A multi-reactive resource coordination optimization method for new energy large base

Abstract

The application discloses a kind of multi-reactive resource coordination optimization methods for new energy large base, it is related to new energy grid-connected control power supply technical field, including: the unified operation model including alternating current network, converter station and multi-reactive resource is constructed;Reactance resource is divided into different speed levels, and dynamic reactive power available capacity envelope is established;Based on node voltage and short-circuit capacity, voltage risk assessment model is constructed to obtain risk indicators in each stage;System operation is divided into three stages before fault prevention, transient suppression during fault and post-fault recovery reconstruction, respectively set differentiated optimization target, make fast type resource be used for transient support in priority, slow type resource is used for steady-state recovery and standby reconstruction;The partition decoupling optimization based on reactive voltage coupling strength and boundary consistency correction output control instruction are used.The application realizes the whole process voltage safety unified coordination control, reduces the difficulty of large-scale system centralized solution, improves the voltage stability of dc transmission system.

Description

Technical Field

[0001] This invention belongs to the field of power supply technology for grid-connected control of new energy sources. Specifically, it relates to a multi-reactive resource coordination and optimization method for large-scale new energy bases transmitted via ultra-high voltage direct current (UHVDC) transmission systems. It is particularly applicable to scenarios where large-scale wind power and photovoltaic power are transmitted via combined AC systems and UHVDC transmission channels. This method addresses the complex voltage stability problems caused by transient overvoltage, transient undervoltage, and post-fault recovery voltage deviation in the weak system at the sending end due to DC blocking, commutation failure, or AC short-circuit faults. It achieves multi-timescale reactive power coordination, unified closed-loop control of voltage safety throughout the entire process, and stable support throughout the fault process. Background Technology

[0002] Desert, Gobi, and arid regions are rich in wind and solar energy resources, making them important areas for the construction of large-scale new energy bases. These bases are typically located far from load centers, requiring long-distance power transmission via high-voltage AC aggregation systems and ultra-high-voltage direct current (UHVDC) transmission systems. Compared to conventional centralized power grid systems, large-scale new energy bases are characterized by large power generation scale, wide geographical coverage, high access voltage levels, weak load support at the sending end, insufficient short-circuit capacity of the AC system, and a high proportion of power electronic equipment. The large number of wind turbines and photovoltaic inverters connected to the grid via converters reduces the proportion of synchronous power sources in the system, decreasing inertia support, short-circuit current support, and natural reactive power regulation capabilities. Voltage stability issues have evolved from traditional steady-state voltage exceeding limits to a complex problem involving transient overvoltage, transient undervoltage, post-fault recovery voltage deviation, and insufficient dynamic reactive power reserve.

[0003] Unlike renewable energy clusters that transmit power via AC channels, large renewable energy bases transmit power via UHVDC. During this process, the DC converter stations consume significant reactive power and are equipped with reactive power compensation devices such as AC filters and parallel capacitors. When disturbances occur in the UHVDC transmission system, such as DC blocking, commutation failure, AC fault clearing, or large-capacity renewable energy disconnection, the active and reactive power balance within the sending-end renewable energy base changes drastically within a short period. After DC blocking, the reactive power consumption of the converter disappears quickly, while reactive power compensation components such as AC filters and parallel capacitors may remain operational due to control and circuit breaker operation delays, resulting in short-term surplus reactive power and pushing up the voltage of the converter station and renewable energy collection bus. When an AC fault causes a voltage drop, the renewable energy converter needs to provide low-voltage ride-through reactive power support under current-constrained conditions. After the fault is cleared, stability control, power transfer, and slow reactive power equipment operation can cause a lag in voltage recovery at some nodes. Due to significant differences in response speed, control continuity, overload capacity, and regulation duration among wind power, photovoltaic, static var generators, synchronous condensers, parallel capacitor banks, on-load tap-changing transformers, and converter station filters, reactive power optimization of a single device or a single stage is insufficient to meet the voltage safety control requirements of the entire process in a large-scale new energy base. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-reactive-resource coordination and optimization method for large-scale new energy bases via ultra-high voltage direct current (UHVDC) transmission systems. This method constructs a multi-reactive-resource time-series coordination and partitioned decoupling optimization system with full-process voltage safety as the main focus. This addresses the complex voltage stability problems encountered by existing large-scale new energy bases during DC transmission disturbances, such as transient overvoltage, transient undervoltage, and recovery voltage deviation, due to reduced system synchronous power supply ratio and weak anti-disturbance capability. It also addresses the technical problem of the inability to reconfigure dynamic reactive power reserves after fault clearance due to long-term extreme operation of fast resources and uncoordinated operation of slow resources. Furthermore, it solves the technical problem that existing centralized reactive power optimization methods suffer from excessive computational complexity and difficulty in achieving rapid online coordination solutions when dealing with large-scale new energy bases.

[0005] To solve the above problems, the technical solution adopted by the present invention is as follows:

[0006] A method for coordinated optimization of multiple reactive power resources for large-scale new energy bases includes the following steps:

[0007] S1. Obtain the grid topology, operation mode, DC power transmission, reactive power compensation configuration of converter stations, grid connection point information of wind farms and photovoltaic power stations of the new energy base, as well as the capacity, response time and control mode parameters of reactive power resources, and establish a unified operation model that can reflect the surplus reactive power characteristics of converter stations and the insufficient short-circuit capacity of weak systems at the sending end under DC power transmission disturbances, including AC network, DC converter station, new energy base and multiple reactive power resources.

[0008] S2. The multiple reactive resources are divided into millisecond-level fast resources, hundred-millisecond-level dynamic resources, second-level discrete resources, and minute-level steady-state adjustment resources according to their response time and control characteristics. The dynamic reactive available capacity envelope of wind power and photovoltaic grid-connected converters, static var generators, synchronous condensers, parallel capacitor banks, on-load tap-changing transformers, and converter station filters is established. The dynamic reactive available capacity envelope is used to characterize the real adjustable boundary of each resource before, during, and after the fault.

[0009] S3. Based on node voltage, short-circuit capacity, DC power disturbance and the dynamic reactive available capacity envelope, construct a voltage risk assessment model that simultaneously covers transient overvoltage risk, transient undervoltage risk and recovery voltage deviation risk, and obtain voltage risk indicators for each key node before, during and after the fault.

[0010] S4. The system operation process is divided into the pre-fault prevention and control stage, the transient suppression stage during the fault, and the post-fault recovery and reconstruction stage, based on the fault process as the trigger condition. Differentiated optimization objectives and constraints are established for each stage. The three stages are organically connected through dynamic reactive power reserve indicators and full-process voltage risk indicators, so that the control results of the previous stage reserve adjustment margin for the next stage.

[0011] S5. In the pre-fault prevention and control phase, with the goals of reducing network losses, reducing voltage deviation, and maintaining dynamic reactive power reserve, the preventive operating points of each reactive power resource are determined. In the transient suppression phase during the fault, with the goals of suppressing transient overvoltage peaks, supporting transient undervoltage, and preventing converter current from exceeding limits, the dynamic control commands for the millisecond-level fast resources and the hundred-millisecond-level dynamic resources are determined. In the post-fault recovery and reconfiguration phase, with the goals of steady-state voltage recovery, coordinated action of the second-level discrete resources and the minute-level steady-state regulation resources, and dynamic reactive power reserve reconfiguration, the recovery control strategy for reactive power resources is determined.

[0012] S6. Divide the new energy base into zones according to the reactive voltage coupling strength, establish a zone optimization sub-model for each zone, and achieve inter-zone coordination through boundary bus voltage consistency correction.

[0013] S7. Output control commands for each reactive resource based on the coordination results. The control commands include reactive current commands for renewable energy converters, reactive power commands for static var generators, excitation adjustment commands for synchronous condensers, switching commands for parallel capacitor banks, and tap position adjustment commands for on-load tap-changing transformers.

[0014] Further, in step S2, the dynamic reactive power available capacity envelope is represented as:

[0015]

[0016] in, as reactive resources At any moment Dynamic available reactive power capacity Available state functions to reflect equipment interlocking, current limiting, or operation delay. This is the maximum reactive power capacity of the equipment. For the apparent power capacity of the device, For the equipment at all times active power, For initial no-work output, This is the reactive ramp rate.

[0017] Furthermore, in step S3, the voltage risk assessment model provides a unified evaluation basis for optimization in the pre-fault prevention and control stage, the transient suppression stage during the fault, and the post-fault recovery and reconfiguration stage, thereby achieving closed-loop management of voltage risk throughout the entire process; the comprehensive voltage risk index of the voltage risk assessment model is expressed as:

[0018]

[0019] in, For nodes Comprehensive voltage risk index, For nodes in the transient process Maximum voltage, This is the upper limit of the node voltage. For nodes in the transient process The minimum voltage, This is the lower limit of the node voltage. This refers to the node voltage during the post-fault recovery phase. The node reference voltage, This represents the function that takes the positive part. , , These are the weighting coefficients.

[0020] Furthermore, in step S5, the transient suppression stage during the fault period adopts a transient voltage rise prediction model that considers the coupling relationship between the surplus reactive power of the converter station and the short-circuit capacity of the AC system after DC blocking, expressed as:

[0021]

[0022] in, For converter station bus The predicted value of transient pressure rise, The correction factor is determined by the system short-circuit ratio and voltage level. This refers to the surplus reactive power on the converter station side after a DC power outage. For converter station bus Short-circuit capacity at the location, The set of reactive resources participating in transient control, as reactive resources Converter station bus Voltage sensitivity, as reactive resources The reactive power regulation.

[0023] Furthermore, in step S5, the new energy converter adopts a virtual synchronous control method with amplitude-phase coordinated compensation, and its internal voltage amplitude reference and internal voltage phase reference are expressed as follows:

[0024]

[0025]

[0026] in, For new energy converters Internal voltage amplitude reference value, This represents the real-time voltage amplitude at the grid connection point. This represents the steady-state voltage amplitude before the fault. This is the amplitude compensation coefficient. This is the internal voltage phase reference value. For the real-time voltage phase at the grid connection point, The phase jump variable before and after the fault occurs or is cleared. This is the phase compensation coefficient.

[0027] Furthermore, in step S5, during the low-voltage ride-through process, the reactive current command meter of the renewable energy converter and the reactive current deviation caused by the dynamics of the phase-locked loop are expressed as follows:

[0028]

[0029] in, For new energy converters reactive current command, This refers to the reactive current prior to the fault. For low voltage ride-through reactive power support factor, The low voltage ride-through trigger voltage threshold, This represents the actual voltage amplitude at the grid connection point. Rated reactive current, This refers to the reactive current deviation caused by the dynamics of the phase-locked loop.

[0030] Furthermore, in step S6, the new energy base is partitioned based on the reactive power voltage coupling strength, and the nodes... With nodes The coupling weights between them are expressed as:

[0031]

[0032] in, For nodes With nodes The coupling weights between them For nodes Voltage to node The sensitivity of reactive power injection For nodes Voltage to node The sensitivity of reactive power injection For nodes With nodes Electrical distance between them , , These are the weighting coefficients.

[0033] Furthermore, in step S6, the partition boundary bus adopts a consistency correction mechanism. In the next iteration, the boundary bus voltage constraint is updated to:

[0034]

[0035] in, For the first Partitioning in the next iteration For boundary busbar Calculate the voltage. For all adjacent partitions, the boundary bus Calculate the weighted average value of the voltage. For the first The correction step size of the next iteration is such that when the voltage deviation of all boundary buses is less than the preset convergence threshold, the overall network coordinated optimization result is output.

[0036] Furthermore, in step S5, the objective function of the optimization model in the pre-fault prevention and control stage is expressed as:

[0037]

[0038] in, To prevent the control objective function, For active network loss, For the set of monitored busbars, For nodes voltage, For nodes The reference voltage, For reactive resource collection, as reactive resources The current unproductive effort, as reactive resources The upper limit of reactive power, as reactive resources The lower limit of reactive power, , , For the target weight, and Resources Adjust the importance coefficient of the reserve to be increased or decreased.

[0039] Furthermore, in step S5, the optimization model for the transient suppression stage during the fault period adopts a discrete time window, and its objective function is expressed as:

[0040]

[0041] in, Let the transient suppression objective function be... For the set of critical voltage nodes, This represents the number of discrete sampling points within the time window. Sampling time, For nodes At any moment voltage, This is the upper limit of voltage. This is the lower limit of voltage. This represents the function that takes the positive part. To facilitate rapid resource aggregation, For the converter or static var generator at time The output current, To limit the allowable current, , , These are the weighting coefficients.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] (1) This invention breaks the limitations of single equipment or single stage optimization. It maps reactive resources to three different control stages: pre-fault prevention, transient suppression and post-fault recovery according to the response speed. This enables fast resources to solve instantaneous voltage risks, dynamic resources to provide transient support, and discrete and slow resources to provide recovery and backup reconfiguration. It realizes the unified closed-loop coordination of the entire process of transient overvoltage suppression, low voltage ride-through support, voltage recovery and dynamic reactive power reserve maintenance, which significantly improves the voltage safety margin and operational stability of the DC transmission system of the new energy base.

[0044] (2) A dynamic available reactive power capacity envelope model is proposed, which can accurately reflect the actual adjustable capacity of the new energy converter under the influence of active power output occupation, current limiting protection and the action delay of different equipment, and provides a quantitative constraint boundary for precise coordinated control at each stage.

[0045] (3) A unified quantitative model for voltage risk applicable to large-scale new energy bases has been established, which can simultaneously characterize transient overvoltage, transient undervoltage and recovery voltage deviation, providing a unified evaluation basis for multi-stage optimization target setting and priority allocation of control resources.

[0046] (4) A transient voltage rise prediction model considering the coupling of the surplus reactive power of the converter station and the AC short-circuit capacity was proposed, revealing the amplification effect of surplus reactive power on voltage rise under weak sending end system, so that the transient overvoltage suppression after DC blocking has a clear quantitative basis.

[0047] (5) A virtual synchronous control method for amplitude-phase coordinated compensation of new energy converter is proposed, which effectively avoids the serious output current impact caused by sudden changes in voltage amplitude and phase due to grid faults, and achieves the optimal trade-off between current impact suppression and maximum reactive power support capability.

[0048] (6) A partition decoupling optimization and boundary consistency correction mechanism based on reactive voltage coupling strength is proposed, which transforms the centralized optimization problem of the whole network into a parallel optimization problem in a highly coupled partition. This significantly reduces the difficulty of centralized optimization solution caused by the massive number of nodes and discrete variables in large-scale new energy bases, and improves the feasibility and solution speed of online application.

[0049] (7) By clarifying the specific optimization objective functions of the three stages, the network loss and backup reserves during normal operation are taken into account, and the voltage over-limit is contained by millisecond-level resources when a fault occurs. This ensures that the control results of the previous stage will not cause the subsequent stage to lack adjustment margin, and realizes the theoretical unity and the operability of the control strategy in engineering implementation.

[0050] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, embodiments of the present invention are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0051] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of the multi-reactive-resource coordination and optimization method for large-scale new energy bases described in the embodiment. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.

[0054] like Figure 1 As shown, this embodiment of the invention provides a method for coordinating and optimizing multiple reactive power resources in a system for transmitting large-scale new energy bases via ultra-high voltage direct current (UHVDC), as detailed below:

[0055] Step S1: Obtain the grid topology, operation mode, DC power transmission, reactive power compensation configuration of converter stations, grid connection point information of wind farms and photovoltaic power stations of the new energy base, as well as the capacity, response time and control mode parameters of various reactive resources, and establish a unified operation model that includes AC network, DC converter station, new energy power station and multiple reactive resources.

[0056] Suppose the system includes Each bus node One branch line for communication A new energy power station and A controllable or semi-controllable reactive resource. Node The voltage phasor is represented as ,in The node voltage amplitude, Let be the node voltage phase angle. The system admittance matrix is ​​denoted as . ,in Here is the conductance matrix. For susceptance matrix, The imaginary unit. Node The AC power flow balance equation is:

[0057]

[0058]

[0059] in, For nodes Injected active power, For nodes Injected reactive power, and These are the nodes in the admittance matrix. With nodes The conductivity and susceptivity of the elements between them The phase angle difference between nodes is used. The steady-state operating point before the fault is obtained through this power flow equation, and voltage sensitivity, reactive power reserve, and voltage risk after DC disturbance are calculated based on this.

[0060] Step S2: For multi-reactive-resource modeling, this invention classifies multi-reactive-resources into four categories according to response time and control characteristics. The first category is millisecond-level fast resources, mainly including wind power converters, photovoltaic inverters, and some station-level SVGs with fast voltage control functions. These are characterized by fast response speed but are significantly limited by current capacity. The second category is hundred-millisecond-level dynamic resources, mainly including synchronous condensers and large-capacity SVGs. These are characterized by strong transient support capabilities and a certain short-term overload capacity. The third category is second-level discrete resources, mainly including parallel capacitor banks and reactor banks. These are characterized by large capacity but discrete operation and switching delays. The fourth category is minute-level steady-state regulating resources, mainly including on-load tap-changing transformers. These are characterized by suitability for long-term voltage distribution adjustment but not suitable for participating in instantaneous fault control. To uniformly describe the actual controllability of the above resources at any given time, this invention constructs a dynamic reactive-reactive-available capacity envelope:

[0061]

[0062] In the formula, Indicates the first A useless resource, Indicates the time since the disturbance occurred. Representing resources At any moment The maximum reactive power capacity that can be controlled. This is a function representing the available state of the equipment. It takes a smaller value or zero when the equipment has not yet started, is locked out, or is under current limiting protection; and takes one when the equipment can participate in control normally. The rated maximum reactive power capacity of the equipment. For the apparent power capacity of the device, To contribute to the equipment This represents the remaining reactive power after the active power has occupied its capacity. For initial no-work output, The reactive power ramp rate is the variable rate of change per unit time. This model allows the same optimization framework to simultaneously characterize the differences in how converter capacity is affected by active power output, how SVG response is affected by time constant, how synchronous condensers are affected by excitation dynamics, and how capacitors and transformers are affected by operating time delay.

[0063] For wind power and photovoltaic grid-connected converters, this invention employs a model combining virtual synchronous control and transient amplitude-phase compensation. The active frequency outer loop of the converter simulates the rotor motion characteristics of a synchronous machine.

[0064]

[0065] in, For converter virtual inertia, Its internal angular frequency, This is a reference value for active power. This refers to the actual output active power. The active damping coefficient is... This is the rated angular frequency. The reactive voltage outer loop uses droop control.

[0066]

[0067] in, This is a reference value for reactive power. This is the initial reactive power setting value. This is the reactive voltage droop factor. The voltage amplitude at the grid connection point. This is the reference value for the grid connection point voltage.

[0068] When a DC blockage or AC fault occurs at a large-scale new energy base, the voltage at the grid connection point of the station may experience not only amplitude jumps but also phase abrupt changes. If the voltage reference value inside the converter is not corrected according to the system state, a large voltage difference will be generated across the filter reactor, which can easily lead to output current surges. Therefore, this invention sets up amplitude compensation control:

[0069]

[0070] And set phase compensation control:

[0071]

[0072] in, This is the reference value for the voltage amplitude inside the converter. For the real-time voltage at the grid connection point, This is the steady-state voltage before the fault. This is the amplitude compensation coefficient. This is an internal phase reference value. For the real-time phase of the grid connection point, This refers to the phase jump variable at the moment the fault occurs or is cleared. This is the phase compensation coefficient.

[0073] This control ensures that the converter's internal potential neither completely locks onto the pre-fault reference value nor completely passively follows the grid connection point voltage during transient processes, but rather forms an optimizable trade-off between current surge suppression and reactive power support capabilities.

[0074] During low-voltage ride-through, the reactive current output of the renewable energy converter is also affected by the dynamics of the phase-locked loop and current limiting. This invention represents the reactive current command as:

[0075]

[0076] in, For converter reactive current command, This refers to the reactive current prior to the fault. For low voltage ride-through reactive power support factor, The low voltage ride-through trigger voltage threshold, Indicates taking the positive part. Rated current, This refers to the reactive current deviation caused by the dynamics of the phase-locked loop (PLL). The PLL deviation can be approximated by the small-signal relationship:

[0077]

[0078] in, For the d-axis current of the converter, This is used to estimate the deviation between the phase of the phase and the actual voltage phase of the phase-locked loop (PLL). If the PLL adopts a second-order structure, its phase tracking transfer function can be expressed as:

[0079]

[0080] In the formula, For the Laplace operator, This is the proportional gain of the phase-locked loop. This is the phase-locked loop integral coefficient. This term is used to correct the deviation between the actual reactive power output of the new energy unit and the ideal command during transient optimization, thereby preventing the control command from exceeding the actual capacity of the converter.

[0081] For a static var generator, let the first... Taiwan SVG output reactive power is Its instruction value The response time constant is Then its dynamic process can be represented by a first-order element:

[0082]

[0083] In discrete-time optimization, if the sampling interval is... , No. The reactive power of the SVG at a given moment can be written as:

[0084]

[0085] in, For the first The actual reactive power output at each sampling time. For the first The reactive power command at each sampling time. This model can be embedded with a transient optimization model, allowing the SVG to prioritize fast voltage regulation tasks.

[0086] For the camera condenser, let the voltage at the camera condenser terminal be... The transient internal potential is The direct-axis transient reactance is Then, under the approximate condition of neglecting active power output, its reactive power output can be expressed as:

[0087]

[0088] in, The reactive power output of the condenser is adjusted. The excitation dynamics of the condenser can be expressed as:

[0089]

[0090] in, The direct-axis transient open-circuit time constant. This is the excitation voltage. It is a direct-axis synchronous reactance. The current is d-axis current. This model demonstrates that a synchronous condenser can naturally provide reactive power during voltage surges by relying on electromagnetic transients, while simultaneously maintaining voltage support through excitation regulation.

[0091] For a parallel capacitor bank, let the first... The voltage of the capacitor bank connected to the bus is Single group susceptance is The number of input groups is The maximum number of groups is Then its reactive power output is:

[0092]

[0093] in, This is the reactive power output of the capacitor bank. Because... These are integer variables; such resources are primarily used for pre-fault prevention and post-fault recovery, and are not used as continuous control resources during a fault. For an on-load tap-changing transformer, let the primary voltage be... The secondary voltage is , change ratio ,but:

[0094]

[0095] in, This refers to the turns ratio corresponding to the current tap position of the on-load tap-changing transformer. to This is a set of selectable turns ratios. This model is used to slowly correct the voltage distribution during the steady-state recovery phase after a fault.

[0096] Step S3: After completing resource modeling, construct a voltage risk assessment model for the new energy base based on node voltage, short-circuit capacity, DC power disturbance, and the dynamic reactive power availability envelope. For key nodes... The comprehensive risk indicators are:

[0097]

[0098] The first item corresponds to transient overvoltage risk, the second item corresponds to transient undervoltage risk, and the third item corresponds to post-fault recovery voltage deviation risk. The maximum node voltage within the transient time window. This is the upper limit of voltage. The minimum node voltage within the transient time window. This is the lower limit of voltage. To restore the stage voltage, The target reference voltage, , , This risk model is used to reflect the control priorities of different risks. It is used to select key control nodes, determine the priority of reactive resources, and serve as a unified evaluation basis for the three-stage optimization.

[0099] Steps S4 and S5 divide the system operation process into a pre-fault prevention and control stage, a fault-period transient suppression stage, and a post-fault recovery and reconfiguration stage, and establish differentiated optimization objectives and constraints for each stage. In the pre-fault prevention and control stage, with the objectives of reducing network losses, decreasing voltage deviation, and maintaining dynamic reactive power reserve, the preventative operating points of each reactive power resource are determined. Specifically, while the system is still operating normally, the operating points of reactive power resources are adjusted to ensure low network losses, reasonable voltage distribution, and sufficient dynamic reactive power reserve. Let... For branch road collection, branch road The resistance is The trend has contributed to Unreactive current The voltage at the first end is The active power loss target can then be expressed as:

[0100]

[0101] set up For reactive resource collection, resources The current reactive power output is It can be used as a reserve. It can be lowered to reserve. ,in and These represent the upper and lower limits of reactive power, respectively. The pre-fault prevention control optimization model is as follows:

[0102]

[0103] in, To prevent the control objective function, For the set of monitored busbars, , , For the target weight, and Resources The importance coefficients of the reserve are adjusted upwards and downwards. This model simultaneously satisfies power flow balance constraints, node voltage constraints, reactive power resource capacity constraints, transformer tap constraints, and capacitor switching constraints. Its core effect is to avoid running dynamic resources such as SVG, renewable energy converters, and synchronous condensers near capacity limits for extended periods before a fault occurs, thus preserving control space for subsequent transient disturbances.

[0104] The goal of the transient suppression phase during a fault is to handle rapid voltage changes during DC blocking, AC short circuits, or fault clearing. In a DC blocking scenario, the reactive power consumption of the converter station decreases rapidly, while filters and capacitors may not yet be disconnected. In this case, the surplus reactive power can be expressed as:

[0105]

[0106] in, For the converter station side, there is surplus reactive power. For the filter's reactive power, For the reactive power of the parallel capacitor, This refers to the reactive power consumed by the converter before the fault. For the reactive power response increment of the new energy converter, For SVG reactive response increment, The reactive power response increment of the synchronous condenser. The predicted transient voltage rise value of the converter station bus is:

[0107]

[0108] In the formula, For converter station bus Short-circuit capacity, To account for correction factors for short-circuit ratio, operating voltage, and network nonlinearity, For resources busbar Voltage sensitivity, For resources The reactive power regulation amount. This formula shows that in a weak-sending system with low short-circuit capacity, the same surplus reactive power will cause a higher voltage rise. Therefore, transient overvoltage suppression should prioritize reactive power resources near the converter station that are highly sensitive and have a fast response.

[0109] During the transient suppression phase of a fault, dynamic control commands for fast reactive power resources are determined with the objectives of suppressing transient overvoltage peaks, supporting transient undervoltage, and preventing converter current from exceeding limits. The optimization model for the transient suppression phase employs a discrete-time window. ,in Let be the number of discrete sampling points. The optimization objective is:

[0110]

[0111] in, Let the transient suppression objective function be... For the set of critical voltage nodes, For nodes At any moment voltage, To facilitate rapid resource aggregation, For the transformer or SVG at time The output current, To limit the allowable current, , , These are the weighting coefficients. The first term suppresses overvoltage, the second term supports low voltage, and the third term prevents current surges from triggering current limiting or blocking. This optimization model also satisfies dynamic available capacity constraints:

[0112]

[0113] in, For resources At any moment It can increase non-functional ability. This reduces non-functionality. For renewable energy converters, the current circle constraint should also be satisfied:

[0114]

[0115] in, and The converter at time t is respectively The d-axis and q-axis currents. This constraint ensures that when active power output occupies the current capacity, the reactive power support command will not exceed the converter's current capacity.

[0116] During the post-fault recovery and reconfiguration phase, the recovery control strategy for reactive power resources is determined with the goals of steady-state voltage recovery, coordinated operation of slow-speed equipment, and dynamic reactive power reserve reconfiguration. Specifically, the objective is to coordinate slow-speed equipment and dynamic resources to restore the voltage to the target range and re-establish dynamic reactive power reserve. The optimization objective is as follows:

[0117]

[0118] in, To restore and reconstruct the objective function, It is a collection of discrete-action devices, including capacitor banks and on-load tap-changing transformers. For equipment Action cost or action penalty coefficient This refers to the change in equipment speed or switching status. , , These are weighting coefficients. The first term is used to reduce the voltage deviation after recovery, the second term is used to avoid frequent operation of slow-speed equipment, and the third term is used to reconfigure reactive power reserves. Constraints at this stage include power flow balance constraints, voltage constraints, equipment capacity constraints, transformer tap-out integer constraints, and capacitor switching integer constraints. Through optimization at this stage, fast resources can gradually withdraw from transient limit support states, and slow resources can take over steady-state voltage regulation tasks, thereby avoiding long-term high-load operation of fast resources.

[0119] Step S6: For large-scale renewable energy bases, if the entire network is directly optimized centrally, the number of decision variables increases rapidly with the number of renewable energy power plants, reactive power resources, and time discrete points. Therefore, this invention partitions the renewable energy bases according to the voltage sensitivity matrix and electrical distance, establishes partitioned optimization sub-models, and achieves inter-regional coordination through boundary bus voltage consistency correction. First, the reactive power voltage sensitivity matrix is ​​calculated. Linearization of the power flow equations yields:

[0120]

[0121] in, This is the active power increment vector of the node. This is the reactive power increment vector of the node. This is the node phase angle increment vector. This is the node voltage magnitude increment vector. , , , This is a block matrix of the power flow Jacobian matrix. In scenarios where active power disturbances are small or reactive voltage relationships are dominant, it can be approximated by a reduced-order Jacobian matrix:

[0122]

[0123] Therefore, node For nodes The voltage sensitivity of reactive power injection is:

[0124]

[0125] Based on this, the coupling weight between nodes is defined as follows:

[0126]

[0127] in, For nodes With nodes The electrical distance between them can be determined by equivalent impedance or the shortest electrical path; , , These are the weighting coefficients. According to... Construct a coupling diagram and assign nodes with high coupling strength to the same control zone, so that the reactive voltage correlation within the zone is strong, and the zones are coupled through a small number of boundary buses.

[0128] Suppose the system is divided into The partition, the first The set of internal nodes of each partition is The set of boundary busbars is Local reactive power resources are aggregated as The partitioning optimization subproblem can be represented as:

[0129]

[0130] in, For partitioning The stage objective function, These are the control variables within the zone, including reactive power output, reactive current, switching status, and transformer tap position. For boundary bus voltage constraints. Since the boundary bus is simultaneously affected by adjacent zones, this invention employs a boundary bus consistency correction mechanism. After the next iteration, if adjacent partitions are opposite to the boundary bus... The given voltage values ​​are respectively ,in The consistency value is the number of partitions associated with the boundary bus.

[0131]

[0132] in, For partitioning For boundary busbar The reliability weights can be set based on the short-circuit capacity, sensitivity intensity, or power flow convergence quality within the partition. The partition is then updated. Inner boundary bus voltage constraint:

[0133]

[0134] in, Let be the iteration step size. The convergence criterion is:

[0135]

[0136] in, This is the set of boundary buses for the entire network. This is the boundary voltage consistency convergence threshold. When this condition is met, the voltage constraints between partitions are considered consistent, and the control strategy for each partition is output; otherwise, parallel optimization and boundary correction between partitions continue. This mechanism avoids the boundary voltage inconsistency problem caused by independent solutions for each partition, while reducing the scale of centralized solution across the entire network.

[0137] In practical implementation, the method of this invention operates according to the following control logic. First, under normal operating conditions, the system periodically performs pre-fault prevention control. Based on the current renewable energy output, DC power transmission, AC system short-circuit capacity, and reactive power equipment status, it calculates the voltage risk and reactive power reserve of each node, obtaining the preventive reactive power output setpoint. When disturbance signals such as DC blocking, commutation failure, AC short circuit, or fault clearing are detected, the control logic switches to the transient suppression stage. Based on the transient voltage risk, surplus reactive power prediction value, and available rapid resource capacity, it generates rapid control commands for the renewable energy converter, SVG, and synchronous condenser. After the transient risk is resolved and the system enters a new quasi-steady state, the control logic switches to the recovery and reconfiguration stage, coordinating parallel capacitors, on-load tap-changing transformers, and dynamic reactive power resources to restore node voltage and re-reserve reactive power reserves. The three stages are not isolated from each other but are connected through reactive power reserves, equipment status, and voltage risk indicators, ensuring that the control results of the previous stage do not result in a lack of adjustment margin in the subsequent stage. Specifically, the pre-fault prevention and control phase reserves millisecond- and hundred-millisecond-level rapid adjustment space for resources during the transient suppression phase by keeping dynamic resources operating away from capacity boundaries. During the transient suppression phase, voltage over-limit is curbed through dynamic support from fast resources, and equipment operation status information is preserved for the post-fault recovery and reconfiguration phase. The post-fault recovery and reconfiguration phase restores the initial adjustment margin for the next round of pre-fault prevention and control by coordinating slow resources to take over steady-state regulation, enabling fast resources to exit extreme states, and re-establishing dynamic reactive power reserve. This forms a closed-loop control for voltage safety throughout the entire process.

[0138] Step S7: Output control commands for each reactive resource based on the coordination results. The control commands include reactive current commands for renewable energy converters, reactive power commands for static var generators, excitation adjustment commands for synchronous condensers, switching commands for parallel capacitor banks, and tap position adjustment commands for on-load tap-changing transformers.

[0139] This invention achieves full-process coordinated control of multiple reactive resources in large-scale renewable energy bases through dynamic reactive power availability envelope, unified voltage risk index, DC disturbance transient voltage rise prediction, amplitude-phase compensation virtual synchronous control, three-stage coordinated optimization, and partition boundary consistency correction. This method adapts to the operating characteristics of high-proportion renewable energy, high-proportion power electronic equipment, and weak AC transmission-end systems. It fully leverages the complementary advantages of renewable energy converters, SVG, synchronous condensers, capacitor banks, and on-load tap-changing transformers at different time scales, improving the system's voltage safety support capability against large power disturbances.

[0140] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for coordinated optimization of multiple reactive power resources for large-scale new energy bases, characterized in that, Includes the following steps: S1. Obtain the grid topology, operation mode, DC power transmission, reactive power compensation configuration of converter stations, grid connection point information of wind farms and photovoltaic power stations of the new energy base, as well as the capacity, response time and control mode parameters of reactive power resources, and establish a unified operation model that can reflect the surplus reactive power characteristics of converter stations and the insufficient short-circuit capacity of weak systems at the sending end under DC power transmission disturbances, and includes AC network, DC converter station, new energy power station and multiple reactive power resources. S2. The multiple reactive resources are divided into millisecond-level fast resources, hundred-millisecond-level dynamic resources, second-level discrete resources, and minute-level steady-state adjustment resources according to their response time and control characteristics. The dynamic reactive available capacity envelope of wind power and photovoltaic grid-connected converters, static var generators, synchronous condensers, parallel capacitor banks, on-load tap-changing transformers, and converter station filters is established. The dynamic reactive available capacity envelope is used to characterize the real adjustable boundary of each resource before, during, and after the fault. S3. Based on node voltage, short-circuit capacity, DC power disturbance and the dynamic reactive available capacity envelope, construct a voltage risk assessment model that simultaneously covers transient overvoltage risk, transient undervoltage risk and recovery voltage deviation risk, and obtain voltage risk indicators for each key node before, during and after the fault. S4. The system operation process is divided into the pre-fault prevention and control stage, the transient suppression stage during the fault, and the post-fault recovery and reconstruction stage, based on the fault process as the trigger condition. Differentiated optimization objectives and constraints are established for each stage. The three stages are organically connected through dynamic reactive power reserve indicators and full-process voltage risk indicators, so that the control results of the previous stage reserve adjustment margin for the next stage. S5. In the pre-fault prevention and control phase, with the goals of reducing network losses, reducing voltage deviation, and maintaining dynamic reactive power reserve, the preventive operating points of each reactive power resource are determined. In the transient suppression phase during the fault, with the goals of suppressing transient overvoltage peaks, supporting transient undervoltage, and preventing converter current from exceeding limits, the dynamic control commands for the millisecond-level fast resources and the hundred-millisecond-level dynamic resources are determined. In the post-fault recovery and reconfiguration phase, with the goals of steady-state voltage recovery, coordinated action of the second-level discrete resources and the minute-level steady-state regulation resources, and dynamic reactive power reserve reconfiguration, the recovery control strategy for reactive power resources is determined. S6. Divide the new energy base into zones according to the reactive voltage coupling strength, establish a zone optimization sub-model for each zone, and achieve inter-zone coordination through boundary bus voltage consistency correction. S7. Output control commands for each reactive resource based on the coordination results. The control commands include reactive current commands for renewable energy converters, reactive power commands for static var generators, excitation adjustment commands for synchronous condensers, switching commands for parallel capacitor banks, and tap position adjustment commands for on-load tap-changing transformers.

2. The method according to claim 1, characterized in that, In step S2, the dynamic reactive power available capacity envelope is represented as: in, as reactive resources At any moment Dynamic available reactive power capacity Available state functions to reflect equipment interlocking, current limiting, or operation delay. This is the maximum reactive power capacity of the equipment. For the apparent power capacity of the device, For the equipment at all times active power, For initial no-work output, This is the reactive ramp rate.

3. The method according to claim 1, characterized in that, In step S3, the voltage risk assessment model provides a unified evaluation basis for optimization in the pre-fault prevention and control stage, the transient suppression stage during the fault, and the post-fault recovery and reconfiguration stage, realizing closed-loop management of voltage risk throughout the entire process. The comprehensive voltage risk index of the voltage risk assessment model is expressed as: in, For nodes Comprehensive voltage risk index, For nodes in the transient process Maximum voltage, This is the upper limit of the node voltage. For nodes in the transient process The minimum voltage, This is the lower limit of the node voltage. This refers to the node voltage during the post-fault recovery phase. The node reference voltage, This represents the function that takes the positive part. , , These are the weighting coefficients.

4. The method according to claim 1, characterized in that, In step S5, the transient suppression stage during the fault period adopts a transient voltage rise prediction model that considers the coupling relationship between the surplus reactive power of the converter station and the short-circuit capacity of the AC system after DC blocking, which is expressed as: in, For converter station bus The predicted value of transient pressure rise, The correction factor is determined by the system short-circuit ratio and voltage level. This refers to the surplus reactive power on the converter station side after a DC power outage. For converter station bus Short-circuit capacity at the location, The set of reactive resources participating in transient control, as reactive resources Converter station bus Voltage sensitivity, as reactive resources The reactive power regulation.

5. The method according to claim 1, characterized in that, In step S5, the new energy converter adopts a virtual synchronous control method with amplitude-phase coordinated compensation. Its internal voltage amplitude reference and internal voltage phase reference are expressed as follows: in, For new energy converters Internal voltage amplitude reference value, This represents the real-time voltage amplitude at the grid connection point. This represents the steady-state voltage amplitude before the fault. This is the amplitude compensation coefficient. This is the internal voltage phase reference value. For the real-time voltage phase at the grid connection point, The phase jump variable before and after the fault occurs or is cleared. This is the phase compensation coefficient.

6. The method according to claim 1, characterized in that, In step S5, during the low-voltage ride-through process, the reactive current deviation caused by the reactive current command meter and the dynamics of the phase-locked loop of the renewable energy converter is expressed as follows: in, For new energy converters reactive current command, This refers to the reactive current prior to the fault. For low voltage ride-through reactive power support factor, The low voltage ride-through trigger voltage threshold, This represents the actual voltage amplitude at the grid connection point. Rated reactive current, This refers to the reactive current deviation caused by the dynamics of the phase-locked loop.

7. The method according to claim 1, characterized in that, In step S6, the new energy base is partitioned based on the reactive power voltage coupling strength, and the nodes... With nodes The coupling weights between them are expressed as: in, For nodes With nodes The coupling weights between them For nodes Voltage to node The sensitivity of reactive power injection For nodes Voltage to node The sensitivity of reactive power injection For nodes With nodes Electrical distance between them , , These are the weighting coefficients.

8. The method according to claim 1, characterized in that, In step S6, the partition boundary bus adopts a consistency correction mechanism. In the next iteration, the boundary bus voltage constraint is updated to: in, For the first Partitioning in the next iteration For boundary busbar Calculate the voltage. For all adjacent partitions, the boundary bus Calculate the weighted average value of the voltage. For the first The correction step size of the next iteration is such that when the voltage deviation of all boundary buses is less than the preset convergence threshold, the overall network coordinated optimization result is output.

9. The method according to claim 1, characterized in that, In step S5, the objective function of the optimization model in the pre-fault prevention and control stage is expressed as: in, To prevent the control objective function, For active network loss, For the set of monitored busbars, For nodes voltage, For nodes The reference voltage, For reactive resource collection, as reactive resources The current unproductive effort, as reactive resources The upper limit of reactive power, as reactive resources The lower limit of reactive power, , , For the target weight, and Resources Adjust the importance coefficient of the reserve to be increased or decreased.

10. The method according to claim 1, characterized in that, In step S5, the optimization model for the transient suppression stage during the fault period adopts a discrete time window, and its objective function is expressed as: in, Let the transient suppression objective function be... For the set of critical voltage nodes, This represents the number of discrete sampling points within the time window. Sampling time, For nodes At any moment voltage, This is the upper limit of voltage. This is the lower limit of voltage. This represents the function that takes the positive part. To facilitate rapid resource aggregation, For the converter or static var generator at time The output current, To limit the allowable current, , , These are the weighting coefficients.

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