An Ultra-Low Frequency Oscillation Suppression Method and System Based on Grey Wolf Optimization Algorithm

Abstract

The present invention discloses a method and system for suppressing ultra-low frequency oscillation based on the grey wolf optimization algorithm, belonging to the technical field of power system stability control. The method for suppressing ultra-low frequency oscillation based on the grey wolf optimization algorithm provided by the present invention obtains the damping characteristics of the power system where the hydro-generating unit is located, quantifies the dynamic energy difference between the mechanical power and the electromagnetic power into an energy increment, directly characterizes the influence of the energy interaction of the hydro-generating unit on ULFO, thereby reflecting the energy dynamic process under actual working conditions and avoiding misjudgment of the contribution degree caused by model simplification; by real-time tracking the change rate of the energy increment over time, dynamically calculates the negative damping contribution degree of each hydro-generating unit to ULFO, and accurately identifies the hydro-generating units with high negative damping contribution to ULFO; by using an improved grey wolf optimization algorithm to optimize the control parameters of the additional damping controller, it realizes jumping out of the local optimal solution and improves the convergence speed.

Description

Technical Field

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

[0002] With the wide application of high-head and large-capacity hydro-generating units in the power system, ultra-low frequency oscillation (ULFO) has gradually become a prominent problem threatening the safe and stable operation of the power grid. ULFO is mainly caused by the negative damping effect triggered by improper parameter configuration of the hydro-turbine governing system, specifically manifested as the system frequency continuously fluctuating within a low-frequency range (frequency below 0.1 Hz). If not suppressed in time, this situation may further evolve into serious accidents such as cascading unit tripping and even large-scale power outages.

[0003] In the current technical system, the suppression measures for ULFO have limitations. Specifically, the traditional small-signal stability analysis method is based on a linearized model, making it difficult to accurately quantify the contribution degree of different units to ULFO under complex working conditions, thus weakening the pertinence and effectiveness of the control strategy. On the other hand, the parameter optimization of conventional damping controllers usually relies on the particle swarm optimization (PSO) algorithm, but this particle swarm optimization algorithm has problems such as slow convergence speed, being easily trapped in local optimal solutions, and being difficult to adapt to the dynamic regulation requirements of multiple time scales.

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

[0005] The purpose of the present invention is to provide an ultra-low frequency oscillation suppression method and system based on a grey wolf optimization algorithm, aiming to solve the limitations faced in the current technical field for ultra-low frequency oscillation suppression.

[0006] The present invention solves the above technical problems through the following technical solutions:

[0007] An ultra-low frequency oscillation suppression method based on a grey wolf optimization algorithm, comprising the following steps:

[0008] S1. Obtain the damping characteristics of the power system where the hydro-generating unit is located, establish the energy change rate of the hydro-generating unit injecting into the power system where it is located, and calculate the energy increment of the hydro-generating unit injecting into the power system where it is located through integration;

[0009] S2. Analyze the change trend of energy increment over time, determine the contribution degree of each hydropower unit to ultra-low frequency oscillation, and obtain the hydropower units with high contribution degree;

[0010] S3. Perform phase compensation and negative damping elimination for the hydropower units with high contribution degree through an additional damping controller, where the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm. The control parameters are the phase compensation time constant and the gain coefficient, and the optimization objective is to maximize the modal damping ratio of ultra-low frequency oscillation.

[0011] A further improvement of the present invention lies in that: the improved grey wolf optimization algorithm is specifically:

[0012] Use Tent chaotic mapping to initialize the population and obtain the value range of the control parameters;

[0013] Update the positions of grey wolves based on the adaptive weight factor. With the goal of maximizing the modal damping ratio of ultra-low frequency oscillation, use the penalty function method to constrain the value range of the control parameters and obtain the optimal control parameters.

[0014] A further improvement of the present invention lies in that: Tent chaotic mapping is specifically:

[0015]

[0016] Where, is the current iteration number, is the th iteration of the chaotic variable value, and the value range is [0, 1]; is the +1th iteration of the chaotic variable value.

[0017] A further improvement of the present invention lies in that: the adaptive weight factor is specifically:

[0018]

[0019] Where, is the adaptive weight factor; is the minimum weight factor; is the maximum weight factor; is the maximum number of iterations.

[0020] A further improvement of the present invention lies in that: the range of the phase compensation time constant is [0, 6]; the range of the gain coefficient is [0.1, 1].

[0021] A further improvement of the present invention lies in that: the use of the penalty function method to constrain the value range of the control parameters is specifically:

[0022]

[0023] Among them, is the optimal solution of the modal damping ratio of ultra-low frequency oscillation; is the phase compensation time constant; is the gain coefficient; is the objective function value after penalty function correction.

[0024] A further improvement of the present invention lies in that: S1 specifically includes the following steps:

[0025] S1.1. Obtain the mechanical torque and the electromagnetic torque through the rotor motion equation, where the rotor motion equation is:

[0026]

[0027] Among them, is the inertia time constant; is the mechanical torque; is the electromagnetic torque; is the damping coefficient; is the rotational speed deviation; is the change rate of rotational speed deviation;

[0028] S1.2. Decompose the mechanical torque and the electromagnetic torque into damping components and synchronous components, and calculate the damping characteristics of the power system where the hydropower unit is located;

[0029] S1.3. Based on the damping characteristics, establish the energy change rate injected by the hydropower unit into the power system where it is located ;

[0030]

[0031] Among them, is the change in electromagnetic power; is the initial angular velocity of the hydropower unit;

[0032] 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:

[0033]

[0034] Among them, is the time differential.

[0035] A further improvement of the present invention lies in that: Analyzing the change trend of the energy increment over time, the specific method for determining the contribution degree of each hydropower unit to ultra-low frequency oscillation is:

[0036] When the energy increment continuously increases and the slope is positive, it is determined that the contribution degree of the hydropower unit to ultra-low frequency oscillation is high, and the hydropower unit is a hydropower unit with a high contribution degree;

[0037] When the energy increment continuously decreases and the slope is negative, it is determined that the contribution degree of the hydropower unit to the ultra-low frequency oscillation is low, and the hydropower unit is a hydropower unit with a low contribution degree.

[0038] A further improvement of the present invention lies in that: the phase compensation and negative damping elimination for the hydropower unit with a high contribution degree by the additional damping controller are specifically as follows:

[0039] An additional damping controller is introduced before the speed governor PID control link of the hydropower unit with a high contribution degree, and the mechanical torque phase is adjusted through the additional damping controller to be in phase with the frequency deviation of the system where the hydropower unit is located, so as to eliminate the negative damping effect.

[0040] The present invention also provides an ultra-low frequency oscillation suppression system based on the grey wolf optimization algorithm, including the following modules:

[0041] 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 injected by the hydropower unit into the power system where it is located, and obtain the energy increment injected by the hydropower unit into the power system where it is located through integral calculation;

[0042] The contribution degree evaluation module is used to analyze the change trend of the energy increment over time, determine the contribution degree of each hydropower unit to the ultra-low frequency oscillation, and obtain the hydropower unit with a high contribution degree;

[0043] The control module is used to perform phase compensation and negative damping elimination for the hydropower unit with a high contribution degree through the additional damping controller, wherein the control parameters of the additional damping controller are optimized by the improved grey wolf optimization algorithm, 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.

[0044] Compared with the prior art, the positive and progressive effects of the present invention are as follows:

[0045] The ultra-low frequency oscillation suppression method based on the grey wolf optimization algorithm provided by the present invention realizes the rapid suppression of ULFO and the comprehensive improvement of the system frequency stability through the collaborative control of energy dynamic characteristic analysis, accurate evaluation of the contribution degree of hydropower units and parameter optimization. Specifically, by obtaining the damping characteristics of the power system where the hydropower unit is located, quantifying the dynamic energy difference between the mechanical power and the electromagnetic power into the energy increment, directly characterizing the influence of the energy interaction of the hydropower unit on ULFO, thereby reflecting the energy dynamic process under the actual working conditions and avoiding the misjudgment of the contribution degree caused by model simplification; by tracking the change rate of the energy increment over time in real time, dynamically calculating the negative damping contribution degree of each hydropower unit to ULFO, and accurately identifying the hydropower unit with a high negative damping contribution to ULFO; by optimizing the control parameters of the additional damping controller by using the improved grey wolf optimization algorithm, it is realized to jump out of the local optimal solution and improve the convergence speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a 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 an improper limitation of the present invention.

[0047] Figure 1 It is a schematic flowchart of the ultra-low frequency oscillation suppression method based on the grey wolf optimization algorithm of the present invention;

[0048] Figure 2 It is a schematic diagram of the system of Embodiment 1 of the present invention;

[0049] Figure 3 It is a frequency waveform diagram of the DC (Direct Current) transmitter in Embodiment 1 of the present invention, where the abscissa is time t and the ordinate is frequency f;

[0050] Figure 4 It is a schematic diagram of the energy increment of the hydro-generating units G1 to G4 in Embodiment 1 of the present invention, where the abscissa is the hydro-generating units G1 to G4 and the ordinate is the energy increment;

[0051] Figure 5 It is a schematic diagram of the system frequency comparison between the method of the present invention and the traditional PSO method, where the abscissa is time t and the ordinate is frequency f. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] In the description of the present invention, it should be understood that the terms "including" and "comprising" indicate the presence of the 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 their combinations.

[0054] It should also be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification and claims of the present invention, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0055] It should be understood that although terms such as first, second, and third may be used in the embodiments of the present invention to describe preset ranges and the like, these preset ranges should not be limited to these terms. These terms are only used to distinguish the 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.

[0056] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (stated condition or event)" or "in response to detecting (stated condition or event)".

[0057] Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the drawings. These figures are not drawn to scale, where for the purpose of clear expression, some details are enlarged and some details may be omitted. The shapes of various regions and layers shown in the figures and their relative sizes and positional relationships are merely exemplary, and in practice, there may be deviations due to manufacturing tolerances or technical limitations, and those skilled in the art can design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0058] Glossary:

[0059] CloudPSS (Cloud-based Power System Simulator): An integrated energy network analysis tool that combines Internet, cloud computing, and parallel computing technologies.

[0060] Standard 4M2A system model: Refers to an industrial control system model that uses 4 - 20mA analog signals for data transmission.

[0061] The following further elaborates on the present invention in detail in conjunction with the drawings and specific embodiments, which is an explanation rather than a limitation of the present invention.

[0062] See Figure 1 , a method for suppressing ultra-low frequency oscillation based on the grey wolf optimization algorithm, comprising the following steps:

[0063] S1. Obtain the damping characteristics of the power system where the hydropower unit is located, establish the energy change rate of the hydropower unit injecting into the power system where it is located, and calculate the energy increment of the hydropower unit injecting into the power system where it is located through integration;

[0064] S2. Analyze the variation trend of the energy increment over time, determine the contribution degree of each hydropower unit to the ultra-low frequency oscillation, and obtain the hydropower units with high contribution degrees.

[0065] S3. Perform phase compensation and negative damping elimination for the hydropower units with high contribution degrees through an additional damping controller, where the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm. The control parameters are the phase compensation time constant and the gain coefficient, and the optimization objective is to maximize the modal damping ratio of the ultra-low frequency oscillation.

[0066] The ultra-low frequency oscillation suppression method based on the grey wolf optimization algorithm provided by the present invention realizes the rapid suppression of ULFO and the comprehensive improvement of the system frequency stability through the collaborative control of energy dynamic characteristic analysis, accurate evaluation of the contribution degree of hydropower units, and parameter optimization. Specifically, by obtaining the damping characteristics of the power system where the hydropower units are located, quantifying the dynamic energy difference between the mechanical power and the electromagnetic power as the energy increment, directly characterizing the impact of the energy interaction of the hydropower units on ULFO, thus reflecting the energy dynamic process under actual working conditions and avoiding misjudgment of the contribution degree caused by model simplification; by real-time tracking the change rate of the energy increment over time, dynamically calculating the negative damping contribution degree of each hydropower unit to ULFO, and accurately identifying the hydropower units with high negative damping contribution to ULFO; by optimizing the control parameters of the additional damping controller by using an improved grey wolf optimization algorithm, realizing jumping out of the local optimal solution and improving the convergence speed.

[0067] Specifically, the improved grey wolf optimization algorithm is as follows:

[0068] Use Tent chaotic mapping to initialize the population to obtain the value range of the control parameters.

[0069] Update the positions of the grey wolves based on the adaptive weight factor, and use the penalty function method to constrain the value range of the control parameters with the goal of maximizing the modal damping ratio of the ultra-low frequency oscillation to obtain the optimal control parameters.

[0070] Specifically, Tent chaotic mapping is as follows:

[0071]

[0072] where is the current iteration number, is the th iteration value of the chaotic variable, and the value range is [0, 1]; is the +1th iteration value of the chaotic variable.

[0073] Specifically, the adaptive weight factor is as follows:

[0074]

[0075] Among them, is the adaptive weight factor; is the minimum weight factor; is the maximum weight factor; is the maximum number of iterations.

[0076] Specifically, the range of the phase compensation time constant is [0, 6]; the range of the gain coefficient is [0.1, 1].

[0077] Specifically, the constraint on the value range of the control parameters by using the penalty function method is specifically as follows:

[0078]

[0079] Among them, is the optimal solution of the modal damping ratio of ultra-low frequency oscillation; is the phase compensation time constant; is the gain coefficient; is the value of the objective function after penalty function correction.

[0080] Specifically, S1 specifically includes the following steps:

[0081] S1.1. Obtain the mechanical torque and the electromagnetic torque through the rotor motion equation, where the rotor motion equation is:

[0082]

[0083] Among them, is the inertia time constant; is the mechanical torque; is the electromagnetic torque; is the damping coefficient; is the speed deviation; is the rate of change of speed deviation;

[0084] S1.2. Decompose the mechanical torque and the electromagnetic torque into damping components and synchronous components, and calculate the damping characteristics of the power system where the hydropower unit is located;

[0085] S1.3. Based on the damping characteristics, establish the energy change rate injected by the hydropower unit into the power system where it is located ;

[0086]

[0087] Among them, is the change in electromagnetic power; is the initial angular velocity of the hydropower unit;

[0088] S1.4. Calculate the energy increment injected by the hydropower unit into the power system where it is located by integrating the energy change rate , specifically as follows:

[0089]

[0090] where, is the time differential.

[0091] Specifically, the analysis of the change trend of the energy increment over time to determine the contribution degree of each hydropower unit to the ultra - low - frequency oscillation is specifically as follows:

[0092] When the energy increment continuously increases and the slope is positive, it is determined that the contribution degree of the hydropower unit to the ultra - low - frequency oscillation is high, and the hydropower unit is a high - contribution - degree hydropower unit;

[0093] When the energy increment continuously decreases and the slope is negative, it is determined that the contribution degree of the hydropower unit to the ultra - low - frequency oscillation is low, and the hydropower unit is a low - contribution - degree hydropower unit.

[0094] Specifically, the phase compensation and negative - damping elimination for the high - contribution - degree hydropower unit by the additional damping controller are specifically as follows:

[0095] Introduce an additional damping controller before the speed governor PID control link of the high - contribution - degree hydropower unit, and adjust the mechanical torque phase through the additional damping controller to make it in - phase with the frequency deviation of the system where the hydropower unit is located, and eliminate the negative - damping effect.

[0096] Based on the same inventive concept, the present invention also provides an ultra - low - frequency oscillation suppression system based on the grey wolf optimization algorithm, including the following modules:

[0097] Energy increment module, 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 it is located, and calculate the energy increment of the hydropower unit injected into the power system where it is located by integration;

[0098] Contribution degree evaluation module, used to analyze the change trend of the energy increment over time, determine the contribution degree of each hydropower unit to the ultra - low - frequency oscillation, and obtain the high - contribution - degree hydropower units;

[0099] Control module, used to perform phase compensation and negative - damping elimination for the high - contribution - degree hydropower unit through an additional damping controller, where the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm, the control parameters are the phase compensation time constant and the gain coefficient, and the optimization objective is to maximize the modal damping ratio of the ultra - low - frequency oscillation.

[0100] Embodiment 1

[0101] A simulation model based on the standard 4M2A system model was built in CloudPSS:

[0102] Build the simulation model and load step disturbance: See Figure 2 , Region ① is the DC sending end, Region ② is the receiving end. Region ① contains four hydro-generators, namely G1, G2, G3 and G4; Region ② contains two hydro-generators, namely G5 and G6. All hydro-generators are high-head and high-capacity hydro-generator units with a rated capacity of 900 MV·A. The rated transmission power of the DC sending-end system is 400 MW, and the load L 1 in Region ① is 2188 MW, and the load L 2 in Region ② is 1854 MW. The governor parameters of each hydro-generator unit are shown in the following table:

[0103]

[0104] See Figure 3 , at t = 5 s, the load disturbance in Region ① is simulated as a 100 MW load power loss; after the load disturbance, ultra-low frequency oscillation occurs, with a frequency of 0.064 Hz and a damping ratio of -0.003.

[0105] Therefore, in order to suppress the ultra-low frequency oscillation, it is necessary to sort the contribution degrees of the hydro-generator units to the ultra-low frequency oscillation, then install additional damping controllers on the hydro-generator units with high contribution degrees, and optimize the control parameters of the additional damping controllers.

[0106] Obtain the damping characteristics of the power system where the hydro-generator units are located, establish the energy change rate of the hydro-generator units injecting into the power system where they are located, and calculate the energy increment of the hydro-generator units injecting into the power system where they are located through integration: See Figure 4 , is the energy increment injected into the network by hydro-generator units G1~G4. It can be seen that the energy increments E Hamilton of G1 and G2 gradually increase with time, indicating that the energy injected into the system continues to increase. In contrast, the energy increments E Hamilton of G3 and G4 gradually decrease with time, indicating that the energy injected into the system continues to decrease; by comparing the energy increments E Hamilton of each hydro-generator unit, the sorting of the contribution of the hydro-generator units to the ultra-low frequency oscillation is obtained as G1 = G2 > G3 = G4.

[0107] Obtain high - contribution hydropower units G1 and G2, and perform phase compensation and negative damping elimination for the high - contribution hydropower units through an additional damping controller. Among them, the control parameters of the additional damping controller are optimized by an improved grey wolf optimization algorithm. The control parameters are the phase compensation time constant and the gain coefficient, and the optimization objective is to maximize the modal damping ratio of ultra - low - frequency oscillation. In order to suppress ultra - low - frequency oscillation, an additional damping controller is installed on the governors of G1 and G2.

[0108] 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 s, 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).

[0109] Taking G1 as an example, for phase compensation and negative damping elimination, the optimization process of the control parameters of the additional damping controller is as follows: the population size is 50, and k max is 100.

[0110] The initial grey wolf population of traditional GWO is randomly generated, which may lead to local optimality. The Tent chaos sequence is characterized by better regularity and ergodicity. Compared with other mappings, the Tent chaos mapping generates a more uniform sequence distribution. Therefore, the Tent chaos mapping is used to initialize the grey wolf population.

[0111] The specific implementation process of the improved grey wolf optimization algorithm is as follows:

[0112] 1. Tent chaos initialization of population generation

[0113] (1) Set the population size to 50 and the search dimension to 2 (corresponding to the phase compensation time constant T i and the gain coefficient K);

[0114] (2) Based on the Tent chaos mapping, generate a chaos sequence:

[0115]

[0116] (3) Map the chaos sequence to the value range of the control parameters:

[0117] 、

[0118] is the value of the i - th chaos sequence at the k - th iteration; is the value of the (2k−1) - th chaos variable; is the control parameter at the k-th iteration; is the value of the 2k-th chaotic variable; is the number of iterations (k = 1, 2,..., 100);

[0119] This process is used to ensure that the initial solution of the control parameter is uniformly distributed in the intervals [0, 6] and [0.1, 1], avoiding local aggregation caused by traditional random initialization.

[0120] 2. Adaptive Weight Dynamic Adjustment

[0121] Update the gray wolf position based on the adaptive weight factor:

[0122] Adaptive weight factor is:

[0123]

[0124] where = 0.9; = 0.4;

[0125] In the initial stage (t < 30): ω > 0.7, enhancing the global search ability and quickly locating potential optimal regions; in the middle stage (30 ≤ t < 70): normal iteration; in the later stage (t ≥ 70): ω < 0.45, improving the local development accuracy and refining parameter adjustment; at the beginning of the iteration, the value of ω is large, which helps with global optimization; ω gradually decreases at the end of the iteration, allowing the gray wolf to better search around the prey and obtain a better solution.

[0126] The gray wolf position is updated as:

[0127]

[0128] where is the position of the new generation of gray wolves; , , are the positions of the lead wolves (optimal solutions), where is the current optimal solution (corresponding to the optimal individual α wolf); is the sub-optimal solution (corresponding to the sub-optimal individual β wolf); is the third-best solution (corresponding to the third-best individual γ wolf); The α, β, and δ wolves represent the current optimal solutions, and the adaptive weight balances the exploration and development capabilities.

[0129] Optimization objective and constraint handling: Taking the maximization of the modal damping ratio ξ of ultra-low frequency oscillation as the objective function, using the penalty function method to constrain the value range of the control parameter, and obtaining the optimal control parameter:

[0130]

[0131] Among them, is the objective function value after penalty function correction, representing the comprehensive fitness value considering the parameter constraint conditions, and is used for the individual quality evaluation of GWO.

[0132] The phase compensation time constant and gain coefficient of the additional damping controller of G2 are optimized by the method described for G1. The control parameters of the optimized additional damping controllers of G1 and G2 are shown in Table 1:

[0133] Table 1 Control Parameters

[0134]

[0135] It can be seen that when the G1 generator is equipped with an additional damping controller, at the ultra-low frequency oscillation mode of 0.064 Hz, the phase angle difference 0 decreases by 52°; at this time, the G1 hydropower unit provides positive damping, achieving the elimination of negative damping and a comprehensive improvement in dynamic stability.

[0136] When the speed governors of G1 and G2 generators are equipped with additional additional damping controllers and the same load step disturbance is simulated, the system frequencies of the proposed method and the traditional PSO method are as Figure 5 shown. When the G1 and G2 generators are equipped with additional damping controllers, the main vibration modes of the system frequency almost remain unchanged, and the damping ratio increases from -0.003 to 0.325, effectively suppressing 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 demonstrates the effectiveness of the method proposed by the present invention.

[0137] Finally, it should be noted that the above-listed embodiments exist only as one or more specific manifestation forms of the technical solution of the present invention. Their purpose is to clearly elaborate the concept, principle and application method of the present invention through specific examples, rather than intending 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 proposed technical idea and innovation point, rather than its manifestation form or implementation means.

[0138] For those of ordinary skill in the art, after thoroughly reading and understanding the technical solution of the present invention, they are fully capable of making various forms of changes, modifications, or equivalent replacements to the specific implementation manners 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 the algorithm process to improve efficiency, replacing some technical components to achieve better compatibility or reduce costs, etc. As long as the changed technical solution still substantially maintains the technical features required to be protected by the original invention, that is, it can still achieve the core functions and effects of the present invention, then these changes should be regarded as falling within the protection scope of the pending claims of the present invention.

[0139] In addition, with the continuous progress and development of technology, new technical means and methods are emerging continuously, which also provides broad space for the further improvement and perfection of the present invention. Therefore, the protection scope of the present invention should also include those reasonably foreseeable improvements and expansions based on the existing technology. As long as these improvements and expansions do not depart from the basic principles and core concepts of the present invention, they should be regarded as equivalents of the present invention and are equally protected by the patent right.

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, performing phase compensation and negative damping elimination for the high-contribution hydropower unit 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; 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 gray wolf is updated based on the adaptive weight factor, with the goal of maximizing the modal damping ratio of ultra-low frequency oscillation. The penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters. 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; 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.

2. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1, 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.

3. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1 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].

4. 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.

5. The ultra-low frequency oscillation suppression method based on the Grey Wolf Optimization Algorithm according to claim 1 is 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.

6. 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.

7. 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 hydropower unit with a high contribution 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; the improved Grey Wolf optimization algorithm is specifically 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 gray wolf is updated based on the adaptive weight factor, with the goal of maximizing the modal damping ratio of ultra-low frequency oscillation. The penalty function method is used to constrain the value range of the control parameters to obtain the optimal control parameters. 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; 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.

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