Ultra-low frequency oscillation suppression method and system based on grey wolf optimization algorithm

Abstract

The invention discloses an ultralow frequency oscillation suppression method and system based on a grey wolf optimization algorithm, and belongs to the technical field of power system stability control. According to the ultralow frequency oscillation suppression method based on the grey wolf optimization algorithm, the damping characteristics of the electric power system where the hydroelectric generating set is located are obtained, the dynamic energy difference between the mechanical power and the electromagnetic power is quantized into the energy increment, the influence of energy interaction of the hydroelectric generating set on the ULFO is directly represented, and therefore the energy dynamic process under the actual working condition is reflected; contribution degree misjudgment caused by model simplification is avoided; the change rate of the energy increment along with time is tracked in real time, the negative damping contribution degree of each hydroelectric generating set to the ULFO is dynamically calculated, and the hydroelectric generating set with high negative damping contribution to the ULFO is accurately identified; the control parameters of the additional damping controller are obtained through optimization of the improved grey wolf optimization algorithm, a local optimal solution is jumped out, and the convergence speed is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of power system stability control, and in particular to an ultra-low frequency oscillation suppression method and system based on a grey wolf optimization algorithm. Background Art

[0002] With the widespread application of high-head and large-capacity hydropower units in power systems, ultra-low frequency oscillation (ULFO) has gradually become a prominent problem threatening the safe and stable operation of power grids. ULFO is mainly caused by the negative damping effect caused by improper configuration of turbine speed control system parameters. Specifically, the system frequency continues to fluctuate in the low-frequency range (frequency below 0.1 Hz). If it is not suppressed in time, this situation may further evolve into a serious accident of unit chain disconnection or even large-scale power outage.

[0003] In the current technical system, there are limitations in the suppression measures for ULFO. Specifically, the traditional small disturbance stability analysis method is based on a linearized model, which makes it difficult to accurately quantify the contribution of different units to ULFO under complex working conditions, thus weakening the pertinence and effectiveness of the control strategy; on the other hand, the conventional damping controller parameter optimization usually relies on the particle swarm optimization (PSO), but the particle swarm optimization has the problems of slow convergence speed, easy to fall into the local optimal solution, and difficult to adapt to the dynamic regulation requirements of multiple time scales.

[0004] Therefore, there is an urgent need for a ULFO suppression method that can accurately locate key oscillation sources and optimize control parameters to achieve the elimination of negative damping and the overall improvement of dynamic stability. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for ultra-low frequency oscillation suppression based on the Grey Wolf Optimization Algorithm, aiming to solve the limitations faced by ultra-low frequency oscillation suppression in the current technical field.

[0006] The present invention solves the above technical problems through the following technical solutions: A method for suppressing ultra-low frequency oscillation based on a grey wolf optimization algorithm comprises the following steps: S1. Obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located by integral calculation; S2. Analyze the changing trend of energy increment over time, determine the contribution of each hydropower unit to the ultra-low frequency oscillation, and obtain the hydropower unit with high contribution; S3. Perform phase compensation and negative damping elimination for high-contribution hydropower units through an additional damping controller, wherein the control parameters of the additional damping controller are obtained by optimizing the improved grey wolf optimization algorithm, and the control parameters are the phase compensation time constant and the gain coefficient, and the optimization goal is to maximize the modal damping ratio of the ultra-low frequency oscillation.

[0007] The further improvement of the present invention is that: the improved grey wolf optimization algorithm is specifically: The Tent chaotic map is used to initialize the population and obtain the value range of the control parameters; The position of the grey wolf is updated based on the adaptive weight factor, and the penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters with the goal of maximizing the modal damping ratio of the ultra-low frequency oscillation.

[0008] The further improvement of the present invention is that the Tent chaotic mapping is specifically:

[0009] in, is the current iteration number, For the The chaotic variable value of the iteration is [0,1]; For the +1 iteration of the chaos variable value.

[0010] A further improvement of the present invention is that the adaptive weight factor is specifically:

[0011] in, is the adaptive weight factor; is the minimum weight factor; is the maximum weight factor; is the maximum number of iterations.

[0012] A further improvement of the present invention is that: the range of the phase compensation time constant is [0, 6]; the range of the gain coefficient is [0.1, 1].

[0013] A further improvement of the present invention is that: the penalty function method is used to constrain the value range of the control parameter as follows:

[0014] in, It is the optimal solution of modal damping ratio for ultra-low frequency oscillation; is the phase compensation time constant; is the gain coefficient; is the objective function value after correction by penalty function.

[0015] A further improvement of the present invention is that S1 specifically comprises the following steps: S1.1. The mechanical torque and electromagnetic torque are obtained through the rotor motion equation, where the rotor motion equation is:

[0016] in, is the inertia time constant; is the mechanical torque; is the electromagnetic torque; is the damping coefficient; is the speed deviation; is the speed deviation change rate; S1.2, decompose the mechanical torque and electromagnetic torque into damping component and synchronous component, and calculate the damping characteristics of the power system where the hydropower unit is located; S1.3. Based on the damping characteristics, establish the energy change rate of the hydropower unit injected into the power system where it is located ;

[0017] in, is the change of electromagnetic power; is the initial angular velocity of the hydropower unit; S1.4. By integrating the energy change rate, calculate the energy increment injected by the hydropower unit into the power system where it is located , specifically:

[0018] in, is the time differential.

[0019] A further improvement of the present invention is that: the analysis of the change trend of energy increment over time and the determination of the contribution of each hydropower unit to the ultra-low frequency oscillation are specifically as follows: When the energy increment continues to increase and the slope is positive, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is high, and the hydropower unit is a hydropower unit with high contribution; When the energy increment continues to decrease and the slope is negative, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is low, and the hydropower unit is a hydropower unit with low contribution.

[0020] A further improvement of the present invention is that the phase compensation and negative damping elimination for the high-contribution hydropower unit by using the additional damping controller is specifically as follows: An additional damping controller is introduced before the PID control link of the speed regulator of the high-contribution hydropower unit. The mechanical torque phase is adjusted by the additional damping controller to make it in phase with the frequency deviation of the system where the hydropower unit is located, thereby eliminating the negative damping effect.

[0021] The present invention also provides an ultra-low frequency oscillation suppression system based on the gray wolf optimization algorithm, comprising the following modules: The energy increment module is used to obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located through integral calculation; Contribution evaluation module, used to analyze the trend of energy increment over time, determine the contribution of each hydropower unit to ultra-low frequency oscillation, and obtain the hydropower units with high contribution; A control module is used to perform phase compensation and negative damping elimination for a high-contribution hydropower unit through an additional damping controller, wherein the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm, and the control parameters are a phase compensation time constant and a gain coefficient, and the optimization goal is to maximize the modal damping ratio of ultra-low frequency oscillations.

[0022] Compared with the prior art, the positive and progressive effects of the present invention are: The ultra-low frequency oscillation suppression method based on the Gray Wolf Optimization Algorithm provided by the present invention realizes the rapid suppression of ULFO and the overall improvement of system frequency stability through the analysis of energy dynamic characteristics, accurate evaluation of the contribution of hydropower units and coordinated control of parameter optimization. Specifically, by obtaining the damping characteristics of the power system where the hydropower unit is located, the dynamic energy difference between mechanical power and electromagnetic power is quantified as energy increment, and the influence of the energy interaction of the hydropower unit on the ULFO is directly characterized, thereby reflecting the energy dynamic process under actual working conditions and avoiding the misjudgment of contribution caused by model simplification; by real-time tracking the rate of change of energy increment over time, the negative damping contribution of each hydropower unit to the ULFO is dynamically calculated, and the hydropower units with high negative damping contribution to the ULFO are accurately identified; by using the improved Gray Wolf Optimization Algorithm to optimize the control parameters of the additional damping controller, it is possible to jump out of the local optimal solution and improve the convergence speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings in the specification are used to provide further understanding of the present invention and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0024] Figure 1 It is a flow chart of the ultra-low frequency oscillation suppression method based on the Grey Wolf optimization algorithm of the present invention; Figure 2 This is a system schematic diagram of Embodiment 1 of the present invention; Figure 3 1 is a frequency waveform diagram of a DC (Direct Current) transmitting end in the first embodiment of the present invention, where the horizontal axis is time t and the vertical axis is frequency f; Figure 4 Schematic diagram of energy increment of hydropower generating units G1 to G4 in the first embodiment of the present invention, where the horizontal axis represents the hydropower generating units G1 to G4 and the vertical axis represents the energy increment; Figure 5 It is a schematic diagram of system frequency comparison between the method of the present invention and the traditional PSO method, where the horizontal axis is time t and the vertical axis is frequency f. DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] In the description of the present invention, it should be understood that the terms “include” and “comprises” indicate the presence of described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0027] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an" and "the" are intended to include plural forms unless the context clearly indicates otherwise.

[0028] It should be understood that, although the terms first, second, third, etc. may be used to describe preset ranges, etc. in the embodiments of the present invention, these preset ranges should not be limited to these terms. These terms are only used to distinguish preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0029] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0030] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0031] Glossary: CloudPSS (Cloud-based Power System Simulator): is a comprehensive energy network analysis tool that combines the Internet, cloud computing, and parallel computing technologies.

[0032] Standard 4M2A system model: refers to an industrial control system model that uses 4-20mA analog signals for data transmission.

[0033] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments, which are intended to explain the present invention rather than to limit it.

[0034] See also Figure 1 , a method for suppressing ultra-low frequency oscillation based on the gray wolf optimization algorithm, comprising the following steps: S1. Obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located by integral calculation; S2. Analyze the changing trend of energy increment over time, determine the contribution of each hydropower unit to the ultra-low frequency oscillation, and obtain the hydropower unit with high contribution; S3. Perform phase compensation and negative damping elimination for high-contribution hydropower units through an additional damping controller, wherein the control parameters of the additional damping controller are obtained by optimizing the improved grey wolf optimization algorithm, and the control parameters are the phase compensation time constant and the gain coefficient, and the optimization goal is to maximize the modal damping ratio of the ultra-low frequency oscillation.

[0035] The ultra-low frequency oscillation suppression method based on the Gray Wolf Optimization Algorithm provided by the present invention realizes the rapid suppression of ULFO and the overall improvement of system frequency stability through the analysis of energy dynamic characteristics, accurate evaluation of the contribution of hydropower units and coordinated control of parameter optimization. Specifically, by obtaining the damping characteristics of the power system where the hydropower unit is located, the dynamic energy difference between mechanical power and electromagnetic power is quantified as energy increment, and the influence of the energy interaction of the hydropower unit on the ULFO is directly characterized, thereby reflecting the energy dynamic process under actual working conditions and avoiding the misjudgment of contribution caused by model simplification; by real-time tracking the rate of change of energy increment over time, the negative damping contribution of each hydropower unit to the ULFO is dynamically calculated, and the hydropower units with high negative damping contribution to the ULFO are accurately identified; by using the improved Gray Wolf Optimization Algorithm to optimize the control parameters of the additional damping controller, it is possible to jump out of the local optimal solution and improve the convergence speed.

[0036] Specifically, the improved grey wolf optimization algorithm is as follows: The Tent chaotic map is used to initialize the population and obtain the value range of the control parameters; The position of the grey wolf is updated based on the adaptive weight factor, and the penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters with the goal of maximizing the modal damping ratio of the ultra-low frequency oscillation.

[0037] Specifically, the Tent chaos map is as follows:

[0038] in, is the current iteration number, For the The chaotic variable value of the iteration is [0,1]; For the +1 iteration of the chaos variable value.

[0039] Specifically, the adaptive weight factor is:

[0040] in, is the adaptive weight factor; is the minimum weight factor; is the maximum weight factor; is the maximum number of iterations.

[0041] Specifically, the range of the phase compensation time constant is [0, 6]; the range of the gain coefficient is [0.1, 1].

[0042] Specifically, the penalty function method is used to constrain the value range of the control parameter as follows:

[0043] in, It is the optimal solution of modal damping ratio for ultra-low frequency oscillation; is the phase compensation time constant; is the gain coefficient; is the objective function value after correction by penalty function.

[0044] Specifically, S1 includes the following steps: S1.1. The mechanical torque and electromagnetic torque are obtained through the rotor motion equation, where the rotor motion equation is:

[0045] in, is the inertia time constant; is the mechanical torque; is the electromagnetic torque; is the damping coefficient; is the speed deviation; is the speed deviation change rate; S1.2, decompose the mechanical torque and electromagnetic torque into damping component and synchronous component, and calculate the damping characteristics of the power system where the hydropower unit is located; S1.3. Based on the damping characteristics, establish the energy change rate of the hydropower unit injected into the power system where it is located ;

[0046] in, is the change of electromagnetic power; is the initial angular velocity of the hydropower unit; S1.4. By integrating the energy change rate, calculate the energy increment injected by the hydropower unit into the power system where it is located , specifically:

[0047] in, is the time differential.

[0048] Specifically, the analysis of the change trend of energy increment over time and the determination of the contribution of each hydropower unit to the ultra-low frequency oscillation are as follows: When the energy increment continues to increase and the slope is positive, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is high, and the hydropower unit is a hydropower unit with high contribution; When the energy increment continues to decrease and the slope is negative, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is low, and the hydropower unit is a hydropower unit with low contribution.

[0049] Specifically, the phase compensation and negative damping elimination for the high-contribution hydropower unit by using the additional damping controller are as follows: An additional damping controller is introduced before the PID control link of the speed regulator of the high-contribution hydropower unit. The mechanical torque phase is adjusted by the additional damping controller to make it in phase with the frequency deviation of the system where the hydropower unit is located, thereby eliminating the negative damping effect.

[0050] Based on the same inventive concept, the present invention also provides an ultra-low frequency oscillation suppression system based on the gray wolf optimization algorithm, comprising the following modules: The energy increment module is used to obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located through integral calculation; Contribution evaluation module, used to analyze the trend of energy increment over time, determine the contribution of each hydropower unit to ultra-low frequency oscillation, and obtain the hydropower units with high contribution; A control module is used to perform phase compensation and negative damping elimination for a high-contribution hydropower unit through an additional damping controller, wherein the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm, and the control parameters are a phase compensation time constant and a gain coefficient, and the optimization goal is to maximize the modal damping ratio of ultra-low frequency oscillations.

[0051] Embodiment 1 A simulation model based on the standard 4M2A system model was built in CloudPSS: Building simulation models and load step disturbances: See Figure 2 , area ① is the DC transmitting end, area ② is the receiving end, area ① contains four hydro-generators, namely G1, G2, G3 and G4; area ② contains two hydro-generators, namely G5 and G6, all of which are high-head, high-capacity hydro-generators with a rated capacity of 900 MV·A. The rated transmission power of the DC transmitting end system is 400MW, the load L1 of area ① is 2188 MW, and the load L2 of area ② is 1854 MW. The speed regulator parameters of each hydro-generator are shown in the table:

[0052] See also Figure 3 At t=5s, the load disturbance in area ① is simulated as a load power loss of 100MW; after the load disturbance, ultra-low frequency oscillation occurs with a frequency of 0.064Hz and a damping ratio of -0.003.

[0053] Therefore, in order to suppress ultra-low frequency oscillation, it is necessary to sort the ultra-low frequency oscillation contribution of the hydropower units, then install additional supplementary damping controllers on the hydropower units with high contributions, and optimize the control parameters of the supplementary damping controllers.

[0054] Obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system, and obtain the energy increment injected into the power system by the hydropower unit through integral calculation: Figure 4 , is the energy increment injected into the network by hydropower units G1~G4. It can be seen that the energy increment E of G1 and G2 Hamilton It gradually increases with time, which indicates that the energy injected into the system continues to increase. In contrast, the energy increment E of G3 and G4 Hamilton It gradually decreases over time, which indicates that the energy injected into the system continues to decrease; by comparing the energy increment E of each hydropower unit Hamilton , the ranking of the contribution of hydropower units to ultra-low frequency oscillation is G1=G2>G3=G4.

[0055] The high-contribution hydropower units, namely G1 and G2, are obtained, and phase compensation and negative damping elimination are performed for the high-contribution hydropower units through an additional damping controller, wherein the control parameters of the additional damping controller are optimized by the improved Grey Wolf optimization algorithm, and the control parameters are the phase compensation time constant and the gain coefficient. The optimization goal is to maximize the modal damping ratio of the ultra-low frequency oscillation: In order to suppress the ultra-low frequency oscillation, an additional damping controller is installed on the speed regulators of G1 and G2.

[0056] Since the ultra-low frequency oscillation frequency is between 0.01 Hz and 0.1 Hz, the time constant of filter T1 is set to 1.59 and T2 is set to 15.9; the simulation model is identified by simulating a step disturbance of the opening of G1. At t=5 seconds, a 2% opening step disturbance occurs at the outlet of G1; the control parameters of the additional damping controller are optimized using the improved GWO (Grey Wolf Optimizer).

[0057] Taking G1 as an example, phase compensation and negative damping elimination are performed. The optimization process of the control parameters of the additional damping controller is as follows: the population size is 50, k max is 100.

[0058] The initial gray wolf population of traditional GWO is randomly generated, which may lead to local optimality, while the Tent chaotic sequence is characterized by better regularity and ergodicity; compared with other mappings, the Tent chaotic mapping produces a more uniform sequence distribution, so the Tent chaotic mapping is used to initialize the gray wolf population.

[0059] The specific implementation process of the improved gray wolf optimization algorithm is as follows: 1. Tent chaos initialization population generation (1) Set the population size to 50 and the search dimension to 2 (corresponding to the phase compensation time constant T i and gain factor K); (2) Generate chaotic sequence based on Tent chaotic mapping:

[0060] (3) Map the chaotic sequence to the value range of the control parameter: ,

[0061] is the value of the i-th chaotic sequence at the k-th iteration; is the value of the 2k−1th chaotic variable; is the control parameter at the kth iteration; is the value of the 2kth chaotic variable; is the number of iterations (k=1,2,...,100); This process is used to ensure that the initial solutions of the control parameters are uniformly distributed in the interval [0,6] and [0.1,1] to avoid local aggregation caused by traditional random initialization.

[0062] 2. Dynamic adjustment of adaptive weights Update the gray wolf position based on the adaptive weight factor: Adaptive weight factor for:

[0063] in, =0.9; =0.4; In the initial stage (t<30): ω>0.7, enhancing the global search capability and quickly locating the potential optimal area; in the mid-term stage (30≤t<70): normal iteration; in the late stage (t≥70): ω<0.45, improving local development accuracy and refining parameter adjustment; at the beginning of the iteration, the ω value is large, which is conducive to global optimization; ω gradually decreases at the end of the iteration, allowing the gray wolf to better search around the prey and get a better solution.

[0064] Gray wolf position updated to:

[0065] in, Position for the new generation of Gray Wolves; , , is the position of the alpha wolf (optimal solution), where is the current optimal solution (corresponding to the optimal individual α wolf); is the suboptimal solution (corresponding to the suboptimal individual β wolf); is the third best solution (corresponding to the third best individual γ wolf); α, β, and δ wolves represent the current optimal solutions, and the adaptive weights balance the exploration and development capabilities.

[0066] Optimization objectives and constraint processing: Taking the maximization of the modal damping ratio ξ of ultra-low frequency oscillation as the objective function, the penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters:

[0067] in, It is the objective function value after penalty function correction, indicating the comprehensive fitness value after considering parameter constraints, and is used for individual quality evaluation of GWO.

[0068] The phase compensation time constant and gain coefficient of the additional damping controller of G2 are optimized as described in G1. The control parameters of the additional damping controllers of G1 and G2 after optimization are shown in Table 1: Table 1 Control parameters

[0069] It can be seen that when the G1 generator is equipped with an additional damping controller, the phase angle difference 0 is reduced by 52° in the ultra-low frequency oscillation mode of 0.064 Hz; at this time, the G1 hydropower unit provides positive damping, achieving the elimination of negative damping and the overall improvement of dynamic stability.

[0070] When the G1 and G2 generator speed governors are equipped with additional damping controllers, the same load step disturbance is simulated. The system frequencies of the proposed method and the traditional PSO method are as follows: Figure 5 As shown in the figure, when the G1 and G2 generators are equipped with additional damping controllers, the main vibration mode of the system frequency remains almost unchanged, and the damping ratio increases from -0.003 to 0.325, which effectively suppresses the ultra-low frequency oscillation. It can be seen that the method of the present invention performs better than PSO in optimizing the control parameters of the additional damping controller, which also shows the effectiveness of the method proposed in the present invention.

[0071] Finally, it should be noted that the above-listed embodiments exist only as one or more specific forms of expression of the technical solution of the present invention. Their purpose is to clearly explain the concept, principle and application of the present invention through specific examples, and it is by no means intended to limit the protection scope of the present invention to these specific embodiments. In fact, the real value of the present invention lies in the technical ideas and innovations it proposes, rather than its form of expression or means of implementation.

[0072] For ordinary technicians in the relevant technical field, after in-depth reading and understanding of the technical solution of the present invention, they are fully capable of making various forms of changes, modifications or equivalent substitutions to the specific implementation methods of the invention based on their own professional knowledge and skills. These changes may include but are not limited to: adjusting the value range of technical parameters, optimizing algorithm processes to improve efficiency, replacing some technical components to achieve better compatibility or reduce costs, etc. As long as these changed technical solutions still substantially maintain the technical features claimed for protection by the original invention, that is, they can still achieve the core functions and effects of the present invention, then these changes should be deemed to fall within the scope of protection of the pending claims of the present invention.

[0073] In addition, with the continuous progress and development of technology, new technical means and methods continue to emerge, which also provides broad space for further improvement and perfection of the present invention. Therefore, the protection scope of the present invention should also include those reasonably foreseeable improvements and extensions based on the existing technology. As long as these improvements and extensions do not deviate from the basic principles and core concepts of the present invention, they should be regarded as equivalents of the present invention and are also protected by patent rights.

Claims

1. A method for suppressing ultra-low frequency oscillation based on the Grey Wolf optimization algorithm, characterized in that: The following steps are involved: S1. Obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located by integral calculation; S2. Analyze the changing trend of energy increment over time, determine the contribution of each hydropower unit to the ultra-low frequency oscillation, and obtain the hydropower unit with high contribution; S3. Perform phase compensation and negative damping elimination for high-contribution hydropower units through an additional damping controller, wherein the control parameters of the additional damping controller are obtained by optimizing the improved grey wolf optimization algorithm, and the control parameters are the phase compensation time constant and the gain coefficient, and the optimization goal is to maximize the modal damping ratio of the ultra-low frequency oscillation.

2. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1, characterized in that: The improved grey wolf optimization algorithm is specifically: The Tent chaotic map is used to initialize the population and obtain the value range of the control parameters; The position of the grey wolf is updated based on the adaptive weight factor, and the penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters with the goal of maximizing the modal damping ratio of the ultra-low frequency oscillation.

3. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 2 is characterized in that: Tent chaos mapping is specifically: in, is the current iteration number, For the The chaotic variable value of the iteration is [0,1]; For the +1 iteration of the chaos variable value.

4. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 3 is characterized in that: The adaptive weight factor is specifically: in, is the adaptive weight factor; is the minimum weight factor; is the maximum weight factor; is the maximum number of iterations.

5. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 4 is characterized in that: The range of the phase compensation time constant is [0,6]; the range of the gain coefficient is [0.1,1].

6. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 5, characterized in that: The penalty function method is used to constrain the value range of the control parameter as follows: in, It is the optimal solution of modal damping ratio for ultra-low frequency oscillation; is the phase compensation time constant; is the gain coefficient; is the objective function value after correction by penalty function.

7. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1, characterized in that: S1 specifically includes the following steps: S1.

1. The mechanical torque and electromagnetic torque are obtained through the rotor motion equation, where the rotor motion equation is: in, is the inertia time constant; is the mechanical torque; is the electromagnetic torque; is the damping coefficient; is the speed deviation; is the speed deviation change rate; S1.2, decompose the mechanical torque and electromagnetic torque into damping component and synchronous component, and calculate the damping characteristics of the power system where the hydropower unit is located; S1.

3. Based on the damping characteristics, establish the energy change rate of the hydropower unit injected into the power system where it is located ; in, is the change of electromagnetic power; is the initial angular velocity of the hydropower unit; S1.

4. By integrating the energy change rate, calculate the energy increment injected by the hydropower unit into the power system where it is located , specifically: in, is the time differential.

8. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1, characterized in that: The analysis of the change trend of energy increment over time and the determination of the contribution of each hydropower unit to the ultra-low frequency oscillation are specifically as follows: When the energy increment continues to increase and the slope is positive, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is high, and the hydropower unit is a hydropower unit with high contribution; When the energy increment continues to decrease and the slope is negative, it is determined that the contribution of the hydropower unit to the ultra-low frequency oscillation is low, and the hydropower unit is a hydropower unit with low contribution.

9. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1, characterized in that: The phase compensation and negative damping elimination for the high-contribution hydropower unit by using the additional damping controller are specifically as follows: An additional damping controller is introduced before the PID control link of the speed regulator of the high-contribution hydropower unit. The mechanical torque phase is adjusted by the additional damping controller to make it in phase with the frequency deviation of the system where the hydropower unit is located, thereby eliminating the negative damping effect.

10. An ultra-low frequency oscillation suppression system based on the Grey Wolf optimization algorithm, characterized in that: Includes the following modules: The energy increment module is used to obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injected into the power system where the hydropower unit is located, and obtain the energy increment injected into the power system where the hydropower unit is located through integral calculation; Contribution evaluation module, used to analyze the trend of energy increment over time, determine the contribution of each hydropower unit to ultra-low frequency oscillation, and obtain the hydropower units with high contribution; A control module is used to perform phase compensation and negative damping elimination for a high-contribution hydropower unit through an additional damping controller, wherein the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm, and the control parameters are a phase compensation time constant and a gain coefficient, and the optimization goal is to maximize the modal damping ratio of ultra-low frequency oscillation.

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