Stable control method and system for accessing network construction type heterogeneous power supply to direct current system

Abstract

The invention relates to a stable control method and a stable control system for accessing a network construction type heterogeneous power supply to a direct current system, belongs to the technical field of power system control, and solves the problem of serious active power vacancy when an alternating current tie line of an existing multi-source access direct current sending end system fails. The method comprises the steps that energy flow paths among subsystems in the system are analyzed to identify key control links causing instability of the system and orthogonal interaction energy of the key control links, and the orthogonal interaction energy is an interaction energy item which has the largest influence on the stability of the system in interaction energy among modules of the subsystems; based on a minimization principle of total stored energy of the system, coordinating and adjusting a doubly-fed fan active instruction, a direct current system current instruction and an energy storage active instruction in real time; keeping a negative value according to the total interaction energy of the system to compensate the orthogonal interaction energy among the subsystems; and according to the state feedback signal, the active power instruction of each subsystem is dynamically adjusted in combination with the control switching logic. The adaptive capacity and the dynamic recovery performance are improved, and accurate matching and quick response to various fault working conditions are achieved.

Description

Technical Field

[0001] This invention relates to the field of power system control technology, and in particular to a method and system for stable control of grid-connected heterogeneous power sources in a DC system. Background Technology

[0002] With the large-scale integration of multiple new energy sources such as wind power and energy storage, the inertia support capacity of DC sending-end systems is gradually weakening, and system frequency stability is severely challenged. When multiple faults occur in the AC tie line (such as an N-2 fault), the sending-end system experiences a significant active power deficit, leading to a continuous drop in system frequency. Traditional DC frequency auxiliary control measures are insufficient to meet the system's frequency regulation requirements. Existing research mainly employs additional DC frequency control or coordinated control strategies, but fails to deeply analyze the interactive effects of multi-source systems from an energy flow perspective. It also lacks mechanisms for identifying and compensating for orthogonal interactive energy, making it difficult to fully leverage the synergistic effects of each subsystem and improve system resilience. Summary of the Invention

[0003] Based on the above analysis, the embodiments of the present invention aim to provide a stable control method and system for grid-connected heterogeneous power sources in DC systems, in order to solve the problem of severe active power deficit when AC tie-line faults occur in existing multi-source DC sending-end systems.

[0004] On one hand, embodiments of the present invention provide a method for stable control of a grid-connected heterogeneous power supply connected to a DC system, comprising: analyzing the energy flow paths between subsystems in the system to identify key control links that cause system instability and their positive interactive energy, wherein the positive interactive energy is the interactive energy item with the greatest impact on system stability among the interactive energy between subsystem modules; coordinating and adjusting the active power command of the doubly-fed wind turbine, the DC system current command, and the energy storage active power command in real time based on the principle of minimizing the total stored energy of the system; compensating the positive interactive energy between subsystems by keeping the total interactive energy of the system negative; and dynamically adjusting the active power command of each subsystem according to the state feedback signal and in combination with the control switching logic, wherein the dynamic energy model of each subsystem includes stored energy, dissipated energy, and interactive energy.

[0005] The beneficial effects of the above technical solution are as follows: Compared with traditional methods that rely solely on power or frequency deviation, identifying the interactive energy paths and positive interactive energy terms between different subsystems based on the multi-subsystem interactive energy model can accurately locate the key control links that amplify oscillations under Nm faults, providing higher resolution control basis; through the coordinated optimization of multi-source active power commands, energy accumulation and system impact during faults are effectively reduced; through orthogonal interactive energy dynamic compensation, the system's ability to suppress adverse energy interactions is significantly enhanced, improving oscillation stability; by using multiple state variables such as DC current and system frequency as feedback signals, combined with control switching logic, the active power commands of each subsystem are dynamically adjusted, improving the system's adaptive capability and dynamic recovery performance, and achieving accurate matching and rapid response to various fault conditions.

[0006] Further improvements to the above method involve analyzing the energy flow paths between subsystems in the system to identify key control elements that cause system instability and their corresponding positive interaction energies. This includes: constructing a multi-subsystem model, wherein the multi-subsystems include a thermal power unit inertial quantum system, a thermal power unit d-axis subsystem, a thermal power unit q-axis subsystem, a virtual inertial control subsystem, a phase-locked loop subsystem, a doubly-fed induction generator (DFIG) d-axis system, a DFIG q-axis system, a rectifier-side subsystem, an inverter-side subsystem, and a DC line subsystem; analyzing the energy flow paths between the subsystems to calculate the interaction energy between the multi-subsystems; calculating the rate of change of interaction energy based on the interaction energy between the multi-subsystems; and identifying the key control elements that cause system instability and their corresponding positive interaction energies based on the rate of change of interaction energy.

[0007] Further improvements to the above method, based on the rate of change of the interaction energy, identify the key control links that cause system instability and their positive interaction energies, further including: when the current rate of change of the interaction energy between different subsystems is negative, negative interaction energy is beneficial to the stable operation of the system, wherein the smaller the rate of change of the negative interaction energy, the higher the stability level; when the current rate of change of the interaction energy between different subsystems is zero, the corresponding interaction energy is irrelevant to the system stability level; when the current rate of change of the interaction energy between different subsystems is positive, positive interaction energy is detrimental to the stable operation of the system, wherein the larger the rate of change of the positive interaction energy, the more detrimental it is to the stability of the system; and determining the oscillation source that induces system oscillation based on the maximum rate of change of the positive interaction energy.

[0008] Based on further improvements to the above method, the interaction energy between the multiple subsystems includes: the interaction energy between the inertial quantum system and the constant current control subsystem; the interaction energy between the inertial quantum system and the doubly-fed induction generator (DFIG) q-axis subsystem; the interaction energy between the thermal power unit d-axis subsystem and the thermal power unit q-axis subsystem; the interaction energy between the phase-locked loop (PLL) subsystem and the inertial quantum system; the interaction energy between the DFIG d-axis subsystem and the DFIG q-axis subsystem; the interaction energy between the DFIG d-axis subsystem and the inertial quantum system; the interaction energy between the DFIG d-axis subsystem and the PLL subsystem; the interaction energy between the constant current control subsystem and the DC line subsystem; the interaction energy between the constant current control subsystem and the DFIG q-axis subsystem; and the interaction energy between the constant turn-off angle control subsystem and the DC line subsystem.

[0009] Based on the above method, further improvements are made to the principle of minimizing the total stored energy of the system. The real-time coordination and adjustment of the active power command of the doubly fed wind turbine, the DC system current command, and the active power command of the energy storage further include: after the energy storage subsystem is connected, the total stored energy of the grid-type heterogeneous power supply connected to the DC system is calculated based on the cumulative energy of the thermal power unit subsystem, the doubly fed wind turbine subsystem, the rectifier side subsystem, and the energy storage subsystem after the N-2 fault.

[0010] The total stored energy of the system is minimized by coordinating and adjusting the active power command of the doubly fed wind turbine, the current command of the DC system, and the active power command of the energy storage in real time.

[0011] Further improvements to the above method, compensating for the positive interactive energy between subsystems by keeping the total system interactive energy negative, further include: taking partial derivatives of the active power command of the doubly-fed induction generator (DFIG), the DC system current command, and the energy storage active power command respectively based on the dynamic energy model of each subsystem, and constructing a gradient relationship between dynamic energy and the active power command of the DFIG, the DC system current command, and the energy storage active power command; and adjusting the active power command of the DFIG, the DC system current command, and the energy storage active power command in reverse according to the gradient relationship, so that the positive interactive energy gradually decreases so that the total system interactive energy remains negative.

[0012] Based on further improvements to the above method, the control switching logic further includes: after an N-2 fault occurs in the grid-connected heterogeneous power supply DC system, performing low voltage ride-through control switching, DC rectifier side control switching, and inverter side control switching for the doubly fed wind turbine.

[0013] Based on further improvements to the above method, after an N-2 fault occurs in a grid-connected heterogeneous power supply connected to a DC system, the low-voltage ride-through control switching of the doubly-fed induction generator (DFIG) wind turbine further includes: when the grid voltage drops sharply and the system frequency falls rapidly, the change in the d-axis current command of the wind turbine directly affects the active power output of the inertial quantum system, thereby adjusting the system frequency disturbance power term; the adjustment of the d-axis current command of the wind turbine affects the rotor d-axis current, thereby changing the d-axis electromotive force and the related transient / subtransient energy distribution; the change in the q-axis current command of the wind turbine affects the reactive power regulation capability of the wind turbine; the change in the dq-axis current of the wind turbine leads to a change in the grid connection point voltage, thereby affecting the phase change Δθ of the phase-locked loop tracking phase. pll This causes disturbances in the phase-locked loop subsystem; and the switching process of the wind turbine output power command triggers ΔP in the virtual inertia control module. eref Dynamic adjustment of link state variables alters their response to frequency fluctuations.

[0014] Based on the further improvement of the above method, after an N-2 fault occurs in the grid-connected heterogeneous power supply connected to the DC system, the control switching of the DC rectifier side and the inverter side further includes: after an N-2 fault occurs in the grid-connected heterogeneous power supply connected to the DC system, the rectifier side switches from constant current control to minimum firing angle control, and the inverter side switches from constant turn-off angle control to constant current control.

[0015] On the other hand, embodiments of the present invention provide a grid-type heterogeneous power supply access DC system stability control system, comprising: an interaction path identification module, used to analyze the energy flow paths between subsystems in the system to identify key control links that cause system instability and their positive interaction energy, wherein the positive interaction energy is the interaction energy item with the greatest impact on system stability among the interaction energy between subsystem modules; an instruction coordination adjustment module, used to coordinate and adjust the active power command of the doubly-fed wind turbine, the DC system current command, and the energy storage active power command in real time based on the principle of minimizing the total system stored energy; an interaction energy compensation module, used to compensate for the positive interaction energy between subsystems by keeping the total system interaction energy negative; and a state feedback adjustment module, used to dynamically adjust the active power command of each subsystem based on the state feedback signal and in combination with control switching logic, wherein the dynamic energy model of each subsystem includes stored energy, dissipated energy, and interaction energy.

[0016] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0017] 1. Compared to traditional methods that rely solely on power or frequency deviations, the multi-subsystem interactive energy model identifies interactive energy paths and positive interactive energy terms between different subsystems, enabling precise location of key control links that amplify oscillations under Nm faults and providing higher-resolution control basis. Through the coordinated optimization of multi-source active power commands, it effectively reduces energy accumulation and system impact during faults. Through orthogonal interactive energy dynamic compensation, it significantly enhances the system's ability to suppress adverse energy interactions and improves oscillation stability. By using multiple state variables such as DC current and system frequency as feedback signals and combining them with control switching logic to dynamically adjust the active power commands of each subsystem, it can improve the system's adaptability and dynamic recovery performance, achieving accurate matching and rapid response to various fault conditions.

[0018] 2. Compared to using only fixed control logic, this step improves the system's adaptability and dynamic recovery performance, enabling precise matching and rapid response to various fault conditions. Specifically, by conducting in-depth analysis of the energy flow paths among multiple subsystems and implementing real-time collaborative control, the negative impact of orthogonal interactive energy on the system can be significantly suppressed, achieving timely compensation for the active power deficit of the DC sending-end system after a fault. Simulation results show that after adopting the method of this invention, the system frequency fluctuation amplitude is reduced, the recovery speed is accelerated, and the overall system stability is significantly improved. Simultaneously, the collaborative control strategy can accurately match the active power output allocation of each subsystem, fully leveraging the comprehensive effects of various energy resources.

[0019] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0020] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts.

[0021] Figure 1 A flowchart of a method for coordinated active power control in a multi-source DC transmission system;

[0022] Figure 2 Topology diagram of a multi-source DC transmission system;

[0023] Figure 3 This describes the energy flow path after a fault in the N-2 multi-source DC transmission system.

[0024] Figure 4 For coordinated control of the DC transmission system;

[0025] Figure 5 The active power output of the doubly-fed wind turbine when 50% of the large-capacity power grid is cut off in scenario one;

[0026] Figure 6 The DC current is cut off when 50% of the large-capacity power grid is in scenario one.

[0027] Figure 7 The frequency of the DC transmission system when 50% of the large-capacity power grid is removed in scenario one;

[0028] Figure 8 The output power of thermal power units, doubly fed wind turbines, and energy storage is cut off when 50% of the large-capacity power grid is removed in scenario one.

[0029] Figure 9 The dynamic changes in the frequency of the DC sending-end system are described in Scenario 2 (cutting off 20% of the small-capacity power grid);

[0030] Figure 10 The curves depicting the variation of DC system current under the same scenario are described.

[0031] Figure 11 The output power variations of thermal power units, doubly fed wind turbines, and energy storage devices are described.

[0032] Figure 12 and Figure 13 The total interactive energy and total energy change correspond to Scenario 1 (cutting off 50% of the large-capacity power grid);

[0033] Figure 14 and Figure 15 The total interactive energy and total energy change correspond to Scenario 2 (cutting off 20% of the large-capacity power grid).

[0034] Figure 16 This is a schematic diagram of an active power coordinated control method for a multi-source access DC transmission system. Detailed Implementation

[0035] Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not intended to limit the scope of the present invention.

[0036] refer to Figure 1A specific embodiment of the present invention discloses a method for stable control of a grid-connected heterogeneous power supply connected to a DC system, comprising: in step S101, analyzing the energy flow paths between subsystems in the system to identify key control links that cause system instability and their positive interaction energy, wherein the positive interaction energy is the interaction energy item with the greatest impact on system stability among the interaction energy between subsystem modules; in step S102, based on the principle of minimizing the total stored energy of the system, coordinating and adjusting the active power command of the doubly-fed induction generator, the DC system current command, and the energy storage active power command in real time; in step S103, compensating for the positive interaction energy between subsystems by keeping the total interaction energy of the system negative; in step S104, dynamically adjusting the active power command of each subsystem based on the state feedback signal and combined with the control switching logic, wherein the dynamic energy model of each subsystem includes stored energy, dissipated energy, and interaction energy.

[0037] Compared with existing technologies, the grid-type heterogeneous power supply access DC system stability control method provided in this embodiment, compared with traditional methods that only rely on power or frequency deviation, identifies the interactive energy paths and positive interactive energy terms between different subsystems based on a multi-subsystem interactive energy model. This allows for precise location of key control links that amplify oscillations under Nm faults, providing higher resolution control basis. Through the coordinated optimization of multi-source active power commands, it effectively reduces energy accumulation and system impact during faults. Through orthogonal interactive energy dynamic compensation, it significantly enhances the system's ability to suppress adverse energy interactions and improves oscillation stability. By using multiple state variables such as DC current and system frequency as feedback signals and combining them with control switching logic to dynamically adjust the active power commands of each subsystem, it can improve the system's adaptive capability and dynamic recovery performance, achieving accurate matching and rapid response to various fault conditions.

[0038] In the following text, refer to Figure 1 The following provides a detailed description of each step in the stable control method for grid-connected heterogeneous power sources in a DC system according to an embodiment of the present invention.

[0039] In step S101, the energy flow paths between the subsystems in the system are analyzed to identify the key control links that cause system instability and their positive interaction energies. The positive interaction energy is the interaction energy term with the greatest impact on system stability among the interaction energies between subsystem modules. Specifically, the energy flow paths between the subsystems are analyzed, and based on a multi-subsystem interaction energy model, the interaction energy paths and positive interaction energy terms between different subsystems are identified. Compared to traditional methods that rely solely on power or frequency deviations, this method can accurately locate the key control links that amplify oscillations under Nm faults, providing a higher resolution control basis.

[0040] The "dominant energy term (i.e., the positive interaction energy term)" refers to the energy flux term that has the greatest impact on system stability during energy interactions between system submodules. It is identified by the magnitude and sign of the rate of change of the interaction energy; the positive interaction energy term with the largest rate of change is the dominant energy term that causes system instability.

[0041] For example, in the energy interaction between the inertial quantum system and the DC current control subsystem, when the rate of change of the interaction energy is consistently positive, it indicates that the energy flow promotes the accumulation of system energy and is one of the dominant factors of oscillation, which should be prioritized for suppression and compensation.

[0042] Specifically, analyzing the energy flow paths between the subsystems in the system to identify the key control links that cause system instability and their positive interactive energies further includes: constructing a multi-subsystem model, wherein the multi-subsystems include the thermal power unit inertial quantum system, the thermal power unit d-axis subsystem, the thermal power unit q-axis subsystem, the virtual inertial control subsystem, the phase-locked loop subsystem, the doubly-fed induction generator d-axis system, the doubly-fed induction generator q-axis system, the rectifier side subsystem, the inverter side subsystem, and the DC line subsystem; analyzing the energy flow paths between the subsystems in the system to calculate the interactive energy between the multi-subsystems; calculating the rate of change of interactive energy based on the interactive energy between the multi-subsystems; and identifying the key control links that cause system instability and their corresponding positive interactive energies based on the rate of change of interactive energy.

[0043] refer to Figure 2 The multi-source DC transmission system includes:

[0044] (1) Inertial quantum system of thermal power unit

[0045]

[0046] In the formula: Δθ s Δf is the change in phase angle of the sending-end system; H is the change in frequency of the sending-end system; D is the inertia of the sending-end system; and D is the damping coefficient of the sending-end system. ref This refers to the change in the frequency reference value of the sending system. H x1 For the phase angle compensation term of the inertial quantum system, it is equal to -2πΔfref; ΔP Σ(Δθs) The total active power increment caused by the phase angle change; ΔP Σ(Δf) ΔP represents the increase in total active power caused by frequency changes. Σ The sum of the active power increments of each subsystem of the system; H y1 The frequency perturbation power term of the inertial quantum system is equal to ΔP. Σ .

[0047] satisfy:

[0048]

[0049] Where: R is the governor droop coefficient; s r U represents the slip ratio of the doubly-fed wind turbine. s0 and i sq0 The voltage at the grid connection point and the current on the q-axis of the doubly-fed induction generator stator are measured when the power supply system is operating normally; ΔU s Δi represents the change in voltage at the grid connection point of the doubly-fed induction generator (DFIG). sd i represents the change in the d-axis current of the doubly-fed induction generator stator; sd0 The current Δθ of the stator d-axis of the doubly-fed induction generator during normal operation of the feed-end system. pll α is the change in phase angle of the phase-locked loop; r0 i dr0 and u dr0 These represent the steady-state firing angle, steady-state current, and steady-state voltage on the rectifier side during steady-state operation of the sending-end system; Δi dr Δα represents the change in DC current on the rectifier side. r x is the change in firing angle; sr The commutation reactance on the rectifier side; ΔP TPP ΔP represents the change in active power output of a thermal power unit. LCC ΔP represents the change in active power of the converter. DFIG This represents the change in the active power of a doubly-fed wind turbine.

[0050] (2) d-shaft subsystem of thermal power unit

[0051]

[0052] In the formula: T d0 ' is the time constant of the d-axis transient electromotive force; T d0 " is the time constant of the d-axis subtransient electromotive force; ΔE d ' represents the change in transient electromotive force along the d-axis; ΔE d " is the change in the d-axis transient electromotive force; Δi d x′ represents the change in current along the d-axis. d x′ is the d-axis transient reactance; d ′ represents the d-axis subtransient reactance; H x2 The transient electromotive force coupling term caused by the change in d-axis current; H y2 This is a subtransient coupling term caused by the difference between d-axis current and reactance.

[0053] (3) q-shaft subsystem of thermal power unit

[0054]

[0055] In the formula: T q0 ' is the time constant of the q-axis transient electromotive force; T q0 " is the time constant of the q-axis subtransient electromotive force; ΔEq ' is the change in transient electromotive force along the q-axis; ΔE q " is the change in the q-axis transient electromotive force; Δi q x′ represents the change in q-axis current. q x′ is the q-axis transient reactance; q ′ H is the q-axis subtransient reactance; x3 The transient electromotive force coupling term caused by the q-axis current change; H y3 This is a subtransient coupling term caused by the difference between q-axis current and reactance.

[0056] (4) Virtual Inertia Control Subsystem

[0057]

[0058] Where: K dvic and K pvic These are the proportional coefficients of the differential element and the first-order hysteresis element of the virtual inertial quantum system, respectively; Δω pll T represents the change in the rotational speed of the phase-locked loop. pll x is the time constant of the droop control module; vic x is the state variable of the current first-order lag link; vicref The reference value for the state variable of the current first-order lag link; ΔP eref H represents the change in the power command value of the doubly-fed wind turbine. x4 For the coupling term of power command value change; H y4 The virtual inertia is a first-order hysteresis link state variable.

[0059] (5) Phase-locked loop subsystem

[0060]

[0061] In the formula: x pll K represents the state variable of the integral link in the current loop PI controller. p_pll and K i_pll These are the proportional and integral coefficients of the PI controller in the phase-locked loop subsystem, respectively; H x5 For the phase-locked loop input voltage disturbance term; H y5 This is the voltage coupling term in the output of the phase-locked loop PI control.

[0062] (6) Doubly fed fan d-shaft subsystem

[0063]

[0064] In the formula: x DFIG Δi represents the state variable of the integral link in the current loop PI controller. sd K represents the change in the d-axis current of the doubly-fed induction generator stator.p_DFIG and K i_DFIG These are the proportional and integral coefficients of the PI controller in the doubly-fed wind turbine subsystem, respectively; i sd0 The current T in the stator d-axis of the doubly-fed fan during normal operation of the feed-end system; d H is the d-axis time constant of the doubly fed wind turbine converter; x6 The d-axis disturbance power term caused by changes in active power command; H y6 This is the voltage and d-axis current coupling disturbance term; ΔP eref * This represents the change in the active power command of the doubly fed wind turbine after correction.

[0065] (7) Doubly fed fan q-shaft subsystem

[0066] As shown above, controlling the d-axis component of the rotor current of a doubly-fed induction generator (DFIG) can control its active power, and controlling the q-axis component of the rotor current can control its reactive power transmitted to the grid. Therefore, the standard q-axis energy form of the constructed DFIG is:

[0067]

[0068] In the formula: Δi sq T represents the change in the q-axis current of the doubly-fed induction generator stator. q Δi is the q-axis time constant of the doubly-fed wind turbine converter; ar Δi represents the change in AC current on the sending-end converter station. sqref The change in the commanded q-axis current of the doubly-fed wind turbine; C is the equivalent capacitance of the AC filter; H x7 For alternating current variation coupled power term; H y7 This refers to the power term that varies with the q-axis current command.

[0069] (8) Rectifier-side subsystem

[0070]

[0071] In the formula: K ir and K pr For the proportional-integral parameters of the PI controller; ΔI dRref Δi represents the change in the current reference value. drm K represents the measured change in the rectifier-side DC current; mr The gain of the rectifier-side DC current module; T mr The time constant of the rectifier-side DC current module; ΔU d R is the change in capacitor voltage; d and L d These are the DC dynamic line resistance and inductance, respectively; H x8 For DC current command coupling disturbance term; H y8This is the firing angle and voltage coupling disturbance term.

[0072] (9) Inverter-side subsystem

[0073]

[0074] In the formula: K pi1 and K ii1 K represents the proportional-integral parameters of the PI controller. mi1 The gain of the rectifier-side DC current module; T mi1 Δγ is the time constant of the rectifier-side DC current module. ref The command value for the change in arc extinction angle; Δγ m H is the command value for the change in arc extinction angle; x9 The disturbance term is the change in the reference value of the arc extinction angle; H y9 The disturbance term for the measured arc extinction angle; Δγ m This measures the change in the arc extinction angle.

[0075] (10) DC line subsystem

[0076] Since the electrical quantities of a DC line satisfy the KCL equation, the DC voltage change ΔU is chosen. d and DC current change Δi di As a state variable, the energy standard form of the DC line subsystem is established as follows:

[0077]

[0078] In the formula: C d For DC line capacitance to ground; L d γ0 represents the DC line inductance. γ0 is the steady-state value of the arc extinction angle on the inverter side; Δγ is the change in the arc extinction angle; Δi di x represents the change in DC current on the inverter side. si For the commutation reactance on the inverter side; u ai0 This represents the steady-state voltage on the inverter side during normal operation; Δu aim H represents the change in inverter-side voltage. x10 The voltage disturbance term caused by the converter's arc extinction angle; H y10 This is the DC current-reactance coupling disturbance term; Δi di Δi represents the change in direct current. dm x represents the change in the measured value of direct current. si For inverter-side commutation reactance; ΔU d This represents the change in DC line voltage.

[0079] Specifically, based on the rate of change of interaction energy, identifying the key control elements that trigger system instability and their positive interaction energies further includes: when the current rate of change of interaction energy between different subsystems is negative, i.e., when... Negative interaction energy is beneficial for the system to maintain stable operation; the smaller the rate of change of negative interaction energy, the higher the stability level. When the rate of change of current interaction energy between different subsystems is zero, that is, when... When the corresponding interaction energy is independent of the system stability level; when the rate of change of the current interaction energy between different subsystems is positive, that is, when At this time, positive interaction energy is not conducive to the stable operation of the system. In particular, the greater the rate of change of positive interaction energy, the more unfavorable it is for the system to maintain stability. The oscillation source that induces system oscillation is determined based on the maximum rate of change of positive interaction energy (greater than 0).

[0080] refer to Figure 3 The interaction energy between multiple subsystems includes: the interaction energy V between the thermal power unit's inertial quantum system and the rectifier-side subsystem. t_TPP_i_LCC_r The interaction energy V between the inertial quantum system of the thermal power unit and the q-shaft subsystem of the doubly fed fan. t_TPP_i_DFIG_q The interaction energy V between the d-axis and q-axis subsystems of a thermal power unit. t_TPP_d_q The interaction energy V between the phase-locked loop subsystem and the inertial quantum system of the thermal power unit t_pll_i The interaction energy V between the d-axis and q-axis subsystems of the doubly-fed fan. t_DFIG_d_q The interaction energy V between the doubly fed fan d-shaft system and the thermal power unit inertial quantum system t_DFIG_d_TPP_i The interaction energy V between the doubly fed fan d-shaft subsystem and the phase-locked loop subsystem t_DFIG_d_pll Interaction energy between the rectifier subsystem and the DC line subsystem

[0081] V t_LCC_r_line The interaction energy V between the DC line subsystem and the doubly fed wind turbine q-axis subsystem t_LCC_r_DFIG_q The interaction energy V between the inverter-side subsystem and the DC line subsystem t_LCC_i_line .

[0082] In step S102, based on the principle of minimizing the total stored energy of the system, the active power commands of the doubly-fed induction generator (DFIG), the DC system current command, and the energy storage active power command are coordinated and adjusted in real time. This real-time coordinated adjustment of the DFIG, DC system current, and energy storage active power commands, based on the principle of minimizing energy accumulation, differs from the traditional method of adjusting each unit independently. This step effectively reduces energy accumulation and system impact during faults through the collaborative optimization of multi-source active power commands.

[0083] The "energy accumulation minimization principle" is an optimization criterion based on the total accumulated energy of the system (including the interaction energy of each subsystem). That is, by adjusting the control commands, the positive interaction energy accumulation of the system after the fault disturbance is minimized, thereby reducing the impact of negative energy coupling.

[0084] Its relationship with the interactive energy / dominant energy term in step S101 is as follows: Step S101 identifies the dominant interactive energy path and orthogonal energy term in the current system, and step S102 reduces the total accumulation of these orthogonal energy terms by optimizing control commands, thereby improving the dynamic stability of the system.

[0085] Specifically, based on the principle of minimizing the total stored energy of the system, the real-time coordination and adjustment of the active power command of the doubly fed wind turbine, the DC system current command and the active power command of the energy storage further include: after the energy storage subsystem is connected, after the grid-type heterogeneous power supply is connected to the DC system, the total stored energy of the system is calculated based on the cumulative energy of the thermal power unit subsystem, the doubly fed wind turbine subsystem, the rectifier side subsystem and the energy storage subsystem after the N-2 fault.

[0086]

[0087] The total stored energy of the system is minimized by coordinating and adjusting the active power command of the doubly-fed wind turbine, the current command of the DC system, and the active power command of the energy storage in real time.

[0088] In step S103, the positive interaction energy between subsystems is compensated to maintain a negative total system interaction energy. Specifically, the orthogonal interaction energy between subsystems is identified, and compensation commands are calculated in real time to keep the total system interaction energy negative. Unlike existing technologies that only consider active power balance, this step significantly enhances the system's ability to suppress adverse energy interactions and improves oscillation stability through dynamic compensation of orthogonal interaction energy.

[0089] The compensation command is based on the rate of change of orthogonal interactive energy between subsystems. The corresponding calculation method is as follows: First, the real-time rate of change of the dominant interactive energy term is obtained according to the system dynamic model. Then, the gradient relationship between energy and control variables (such as wind turbine active power command, DC current command, and energy storage command) is constructed based on its partial derivative information. Then, the values ​​of the above three types of commands are adjusted in the opposite direction according to the gradient, so that the orthogonal interactive energy term gradually decreases, and finally the total interactive energy of the system becomes negative.

[0090] Specifically, compensating for the positive interaction energy between subsystems by keeping the total system interaction energy negative further includes: taking partial derivatives of the active power command of the doubly-fed induction generator (DFIG), the DC system current command, and the energy storage active power command with respect to the dynamic energy models of each subsystem, and constructing the gradient relationship between dynamic energy and the DFIG, DC system current, and energy storage active power commands; and adjusting the DFIG, DC system current, and energy storage active power commands in reverse according to the gradient relationship, so that the positive interaction energy gradually decreases to keep the total system interaction energy negative.

[0091] In step S104, the active power command of each subsystem is dynamically adjusted based on the state feedback signal and in conjunction with the control switching logic. The dynamic energy model of each subsystem includes stored energy, dissipated energy, and interactive energy. Specifically, the active power command of each subsystem is dynamically adjusted based on multiple state variables such as DC current and system frequency as feedback signals, combined with the control switching logic. Compared to using only fixed control logic, this step improves the system's adaptability and dynamic recovery performance, enabling accurate matching and rapid response to various fault conditions.

[0092] Specifically, the control switching logic further includes: after an N-2 fault occurs in the grid-connected heterogeneous power supply DC system, performing low-voltage ride-through control switching, DC rectifier-side control switching, and inverter-side control switching for the doubly-fed wind turbine.

[0093] (1) Low voltage ride-through control switching

[0094] During the low-voltage ride-through control strategy switching process, the wind turbine control structure changes, involving the dynamic behavior adjustments of the multiple subsystems mentioned above:

[0095] Related to the inertial quantum system of thermal power units: When the grid voltage drops sharply and the system frequency falls rapidly, the d-axis current command of the wind turbine changes (i sdref This will directly affect the active power output of the inertial quantum system, thereby adjusting the system's frequency perturbation power term;

[0096] Related to the d-shaft subsystem of thermal power units: Adjustment of the fan d-shaft current command affects the rotor d-shaft current (i sd This alters the d-axis electromotive force and the associated transient / subtransient energy distribution, which is reflected in changes in the storage terms of the subsystem energy model.

[0097] Associated with the q-shaft subsystem of thermal power units: fan q-shaft current command (i sqref Changes in the reactive power regulation capability of the wind turbine affect the voltage at the grid connection point, and this process is achieved through alternating current i. ar It interacts with the filter capacitor to form a q-axis subsystem;

[0098] Related to the phase-locked loop (PLL) subsystem: Changes in the dq-axis current of the wind turbine cause changes in the grid connection point voltage, which in turn affects the PLL tracking phase change Δθ. pll This causes a disturbance in the phase-locked loop subsystem;

[0099] Related to the virtual inertia control subsystem: The switching process of the wind turbine output power command will trigger ΔP in the virtual inertia control module. eref Dynamic adjustment of link state variables to change their response to frequency fluctuations;

[0100] During the low voltage ride-through (LVRT) phase, to ensure the safe operation of the doubly-fed induction generator (DFIG) wind turbine and to meet grid connection requirements during sudden voltage drops in the grid, its control strategy will dynamically switch, and the control structure of the DFIG wind turbine will change. During this process, the d-axis and q-axis current command values ​​output by the DFIG wind turbine are reconstructed and calculated.

[0101]

[0102] In the formula, K is the reactive current support coefficient; U N Rated voltage at the grid connection point; I N i is the stator rated current of the doubly fed wind turbine; sdref i is the commanded value of the stator d-axis current of the doubly fed wind turbine; sqref This refers to the commanded value of the stator q-axis current of the doubly-fed wind turbine; U s This is the grid connection voltage for the doubly fed wind turbine.

[0103] Due to the low voltage ride-through operation mode, the power control outer loop switches to current inner loop control. Therefore, for items containing active power outer loop increments, the switch will be made to items containing inner loop current command values. The switched items are:

[0104]

[0105] The expressions for the active outer loop and the first-order lag link before control switching are as follows:

[0106]

[0107] Where: K pDFIG K is the PI proportionality coefficient; iDFIG For PI integral coefficients; The change in active power command is corrected; ΔP e For active power error; Δi sdref This represents the change in the d-axis current command.

[0108] From the above formula, combined with the grid voltage drop to 0.9U N Boundary conditions can be used to obtain the change in the dq-axis current command value of the fan output after the control switch:

[0109]

[0110] From the equation, the switching term energy after control switching can be obtained as:

[0111]

[0112] (2) DC side control switching and inverter side control switching

[0113] After an N-2 fault occurs in a grid-connected heterogeneous power supply connected to a DC system, the control switching of the DC rectifier side and the inverter side further includes: after an N-2 fault occurs in a grid-connected heterogeneous power supply connected to a DC system, the rectifier side switches from constant current control to minimum firing angle control, and the inverter side switches from constant turn-off angle control to constant current control.

[0114] Following the N-2 fault, the switching of the DC-side control strategy alters the control structures of both the rectifier and inverter sides of the HVDC transmission system. The rectifier side switches from constant current control to minimum firing angle control, while the inverter side switches from constant turn-off angle control to constant current control. Specifically, the inverter-side current command value I... dIref With rectifier side current command value I dRref satisfy:

[0115] I dIref =I dRref -I M

[0116] In the formula I M This represents the current margin, typically taken as 0.1 pu, or 10% of the rated DC current. Since the value is very small, we can let I be... dIref =I dRref This facilitates subsequent calculations.

[0117] When the DC system is running, the constant current controller outputs a leading firing angle β. CC The fixed turn-off angle controller outputs a leading trigger angle β. CEA The maximum value comparison module filters out the maximum value of the lead trigger angle and outputs it, that is, when β CC >β CEA At this time, the control strategy will switch, and the inverter side will switch from constant turn-off angle control to constant current control. The following formula is β CEA β CC and β inv The relationship between the three:

[0118]

[0119] The mathematical model for when the inverter side switches to constant current control mode is:

[0120]

[0121] The mathematical model for the rectifier side switching to minimum firing angle control mode is as follows:

[0122]

[0123] Furthermore, the dynamic energy model of each subsystem includes:

[0124] refer to Figure 3The dynamic energy model of this subsystem consists of three parts: stored energy, dissipated energy, and interactive energy.

[0125] The above energy model expression can be used to characterize the energy state characteristics of each subsystem and establish a correspondence with the aforementioned subsystems, as explained below:

[0126] The inertial quantum system of a thermal power unit mainly involves the storage of electromagnetic kinetic energy. Its energy changes are reflected in the momentum term and frequency change term, which can be corresponding to ΔIs in the above formula. 2 item;

[0127] Rectifier / inverter subsystem: including equivalent inductance L k With capacitor C k In a power electronic converter system, voltage and current disturbances directly affect the accumulation of electromagnetic energy, corresponding to stored energy terms and interactive energy terms.

[0128] The energy disturbance of the d / q shaft subsystem of the thermal power unit is mainly generated through current changes, which affects the inductive energy storage and energy coupling behavior of the system, corresponding to the interaction term ΔU·ΔI in the expression;

[0129] Phase-locked loop and virtual inertia control subsystem: Its dynamic adjustment will cause frequency disturbances and changes in control signal feedback, which can be addressed by ∫ΔI in the model. 2 The dissipated energy term dt describes the intensity of its effect;

[0130]

[0131] Where, ΔV s ΔV d ΔV t These represent the changes in the subsystem's stored energy, dissipated energy, and interactive energy, respectively; K a K b All coefficients are greater than 0; R k L k C k These represent the equivalent resistance, equivalent inductance, and equivalent capacitance in the subsystem, respectively; ΔU and ΔI represent the instantaneous changes in the output voltage and current at the subsystem ports, respectively.

[0132] Furthermore, the calculation of the interaction energy change between each subsystem using the interaction energy change includes:

[0133] Furthermore, this derivative yields the rate of change of interaction energy between the subsystems:

[0134] The derivative of the interaction energy change of each subsystem with respect to time. Defined as the rate of change of interaction energy, as follows:

[0135]

[0136] The sign and magnitude of the rate of change of interactive energy are used as criteria for identifying oscillation sources.

[0137] Furthermore, the active power commands for adjusting each subsystem based on energy flow include:

[0138] The total cumulative energy of the DC transmission system after considering energy storage integration can be expressed as:

[0139]

[0140] Whether the DC sending-end system can resume stable operation after an N-2 fault is characterized by the total stored energy required by the active power command value of the doubly-fed induction generator (DFIG). DC current command value ΔI dRref and the active power command value ΔP for energy storage ESS_ref The three work together in a coordinated manner.

[0141] Therefore, in order to reduce the impact of positive interaction energy on the transient characteristics of the system, it should be made To be as small as possible, then its effect on ΔI dRref and ΔP ESS_ref The partial differential expressions are as follows:

[0142]

[0143] In the formula: ΔI represents the change in the active power command value of the doubly-fed induction generator (DFIG). eref This represents the change in the commanded value of the DC rectifier side current. The change in the active power command value of the energy storage system; s r K represents the slip ratio. i_DFIG K p_DFIG For the integral and proportional coefficients of the PI controller in the doubly-fed wind turbine subsystem; ΔU s ΔI represents the change in voltage at the grid connection point of the doubly-fed induction generator (DFIG). sd ω represents the change in the d-axis current of the doubly-fed induction generator stator. n Δω is the system synchronization angular frequency. sys α is the change in system frequency. r0 T is the steady-state firing angle on the rectifier side. DFIG The time constant of the active power control loop for the doubly-fed wind turbine;

[0144] for Its monotonicity cannot be directly determined; it is necessary to further calculate its second-order differential.

[0145]

[0146] The active power command value and the output electromagnetic power of a doubly-fed induction generator (DFIG) are related as follows:

[0147]

[0148] We can obtain:

[0149]

[0150] As can be seen from (65), after the N-2 fault... Δi sd <0, ΔU s <0, therefore There may be a minimum value, and the minimum value exists under certain conditions, but whether it can be obtained depends on whether it is within the adjustable boundary of the instruction value.

[0151]

[0152] The above equation is a first-order differential equation with respect to variables. Ignoring higher-order terms, its solution is:

[0153]

[0154] The aforementioned dominant energy identification method based on the positive and negative values ​​of the rate of change of interactive energy (which can be regarded as the engineering criterion form of Lyapunov's first method) is used to qualitatively identify unfavorable energy flow paths. Lyapunov's second method further quantitatively determines the system's stability boundary conditions by constructing a total energy function and setting its derivative to negative (dV / dt<0), and derives specific control quantities (such as P). eref The adjustment range of ). Together, they constitute the "identification + constraint" dual-support logic in the stability criterion system of this invention.

[0155] refer to Figure 4 The rate of change of energy can be determined by Lyapunov's second method. The system is in a critical stable state, from which the stable operating boundary of the system can be determined, and the adjustment range of the active power command value of the doubly-fed wind turbine can be obtained:

[0156]

[0157] By comparing the calculated minimum value with the adjustment boundary of the active power command value of the doubly-fed wind turbine, we can obtain:

[0158]

[0159] It can be seen that the minimum value exists within the adjustment range of the active power command value of the doubly-fed induction generator (DFIG). Therefore, the active power command value of the DFIG is:

[0160]

[0161] For the partial derivative of the interaction energy with respect to the DC current command value, i.e. Δα after N-2 fault r >0, then It is a monotonically decreasing function, and the adjustment amount of the DC current command value is taken at the adjustment boundary. Therefore, the adjustment range of the DC current command value can be obtained as follows:

[0162]

[0163] Therefore, the DC current command value is:

[0164]

[0165] Similarly, for the interactive energy change rate of the reactive energy storage active power command value regulation, the frequency decreases after the N-2 fault, i.e., Δω ESS <0, then Also a monotonically decreasing function, the adjustment amount of the energy storage active power command value is taken at the adjustment boundary, and the adjustment range of the energy storage active power command value can be obtained as follows:

[0166] -P ESS_ref0 ≤ΔP ESS_ref ≤cosθ ESS0 ΔI ESS

[0167] Energy storage active power command value:

[0168] ΔP ESS_ref =cosθ ESS0 ΔI ESS

[0169] A control structure can be established that coordinates and complements the active power command of the doubly-fed wind turbine, the DC current command, and the active power command of the energy storage. By collecting the state variables of the DC sending end system in real time, the real-time active power command value of the doubly-fed wind turbine, the constant current command value of the rectifier side, and the active power command value of the energy storage can be obtained. This compensates for positive interaction energy, ensures that the total energy of the system is always negative, and thus ensures stability.

[0170] Assume the structure of a multi-source DC transmission system is as follows: Figure 3As shown, the system includes doubly-fed induction generator (DFIG) wind turbines, a DC transmission system (constant current controlled high-voltage direct current transmission), and energy storage devices. The simulation was performed using the MATLAB / Simulink platform, with two scenarios: a DC transmission system with a rated transmission capacity of 8000MW, and an AC tie-line N-2 fault occurring at 5 seconds. Scenario 1 involves disconnecting a 4000MW large-capacity grid (50% capacity), in which case wind power accounts for 30% and energy storage accounts for 10% of the system; Scenario 2 involves disconnecting a 1600MW small-capacity grid (20% capacity), in which case wind power accounts for 30% and energy storage accounts for 10%. Taking Scenario 1 as an example: before the fault, the output power of the thermal power units, DFIG wind turbines, and energy storage is distributed according to their respective inertia, with proportions of 60%, 30%, and 10%, respectively. Figure 9 The dynamic changes in the frequency of the DC sending system are described in Scenario 2 (cutting off 20% of the small-capacity power grid). Figure 10 The curves describing the variation of DC system current under the same scenario are presented. Figure 11 The output power variations of thermal power units, doubly fed wind turbines, and energy storage devices are described. Figure 12 and Figure 13 The total interactive energy and total energy change correspond to Scenario 1 (cutting off 50% of the large-capacity power grid). Figure 14 and Figure 15 The total interactive energy and total energy change correspond to Scenario 2 (cutting off 20% of the large-capacity power grid).

[0171] Example 1:

[0172] Step 1: At the moment of the fault, the system detects a sharp drop in DC current and a frequency shift. The controller first performs energy flow analysis to accurately locate unfavorable factors such as the interaction energy flow gain between the inertial quantum system and the DC-side constant current control subsystem. Step 2: Based on the goal of minimizing energy accumulation, the controller synchronously adjusts the commands of each subsystem: reducing the active power command value of the doubly-fed induction generator (DFIG), increasing the DC-side current command value, and increasing the active power output of the energy storage system. This allows the active load to be shared between wind power and energy storage, and reshapes the energy flow path. Step 3: An orthogonal interactive energy compensation loop added to the control structure ensures that the system's interactive energy is always negative. Through the synergistic complementarity between the DFIG, DC current, and energy storage commands, unfavorable energy coupling is effectively suppressed, oscillations are suppressed, and frequency recovery is accelerated. Step 4: Simulation results are as follows... Figures 5-7 As shown: After adopting the collaborative control of this invention, the active power output of the doubly-fed wind turbine quickly stabilizes at a new equilibrium point, with a significantly smaller fluctuation amplitude than that under decentralized regulation; the DC-side current waveform is smoother; the system frequency recovery speed is faster and the oscillation amplitude is reduced (see [references]). Figure 6 and Figure 7 Step 5: The active power output distribution of each power source in Scenario 1 is as follows: Figure 8As shown, the total system output remained unchanged at 8000MW before and after the fault, with the output of thermal power, doubly fed wind turbines and energy storage being approximately 60%, 30% and 10% respectively. This indicates that the control method of the present invention accurately achieved the coordinated allocation of active power output of each subsystem.

[0173] As can be seen from the above embodiments, the cooperative control method of the present invention can accurately identify and compensate for orthogonal interactive energy in the DC sending-end system, realize rapid recovery of active power output and frequency after a fault, and significantly improve the system's recovery capability and frequency support performance. The above embodiments are merely preferred embodiments of the present invention. Those skilled in the art can make several equivalent modifications and improvements without departing from the principle of the present invention, all of which should be covered within the protection scope of the present invention.

[0174] refer to Figure 16 Another specific embodiment of the present invention discloses a stable control method for a grid-type heterogeneous power supply connected to a DC system, comprising: an interaction path identification module M1, used to analyze the energy flow paths between subsystems in the system to identify key control links that cause system instability and their positive interaction energy, wherein the positive interaction energy is the interaction energy item with the greatest impact on system stability among the interaction energy between subsystem modules; an instruction coordination adjustment module M2, used to coordinate and adjust the active power command of the doubly-fed wind turbine, the DC system current command, and the energy storage active power command in real time based on the principle of minimizing the total stored energy of the system, to optimize the energy flow path and reduce energy accumulation; an interaction energy compensation module M3, used to compensate for the positive interaction energy between subsystems by keeping the total interaction energy of the system negative, thereby suppressing adverse energy interactions; and a state feedback adjustment module M4, used to dynamically adjust the active power command of each subsystem based on the state feedback signal and in combination with the control switching logic, wherein the dynamic energy model of each subsystem includes stored energy, dissipated energy, and interaction energy, to improve the system's recovery capability and frequency support strength after a fault.

[0175] Compared with existing technologies, this invention achieves at least the following beneficial effects: By conducting in-depth analysis of the energy flow paths among multiple subsystems and implementing real-time cooperative control, the negative impact of orthogonal interactive energy on the system can be significantly suppressed, and timely compensation for the active power deficit of the DC sending-end system after a fault can be achieved. Simulation results show that after adopting the method of this invention, the system frequency fluctuation amplitude is reduced, the recovery speed is accelerated, and the overall system stability is significantly improved. Simultaneously, the cooperative control strategy can accurately match the active power output allocation of each subsystem (e.g., ...). Figure 7 The thermal power units, doubly fed wind turbines, and energy storage units account for 60%, 30%, and 10% respectively, fully leveraging the comprehensive effects of various energy resources.

[0176] Those skilled in the art will understand that all or part of the processes of the methods described in the above embodiments can be implemented by a computer program instructing related hardware, and the program can be stored in a computer-readable storage medium. The computer-readable storage medium may be a disk, optical disk, read-only memory, or random access memory, etc.

[0177] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for stable control of grid-connected heterogeneous power sources in a DC system, characterized in that, include: The energy flow paths between the subsystems in the system are analyzed to identify the key control links that cause system instability and their positive interaction energy. The positive interaction energy is the interaction energy item with the greatest impact on system stability among the interaction energy between the modules of each subsystem. Based on the principle of minimizing the total stored energy of the system, the active power command of the doubly fed wind turbine, the current command of the DC system and the active power command of the energy storage are coordinated and adjusted in real time. The positive interaction energy between each subsystem is compensated based on the total system interaction energy remaining negative. Based on the status feedback signal and combined with the control switching logic, the active power command of each subsystem is dynamically adjusted. The dynamic energy model of each subsystem includes stored energy, dissipated energy, and interactive energy.

2. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 1, characterized in that, Analyzing the energy flow paths between subsystems within the system to identify key control elements that trigger system instability and their positive interaction energies further includes: A multi-subsystem model is constructed, wherein the multi-subsystem includes a thermal power unit inertial quantum system, a thermal power unit d-axis subsystem, a thermal power unit q-axis subsystem, a virtual inertial control subsystem, a phase-locked loop subsystem, a doubly-fed induction generator d-axis system, a doubly-fed induction generator q-axis system, a rectifier side subsystem, an inverter side subsystem, and a DC line subsystem; The energy flow paths between the subsystems in the system are analyzed to calculate the interaction energy between multiple subsystems; Calculate the rate of change of interaction energy based on the interaction energy between the multiple subsystems; Based on the rate of change of the interaction energy, the key control links that cause system instability and the corresponding positive interaction energy are identified.

3. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 2, characterized in that, Based on the rate of change of the interactive energy, identifying the key control elements that trigger system instability and their positive interactive energies further includes: When the rate of change of the current interaction energy between different subsystems is negative, negative interaction energy is beneficial to the stable operation of the system. The smaller the rate of change of the negative interaction energy, the higher the stability level. When the rate of change of the current interaction energy between different subsystems is zero, the corresponding interaction energy is independent of the system stability level; When the rate of change of the current interaction energy between different subsystems is positive, the positive interaction energy is not conducive to the stable operation of the system. The larger the rate of change of the positive interaction energy, the more unfavorable it is for the system to maintain stability. The oscillation source that induces system oscillation is determined based on the maximum rate of change of the positive interaction energy.

4. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 2, characterized in that, The interaction energy between the multiple subsystems includes: The interaction energy between the inertial quantum system and the constant current control subsystem; The interaction energy between the inertial quantum system and the doubly fed wind turbine q-axis subsystem; The interaction energy between the d-axis subsystem and the q-axis subsystem of a thermal power unit; The interaction energy between the phase-locked loop subsystem and the inertial quantum system; The interaction energy between the d-axis subsystem and the q-axis subsystem of the doubly-fed fan; The interaction energy between the d-axis subsystem and the inertial quantum system of a doubly-fed wind turbine; The interaction energy between the d-shaft subsystem and the phase-locked loop subsystem of the doubly-fed wind turbine; The interaction energy between the constant current control subsystem and the DC line subsystem; The interaction energy between the constant current control subsystem and the doubly fed fan q-axis subsystem; The interaction energy between the constant off-angle control subsystem and the DC line subsystem.

5. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 1, characterized in that, Based on the principle of minimizing the total stored energy of the system, the real-time coordinated adjustment of the active power command of the doubly-fed wind turbine, the DC system current command, and the energy storage active power command further includes: After the energy storage subsystem is connected, the total stored energy of the grid-type heterogeneous power supply connected to the DC system is calculated based on the cumulative energy of the thermal power unit subsystem, the doubly fed wind turbine subsystem, the rectifier side subsystem and the energy storage subsystem after the N-2 fault. The total stored energy of the system is minimized by coordinating and adjusting the active power command of the doubly fed wind turbine, the current command of the DC system, and the active power command of the energy storage in real time.

6. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 5, characterized in that, The compensation for the positive interaction energy between subsystems, based on maintaining a negative total system interaction energy, further includes: Based on the dynamic energy models of each subsystem, partial derivatives are calculated with respect to the active power command of the doubly-fed induction generator (DFIG), the current command of the DC system, and the active power command of the energy storage system. Gradient relationships between dynamic energy and these commands are then constructed. The active power command of the doubly fed wind turbine, the current command of the DC system, and the active power command of the energy storage are adjusted in reverse according to the gradient relationship, so that the positive interaction energy is gradually reduced so that the total interaction energy of the system remains negative.

7. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 1, characterized in that, The control switching logic further includes: after an N-2 fault occurs in the grid-connected heterogeneous power supply DC system, performing low voltage ride-through control switching, DC rectifier side control switching, and inverter side control switching for the doubly fed wind turbine.

8. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 7, characterized in that, Following an N-2 fault in a grid-connected heterogeneous power supply DC system, the low-voltage ride-through control switching of the doubly-fed wind turbine further includes: When the grid voltage drops sharply and the system frequency falls rapidly, the change in the d-axis current command of the wind turbine directly affects the active power output of the inertial quantum system, thereby adjusting the system frequency disturbance power term. The adjustment of the fan d-axis current command affects the rotor d-axis current, which in turn changes the d-axis electromotive force and the related transient / subtransient energy distribution; Changes in the q-axis current command of the fan affect the fan's reactive power regulation capability. Changes in the dq-axis current of the wind turbine lead to changes in the grid connection point voltage, which in turn affects the phase change Δθ of the phase-locked loop (PLL). pll This causes disturbances in the phase-locked loop subsystem; and The switching process of the wind turbine output power command will trigger ΔP in the virtual inertia control module. eref Dynamic adjustment of link state variables alters their response to frequency fluctuations.

9. The method for stable control of grid-connected heterogeneous power sources in a DC system according to claim 7, characterized in that, After an N-2 fault occurs in a grid-connected heterogeneous power supply DC system, the control switching of the DC rectifier side and the inverter side further includes: After an N-2 fault occurs in a grid-connected heterogeneous power supply connected to a DC system, the rectifier side switches from constant current control to minimum firing angle control, and the inverter side switches from constant turn-off angle control to constant current control.

10. A grid-type heterogeneous power supply connection stability control system for DC systems, characterized in that, include: The interaction path identification module is used to analyze the energy flow paths between subsystems in the system to identify the key control links that cause system instability and their positive interaction energy. The positive interaction energy is the interaction energy item with the greatest impact on system stability among the interaction energy between subsystem modules. The instruction coordination and adjustment module is used to coordinate and adjust the active power instructions of the doubly-fed wind turbine, the DC system current instructions, and the energy storage active power instructions in real time based on the principle of minimizing the total stored energy of the system. An interactive energy compensation module is used to compensate for the positive interactive energy between each subsystem based on keeping the total interactive energy of the system negative. The status feedback adjustment module is used to dynamically adjust the active power command of each subsystem based on the status feedback signal and the control switching logic. The dynamic energy model of each subsystem includes stored energy, dissipated energy, and interactive energy.

Images