SVG multi-working condition control parameter optimization method and system

Abstract

The application discloses an SVG multi-working condition control parameter optimization method and system, calculates system stability margin through establishing a new energy station single-input single-output admittance model without SVG, positions a critical stable working condition after traversing the working condition of the new energy station, sets the running working condition range of the SVG and judges the system stability margin after the SVG accesses the critical stable working condition of the new energy station, calculates the system impedance ratio sensitivity of the new energy station with the SVG, positions and adjusts the leading control parameter of the SVG to meet the system margin target. The application comprehensively considers the impedance characteristic change of the SVG under different running working conditions, improves the stability margin of the new energy station with the SVG under multi-working conditions, and reduces the wide-frequency oscillation risk caused by the interaction between the new energy station and the power grid. The application can be widely applied to wind power, photovoltaic and other new energy stations with the SVG, provides a systematic solution method for the parameter setting and stable control of the SVG under multiple running scenes, and enhances the stability and working condition adaptability of the new energy grid-connected system.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and in particular to a method and system for optimizing SVG multi-condition control parameters. Background Technology

[0002] To ensure that the voltage at renewable energy power plants remains at a qualified level, a Static Var Generator (SVG) is typically installed at the 35kV busbar within the plant to enable rapid and flexible voltage regulation. However, the integration of SVGs can adversely affect the small-disturbance stability of renewable energy grid-connected systems. The impedance of renewable energy grid-connected systems containing SVGs interacts with the grid impedance, making the system prone to broadband oscillations, which seriously threaten the safe and stable operation of the renewable energy grid-connected system.

[0003] The control parameters of the SVG (Static Var Generator) significantly affect the impedance characteristics of the renewable energy grid-connected system. Therefore, adjusting the SVG control parameters appropriately can effectively improve the system's stability margin. Existing technologies guide parameter adjustment by establishing a local impedance model and calculating impedance sensitivity. However, this method has limitations. It typically only optimizes for the subsynchronous / supersynchronous frequency band and lacks a multi-condition SVG parameter adjustment approach to address broadband oscillations, resulting in poor suppression of broadband oscillations. Furthermore, existing technologies do not consider the impact of SVG operation under multiple conditions on system stability, making the parameter adjustment results insufficient for stable system operation under various SVG operating conditions, and the parameter optimization results lack adaptability. Therefore, there is an urgent need to propose an SVG parameter optimization method that can adapt to multi-condition operation to enhance the stability of the renewable energy grid-connected system across multiple operating conditions and ensure its safety and stability under complex operating conditions. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and system for optimizing SVG multi-condition control parameters to effectively suppress the risk of broadband oscillation caused by SVG access, in order to address the shortcomings of the existing technology.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for optimizing SVG multi-condition control parameters, comprising the following steps:

[0006] S1. Establish broadband frequency coupling admittance Y for new energy power stations without SVG. w Obtain the grid impedance Z g ; Calculate the single-input single-output admittance model Y of the new energy power station w_SISO Based on Y w_SISOThe phase stability margin of the renewable energy power station is calculated based on the grid impedance. By iterating through and calculating the phase stability margin of the renewable energy power station under various operating conditions, the critical stability condition and oscillation risk frequency band are located, and the admittance Y of the renewable energy power station under the critical stability condition is output. wc With grid impedance Z gc ;

[0007] S2, Based on the admittance Y of the new energy power station under the critical stability condition wc With grid impedance Z gc Calculate Q j Under operating conditions, the single-input single-output admittance Y of SVG connected to a new energy power station wj_SISO Based on Y wj_SISO and grid impedance Z gc Calculate the impedance ratio Z of a new energy power station system containing SVG. ratios Regarding the phase stability margin, if the phase stability margin of a new energy power station system with SVG is lower than that of a new energy power station without SVG, then proceed to step S3; Q j The range of values ​​for is [Q min Q max ];

[0008] S3, Impedance ratio Z of new energy power station system with SVG ratios Calculate the relative sensitivity Rλ of each control parameter of the SVG. k Based on the oscillation risk frequency band and the calculation results of relative sensitivity, the dominant control parameter of the SVG is located, and the absolute value of the relative sensitivity of the dominant control parameter at the oscillation risk frequency band is |Rλ. k Maximum;

[0009] S4. Set the phase stability margin constraint target condition, and adjust the SVG dominant control parameters until the constraint target condition is met, and obtain Q. j The optimal dominant control parameter value of the SVG under the given operating condition is determined, and the process returns to step S2 to set the next SVG operating condition to be calculated, proceeding to the next iteration. Otherwise, if Q... j If the parameter optimization program fails to converge under certain operating conditions, then SVG should be prohibited from running on Q. j Under operating conditions.

[0010] In step S1, by iteratively calculating the phase stability margin of the new energy power station under various operating conditions, the critical stability operating conditions and oscillation risk frequency bands are located, which can expand the parameter optimization target from a single frequency band to the entire frequency band and the worst operating conditions. Step S2 further optimizes the parameters under different SVG operating conditions. j The stability margin after SVG integration is evaluated to achieve multi-condition coverage. Step S3 introduces the impedance ratio Z of the new energy power station system containing SVG. ratios Based on this, the relative sensitivity Rλ of each control parameter is calculated. kThe impedance ratio directly reflects the overall stability change of the system after SVG connection. Relative sensitivity analysis can accurately identify the SVG control parameters with the greatest impact in the oscillation risk frequency band, giving parameter adjustment a clear system-level guide, avoiding blind adjustments, and achieving precise optimization. S4 sets the phase stability margin constraint target, and adjusts the parameters through iterative optimization until the stability margin requirement is met. Therefore, this invention forms a systematic, multi-condition parameter optimization process with strong engineering feasibility and stability assurance capabilities, and can effectively suppress the broadband oscillation risk caused by SVG connection.

[0011] Single-input single-output admittance model Y of new energy power station w_SISO The expression is:

[0012] ;

[0013] Among them, Y w_11 Y w_12 Y w_21 Y w_22 For the broadband frequency coupling admittance Y of new energy power stations without SVG w The four elements, Z g_11 Z g_22 These are the positive-sequence impedance and negative-sequence impedance of the power grid.

[0014] The above model uses the 2×2 frequency-coupled admittance matrix Y of the new energy power station. w With the 2×2 impedance matrix Z of the power grid g The complex interactions between them can be simplified into a single-input, single-output model, which retains the frequency coupling characteristics and thus ensures the accuracy of the model while simplifying the subsequent analysis and application.

[0015] Q j Under operating conditions, the single-input single-output admittance Y of SVG connected to a new energy power station wj_SISO The calculation formula is:

[0016] ;

[0017] in, , , , For the admittance Y of new energy power stations under critical stable operating conditions wc The four elements, , The grid impedance Z of the new energy power station under critical stability conditions gc diagonal elements, , , , For SVG operating conditions Q jTime-frequency coupling admittance Y svgj The four elements in it.

[0018] The formula for calculating the phase stability margin of a new energy power station is: Among them, Z ratio For the impedance ratio of a new energy power station system without SVG, ω co At the frequency point where the impedance ratio amplitude is 1, γ s Let arg be the phase stability margin of the new energy power station system, and arg be the phase function for calculating the impedance.

[0019] The formula for calculating the relative sensitivity is:

[0020] ;

[0021] Among them, Z ratios For the impedance ratio of a new energy power station system containing SVG, k0 and k p Z represents the initial value and disturbance value of a certain control parameter k in the SVG, respectively. ratios_0 (s r ) and Z ratios_p (s r ) are frequencies f r The impedance ratio before and after the disturbance of the SVG control parameter k, s r =j2πf r , The grid impedance Z under critical steady-state conditions gc of Element in s r The impedance value below.

[0022] The change in the molecule of relative sensitivity is the impedance ratio Z of the new energy power station system containing SVG. ratios This allows relative sensitivity to directly measure the impact of minute changes in SVG parameters on the overall stability margin of the system. Parameter optimization guided by this principle can ensure that parameter adjustments directly and effectively improve system-level stability.

[0023] The expression for the dominant control parameter is: Where Δk is the parameter variation step size, k i k represents the dominant control parameter of the SVG in step i. i+1 Let represent the dominant control parameters of the SVG after the (i+1)th update, and 'sign' be the sign function. The input to the sign function 'sign' is the real part of the impedance ratio sensitivity, and the sign of this real part directly corresponds to the direction of the influence of parameter adjustment on the system's phase stability margin. This ensures that each iteration is explicitly directed towards improving stability, further suppressing the risk of broadband oscillations caused by SVG access.

[0024] The constraint objective condition is expressed as follows: The phase margin set by this constraint objective condition is much higher than the critical phase margin, ensuring that the system has high safety and stability.

[0025] The (j+1)th SVG working condition Q to be calculated j+1 Represented as: Q j+1 =Q j +ΔQ, where ΔQ is the step size for the change in operating conditions. Here, Q represents the reactive power value output by the SVG (Q0). j That is, setting the reactive power Q of the SVG output. j This operating condition), namely the SVG's operating condition, is when the operating condition Q changes, the SVG's frequency coupling admittance Y svg The value of ΔQ will change. The setting of ΔQ needs to comprehensively consider both optimization accuracy and computational efficiency; in this invention, ΔQ = 0.5MVar is set.

[0026] As an inventive concept, the present invention also provides an SVG multi-condition control parameter optimization system, including a memory, a processor, and a computer program stored in the memory; the processor executes the computer program to implement the steps of the above method.

[0027] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention can accurately and efficiently adjust the SVG control parameters to address the broadband oscillation stability problem, thereby significantly improving the stability margin of the new energy grid-connected system across the entire frequency band and multiple operating conditions. By establishing and utilizing a single-input single-output model between the new energy power station and the grid to locate the oscillation risk frequency band, and combining it with impedance ratio sensitivity analysis, this invention can accurately identify the key SVG parameters that have the greatest impact on the broadband oscillation characteristics of the system, thus overcoming the limitation of traditional methods that only optimize parameters for a single frequency band. Furthermore, this method fully considers the multi-condition characteristics of SVG in actual operation. By observing the variation law of impedance ratio sensitivity at different operating points, it achieves the broad adaptability of parameter optimization results to various operating conditions, effectively solving the problem of insufficient stability effect of existing methods when SVG operating conditions change. This invention not only effectively suppresses the broadband oscillation risk caused by SVG access, but also significantly improves the engineering practicality and system robustness of parameter tuning, providing reliable technical support for the safe and stable operation of new energy power stations containing SVG. Attached Figure Description

[0028] Figure 1 This is an embodiment of the new energy power station topology containing SVG according to the present invention;

[0029] Figure 2 This is a flowchart of an embodiment of the present invention for optimizing SVG multi-condition parameters of impedance ratio sensitivity of new energy power stations;

[0030] Figure 3The present invention provides the impedance ratio relative sensitivity calculation results and parameter location results according to an embodiment of the present invention.

[0031] Figure 4 This invention provides an embodiment of the stability margin of renewable energy power plants before and after SVG parameter optimization.

[0032] Figure 5 This is a waveform of the 35kV bus voltage and current of a renewable energy power station before parameter optimization when the SVG is running at Q=0MVar according to an embodiment of the present invention.

[0033] Figure 6 This is a waveform of the 35kV bus voltage and current of an SVG operating at Q=0MVar in an embodiment of the present invention, after parameter optimization and input into a new energy power station. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Example 1

[0036] Figure 1 The topology of the new energy power station containing SVG in Embodiment 1 of the present invention consists of direct-drive wind turbine units Y1-Y 15 Box-type transformer T1-T 15 Internal collection lines and main transformer T m Composition. The direct-drive wind turbine is connected to the 35kV feeder via a box-type transformer, and the cascaded SVG is connected to the 35kV busbar. g Y is the equivalent impedance of the power grid on the 35kV side. w For the frequency coupling admittance of the new energy power station, Y svg This is the frequency coupling admittance of the SVG.

[0037] like Figure 2 As shown in Embodiment 1 of the present invention, an SVG multi-condition control parameter optimization method for suppressing broadband oscillations in renewable energy power plants includes the following steps:

[0038] 1) Oscillation frequency band location for new energy power stations. Using harmonic linearization or impedance identification methods, establish the broadband frequency coupling admittance Y of new energy power stations without SVG. w Obtain the grid impedance Z g :

[0039]

[0040] Where: Y w_11 Y w_12 Y w_21 Y w_22 The four elements are the frequency coupling admittance of new energy power stations; Z g_11 Z g_22 Given the positive and negative sequence impedances of the power grid; calculate the single-input single-output admittance model Y of the new energy power station. w_SISO :

[0041]

[0042] Based on Y w_SISO Calculate the phase stability margin of new energy power plants based on grid impedance:

[0043]

[0044] Among them: Z ratio For the impedance ratio of a new energy power station system without SVG, ω co At the frequency point where the impedance ratio amplitude is 1, γ s Let arg be the impedance phase stability margin of the new energy power station system, and arg be the impedance phase function. Based on the above method, by iteratively calculating the phase stability margin of each operating condition of the new energy power station, the critical stability condition and the oscillation risk frequency band are located. Under this critical stability condition, the system stability margin is defined as 3°≤γ. s ≤5°, the oscillation risk frequency band is defined as ω co -50π≤ω co ≤ω co +50π. Output admittance Y of new energy power plants under critical stability conditions. wc With grid impedance Z gc :

[0045]

[0046] 2) SVG impedance modeling and stability assessment after integration into renewable energy power plants. The operating range of the SVG is set as [Q...]. min Q max ], calculate the SVG operating condition as Q j Time-frequency coupling admittance Y svgj :

[0047]

[0048] Based on the critical stability condition identified in step 1), calculate Q. j Single-input single-output admittance of SVG connected to a new energy power station under operating conditions:

[0049]

[0050] Based on Y wj_SISO Calculation of impedance ratio Z of new energy power station system including SVG and grid impedance. ratios Phase stability margin with new energy power stations:

[0051]

[0052] If it is determined that the stability margin further decreases after the connection is established, the SVG parameter adjustment program will be started.

[0053] 3) Impedance ratio Z of new energy power station system with SVG ratios Calculate the relative sensitivity of each control parameter of the SVG to determine the dominant control parameter of the SVG. The relative sensitivity of the impedance ratio is:

[0054]

[0055] Where: Rλ k For the impedance ratio relative sensitivity of the SVG control parameter k, k0 and k p Z represents the initial value and disturbance value of parameter k, respectively. ratios_0 (s r ) and Z ratios_p (s r ) are respectively f r The impedance ratio before and after parameter perturbation at a given frequency, s r =j2πf r Based on the oscillation risk frequency band and relative sensitivity calculation results, the dominant control parameter of the SVG is located, and the absolute value of the sensitivity of this dominant control parameter at the oscillation risk frequency band is |Rλ. k |Maximum. Figure 3 The following are the impedance ratio relative sensitivity calculation results and parameter positioning results of an embodiment of the present invention, from... Figure 3 It can be seen that within the oscillation risk frequency band, the proportional parameter k of the SVG inner loop current is located. p_i The absolute value of the sensitivity is the largest, so this parameter needs to be adjusted to meet the system phase stability margin constraint target condition.

[0056] 4) Adjust the dominant control parameters to meet the system margin target. Based on the impedance ratio relative sensitivity obtained in step 3), adjust the dominant control parameters as follows:

[0057]

[0058] Where: Δk is the parameter variation step size, which is taken as 1.0 × 10⁻⁶ here. -5 k i k represents the dominant control parameter of the SVG at the current step i. i+1 This represents the dominant control parameter of the SVG after the (i+1)th step update, where `sign` is the sign function. Set the phase stability margin constraint objective condition:

[0059]

[0060] If the dominant control parameters of the SVG satisfy the constraint objective, output the optimal control parameters of the SVG under this operating condition, and return to step 2) to set the next SVG operating condition Q to be calculated. j+1 =Q j +ΔQ, where ΔQ is the step size of the operating condition change, to proceed to the next cycle; otherwise, if the parameter optimization program cannot converge under this operating condition, then SVG is prohibited from running under this operating condition.

[0061] Figure 4 To illustrate the stability margin of new energy power plants before and after SVG parameter optimization in this embodiment of the invention, from... Figure 4 It can be seen that under this operating condition, the phase stability margin of the SVG after parameter optimization is increased from -1° to 20°, ensuring the stable operation of the system under this operating condition after the SVG is put into operation.

[0062] Figure 5 This is the voltage and current waveform of the 35kV bus after the SVG is put into operation at a new energy power station when the parameters are optimized and the SVG is running at Q=0MVar according to an embodiment of the present invention. Figure 5 It can be seen that after the SVG with unoptimized parameters is connected to the new energy power station, the system is determined to be unstable because the phase stability margin is less than 0°, and the voltage and current at the 35kV bus exhibit oscillation at 123Hz. Figure 6 This is the voltage and current waveform of the 35kV busbar of a renewable energy power station after parameter optimization when the SVG is running at Q=0Mvar according to an embodiment of the present invention. Figure 6 It can be seen that the phase stability margin of the SVG after parameter optimization is greater than 20° when connected to the new energy power station, indicating that the system is stable. The voltage and current at the 35kV bus remain stable after the SVG is put into operation, which proves the effectiveness of the multi-condition SVG parameter optimization method based on the impedance ratio sensitivity of the new energy power station in this embodiment of the invention.

[0063] Example 2

[0064] Embodiment 2 of the present invention provides an optimized system corresponding to Embodiment 1 above, including a memory, a processor, and a computer program stored in the memory; the processor executes the computer program in the memory to implement the steps of the method of Embodiment 1 above.

[0065] In some implementations, the memory may be high-speed random access memory (RAM), and may also include non-volatile memory, such as at least one disk storage device.

[0066] In other implementations, the processor can be any type of general-purpose processor, such as a central processing unit (CPU) or a digital signal processor (DSP), and there is no limitation here.

[0067] Example 3

[0068] Embodiment 3 of the present invention provides a computer-readable storage medium corresponding to Embodiment 1 above, on which a computer program / instructions are stored. When the computer program / instructions are executed by a processor, they implement the steps of the method of Embodiment 1 above.

[0069] A computer-readable storage medium can be a tangible device that holds and stores instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any combination thereof.

[0070] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0071] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0072] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0073] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0074] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An SVG multi-operation condition control parameter optimization method, characterized in that, The method comprises the following steps: S1, establish new energy station broadband frequency coupling admittance Y without SVG w , get grid impedance Z g ; calculate new energy station single-input single-output admittance model Y w_SISO , calculate new energy station phase stability margin based on Y w_SISO and grid impedance; by traversing the calculation of new energy station phase stability margin of each working condition, locate the critical stable working condition and oscillation risk frequency band, output new energy station admittance Y wc and grid impedance Z gc under the critical stable working condition; S2, based on the critical stable operating condition, the new energy station admittance Y wc and the grid impedance Z gc , calculate Q j The single-input single-output admittance Y of the SVG accessing the new energy station under the operating condition wj_SISO ; based on Y wj_SISO and the grid impedance Z gc , calculate the SVG-containing new energy station system impedance ratio Z ratios and the phase stability margin, if the phase stability margin of the SVG-containing new energy station system is lower than the phase stability margin of the new energy station without SVG, enter step S3; the value range of Q j is [Q min , Q max ]. S3, impedance ratio Z of the SVG-based new energy station system ratios calculating the relative sensitivity Rλ of each control parameter of the SVG k locating the dominant control parameter of the SVG according to the oscillation risk frequency band and the calculation result of the relative sensitivity, the absolute value |Rλ k | of the relative sensitivity of the dominant control parameter at the oscillation risk frequency band is maximum S4, set a phase stability margin constraint target condition, adjust the SVG main control parameter until the constraint target condition is met, obtain Q j the optimal main control parameter value of the SVG under the working condition, return to step S2 to set the next SVG working condition to be calculated, and perform the next round of circulation, otherwise if the parameter optimization program cannot converge under the working condition Q j the working condition. The SVG is prohibited from running under the working condition Q j the working condition.

2. The method of claim 1, wherein, New energy station single-input single-output admittance model Y w_SISO The expression is: ； wherein Y w_11 , Y w_12 , Y w_21 , Y w_22 are four elements of the SVG-free new energy station wideband frequency coupling admittance Y w , Z g_11 , Z g_22 are the positive sequence impedance and negative sequence impedance of the power grid.

3. The method of claim 2, wherein, Q j The single-input single-output admittance Y of the SVG connected to the new energy station under the working condition wj_SISO The calculation formula is: ； in, , , , For the admittance Y of new energy power plants under critical stable operating conditions wc The four elements, , The grid impedance Z of the new energy power station under critical stability conditions gc diagonal elements, , , , For SVG operating conditions Q j Time-frequency coupling admittance Y svgj The four elements in it.

4. The method of claim 2, wherein, The calculation formula of the phase stability margin of the new energy station is: ; wherein, Z ratio is the impedance ratio of the new energy station system without SVG, ω co is the frequency point with the impedance ratio amplitude of 1, γ s is the phase stability margin of the new energy station system, and arg is the calculation impedance phase function.

5. The method of claim 1, wherein, The relative sensitivity calculation formula is: ； Among them, Z ratios For the impedance ratio of a new energy power station system containing SVG, k0 and k p Z represents the initial value and disturbance value of a certain control parameter k in the SVG, respectively. ratios_0 (s r ) and Z ratios_p (s r ) are frequencies f r The impedance ratio before and after the disturbance of the SVG control parameter k, s r =j2πf r , The grid impedance Z under critical steady-state conditions gc of Element in s r The impedance value under Z g_11 This is the positive sequence impedance of the power grid.

6. The method of claim 5, wherein, The main control parameter expression is: ; wherein, Δk is a parameter change step, k i represents the SVG main control parameter of the i-th step, k i+1 represents the SVG main control parameter updated at the i+1-th step, and sign is a sign function.

7. The method of claim 1, wherein, The constraint target condition is expressed as: ; is a phase stability margin.

8. The method of claim 1, wherein, the j+1th SVG operating condition to be calculated Q j+1 is expressed as: Q j+1 = Q j + ΔQ, and ΔQ is an operating condition change step.

9. An SVG multi-condition control parameter optimization system, comprising a memory, a processor and a computer program stored on the memory; characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1-8.

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