CN116780502B - Method and system for determining influence of power generation energy on low-frequency oscillation of power system - Google Patents

Abstract

The invention discloses a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system, and relates to the field of new energy power system stability analysis. The method includes: first establishing a small signal model of each power generation energy; the power generation energy includes photothermal energy and thermal power energy. , photovoltaic energy and wind power energy; then determine the state matrix of the new energy power system model; determine the sensitivity matrix of the damping torque of each power generation energy region in each mode according to the state matrix and the oscillation mode of the new energy power system; and then according to the state matrix And the sensitivity matrix determines the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy region under each oscillation mode; finally, based on the regional damping, the access location and power of each power generation energy are determined. Based on the state matrix and the sensitivity matrix, the present invention can determine the regional damping of low-frequency oscillation of the new energy power system in each power generation energy region under each mode, and can further analyze the low-frequency oscillation of the power system.

Description

A method and system for determining the impact of power generation energy on low-frequency oscillation of the power system

Technical field

The invention relates to the field of new energy power system stability analysis, and in particular to a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system.

Background technique

In recent years, high-energy-consuming and high-pollution thermal power units have been gradually replaced by new energy sources such as wind power, photovoltaics, and solar thermal. The resulting problem is that the integration of large-scale new energy stations may have a negative impact on the stability of the power system. Especially when new energy sources such as wind power, photovoltaics, and photovoltaics fluctuate or malfunction, it may cause violent fluctuations in the power system. Therefore, it is particularly important to analyze the low-frequency oscillation of new energy power systems including photothermal power generation, wind power, and photovoltaics. important.

However, the research on low-frequency oscillation of new energy power systems in the existing technology mainly focuses on the situation of a single new energy source connected to the grid, and there is a lack of research on the situation of multiple new energy sources connected to the grid. Moreover, the existing technology does not focus on power systems containing photothermal power generation. There are few studies on stability, and the impact of grid-connected solar thermal power generation on the low-frequency oscillation of a high-proportion new energy power system is unclear.

Contents of the invention

The purpose of the present invention is to provide a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system, which can analyze the impact of multiple new energy grid connections on the low-frequency oscillation of the new energy power system.

The invention provides a method for determining the impact of power generation energy on low-frequency oscillation of the power system, including:

Step 1: Establish a small signal model of each power generation energy; the power generation energy includes photothermal energy, thermal power energy, photovoltaic energy and wind power energy; the small signal model of the photothermal energy is established based on the principle of thermal power generation;

Step 2: Determine the state matrix of the new energy power system model; the new energy power system model is determined based on the new energy power system obtained by simulating grid connection of each power generation energy and the small signal model of each power generation energy;

Step 3: According to the state matrix and the oscillation mode of the new energy power system, determine the sensitivity matrix of the damping torque of each power generation energy region in each of the oscillation modes;

Step 4: According to the state matrix and the sensitivity matrix, determine the regional damping of the low-frequency oscillation of the new energy power system by each power generation energy region in each of the oscillation modes;

Step 5: According to the regional damping, determine the access location and access power of each power generation energy source.

Optionally, the steps 3-4 specifically include:

The state matrix is matrix decomposed and expanded by area to determine the generator motor speed variables, the first forward channel matrix and the second forward channel matrix of each of the power generation energy areas; the first forward channel matrix is The forward channel matrix from the power generation energy area to the electromechanical oscillation link of the generator motor in this power generation energy area; the second forward channel matrix is the motor electromechanical link from the power generation energy area to any power generation energy area except this power generation energy area. The forward channel matrix of the oscillation link;

According to the generator speed variable of the power generation energy area, the first forward channel matrix and the oscillation mode of the new energy power system, the power supply provided by the power generation energy area to the current power generation energy area under each oscillation mode is determined. The first damping torque matrix;

According to the generator speed variable of the power generation energy area, the second forward channel matrix and the oscillation mode of the new energy power system, it is determined that the power generation energy area in each oscillation mode is in addition to the current power generation energy area. The second damping torque matrix provided by any power generation energy area;

According to the sensitivity matrix, the first damping torque matrix and the second damping torque matrix, the regional damping provided by the power generation energy area to the low-frequency oscillation of the new energy power system in each mode is calculated; the sensitivity matrix represents the Describe the power generation energy region’s ability to influence modes.

Optional, also includes:

according to Calculate the sensitivity matrix, where S _i,m is the sensitivity matrix of the m-th oscillation mode to the i-th power generation energy area, λ _m is the eigenvalue of the m-th oscillation mode, and T _i ^m is the i-th power generation Damping torque in the energy region.

Optionally, after step 4, also include:

Adjust the access power of each power generation energy source multiple times, and repeat steps 1-4 to obtain the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy region under each oscillation mode;

According to the regional damping corresponding to each of the power generation energy regions obtained through multiple adjustments, the optimal access power of each of the power generation energy sources is determined.

Optionally, after step 4, also include:

Adjust the access position of each power generation energy multiple times and repeat steps 1-4 to obtain the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy region under each oscillation mode;

According to the regional damping corresponding to each power generation energy area obtained through multiple adjustments, the optimal access position of each power generation energy is determined.

Optional, the small signal model of photothermal power generation is as follows:

Among them, ΔX _sg = [Δδ, Δω, ΔE' _q , ΔE' _fd ] is the state vector of the small signal model of photothermal power generation, δ is the power angle, ω is the rotor speed, E' _q is the quadrature axis transient electromotive force, E' _fd is the dynamic value of the automatic voltage regulator; ΔV _sg = [ΔV _x , ΔV _y ] ^T is the input vector of the small signal model of photothermal power generation, V _sg is the terminal voltage of the synchronous generator, V _x , V _y are the components of the machine terminal voltage in the xy coordinate respectively, ΔI _sg = [ΔI _x , ΔI _y ] ^T is the output vector of the small signal model of photothermal power generation, I _sg is the output current of the synchronous generator; I _x and I _y are the components of the output current in the x coordinate and y coordinate respectively, A _sg is the state matrix of the small signal model of photothermal power generation, B _sg is the input matrix of the small signal model of photothermal power generation, C _sg is the photothermal power generation The output matrix of the small signal model, D _sg is the feedforward matrix of the small signal model of photothermal power generation.

Optional, the small signal model of photovoltaic energy is as follows:

Among them, ΔX _p = [ΔE _f Δδ _VSG Δω _VSG ΔV _dc ΔX] ^T is the state vector of the small signal model of photovoltaic energy, E _f is the output voltage of the virtual synchronous machine, δ _VSG is the output voltage phase angle, and ω _VSG is the virtual synchronization The angular velocity of the internal potential of the machine VSG, V _dc is the DC side voltage, ΔX is the intermediate variable, the upper limit of ΔX is 0, ΔU _p = [ΔV _gx ΔV _gy ] ^T is the input vector of the small signal model of photovoltaic energy, U _p is The grid connection point voltage of the virtual synchronous machine, V _gx and V _gy are the components of the virtual synchronous machine grid connection point voltage at the x coordinate and y coordinate, ΔI _p = [ΔI _x ΔI _y ] ^T is the output vector of the small signal model of photovoltaic energy , I _p is the injected current of the virtual synchronous machine, I _x and I _y are the components of the injected current of the virtual synchronous machine in the xy coordinate respectively, A _p is the state matrix of the small signal model of the photovoltaic energy, and B _p is the small signal of the photovoltaic energy. The input matrix of the signal model, C _p is the output matrix of the small signal model of photovoltaic energy, D _p is the feedforward matrix of the small signal model of photovoltaic energy,

C _dc is the capacitance value of the DC side voltage stabilizing capacitor, V _dc(0) is the initial value of the DC side voltage stabilizing capacitor voltage, U _oc is the open circuit voltage of the photovoltaic cell, δ _VSG(0) , I _sc(0) , V _{gx (0)} , V _gy(0) , V _g(0) , δ _VSG(0) , E _f(0) , I _x(0) , I _y(0) are δ _VSG , I _sc , V _gx , respectively. V _gy , V _g , δ _VSG , E _f , I _x , I _y are the initial values obtained after calculation of variable power flow. X _f is the reactance between the virtual synchronous machine voltage output voltage point E _f and the virtual synchronous machine grid connection point V _g , ω _n is the reference frequency of the power grid, J is the inertia constant of the VSG control link, D is the damping coefficient of the VSG control link, K is the voltage coefficient of the VSG control link, D _q is the reactive power coefficient of the VSG control link, K _pv is VSG The proportional coefficient of the PI controller in the P' _ref control link in the control, K _iv is the integral coefficient of the PI controller in the P' _ref control link in the VSG control, and C ₁ and C ₂ are the intermediate variables of the photovoltaic cell UI equation.

Optional, the small signal model of wind power energy is as follows:

Among them, ΔX _W is the state vector of the small signal model of wind power energy, ΔU _W = [ΔV _gx-w , ΔV _gy-w ] is the input vector of the small signal model of wind power energy, and U _W is the grid connection point voltage of PMSG-VSG. , V _gx-w and V _gy-w are the components of the virtual synchronous machine grid connection point voltage at the x coordinate and y coordinate, ΔI _W = [ΔI _gx-w , ΔI _gy-w ] ^T is the small signal model of wind power energy Output vector, I _W is the injection current of PMSG-VSG, I _gx-w and I _gy-w are the components of the virtual synchronous machine injection current in the xy coordinate, A _W is the state matrix of the small signal model of wind power energy, B _W is the input matrix of the small signal model of wind power energy, C _W is the output matrix of the small signal model of wind power energy, and D _W is the feedforward matrix of the small signal model of wind power energy.

Optionally, according to the state matrix and the sensitivity matrix, determine the regional damping of the low-frequency oscillation of the new energy power system by each power generation energy region in each of the oscillation modes, specifically as follows:

According to the formula Calculate the regional damping provided by each power generation energy region to the low-frequency oscillation of the new energy power system;

Among them, D _im is the regional damping provided by the i-th power generation energy region to the new energy power system, S _i,m is the sensitivity matrix of the m-th mode to the i-th power generation energy region, is the torque matrix provided by the i-th power generation energy area to its own area, S _i-,m is the sensitivity matrix of the m-th oscillation mode to the damping torque of the non-i area;/> is the torque matrix provided by the non-i area to the i-th area, S _j,m is the sensitivity matrix of the m-th mode to the j-th power generation energy area,/> It is the torque matrix provided by the jth power generation energy region to its own region.

The invention also provides a system for determining the impact of power generation energy on low-frequency oscillation of the power system, including:

A small signal model building module is used to establish a small signal model of each power generation energy; the power generation energy includes photothermal energy, thermal power energy, photovoltaic energy and wind power energy; the small signal model of the photothermal energy is established based on the principle of thermal power generation;

The state matrix module is used to determine the state matrix of the new energy power system model; the new energy power system model is determined based on the new energy power system obtained by simulating the grid connection of each power generation energy and the small signal model of each power generation energy;

A sensitivity matrix module, configured to determine the sensitivity matrix of the damping torque of each power generation energy region in each of the oscillation modes based on the state matrix and the oscillation mode of the new energy power system;

A damping calculation module, configured to determine, according to the state matrix and the sensitivity matrix, the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy region under each of the oscillation modes;

The position power determination module determines the access location and access power of each power generation energy source based on the regional damping.

According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

The invention provides a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system. The method includes: first establishing a small signal model of each power generation energy; the power generation energy includes photothermal energy, thermal power energy, photovoltaic energy and wind power energy; The small signal model of thermal energy is established based on the principle of thermal power generation; then, the state matrix of the new energy power system model is determined; the new energy power system model is based on the simulated grid connection of each power generation energy to obtain the new energy power system and the small signal model of each power generation energy. ; Then according to the state matrix and the oscillation mode of the new energy power system, determine the sensitivity matrix of the damping torque of each power generation energy region in each oscillation mode; then according to the state matrix and sensitivity matrix, determine the sensitivity matrix of each power generation energy region in each oscillation mode. Regional damping of low-frequency oscillation of new energy power systems under normal conditions; finally, based on regional damping, the access location and access power of each power generation energy source are determined. The present invention establishes the state matrix of the new energy power system model based on the small signal model of photothermal energy, thermal power energy, photovoltaic energy and wind power energy and the sensitivity matrix of the damping torque of each power generation energy area, which can determine the oscillation of each power generation energy area. Regional damping of low-frequency oscillation of the new energy power system under the modal mode. Using each regional damping, the impact of different access locations and different access powers of each new energy source on the low-frequency oscillation of the power system can be analyzed.

Description of the drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the drawings needed to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some of the drawings of the present invention. Embodiments, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without exerting creative efforts.

Figure 1 is a schematic diagram of a power system low-frequency oscillation analysis method provided by an embodiment of the present invention;

Figure 2 is a topological diagram of the photothermal electric field provided by an embodiment of the present invention;

Figure 3 is a VSG control structure diagram provided by an embodiment of the present invention;

Figure 4 is a power control diagram considering photovoltaic output characteristics provided by an embodiment of the present invention;

Figure 5 is a structural diagram of the PMSG-VSG system provided by the embodiment of the present invention;

Figure 6 is a control block diagram of the machine-side converter provided by the embodiment of the present invention;

Figure 7 is a schematic diagram of a new energy power system provided by an embodiment of the present invention;

Figure 8 is a schematic diagram of regional damping provided by an embodiment of the present invention.

Detailed ways

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 only some of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

The purpose of the present invention is to provide a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system, which can analyze the impact of multiple new energy grid connections on the low-frequency oscillation of the new energy power system.

In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

As shown in Figure 1, the present invention provides a method for determining the impact of power generation energy on low-frequency oscillation of the power system, including:

Step 1: Establish a small signal model of each power generation energy; the power generation energy includes photothermal energy, thermal power energy, photovoltaic energy and wind power energy; the small signal model of the photothermal energy is established based on the principle of thermal power generation.

Step 2: Determine the state matrix of the new energy power system model; the new energy power system model is determined based on the new energy power system obtained by simulating grid connection of each power generation energy and the small signal model of each power generation energy.

Step 3: According to the state matrix and the oscillation mode of the new energy power system, determine the sensitivity matrix of the damping torque of each power generation energy region in each of the oscillation modes.

Step 4: According to the state matrix and the sensitivity matrix, determine the regional damping of the low-frequency oscillation of the new energy power system by each power generation energy region in each oscillation mode.

Step 5: According to the regional damping, determine the access location and access power of each power generation energy source.

In some embodiments, when establishing a small signal model of photothermal energy, the photothermal power station mainly includes: the light concentration and heat collection system of the sun island; the steam generation system, turbine generator set and heat storage system of the conventional island. In terms of structure and working principle, the conventional island of the photothermal power generation system is the same as the thermal power generation unit, which belongs to the thermal power generation process. The difference is that the thermal power generation unit heats the water working medium through the combustion of fuel to generate superheated steam, while the photothermal power generation unit uses concentrated light to collect heat. The system collects solar thermal energy, heats the heat transfer medium, and then generates superheated steam through the steam generation system. When only studying the low-frequency oscillation problem of the power system caused by the connection of CSP plants to the power grid, the model of the CSP unit is not essentially different from that of conventional thermal power, and there is no need to establish a special model. This method studies the low-frequency oscillation problem of power systems with multiple new energy sources. Therefore, the photothermal power generation unit adopts the same small signal model as conventional thermal power. Therefore, to establish a small signal model of photothermal energy/small signal model of thermal power, the details can be as follows:

1) Determine the commonly used simplified model of synchronous generators. The model is as follows:

In formula (1), δ is the power angle, ω is the rotor speed, ω ₀ is the synchronous speed, M is the inertia constant of the rotor, D is the damping coefficient, P _m is the mechanical power and electromagnetic power acting on the rotor, E' _q is the transient electromotive force of the quadrature axis, E _q is the no-load electromotive force, and E _fd is the forced no-load electromotive force.

2) Determine the mathematical model of the automatic voltage regulator. The model is as follows:

In formula (2), K _A is the gain of the automatic voltage regulator, T _A is the gain time constant of the automatic voltage regulator, V _t and V _ref are the terminal voltage signal and the reference value of the extreme voltage of the synchronous generator, u _pss is The control signal of the power system stabilizer PSS, E _fd0 and E' _fd are the constant value of the excitation voltage and the dynamic value of the automatic voltage regulator. P _e , E _q and V _t can be calculated by formula (3), as follows:

_In the formula (3 ₎ , X _{d is} the direct _axis synchronous reactance _of the synchronous generator _, and the components of the output current in the xy coordinates.

Specifically, V _d , V _q , I _d and I _q are the components of the machine terminal voltage and output current in the dq coordinate system respectively, which can be calculated by Equation (4).

3) Linearize equations (1) to (4) to obtain the photothermal power small signal model/thermal power small signal model. The model is as follows:

In formula (5), ΔX _sg = [Δδ, Δω, ΔE' _q , ΔE' _fd ] is the state vector of the photothermal power generation small signal model, δ is the power angle, ω is the rotor speed, and E' _q is the quadrature axis temporary State electromotive force, E' _fd is the dynamic value of the automatic voltage regulator; ΔV _sg = [ΔV _x , ΔV _y ] ^T is the input vector of the photothermal power generation small signal model, V _sg is the machine terminal voltage of the synchronous generator, V _x and V _y are the components of the machine terminal voltage in the xy coordinate respectively, ΔI _sg = [ΔI _x , ΔI _y ] ^T is the output vector of the photothermal power generation small signal model, I _sg is the output current of the synchronous generator; I _x and I _y are the components of the output current in the xy coordinate respectively, A _sg is the state matrix of the photothermal power small signal model, B _sg is the input matrix of the photothermal small signal model, and C _sg is the photothermal small signal model. The output matrix, D _sg, is the feedforward matrix of the small signal model of photothermal power generation.

However, compared with conventional thermal power units, the capacity of CSP is smaller, and large-scale CSP farms usually contain multiple CSP units. A large number of CSP units are interconnected and connected to the power system through aggregation networks. Therefore, The structure of the photothermal power plant is shown in Figure 1.

In some embodiments, the small signal model of photovoltaic energy can be established as follows:

When establishing a small-signal model of photovoltaic energy, it is necessary to first establish a photovoltaic cell model, a capacitor model, a grid-side converter and its control model.

1) The details of establishing a photovoltaic cell model can be as follows:

Since photovoltaic power generation is controlled by virtual synchronous gengrators (VSG), the application of VSG technology allows photovoltaic power generation to retain the characteristics of power electronic interface power supply and have characteristics similar to generator rotors. Therefore, in system stability research, it is often Using a practical engineering photovoltaic cell model, the U-I equation of the photovoltaic cell under non-standard conditions is:

In formula (6), I _sc is the short-circuit current, U _oc is the open circuit voltage, and Im and _{U m are} the current and voltage at the maximum power operating point.

2) The details of establishing the capacitor model can be as follows:

Since the function of the capacitor is to stabilize the DC side voltage of the photovoltaic inverter, the capacitor model is as follows:

In the formula, C _dc is the capacitance value of the DC stabilizing capacitor, V _dc is the DC side voltage, I _pv is the current flowing from the photovoltaic cell to the intermediate capacitor, and P _e is the active power from the DC stabilizing capacitor to the inverter.

3) The details of establishing the grid-side converter and its control model can be as follows:

As shown in Figure 2 of the primary topology circuit of the photovoltaic virtual synchronous machine, the grid-side converter is controlled by VSG, and the VSG output voltage control signal is pulse-width modulated to control the switching of the converter. Considering that the electromechanical characteristics are the main research object, high-frequency links such as converter switching are ignored in the analysis. The dynamic equation of the VSG control link can be as follows:

In formula (8), ω _VSG is the angular velocity of the internal potential of VSG, δ _VSG is the output voltage phase angle, ω _n is the grid reference frequency, P _ref and Q _ref are the virtual synchronous machine control signal and reactive power control signal respectively, J is the inertia constant of the virtual synchronous machine control link, D is the damping coefficient, K is the voltage coefficient, E _f is the virtual synchronous machine output voltage, and V _g is the virtual synchronous machine grid connection point voltage.

Among them, P _e and Q _e are the active power and reactive power output by the converter respectively, which can be calculated by the following formula:

However, traditional VSG control is mainly designed for energy storage batteries on the DC side, that is, the DC side is a constant voltage source with infinite capacity, but the dynamic characteristics of photovoltaic cells are more complex. The output range of photovoltaic cells is [0, P _max ], and there are stable working areas and unstable working areas. As shown in Figure 4, VSG control that considers the dynamic characteristics of photovoltaic cells should ensure its operation in a stable area, so the output power of VSG control is limited. The control equations of VSG control links P' _ref and Q' _ref are as follows:

In equation (10), V _dc-mpp is the DC voltage corresponding to the maximum power operating point of the photovoltaic cell, and P _max is the maximum output power. The upper limit of ΔX is set to 0, and the dynamic equation is K _iv is the integral coefficient of the PI controller.

4) Linearize the PV-VSG dynamic model to obtain the small signal model of photovoltaic energy. The model is as follows:

In equation (11), ΔX _p = [ΔE _f Δδ _VSG Δω _VSG ΔV _dc ΔX] ^T is the state vector of the small signal model of photovoltaic energy, E _f is the virtual synchronous machine output voltage, δ _VSG is the output voltage phase angle, ω _VSG is the angular velocity of the internal potential of VSG, V _dc is the DC side voltage, the upper limit of ΔX is 0, ΔU _p = [ΔV _gx ΔV _gy ] ^T is the input vector of the small signal model of photovoltaic energy, and U _p is the virtual synchronous machine Grid point voltage, V _gx and V _gy are the components of the virtual synchronous machine grid point voltage in the xy coordinates, ΔI _p = [ΔI _x ΔI _y ] ^T is the output vector of the small signal model of photovoltaic energy, I _p is the virtual synchronous machine _{The injection current of p} is the output matrix of the small signal model of photovoltaic energy, and D _p is the feedforward matrix of the small signal model of photovoltaic energy.

Among them, C _dc is the capacitance value of the DC side voltage stabilizing capacitor, V _{dc (0)} is the initial value of the DC side voltage stabilizing capacitor voltage, U _oc is the open circuit voltage of the photovoltaic cell, V _{gx (0)} , V _{gy (0)} , V _g(0) , δ _VSG(0) , E _f(0) , I _x(0) , I _y(0) are V _gx , V _gy , V _g , δ _VSG , E _f , I _x , I _y The initial value obtained after variable power flow calculation. X _f represents the reactance between the virtual synchronous machine voltage output voltage (E _f ) point and the virtual synchronous machine grid connection point (V _g ). ω _n is the reference frequency of the power grid, J is the inertia constant of the VSG control link, D is the damping coefficient of the VSG control link, K is the voltage coefficient of the VSG control link, D _q is the reactive power coefficient of the VSG control link, and K _pv is the VSG control The proportional coefficient of the PI controller in the P' _ref control link, K _iv is the integral coefficient of the PI controller in the P' _ref control link in the VSG control, and C ₁ and C ₂ are the photovoltaic cell UI equation parameters.

In some embodiments, a small signal model of wind power energy is established, specifically as follows:

Direct-drive wind turbines mainly include permanent magnet generators, machine-side converters, and grid-side converters. As shown in Figure 4, the generator-side converter adopts vector control, and the grid-side converter adopts virtual synchronous machine control.

When establishing a small-signal model of wind power energy, it is necessary to establish a permanent magnet generator model, a capacitor model, a machine-side converter control model and a grid-side converter control model.

(1) The details of establishing the permanent magnet generator model can be as follows:

In formula (12), L _sd and I _sq are the dq-axis components of the stator winding current respectively, U _sd and U _sq are the dq components of the rotor winding voltage respectively, ω is the angular velocity of the generator, L _q and L _d represent the stator respectively. The dq-axis component of the inductance, ψ _f is the permanent magnetic flux of the rotor.

Specifically, the permanent magnet generator rotor is a single mass model, and its rotor motion equation is as follows:

In formula (13), D _ω is the damping coefficient, J _w is the motor inertia time constant, T _ω and T _e are the mechanical torque and electromagnetic torque of the generator rotor respectively, np is the pole pair number, and ω ₀ is the rotor speed. Reference.

(2) The function of the capacitor is to stabilize the DC side voltage of the wind turbine. The details of establishing the capacitor model can be as follows:

In formula (14), C _dc is the capacitance value of the DC stabilizing capacitor, V _dc is the DC side voltage, P _s is the active power from the machine-side converter to the capacitor, and P _g is the power from the capacitor to the grid-side converter. of active power.

(3) The details of establishing the machine-side converter control model can be as follows:

The machine-side converter adopts vector control, and the control target of the machine-side converter is set to maintain DC voltage stability to effectively utilize the rotor kinetic energy to provide virtual inertia and damping energy. The block diagram of the machine-side converter control model is shown in Figure 6. In the machine-side converter control model, the DC outer loop state quantity x ₁ , the inner loop state quantity x ₂ of I _sq and the inner loop intermediate variable state quantity x ₃ of I _sd are introduced respectively. The dynamic equations are:

In Equation (15), K _i1 , K _i2 and K _i3 are the integral coefficients of the PI controller, I _sqref and I _sdref are the reference values of the dq axis component of the stator winding current respectively.

(4) The details of establishing the grid-side converter control model can be as follows:

The control objective of the grid-side converter is set to inject the maximum power generated by the wind turbine into the grid. In direct-drive wind turbines, the grid-side converter is controlled by a virtual synchronous machine. High-frequency links such as converter switching are ignored in the analysis. The dynamic equation of the VSG control method of wind turbines is the same as that of photovoltaic power generation.

Linearize the PMSG-VSG dynamic model to obtain the small signal model of wind power energy. The model is as follows:

In formula (16), ΔX _W is the state vector of the small signal model of wind power energy, ΔU _W = [ΔV _gx-w , ΔV _gy-w ] is the input vector of the small signal model of wind power energy, and U _W is PMSG-VSG _The grid _- ^connection _{point voltage of} The output vector of , I _W is the injection current of PMSG-VSG, I _gx-w and I _gy-w are the components of the virtual synchronous machine injection current in the xy coordinate. A _W is the state matrix of the small signal model of wind power energy, B _W is the input matrix of the small signal model of wind power energy, C _W is the output matrix of the small signal model of wind power energy, and D _W is the front end of the small signal model of wind power energy. Feed matrix.

In this embodiment, the small signal model of photothermal power generation, the small signal model of thermal power, the small signal model of photovoltaic energy, and the small signal model of wind power energy are represented in a matrix to obtain a new energy power system. State matrix; the new energy power system state matrix includes the power angle vector, speed variable vector and remaining state variable vector of the generator motor, as follows:

As shown in Figure 6, the new energy power system includes thermal power, wind power, photovoltaic power generation and solar thermal power generation. First, the small-signal model equations (5), (11), and (16) of solar thermal, photovoltaic, wind power, and traditional thermal power as well as the dynamic equations of the system load are combined to establish a new energy power system small-signal model, and obtain a new Energy power system state matrix, the state matrix is as follows:

In formula (17), δ is the power angle vector of the synchronous generator or virtual synchronous machine, ω is the rotational speed vector of the generator or virtual synchronous machine, and Z is the remaining state variable vector.

Specifically, the residual state variable vector (Residual State Variable Vector) usually refers to a set of state variables that cannot be measured or estimated in actual power system operation. These unmeasured or estimated state variables are typically estimated through power system modeling and state estimation algorithms.

Power systems usually include many parts and components, such as generators, transformers, transmission lines, loads, etc. Each part has its own physical and electrical parameters, which collectively affect the characteristics and performance of the overall system. Some of these parameters can be obtained through measurement and monitoring, but there are many parameters that cannot be measured directly or cannot be determined at all, such as the status of certain components, the impedance of certain lines, etc. In order to simulate, model, control and fault diagnose power systems, these unknown parameters need to be estimated. In the state estimation algorithm, these unknown parameters are integrated together to form the remaining state variable vector, which is solved using estimation methods. According to the system model and state estimation algorithm, the state quantities of unknown variables can be estimated and presented in the form of vectors by observing and processing the known input and output quantities of the power system.

In some embodiments, steps 3-4 may be as follows:

The state matrix is matrix decomposed and expanded by area to determine the generator motor speed variables, the first forward channel matrix and the second forward channel matrix of each of the power generation energy areas; the first forward channel matrix is The forward channel matrix from the power generation energy area to the electromechanical oscillation link of the generator motor in this power generation energy area; the second forward channel matrix is the motor electromechanical link from the power generation energy area to any power generation energy area except this power generation energy area. The forward channel matrix of the oscillation link;

According to the generator speed variable of the power generation energy area, the first forward channel matrix and the oscillation mode of the new energy power system, the power supply provided by the power generation energy area to the current power generation energy area under each oscillation mode is determined. The first damping torque matrix;

According to the generator speed variable of the power generation energy area, the second forward channel matrix and the oscillation mode of the new energy power system, it is determined that the power generation energy area in each oscillation mode is in addition to the current power generation energy area. The second damping torque matrix provided by any power generation energy area;

According to the sensitivity matrix, the first damping torque matrix and the second damping torque matrix, the regional damping provided by the power generation energy area to the low-frequency oscillation of the new energy power system in each mode is calculated; the sensitivity matrix represents the Describes the power generation energy region’s ability to influence modes.

Among them, the state matrix is matrix decomposed and expanded by area to determine the generator motor speed variable, the first forward channel matrix and the second forward channel matrix of each of the power generation energy areas, specifically as follows:

Divide the power system into four power generation energy regions according to photothermal power generation, wind power, photovoltaic power and traditional thermal power, and then sort each vector according to the region, that is, Δω = [Δω ₁ Δω ₂ Δω ₃ Δω ₄ ] ^T , where ω _i is The i-th power generation energy region generator or virtual synchronous machine speed vector.

Decompose equation (17) by state, and the decomposed new energy power system state matrix is as follows:

According to the decomposed state matrix, we can get [ΔZ] = (SI-A ₃₃ ) ^-1 A ₃₁ [Δδ] + (SI-A ₃₃ ) ^-1 A ₃₂ [Δω], and substitute [ΔZ] into equation (18) ,Available That is/> Formula in/> S is a differential operator. In the calculation, the eigenvalues of the specific modes are substituted. The vector ω is expanded by region as: In formula (25), ω _i is the speed variable vector of the generator or virtual synchronous machine in the i region, and ω _i- is the speed variable vector of the generator or virtual synchronous machine in the non-i region. In the matrix, G _i,i is the first forward channel matrix from the i area to the i area generator or the virtual synchronous machine electromechanical oscillation link, and G _i-,i is the non-i area to i area generator or the virtual synchronous machine electromechanical oscillation link. The second forward channel matrix of .

Among them, according to the generator motor speed variable of the power generation energy area, the first forward channel matrix and the oscillation mode of the new energy power system, it is determined that the power generation energy area moves to the current power generation energy area under each oscillation mode. The first damping torque matrix provided is as follows:

According to the formula Determine the first damping torque matrix provided by the power generation energy area to itself in the target mode, where λ _m is the eigenvalue of the m-th mode,/> is the torque matrix provided by the i region to its own region, and G _i,i is the first forward channel matrix from the i region (i.e., the i-th power generation energy region) to the electromechanical oscillation link of the i region generator or virtual synchronous machine.

Among them, according to the generator motor speed variable of the power generation energy region, the second forward channel matrix and the oscillation mode of the new energy power system, it is determined that the power generation energy region divides the power generation energy in each oscillation mode. The second damping torque matrix provided by any power generation energy area outside the area can be specifically as follows:

According to the formula Determine the second damping torque matrix provided by the non-i area to the i area in the target mode, where λ _m is the eigenvalue of the m-th mode,/> is the torque matrix provided by the non-i area to the i area, G _i-,i is the second forward channel matrix of the electromechanical oscillation link of the generator or virtual synchronous machine from the non-i area to the i area.

Wherein, according to the sensitivity matrix, the first damping torque matrix and the second damping torque matrix, the regional damping provided by the power generation energy area to the low-frequency oscillation of the new energy power system in each mode is calculated; the sensitivity matrix Indicates the ability of the power generation energy region to influence the mode, specifically as follows:

Specifically, the sensitivity matrix S _i,m of the m-th oscillation mode to the i-th region's damping torque is defined to evaluate the power generation energy region's ability to influence the oscillation mode:

In the formula, S _i,m is the sensitivity matrix of the m-th mode to the i region, λ _m is the eigenvalue of the m-th oscillation mode, and T _i ^m is the damping torque of the i-th power generation energy region.

Calculate the regional damping provided by the power generation energy region to the low-frequency oscillation of the new energy power system under each oscillation mode according to formula (20). Formula (20) is:

Among them, D _im is the regional damping provided by the i-th region to the power system, S _i,m is the sensitivity matrix of the m-th mode to the i region, is the torque matrix provided by the i-th region to its own region, S _i-,m is the sensitivity matrix of the m-th mode to the damping torque of the non-i region;/> It is the torque matrix provided by the non-i area to the i-th area.

Specifically, modal analysis is often used to analyze the oscillation behavior and oscillation attenuation capabilities in the system. In oscillation analysis, damping torque is an important parameter that describes the system's ability to dissipate energy during oscillation. The damping torque can be calculated through the sensitivity index of each area to different oscillation modes. Therefore, the sensitivity of the mode to the damping torque of the region is, for a specific oscillation mode, the contribution of each region to the damping torque in the power system, and the damping torque of each region to the specific oscillation mode. Contribution size.

In a power system, the magnitude of the damping torque in a region can be affected by many factors, such as power supply damping, motor inertia, load damping, etc. Therefore, for different oscillation modes, the sensitivity indicators of the damping torque in different regions may be very different. By analyzing the sensitivity index of the damping torque in the modal pair area in the power system, it can help engineers better understand the system oscillation behavior and guide the adjustment of the system's damping torque to improve the stability and reliability of the power system.

In some embodiments, after step 4, it also includes adjusting the access power or access location of each power generation energy source, specifically as follows:

Adjust the access power of each power generation energy source multiple times and repeat steps 1-4 to obtain the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy area under each oscillation mode.

According to the regional damping corresponding to each power generation energy area obtained through multiple adjustments, the optimal access power of each power generation energy source is determined.

Adjust the access position of each power generation energy multiple times and repeat steps 1-4 to obtain the regional damping of the low-frequency oscillation of the new energy power system in each power generation energy area in each mode.

According to the regional damping corresponding to each power generation energy area obtained through multiple adjustments, the optimal access position of each power generation energy is determined.

Since the regional damping of the low-frequency oscillation of the new energy power system by each power generation energy region in each mode can be calculated according to steps 1-4, after calculating the damping provided by the power generation energy to the different modes of low-frequency oscillation of the power system, through More detailed considerations should be made to determine the damping values provided by each power generation energy source to different modes of low-frequency oscillation of the power system under different access locations, access power, and output ratios. In this way, more accurate data can be obtained, and the impact of different new energy access methods on the low-frequency oscillation of the power system can be further analyzed. This impact analysis is usually based on the size of the damping value, because the larger the damping value, the smaller the probability of low-frequency oscillation.

Therefore, it is necessary to compare the damping values of each new energy source to determine the optimal access location, access power, and output ratio to achieve optimal control and management of low-frequency oscillations in the power system. For example, first, based on the determined parameters of the power system, a system small signal model is established. The formulas used in different access systems (photothermal power generation, photovoltaic and wind power systems) are Equation (5), Equation (11) and Equation ( 16). Then, the state matrix is obtained through the models of Equation (5), Equation (11) and Equation (16), which is the matrix shown in Equation (17). For this model, it is necessary to calculate according to the formulas (18) to (20), including calculating the damping value provided by each region to each oscillation mode. Among them, equation (20) is used to calculate the damping provided by each region to each oscillation mode. After calculating the damping provided by each area to each oscillation mode, recalculate the damping value by changing the access power or access location of solar thermal, wind power, photovoltaic, etc. Finally, based on the calculated damping value, the impact of changing the access power or access location of solar heat, wind power, etc. on the low-frequency oscillation of the system is analyzed. For example, when keeping other conditions unchanged and the input power of photothermal power generation gradually increases, it is calculated that the regional damping provided by photothermal power generation first increases and then decreases, that is, there is a maximum value of regional damping, then the regional damping The access power corresponding to the maximum value is the optimal access power of photothermal power generation in the current scenario; while keeping other conditions unchanged, change the wind power access location from the power transmission end to the power reception end, and calculate the wind power supply The regional damping becomes larger, then compared with the power transmission end, the power receiving end is a better access location for wind power in the current scenario.

The invention also provides a system for determining the impact of power generation energy on low-frequency oscillation of the power system, including:

The small signal model building module is used to establish the small signal model of each power generation energy; the power generation energy includes photothermal energy, thermal power energy, photovoltaic energy and wind power energy; the small signal model of the photothermal energy is established based on the principle of thermal power generation.

The state matrix module is used to determine the state matrix of the new energy power system model; the new energy power system model is determined based on the new energy power system obtained by simulating grid connection of each power generation energy and the small signal model of each power generation energy.

A sensitivity matrix module is used to determine the sensitivity matrix of the damping torque of each power generation energy region in each of the oscillation modes based on the state matrix and the oscillation mode of the new energy power system.

A damping calculation module is used to determine, according to the state matrix and the sensitivity matrix, the regional damping of the low-frequency oscillation of the new energy power system by each power generation energy region in each of the oscillation modes.

The position power determination module determines the access location and access power of each power generation energy source based on the regional damping.

To sum up, the present invention has the following advantages:

The invention provides a method and system for determining the impact of power generation energy on low-frequency oscillation of the power system. It establishes a small signal model of the new energy power system with photothermal power generation, wind power, and photovoltaic access, and defines the effects of each region on each oscillation mode. The sensitivity index can clearly and effectively quantify the impact of the integration of various new energy sources such as solar thermal power generation and wind power on the low-frequency oscillation of the power system.

Each embodiment in this specification is described in a progressive manner. Each embodiment focuses on its differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. As for the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple. For relevant details, please refer to the description in the method section.

This article uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method and the core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the present invention There will be changes in the specific implementation methods and application scope of the ideas. In summary, the contents of this description should not be construed as limitations of the present invention.

Claims (9)

1. A method for determining the effect of a power generation energy source on low frequency oscillations of an electrical power system, comprising:

step 1: establishing a small signal model of each power generation energy source; the power generation energy sources comprise a photo-thermal energy source, a thermal power energy source, a photovoltaic energy source and a wind power energy source; the small signal model of the photo-thermal energy source is built based on the thermal power generation principle;

step 2: determining a state matrix of a new energy power system model; the new energy power system model is determined based on a new energy power system obtained by simulating grid connection of each power generation energy and a small signal model of each power generation energy;

step 3: determining a sensitivity matrix of damping torque of each power generation energy area under each oscillation mode according to the state matrix and the oscillation mode of the new energy power system;

step 4: determining the damping of each power generation energy area to the low-frequency oscillation area of the new energy power system under each oscillation mode according to the state matrix and the sensitivity matrix;

wherein, the steps 3-4 specifically comprise:

performing matrix decomposition and region-by-region expansion on the state matrix, and determining a power generation motor rotating speed variable, a first forward channel matrix and a second forward channel matrix of each power generation energy region; the first forward channel matrix is a forward channel matrix of an electromechanical oscillation link of the generator motor from the power generation energy source region to the power generation energy source region; the second forward channel matrix is a forward channel matrix of an electromechanical oscillation link of the generator motor from the power generation energy source region to any power generation energy source region except the power generation energy source region;

Determining a first damping torque matrix provided by the power generation energy region to the power generation energy region under each oscillation mode according to the power generation motor rotating speed variable of the power generation energy region, the first forward channel matrix and the oscillation mode of the new energy power system;

determining a second damping torque matrix provided by the power generation energy region to any power generation energy region except the power generation energy region in each oscillation mode according to the power generation motor rotation speed variable of the power generation energy region, the second forward channel matrix and the oscillation mode of the new energy power system;

calculating the regional damping provided by the power generation energy region to the low-frequency oscillation of the new energy power system under each mode according to the sensitivity matrix, the first damping torque matrix and the second damping torque matrix; the sensitivity matrix represents the influence capacity of the power generation energy source region on the mode;

step 5: and determining the access position and the access power of each power generation energy source according to the regional damping.

2. The determination method according to claim 1, characterized by further comprising:

according toCalculating the sensitivity matrix, wherein S _i,m Sensitivity matrix of mth oscillation mode to ith power generation energy region, lambda _m Is the characteristic value of the mth oscillation mode, T _i ^m Damping torque for the i-th power generation energy region.

3. The method of determining according to claim 1, further comprising, after step 4:

adjusting the access power of each power generation energy source for multiple times, and repeating the steps 1-4 to obtain the damping of each power generation energy source region to the low-frequency oscillation region of the new energy power system in each oscillation mode;

and determining the optimal access power of each power generation energy according to the region damping corresponding to each power generation energy region obtained through multiple adjustment.

4. The method of determining according to claim 1, further comprising, after step 4:

adjusting the access position of each power generation energy source for a plurality of times, and repeating the steps 1-4 to obtain the damping of each power generation energy source region to the low-frequency oscillation region of the new energy power system in each oscillation mode;

and determining the optimal access position of each power generation energy according to the region damping corresponding to each power generation energy region obtained through multiple times of adjustment.

5. The method of claim 1, wherein the small signal model of the photo-thermal energy source is as follows:

ΔI _sg ＝C _sg ΔX _sg +D _sg ΔV _sg

Wherein DeltaX _sg ＝[Δδ，Δω，ΔE′ _q ，ΔE′ _fd ]Is the state vector of a small signal model of the photo-thermal energy source, delta is the power angle, omega is the rotor rotating speed, E' _q Is the quadrature axis transient electromotive force, E' _fd Is the dynamic value of the passive voltage regulator; deltaV _sg ＝[ΔV _x ,ΔV _y ] ^T Input vector of small signal model of photo-thermal energy source, V _sg For the terminal voltage of synchronous generator, V _x 、V _y Respectively the components of the voltage of the machine terminal under xy coordinates, delta I _sg ＝[ΔI _x ,ΔI _y ] ^T Output vector of small signal model of photo-thermal energy source, I _sg Is the output current of the synchronous generator; i _x And I _y The components of the output current in the x coordinate and the y coordinate are respectively A _sg State matrix of small signal model of photo-thermal energy source, B _sg Input matrix of small signal model for photo-thermal energy source, C _sg Output matrix D of small signal model of photo-thermal energy source _sg A feed-forward matrix of a small signal model of the photo-thermal energy source.

6. The method of determining according to claim 1, wherein the small signal model of the photovoltaic energy source is as follows:

wherein DeltaX _p ＝[ΔE _f Δδ _VSG Δω _VSG ΔV _dc ΔX] ^T State vector of small signal model of photovoltaic energy, E _f For virtual synchronous machine output voltage delta _VSG To output the voltage phase angle omega _VSG Angular velocity, V, of internal potential of virtual synchronous machine VSG _dc For the DC side voltage, deltaX is an intermediate variable, deltaX has an upper limit of 0, deltaU _p ＝[ΔV _gx ΔV _gy ] ^T Input vector U of small signal model of photovoltaic energy _p Voltage of grid-connected point of virtual synchronous machine, V _gx 、V _gy For the components of the grid-connected point voltage of the virtual synchronous machine under the x coordinate and the y coordinate, delta I _p ＝[ΔI _x ΔI _y ] ^T Output vector of small signal model of photovoltaic energy, I _p Injection current for virtual synchronous machine, I _x And I _y Respectively injecting components of current under xy coordinates for the virtual synchronous machine, A _p State matrix of small signal model of photovoltaic energy source, B _p Input matrix of small signal model for photovoltaic energy, C _p Output matrix of small signal model of photovoltaic energy source, D _p Is a feed-forward matrix of a small signal model of the photovoltaic energy source,

C _dc is the capacitance value of the direct current side voltage stabilizing capacitor, V _dc(0) Is the initial voltage value of the direct-current side voltage stabilizing capacitor, U _oc Delta for open circuit voltage of photovoltaic cell _VSG(0) 、I _sc(0) 、V _gx(0) 、V _gy(0) 、V _g(0) 、δ _VSG(0) 、E _f(0) 、I _x(0) 、I _y(0) Delta respectively _VSG 、I _sc 、V _gx 、V _gy 、V _g 、δ _VSG 、E _f 、I _x 、I _y Initial value, X obtained after variable power flow calculation _f Output voltage E for virtual synchronous machine _f Point-to-virtual synchronous machine grid-connected point V _g Reactance, omega _n For the reference frequency of the power grid, J is the inertia constant of the VSG control link, D is the damping coefficient of the VSG control link, K is the voltage coefficient of the VSG control link, D _q Reactive power coefficient K of VSG control link _pv For P 'in VSG control' _ref Proportional coefficient, K of control link PI controller _iv For P 'in VSG control' _ref Integral coefficient of control link PI controller, C ₁ 、C ₂ Is an intermediate variable of the U-I equation of the photovoltaic cell.

7. The method of determining according to claim 1, wherein the small signal model of the wind power energy source is as follows:

wherein DeltaX _W State vector delta U of small signal model of wind power energy _W ＝[ΔV _gx-w ,ΔV _gy-w ]Input vector U of small signal model of wind power energy _W Grid-connected point voltage, V of PMSG-VSG _gx-w 、V _gy-w For the components of the grid-connected point voltage of the virtual synchronous machine under the x coordinate and the y coordinate, delta I _W ＝[ΔI _gx-w ,ΔI _gy-w ] ^T Output vector of small signal model of wind power energy source, I _W Injection current for PMSG-VSG, I _gx-w 、I _gy-w Injecting components of current in xy coordinates for a virtual synchronous machine, A _W A state matrix of a small signal model of wind power energy, B _W Input matrix of small signal model of wind power energy source, C _W Output matrix D of small signal model of wind power energy _W Is a feedforward matrix of a small signal model of wind power energy.

8. The method according to claim 1, wherein determining, according to the state matrix and the sensitivity matrix, the damping of each power generation energy region to the region of the new energy power system low-frequency oscillation in each oscillation mode is specifically as follows:

According to the formulaCalculating the region damping provided by each power generation energy region for low-frequency oscillation of the new energy power system;

wherein D is _im Zone damping provided for the ith power generation zone to the new energy power system, S _i,m For the sensitivity matrix of the mth modality to the ith power generation energy region,a torque matrix provided for the ith power generation energy region to the own region, S _i-,m Sensitivity matrix for damping torque for non-i region for mth oscillation mode；/>A torque matrix provided for the non-i region to the i-th region, S _j,m Sensitivity matrix for the mth mode to the jth power generation energy region, +.>A torque matrix provided to the own region for the jth power generation energy region.

9. A system for determining the effect of a source of generated energy on low frequency oscillations of an electrical power system, comprising:

the small signal model building module is used for building a small signal model of each power generation energy source; the power generation energy sources comprise a photo-thermal energy source, a thermal power energy source, a photovoltaic energy source and a wind power energy source; the small signal model of the photo-thermal energy source is built based on the thermal power generation principle;

the state matrix module is used for determining a state matrix of the new energy power system model; the new energy power system model is determined based on a new energy power system obtained by simulating grid connection of each power generation energy and a small signal model of each power generation energy;

The sensitivity matrix module is used for determining a sensitivity matrix of damping torque of each power generation energy area under each oscillation mode according to the state matrix and the oscillation mode of the new energy power system;

performing matrix decomposition and region-by-region expansion on the state matrix, and determining a power generation motor rotating speed variable, a first forward channel matrix and a second forward channel matrix of each power generation energy region; the first forward channel matrix is a forward channel matrix of an electromechanical oscillation link of the generator motor from the power generation energy source region to the power generation energy source region; the second forward channel matrix is a forward channel matrix of an electromechanical oscillation link of the generator motor from the power generation energy source region to any power generation energy source region except the power generation energy source region;

determining a first damping torque matrix provided by the power generation energy region to the power generation energy region under each oscillation mode according to the power generation motor rotating speed variable of the power generation energy region, the first forward channel matrix and the oscillation mode of the new energy power system;

determining a second damping torque matrix provided by the power generation energy region to any power generation energy region except the power generation energy region in each oscillation mode according to the power generation motor rotation speed variable of the power generation energy region, the second forward channel matrix and the oscillation mode of the new energy power system;

The damping calculation module is used for determining the damping of each power generation energy area to the low-frequency oscillation area of the new energy power system under each oscillation mode according to the state matrix and the sensitivity matrix;

calculating the regional damping provided by the power generation energy region to the low-frequency oscillation of the new energy power system under each mode according to the sensitivity matrix, the first damping torque matrix and the second damping torque matrix; the sensitivity matrix represents the influence capacity of the power generation energy source region on the mode;

and the position power determining module is used for determining the access position and the access power of each power generation energy source according to the regional damping.