and position of the particles and calculate the fitness value of each particle; Use the dominance relationship to select the optimal position of the individual and update the optimal position of the individual; Update the external particle swarm until the maximum number of iterations is met.

7. The method for coordinated optimization control of grid-connected operation of a multi-machine tailwater system in a hydropower station according to claim 6, characterized in that: The fuzzy satisfaction evaluation method comprises selecting a fuzzy membership function according to each target fitness value and calculating the fuzzy satisfaction; The standardized satisfaction of each scheme is calculated according to the fuzzy satisfaction rate, and all control schemes are ranked according to their standardized satisfaction rates. The control scheme with the largest standardized satisfaction rate is selected as the optimal coordinated control scheme.

8. A system using the coordinated optimization control method for grid-connected operation of a multi-machine tailwater system of a hydropower station as claimed in any one of claims 1 to 7, characterized in that: It includes mathematical model building module, stable domain solving module, multi-objective optimization function building module, optimization algorithm execution module and fuzzy satisfaction evaluation module; The mathematical model building module constructs a mathematical model of a regulation system for a hydropower station with multiple machines sharing a tailwater surge chamber and a tailwater tunnel and grid-connected operation, including mathematical models of each subsystem; The stability domain solving module uses the Hopf bifurcation theory to solve the stability domain of the speed governor control parameters of each unit to ensure the stability of the system under parameter changes; The multi-objective optimization function establishment module establishes a multi-objective optimization function that takes into account the dynamic regulation performance of the unit frequency, the dynamic regulation performance of the power grid and the surge chamber water level, and selects decision variables; The optimization algorithm execution module executes a multi-objective particle swarm optimization algorithm to optimize the decision variables to obtain multiple control schemes; The fuzzy satisfaction evaluation module uses a fuzzy satisfaction evaluation method to evaluate all control schemes, calculates the standardized satisfaction of each scheme, and selects the scheme with the highest satisfaction.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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