High-proportion new energy grid-connected strength improving method and system

Abstract

The invention provides a high-proportion new energy grid-connected strength improving method and system. The method comprises the following steps: establishing a full-system dynamic matrix model comprising all power supplies and network dynamic characteristics of a system according to system parameters; calculating element admittance sensitivity according to the full-system dynamic matrix model, and determining a dominant element of a characteristic value influencing the stability of the system according to the element admittance sensitivity; calculating the element parameter sensitivity according to the dominant element to obtain the influence condition of the element parameter on the characteristic value of the system stability; and obtaining a parameter optimization scheme for enhancing the stability of the system according to the influence condition. Therefore, by establishing an impedance model of the system and calculating an admittance participation factor and a parameter sensitivity factor, accurate positioning of elements and specific parameters which have great influence on the stability of the system is realized, and the characteristic value change direction corresponding to parameter change is analyzed in combination with the parameter sensitivity factor; and a parameter optimization scheme for effectively improving the high-proportion new energy grid connection strength is obtained.

Description

Technical Field

[0001] The present application relates to the field of power grid analysis and management, and in particular to a method and system for improving the strength of high-proportion new energy grid connection. Background Art

[0002] Based on the development of new energy technologies, the proportion of installed capacity of new energy power generation continues to increase, and the penetration rate of power electronic equipment represented by converters in the power system is growing rapidly, and the power electronic characteristics of the power system are becoming more and more obvious. Compared with synchronous machines, the control strategy of converter interface power supply is more complex and less robust to interference, which makes the dynamic characteristics of power systems with a high proportion of power electronic equipment more complex and more prone to oscillations caused by equipment interaction. The stability of the system is facing more severe challenges. Grid strength is an important indicator to describe the system's ability to maintain stability. Therefore, it is very necessary to accurately evaluate the strength of the grid after a large number of new energy sources are connected.

[0003] With a high proportion of power electronic equipment connected to the power system, the dynamic characteristics of the system are significantly affected, and accurate evaluation of the grid strength of the system after the connection of new energy has attracted attention. The existing indicators for evaluating grid strength are mostly derived from the short-circuit ratio indicators in the traditional power system dominated by synchronous machines. However, these indicators have problems such as being unable to reflect the non-fundamental frequency oscillation phenomenon that may have occurred in the system before reaching the static voltage stability limit and accurately describing the converter and its control strategy. However, there are many existing grid indicators, and there is a lack of a method that can describe the dynamic characteristics of different devices in a high-proportion new energy grid-connected system, indicate the impact of equipment parameter changes on grid strength, and provide guidance for parameter optimization. Summary of the invention

[0004] The purpose of this application is to provide a method and system for improving the grid-connected strength of a high proportion of renewable energy. Based on parameter sensitivity analysis, the quantitative relationship between the change in system eigenvalues ​​and equipment parameters is obtained to evaluate the degree of participation of specific parameters in the eigenvalues ​​through the size of the sensitivity, and the parameter optimization direction for improving the grid strength is determined according to the positive and negative signs of the sensitivity, thereby efficiently and accurately enhancing the small signal stability of the system.

[0005] To achieve the above-mentioned purpose, the method for improving the grid-connected strength of high-proportion new energy provided in the present application specifically includes: establishing a full-system dynamic matrix model including all power sources and network dynamic characteristics of the system according to system parameters; calculating the element admittance sensitivity according to the full-system dynamic matrix model, and determining the dominant element of the characteristic value affecting the stability of the system according to the element admittance sensitivity; calculating the element parameter sensitivity according to the dominant element to obtain the influence of the element parameter on the characteristic value of system stability; and obtaining a parameter optimization scheme for enhancing the stability of the system according to the influence.

[0006] In the above-mentioned method for improving the grid-connected strength of a high proportion of renewable energy, optionally, a full-system dynamic matrix model including the dynamic characteristics of all power sources and networks of the system is established according to system parameters, including: constructing a small-signal model of the power system by impedance modeling of the power source and the power network respectively in the complex frequency domain according to the system parameters; and obtaining a full-system dynamic matrix model by aligning the small-signal models of the power system of each power source through coordinate system.

[0007] In the above-mentioned method for improving the grid-connected strength of high-proportion new energy, optionally, the element admittance sensitivity is calculated according to the dynamic matrix model of the whole system, and the element admittance sensitivity determines the dominant element of the eigenvalue affecting the stability of the system, including: using the matrix determinant as a scalar transfer function to construct a relationship function between the eigenvalue change and the transfer function matrix; according to the relationship function and the dynamic matrix model of the whole system, the influence of the element adjustment on the designated equipment is obtained, and the element admittance sensitivity is obtained according to the influence; and the dominant element of the eigenvalue affecting the stability of the system is determined according to the element admittance sensitivity comparison.

[0008] In the above-mentioned method for improving the grid-connected strength of new energy with a high proportion, optionally, calculating the sensitivity of component parameters according to the dominant component to obtain the influence of component parameters on the characteristic value of system stability includes: obtaining corresponding multiple component parameters according to the dominant component, calculating the sensitivity of the admittance to the component parameters by the chain rule to obtain the component parameter sensitivity; determining the influence of component parameters on the characteristic value of system stability according to the component parameter sensitivity.

[0009] In the above-mentioned method for improving the grid-connected strength of new energy with a high proportion, optionally, obtaining a parameter optimization scheme for enhancing system stability according to the influencing conditions includes: obtaining parameters to be adjusted according to the influencing conditions, and obtaining a correspondence between component parameter changes and eigenvalue changes through the parameters to be adjusted; and determining a parameter optimization scheme for enhancing system stability according to the corresponding relationship.

[0010] The present application also provides a high-proportion new energy grid-connected strength improvement system, which includes: a construction module, which is used to establish a full-system dynamic matrix model including all power supplies and network dynamic characteristics of the system according to system parameters; an analysis module, which is used to calculate the element admittance sensitivity according to the full-system dynamic matrix model, and determine the dominant element of the characteristic value that affects the stability of the system according to the element admittance sensitivity; a calculation module, which is used to calculate the element parameter sensitivity according to the dominant element to obtain the influence of the element parameter on the characteristic value of the stability of the system; and a processing module, which is used to obtain a parameter optimization solution for enhancing the stability of the system according to the influence.

[0011] In the above-mentioned high-proportion new energy grid-connected strength improvement system, optionally, the construction module includes a generation unit and an alignment unit; the generation unit is used to perform impedance modeling of the power supply and the power network respectively in the complex frequency domain according to the system parameters to construct a small signal model of the power system; the alignment unit is used to obtain a dynamic matrix model of the entire system by aligning the coordinate system according to the small signal model of the power system of each power supply.

[0012] In the above-mentioned high-proportion new energy grid-connected strength improvement system, optionally, the analysis module includes a relationship unit, a comparison unit and a positioning unit; the relationship unit is used to construct a relationship function between the eigenvalue change and the transfer function matrix using the matrix determinant as a scalar transfer function; the comparison unit is used to obtain the impact of component adjustment on the specified equipment based on the relationship function and the full system dynamic matrix model analysis, and obtain the component admittance sensitivity based on the impact; the positioning unit is used to determine the dominant component of the eigenvalue that affects the system stability based on the component admittance sensitivity comparison.

[0013] In the above-mentioned high-proportion new energy grid-connected strength improvement system, optionally, the calculation module includes a derivation unit and a determination unit; the derivation unit is used to obtain the corresponding multiple element parameters according to the dominant element, and calculate the sensitivity of the admittance to the element parameter by the chain rule to obtain the element parameter sensitivity; the determination unit is used to determine the influence of the element parameter on the characteristic value of system stability according to the element parameter sensitivity.

[0014] In the above-mentioned high-proportion new energy grid-connected strength improvement system, optionally, the processing module includes: obtaining the parameters to be adjusted according to the influencing conditions, obtaining the corresponding relationship between the component parameter changes and the characteristic value changes through the parameters to be adjusted; and determining the parameter optimization scheme for enhancing the system stability according to the corresponding relationship.

[0015] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0016] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above method.

[0017] The present application also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0018] The beneficial technical effect of the present application is that by establishing an impedance model of the system, calculating the admittance participation factor and the parameter sensitivity factor, the components and specific parameters that have a greater impact on the stability of the system can be accurately located, and the direction of change of the eigenvalue corresponding to the parameter change is analyzed in combination with the parameter sensitivity factor, thereby obtaining a parameter optimization solution that effectively improves the grid-connected strength of a high proportion of new energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The drawings described herein are used to provide a further understanding of the present application, constitute a part of the present application, and do not constitute a limitation of the present application. In the drawings:

[0020] Figure 1 A flow chart of a method for improving the grid-connected strength of high-proportion new energy provided in one embodiment of the present application;

[0021] Figure 2 A schematic diagram of a process for obtaining a dynamic matrix model of the entire system provided in an embodiment of the present application;

[0022] Figure 3 A schematic diagram of a leading element determination process provided by an embodiment of the present application;

[0023] Figure 4 A schematic diagram of a process for obtaining the influence of component parameters on characteristic values ​​of system stability provided in an embodiment of the present application;

[0024] Figure 5 A schematic diagram of a parameter optimization solution acquisition process provided in an embodiment of the present application;

[0025] Figure 6 A schematic diagram of a circuit structure of a single-grid type converter connected to an infinite system provided in one embodiment of the present application;

[0026] Figure 7 A schematic diagram of system pole distribution before and after parameter adjustment provided in an embodiment of the present application;

[0027] Figure 8 A schematic diagram of the spectrum of the dd item of the impedance element of the entire system before and after the parameter adjustment provided in an embodiment of the present application;

[0028] Fig. 9 A schematic diagram of the structure of a modified busbar system 14 provided in an embodiment of the present application;

[0029] Fig.10 A schematic diagram of the pole distribution of a 14-bus system provided in an embodiment of the present application;

[0030] Fig.11 A schematic diagram of the impedance element spectrum of the entire system of a 14-bus system provided in an embodiment of the present application;

[0031] Fig.12 A schematic diagram of pole distribution before and after parameter adjustment of a bus system 14 provided in an embodiment of the present application;

[0032] Fig.13 A schematic diagram of the spectrum before and after the 14-bus system parameter adjustment provided in an embodiment of the present application;

[0033] Fig.14 A structural diagram of a high-proportion new energy grid-connected strength enhancement system provided in one embodiment of the present application;

[0034] Fig.15 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0035] The following will describe the implementation methods of the present application in detail in conjunction with the accompanying drawings and embodiments, so that the implementation process of how the present application applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments in the present application and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present application.

[0036] In addition, the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be performed in an order different from that shown here.

[0037] Please refer to Figure 1 As shown, the method for improving the high-proportion new energy grid-connected intensity provided in this application specifically includes:

[0038] S101 establishes a full system dynamic matrix model including all power supplies and network dynamic characteristics of the system according to system parameters;

[0039] S102 calculates the admittance sensitivity of the components according to the dynamic matrix model of the whole system, and determines the dominant components of the characteristic values ​​that affect the stability of the system according to the admittance sensitivity of the components;

[0040] S103 calculates the sensitivity of component parameters according to the dominant component to obtain the influence of the component parameters on the characteristic value of system stability;

[0041] S104 obtains a parameter optimization solution for enhancing system stability according to the impact situation.

[0042] Specifically, the method for improving the grid-connected strength of high-proportion new energy provided by the present application mainly adopts the following process in practical application: first, a full-system dynamic matrix model including all power supplies and network dynamic characteristics of the system is established in the complex frequency domain; then, based on the calculation of the admittance participation factor, the size and direction of the change in the eigenvalue caused by the change in the admittance of the specific device are judged, and the dominant element affecting the eigenvalue is located; secondly, the sensitivity of the element parameters is calculated, and the sensitivity of the admittance to the specific parameters is calculated according to the chain rule, so as to judge the influence of the element parameters on the eigenvalue; finally, according to the direction of the change of the eigenvalue corresponding to the parameter change, the parameters to be adjusted and their directions are determined to enhance the grid-connected strength of high-proportion new energy. In this way, by establishing the impedance model of the system, calculating the admittance participation factor and the parameter sensitivity factor, the accurate positioning of the components and specific parameters that have a greater impact on the stability of the system is achieved, and the direction of the change of the eigenvalue corresponding to the parameter change is analyzed in combination with the parameter sensitivity factor, and the parameter optimization scheme that effectively improves the grid-connected strength of high-proportion new energy is obtained. The specific implementation logic of each step will be described in detail in the subsequent embodiments, and will not be described in detail here.

[0043] In the above embodiment, the method for improving the high-proportion new energy grid-connected strength provided by the present application includes establishing a full-system dynamic matrix model including all power sources and network dynamic characteristics of the system, calculating the element admittance sensitivity to determine the dominant element of the system stability response, calculating the element parameter sensitivity, and proposing a parameter optimization scheme for enhancing the system stability based on the parameter sensitivity, and the following steps are performed in sequence; please refer to Figure 2 As shown, in one embodiment of the present application, a full system dynamic matrix model including all power supplies and network dynamic characteristics of the system is established according to system parameters, including:

[0044] S201 performs impedance modeling on the power supply and the power network in the complex frequency domain according to the system parameters to construct a small signal model of the power system;

[0045] S202 obtains a dynamic matrix model of the entire system by aligning coordinate systems based on the power system small signal models of each power source.

[0046] In this embodiment, the implementation principle of the admittance modeling of the dynamic elements of the whole system is as follows:

[0047] First, a full-system dynamic matrix model of the multi-machine system is established in the complex frequency domain; the impedance model of the power supply can be simplified through the state space model or obtained through measurement, namely:

[0048]

[0049] where Y Gi and Z Gi They represent the admittance and impedance of the power source connected to bus i in the complex frequency domain, and are the corresponding elements of the dq rotating coordinate system. If there is no power supply at bus i, there is Y Gi =0.

[0050] It should be noted that the small signal model of each power supply in the multi-machine system is established in its own reference coordinate system. Therefore, it is necessary to align the coordinate system through methods such as dynamic embedding. The power admittance matrix Y of the system can be obtained from the admittance models of each power supply after the coordinate system is aligned. G :

[0051]

[0052] where Y G ∈2n×2n represents the admittance matrix of the system power supply, and n is the number of system nodes.

[0053] Small signal model Y of power network N It is the node admittance matrix established in the complex frequency domain dq coordinate system:

[0054]

[0055] where Y Nij represents the mutual admittance element between buses i and j, Y Nii represents the self-admittance element of bus i.

[0056] Consider the perturbation value of the injected current at each bus of the network as input:

[0057] Δu=ΔI=[ΔI1…ΔI i …ΔI n ] T (4)

[0058] Where ΔI i is the injected current disturbance value of bus i, which has two components, dq, namely ΔI i =[ΔI id ,ΔI iq ] T , T represents matrix transpose.

[0059] The voltage change at each bus is output as:

[0060] Δy=ΔU=[ΔU1…ΔU i …ΔU n ] T (5)

[0061] Similarly, ΔU i =[ΔU id ,ΔU iq ] T .

[0062] When there is an injected current disturbance at the bus, there is a shunt between the power supply and the network. The voltage change at the bus can be calculated from the power supply current change and the power supply admittance matrix. The voltage change at the bus and the network injected current are constrained by the power network node admittance matrix. Therefore, the relationship between the bus injected current and the voltage change can be established:

[0063]

[0064] E is the unit matrix, Z and Y are the full system dynamic matrices that reflect the response transfer function of the injected disturbance to the bus. This patent uses the Z matrix to analyze parameter sensitivity, which reflects the corresponding output voltage change when the input is a current disturbance, so it is called the full system impedance matrix.

[0065] Since the small signal model of the power supply and power network is established in the complex frequency domain, the dynamic matrix of the whole system can reflect the dynamic characteristics of the system. And the diagonal elements of the impedance matrix of the whole system reflect the relationship between the admittance of the node connection equipment and the admittance of the rest of the system equivalent to the node, that is:

[0066] Z kk =(Y kk +Y gk ) -1 (7)

[0067] Where Z kk is the impedance of the device connected to the k-node, Y kk is the device admittance connected to node k, Y gk is the admittance of the rest of the system up to the k-node, which is a second-order matrix in the dq coordinate system.

[0068] Please refer to Figure 3 As shown, in one embodiment of the present application, the element admittance sensitivity is calculated according to the dynamic matrix model of the whole system, and the element admittance sensitivity determines the dominant element of the characteristic value affecting the stability of the system, including:

[0069] S301 uses the matrix determinant as a scalar transfer function to construct a relationship function between the eigenvalue variation and the transfer function matrix;

[0070] S302 obtains the influence of the component adjustment on the designated device according to the relationship function and the whole system dynamic matrix model analysis, and obtains the component admittance sensitivity according to the influence;

[0071] S303 determines the dominant component of the characteristic value that affects the stability of the system according to the admittance sensitivity comparison of the components.

[0072] In this embodiment, the implementation principle of the dominant element for determining system stability based on element admittance sensitivity is as follows:

[0073] Research shows that for a scalar transfer function H, if λ is the zero point of the transfer function H, then the change in the eigenvalue when a small disturbance occurs satisfies:

[0074] Δλ=-H′(λ) -1 ΔH(λ) (8)

[0075] Where Δλ is the eigenvalue change, H′(λ) is the value of the derivative of H at λ, and ΔH is the change of H. When considering the transfer function matrix, the matrix determinant can be used as a scalar transfer function, and then equation (8) is used to obtain the relationship between the eigenvalue change and the transfer function matrix.

[0076] Since each element of the impedance matrix of the whole system can reflect all oscillation modes, that is to say, the system eigenvalues ​​are reflected in the poles of the elements of the impedance matrix of the whole system, we take:

[0077] H=Z kk -1 =(Y kk +Y gk ) (9)

[0078] Then the determinant of the H matrix is det Satisfies formula (8), that is:

[0079] Δλ=-H det ′(λ) -1 ·ΔH det (λ) (10)

[0080] The determinant is expanded row by row:

[0081]

[0082] In the formula, H ij is the element in the i-th row and j-th column of the H matrix, C ij H ij The corresponding algebraic cofactors are:

[0083]

[0084] Then the determinant variation satisfies:

[0085]

[0086] In the formula, C and ΔH represent the algebraic cofactor matrix of H matrix and the small signal form H matrix respectively. represents the conjugation of the C matrix, and <·,·> represents the Frobenius inner product operation of the matrix.

[0087] From formula (9), we can know that Z kk is the inverse matrix of H matrix, and the residue is:

[0088]

[0089] The combined equations (10)(13)(14) are:

[0090]

[0091] Among them, T is the transpose operation, and * is the conjugate transpose operation.

[0092] Since the impact of device disturbance on the eigenvalue is considered, the other parts of the network should be considered to remain unchanged when the device is disturbed, that is:

[0093]

[0094] Therefore, when the system is disturbed, the change in the eigenvalue depends on the change in the device admittance and the residue value of the device impedance at the eigenvalue. The admittance participation factor reflects the sensitivity of the eigenvalue to the admittance of a specific device. By calculating the admittance participation factor, the magnitude and direction of the change in the eigenvalue caused by the change in the admittance of a specific device can be determined. Therefore, the components that have a greater impact on the eigenvalue can be located based on the admittance participation factor. On this basis, these components can be adjusted to move the eigenvalue away from the imaginary axis to the left half of the complex plane, thereby enhancing system stability.

[0095] Please refer to Figure 4 As shown, in one embodiment of the present application, calculating the sensitivity of the component parameter according to the dominant component to obtain the influence of the component parameter on the characteristic value of system stability includes:

[0096] S401: obtaining a plurality of corresponding element parameters according to the dominant element, and calculating the sensitivity of the admittance to the element parameters by the chain rule to obtain the element parameter sensitivity;

[0097] S402 determines the influence of the component parameters on the characteristic value of system stability according to the component parameter sensitivity.

[0098] In this embodiment, the implementation principle of calculating the sensitivity of the element parameters is as follows:

[0099] After locating the dominant component that affects the eigenvalue, we hope to enhance the system stability by adjusting the parameters of the dominant component, so we also need to determine the impact of the component parameters on the eigenvalue. According to the chain rule, if the sensitivity of the admittance to the specific parameters is known, that is:

[0100]

[0101] Where ρ is the parameter of the specific device. Substituting equation (17) into equation (16), we get:

[0102]

[0103] Use s in the formula λ,ρ It represents the parameter sensitivity factor, that is, the sensitivity of the eigenvalue change to the parameter change. The parameter sensitivity factor can be used to determine the size and direction of the eigenvalue change when the parameter changes. Therefore, the parameter sensitivity factor can be used to guide parameter adjustment, thereby enhancing system stability.

[0104] In practice, the partial derivative of the device admittance with respect to the parameter can be obtained by approximate calculation:

[0105]

[0106] Among them, Y kk,Δρ (λ) and Y kk (λ) are the device admittance values ​​before and after the parameter change. Therefore, the parameter sensitivity can be calculated by equations (18) and (19), and the parameter configuration can be optimized.

[0107] Please refer to Figure 5 As shown, in one embodiment of the present application, a parameter optimization scheme for enhancing system stability according to the impact situation includes:

[0108] S501: obtaining a parameter to be adjusted according to the influence, and obtaining a corresponding relationship between a change in a component parameter and a change in a characteristic value through the parameter to be adjusted;

[0109] S502 determines a parameter optimization scheme for enhancing system stability according to the corresponding relationship.

[0110] In this embodiment, the implementation principle of improving the grid-connected strength of new energy based on component parameter sensitivity is as follows:

[0111] The component parameter sensitivity factor refers to the eigenvalue. In practice, the admittance participation factor is usually only calculated for the weakly damped oscillation mode to determine the dominant component. Then the parameter sensitivity factor is calculated to determine the parameters that have a great influence on the eigenvalue, and the direction of the eigenvalue change corresponding to the parameter change is determined, thereby determining the parameters to be adjusted and their direction, and enhancing the grid-connected strength of high-proportion new energy.

[0112] In order to more clearly explain the specific application method of the above-mentioned high-proportion new energy grid-connected strength improvement method, the above-mentioned embodiment is further explained with a specific example below. Relevant technical personnel in this field should know that this example does not impose any limitation on this application.

[0113] For the high-proportion renewable energy grid-connected strength improvement method provided in this application, the applicability of the parameter sensitivity factor in a single-machine infinite system is first analyzed. Figure 6The single grid-type converter shown is connected to an infinite system, and the grid impedance is 0.08+0.4ip.u. The bandwidths of the converter current loop, phase-locked loop and DC voltage loop are 350Hz, 15Hz and 15Hz respectively. The system has an eigenvalue λ=(-0.19+30.31i)·2π close to the imaginary axis, so it is prone to oscillations of 30.31Hz. Since it is a single-machine infinite system, only the influence of the grid-type converter parameters on the eigenvalue is considered. The parameter sensitivity factors of the converter current loop, phase-locked loop and DC voltage loop bandwidth under this eigenvalue are calculated and shown in Table 1, where f i 、f pll and f vdc They represent the current loop bandwidth, phase-locked loop bandwidth, and DC voltage loop bandwidth respectively.

[0114] Table 1

[0115]

[0116] It can be seen from Table 1 that the current loop bandwidth parameter sensitivity factor is the largest, so adjusting the current loop bandwidth has the most obvious effect on this eigenvalue. The real part of the current loop bandwidth parameter sensitivity factor is negative, which means that increasing the current loop bandwidth will make the eigenvalue change negative, that is, away from the imaginary axis. Therefore, the eigenvalue can be prevented from approaching the imaginary axis by increasing the current loop bandwidth, thereby improving the system stability. Similarly, the real part of the parameter sensitivity factor of the phase-locked loop bandwidth and the DC voltage loop bandwidth is positive, that is, reducing the phase-locked loop bandwidth and the DC voltage loop bandwidth will increase the damping of the eigenvalue, thereby improving the system stability.

[0117] Thus, the adjustment schemes of the three control parameters are determined: Case 1 increases the current loop bandwidth by 10%, Case 2 reduces the phase-locked loop bandwidth by 10%, and Case 3 reduces the DC voltage loop bandwidth by 10%. Figure 7 The system pole distribution before and after parameter adjustment is given. It can be seen that the dominant poles are far away from the imaginary axis after parameter adjustment, that is, the system stability is improved. Under the premise of the same adjustment amplitude, the pole change caused by adjusting the current loop bandwidth is the largest, that is to say, adjusting the current loop bandwidth has the best effect on improving the power grid strength. Figure 8 The impedance element spectrum of the whole system before and after parameter adjustment is given. The system eigenvalue is reflected as the peak of the spectrum, and the closer to the imaginary axis, the larger the peak value. It can be seen that all three cases will cause the peak value to decrease, that is, the eigenvalue is moved away from the imaginary axis, but the effect of adjusting the current loop bandwidth is the most obvious, which is consistent with the theoretical analysis results of the parameter sensitivity factor. Table 2 shows the error of the calculated eigenvalue change in the three cases. It can be seen that the error is less than 3%, which proves the effectiveness of the parameter sensitivity factor in improving the grid strength of the single-machine infinite system.

[0118] Table 2

[0119]

[0120] Fig. 9 The modified 14-bus 8-machine system shown is used to illustrate the applicability of parameter sensitivity factors in multi-machine systems. Fig.10 The oscillation mode 1 is shown in Figure 1, which is an oscillation of 30.06 Hz. Fig.11 The spectrum of the impedance element of the whole system shows that the grid-type converters connected to buses 11, 12, and 13 and the grid-type converter connected to bus 6 have a large participation in this oscillation mode. Their parameter sensitivity factors are shown in Table 3, where f i 、f pll and f vdc represent the current loop bandwidth, phase-locked loop bandwidth and DC voltage loop bandwidth of the grid-following converter respectively, and f v , m and f f They are respectively the voltage loop bandwidth, droop gain and droop low-pass filter bandwidth of the grid-type converter.

[0121] Table 3

[0122]

[0123] The results of parameter sensitivity factor analysis show that increasing the voltage loop bandwidth of the grid-forming converter GFM6 and the current loop bandwidth of the grid-following converter GFL12 can effectively shift the eigenvalue to the left in the complex plane, which helps to increase the damping of the oscillation mode. Therefore, the voltage loop bandwidth of GFM6 is increased from 300Hz to 500Hz, and the current loop bandwidth of GFL6 is increased from 300Hz to 400Hz. The pole distribution diagram and the spectrum of the impedance matrix elements of the whole system after adjusting the parameters are shown as follows: Fig.12 , Fig.13 shown. Fig.12 The pole distribution diagram shows that after adjusting the parameters, the eigenvalues ​​are far away from the imaginary axis, that is, the stability is improved. Fig.13 The spectrum diagram shows that the resonance peak decreases after adjusting the parameters, which also shows that the system pole is far away from the imaginary axis and the grid strength is improved. Fig.12 , Fig.13 The simulation results are consistent with the theoretical analysis conclusions of parameter sensitivity factors, which illustrates the applicability of parameter sensitivity factors in multi-machine systems.

[0124] Please refer to Fig.14As shown, the present application also provides a high-proportion new energy grid-connected strength improvement system, the system comprising: a construction module, used to establish a full-system dynamic matrix model including all power supplies and network dynamic characteristics of the system according to system parameters; an analysis module, used to calculate the element admittance sensitivity according to the full-system dynamic matrix model, and determine the dominant element of the characteristic value affecting the stability of the system according to the element admittance sensitivity; a calculation module, used to calculate the element parameter sensitivity according to the dominant element to obtain the influence of the element parameter on the characteristic value of the stability of the system; a processing module, used to obtain a parameter optimization scheme for enhancing the stability of the system according to the influence.

[0125] In the above embodiment, the construction module includes a generation unit and an alignment unit; the generation unit is used to perform impedance modeling on the power supply and the power network in the complex frequency domain according to the system parameters to construct a small signal model of the power system; the alignment unit is used to obtain a dynamic matrix model of the whole system by aligning the coordinate system according to the small signal model of the power system of each power supply. The analysis module includes a relationship unit, a comparison unit and a positioning unit; the relationship unit is used to construct a relationship function between the eigenvalue change and the transfer function matrix using the matrix determinant as a scalar transfer function; the comparison unit is used to analyze and obtain the influence of the component adjustment on the specified device according to the relationship function and the dynamic matrix model of the whole system, and obtain the element admittance sensitivity according to the influence; the positioning unit is used to determine the dominant element of the eigenvalue affecting the stability of the system according to the element admittance sensitivity comparison. The calculation module includes a derivation unit and a determination unit; the derivation unit is used to obtain the corresponding multiple element parameters according to the dominant element, and obtain the element parameter sensitivity by calculating the sensitivity of the admittance to the element parameter through the chain rule; the determination unit is used to determine the influence of the element parameter on the eigenvalue of the stability of the system according to the element parameter sensitivity. The processing module includes: obtaining the parameters to be adjusted according to the influence situation, obtaining the corresponding relationship between the component parameter change and the characteristic value change through the parameters to be adjusted; and determining the parameter optimization scheme for enhancing the system stability according to the corresponding relationship.

[0126] Since the principle of solving the problem by this system is similar to the method for improving the intensity of a high proportion of new energy grid-connected, the implementation of this system can refer to the implementation of the method for improving the intensity of a high proportion of new energy grid-connected, and the repeated parts will not be repeated.

[0127] In summary, the present application can take into account the characteristics of all dynamic components of the system, overcoming the shortcomings of traditional grid strength indicators that are only applicable to static voltage stability analysis at base frequency and cannot accurately describe the converter control strategy. And there is no need to obtain the complete system parameters, and locate the components that participate most in the system eigenvalues ​​through engineering-practical impedance models. The sensitivity of admittance to the parameter is further calculated by the change in device admittance before and after the parameter change, so as to obtain the parameter sensitivity factor that describes the degree of participation of the specific parameter in the change in the eigenvalue. The parameter sensitivity factor can accurately analyze the size and direction of the eigenvalue change when adjusting the parameter, thereby determining the device parameters that have the most obvious impact on the eigenvalue, and providing a parameter adjustment method to improve the strength of the grid.

[0128] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0129] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for executing the above method.

[0130] The present application also provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0131] like Fig.15 As shown, the electronic device 600 may further include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily have to include Fig.15 In addition, the electronic device 600 may also include Fig.15 For components not shown, reference may be made to the prior art.

[0132] like Fig.15 As shown, the central processor 100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor devices and / or logic devices. The central processor 100 receives inputs and controls the operations of various components of the electronic device 600.

[0133] The memory 140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 100 may execute the program stored in the memory 140 to implement information storage or processing.

[0134] The input unit 120 provides input to the CPU 100. The input unit 120 is, for example, a key or a touch input device. The power supply 170 is used to provide power to the electronic device 600. The display 160 is used to display display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0135] The memory 140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 140 may also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 600 through the central processor 100.

[0136] The memory 140 may also include a data storage unit (data 143) for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit (driver 144) of the memory 140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0137] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via an antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processor 100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0138] Based on different communication technologies, multiple communication modules 110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide an audio output via the speaker 131 and receive an audio input from the microphone 132, thereby realizing a common telecommunication function. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 130 is also coupled to the central processor 100, so that the sound can be recorded on the local machine through the microphone 132, and the sound stored on the local machine can be played through the speaker 131.

[0139] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0140] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0141] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0142] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0143] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only a specific embodiment of the present application and is not intended to limit the scope of protection of the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the scope of protection of the present application.

Claims

1. A method for improving the intensity of high-proportion new energy grid connection, characterized in that: The method comprises: According to the system parameters, a full system dynamic matrix model including all power supplies and network dynamic characteristics of the system is established; Calculate the admittance sensitivity of the components according to the dynamic matrix model of the whole system, and determine the dominant components of the characteristic values ​​affecting the stability of the system according to the admittance sensitivity of the components; Calculate the sensitivity of component parameters according to the dominant component to obtain the influence of the component parameters on the characteristic value of system stability; A parameter optimization scheme for enhancing system stability is obtained according to the impact situation.

2. The method for improving the high-proportion new energy grid-connected intensity according to claim 1, characterized in that: According to the system parameters, a full system dynamic matrix model including all power supplies and network dynamic characteristics of the system is established, including: According to the system parameters, the impedance modeling of the power supply and the power network is carried out in the complex frequency domain to construct a small signal model of the power system; The dynamic matrix model of the whole system is obtained by aligning the coordinate system according to the small signal model of the power system of each power source.

3. The method for improving the high-proportion new energy grid-connected intensity according to claim 1, characterized in that: The element admittance sensitivity is calculated based on the dynamic matrix model of the whole system. The element admittance sensitivity determines the dominant element of the characteristic value that affects the stability of the system, including: The matrix determinant is used as a scalar transfer function to construct the relationship function between the eigenvalue change and the transfer function matrix; Analyze and obtain the influence of component adjustment on the designated equipment according to the relationship function and the dynamic matrix model of the whole system, and obtain the admittance sensitivity of the component according to the influence; The dominant element of the characteristic value affecting the stability of the system is determined based on the admittance sensitivity comparison of the elements.

4. The method for improving the high-proportion new energy grid-connected intensity according to claim 1, characterized in that: Calculating the sensitivity of the component parameters according to the dominant component to obtain the influence of the component parameters on the characteristic value of system stability includes: Obtaining a plurality of corresponding element parameters according to the dominant element, and calculating the sensitivity of the admittance to the element parameters by the chain rule to obtain the element parameter sensitivity; The influence of the component parameters on the characteristic value of system stability is determined according to the component parameter sensitivity.

5. The method for improving the high-proportion new energy grid-connected intensity according to claim 1, characterized in that: The parameter optimization scheme for enhancing system stability according to the impact situation includes: Obtaining a parameter to be adjusted according to the influence, and obtaining a corresponding relationship between a change in the component parameter and a change in the characteristic value through the parameter to be adjusted; The parameter optimization scheme for enhancing system stability is determined based on the corresponding relationship.

6. A high proportion of new energy grid-connected strength improvement system, characterized in that: The system comprises: A building module for building a full system dynamic matrix model including all power supplies and network dynamic characteristics of the system according to system parameters; An analysis module is used to calculate the admittance sensitivity of the components according to the dynamic matrix model of the whole system, and determine the dominant components of the characteristic values ​​affecting the stability of the system according to the admittance sensitivity of the components; A calculation module, used for calculating the sensitivity of component parameters according to the dominant component to obtain the influence of the component parameters on the characteristic value of system stability; A processing module is used to obtain a parameter optimization solution for enhancing system stability according to the impact situation.

7. The high-proportion new energy grid-connected strength improvement system according to claim 6 is characterized in that: The building module comprises a generation unit and an alignment unit; The generating unit is used to perform impedance modeling on the power supply and the power network in the complex frequency domain according to the system parameters to construct a small signal model of the power system; The alignment unit is used to obtain a dynamic matrix model of the entire system through coordinate system alignment according to the power system small signal model of each power supply.

8. The high-proportion new energy grid-connected strength improvement system according to claim 6 is characterized in that: The analysis module includes a relationship unit, a comparison unit and a positioning unit; The relation unit is used to construct a relation function between the eigenvalue variation and the transfer function matrix by using the matrix determinant as a scalar transfer function; The comparison unit is used to analyze and obtain the influence of the component adjustment on the designated device according to the relationship function and the dynamic matrix model of the whole system, and obtain the component admittance sensitivity according to the influence; The positioning unit is used to determine the dominant element of the characteristic value that affects the stability of the system according to the element admittance sensitivity comparison.

9. The high-proportion new energy grid-connected strength improvement system according to claim 6 is characterized in that: The calculation module includes a derivation unit and a determination unit; The derivation unit is used to obtain a plurality of corresponding element parameters according to the dominant element, and to obtain element parameter sensitivity by calculating the sensitivity of the admittance to the element parameter through the chain rule; The determination unit is used to determine the influence of the component parameter on the characteristic value of system stability according to the component parameter sensitivity.

10. The high-proportion new energy grid-connected strength improvement system according to claim 6, characterized in that: The processing module includes: obtaining the parameters to be adjusted according to the influence situation, obtaining the corresponding relationship between the component parameter change and the characteristic value change through the parameters to be adjusted; and determining the parameter optimization scheme for enhancing the system stability according to the corresponding relationship.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

13. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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