An integrated power system short-circuit current constraint modeling method and device

Abstract

This invention discloses an integrable short-circuit current constraint modeling method and apparatus for power systems. The method constructs a Norton equivalent circuit model by acquiring the electromotive force and subtransient reactance parameters of the synchronous generator before a fault. Through a multi-dimensional constraint transformation strategy, the nonlinear control logic of the inverter power supply is transformed into mixed-integer constraints to obtain the inverter power supply injection current constraint. Based on the node current injection information of the synchronous generator and the inverter power supply injection current constraint, a node admittance matrix of the power system is constructed. Based on the node admittance matrix, network equation constraints of the power system are constructed. The Norton equivalent circuit model, mixed-integer constraints, and network equation constraints are integrated to construct and solve a mixed-integer quadratic constraint optimization model to obtain the short-circuit current value required for power system optimization. This invention solves the problems of mismatched nonlinear control characteristics of high-proportion IBGs and the difficulty of directly embedding existing fault current iterative solvers into upper-level optimization.

Description

Technical Field

[0001] This invention relates to the field of power system operation and optimization technology, specifically to an integrable power system short-circuit current constraint modeling method and apparatus. Background Technology

[0002] With the deepening global advancement of the "dual carbon" goal, new energy power generation technologies, represented by wind power and photovoltaic power generation, have been widely promoted and applied. Inverter interface generators (IBGs) are gradually replacing traditional synchronous generators (SGs) and becoming a core power source component in power systems. Against this backdrop, system strength assessment has become a crucial link in ensuring the safe and stable operation of power systems. Short-circuit current level is a core indicator characterizing system strength, and its accurate calculation is of significant guiding importance for power grid planning and design, operation scheduling, and fault prevention strategy formulation. Traditional short-circuit current calculation methods focus on the fault response characteristics of SGs, equating SGs to the Thevenin model of "constant voltage source in series subtransient reactance." This method is mature in traditional high-proportion SG power systems and can meet the needs of conventional short-circuit current assessment. Meanwhile, considering the fault response characteristics of IBGs, existing research has proposed an iterative fault current solver method. By modeling IBGs as voltage-controlled current sources and using an iterative approach to solve for short-circuit current, this has become an important technical means for short-circuit current assessment in high-proportion IBG-connected systems.

[0003] However, existing technologies have significant limitations in practical applications. On the one hand, the traditional Thevenin model, based on the fault response mechanism of SG, cannot adapt to the fault response characteristics of IBG, which are dominated by complex nonlinear control logic. This leads to a significant decrease in its computational accuracy in systems with a high proportion of IBG, making it difficult to meet the accuracy requirements of system strength assessment. On the other hand, although existing fault current iterative solvers can adapt to the fault response characteristics of IBG, they are essentially independent iterative calculation tools. Their solution process is independent of the mathematical framework of the upper-level optimization problem and cannot be directly embedded into the upper-level optimization model as a complete mathematical subproblem. This makes it difficult to apply precise system strength constraints during the upper-level optimization process, and it is impossible to achieve an integrated closed loop of "short-circuit current assessment - system optimization decision-making," thus restricting the coordinated optimization of power system safety, stability, and economic operation.

[0004] Therefore, there is an urgent need for an integrable power system short-circuit current constraint modeling method to address the problems of mismatch between the nonlinear control characteristics of high-proportion IBG and the difficulty in directly embedding existing fault current iterative solvers into upper-level optimization. Summary of the Invention

[0005] To address these issues, this invention provides an integrable power system short-circuit current constraint modeling method and apparatus, which solves problems such as the incompatibility of traditional short-circuit current calculation methods with the nonlinear control characteristics of high-proportion IBG, and the difficulty of directly embedding existing fault current iterative solvers into upper-level optimization.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an integrable power system short-circuit current constraint modeling method, comprising:

[0007] By obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault, a Norton equivalent circuit model of the synchronous generator is constructed.

[0008] By using a multi-dimensional constraint transformation strategy, the nonlinear control logic of the inverter power supply is transformed into mixed integer constraints, thereby obtaining the inverter power supply injection current constraint in the power system coordinate system.

[0009] Based on the node current injection information of the synchronous generator and the power injection current constraints of the inverter, the node admittance matrix of the power system is constructed; based on the node admittance matrix, the network equation constraints of the power system are constructed.

[0010] The Norton equivalent circuit model, the mixed integer constraints, and the network equation constraints are integrated to construct a mixed integer quadratic constraint optimization model. By solving the mixed integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

[0011] As a preferred embodiment of an integrable power system short-circuit current constraint modeling method, the Norton equivalent circuit model includes parallel admittance and equivalent current source; when constructing the power system node admittance matrix, the parallel admittance is added to the self-admittance corresponding to the physical connection node of the synchronous generator; the component of the equivalent current source is added as a known injected current term to the node current balance equation of the physical connection node of the synchronous generator.

[0012] As a preferred embodiment of an integrable power system short-circuit current constraint modeling method, in the process of transforming the nonlinear control logic of the inverter power supply into the mixed integer constraints through the multi-dimensional constraint transformation strategy, the nonlinear control logic includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive priority principle.

[0013] As a preferred embodiment of an integrable power system short-circuit current constraint modeling method, the steps for transforming the nonlinear control logic into the mixed integer constraints are as follows:

[0014] For the nonlinear curves in the reactive current control, active current control, and low-voltage power control logic, the nonlinear curves are linearized by a piecewise linearization constraint group to obtain the linearization result.

[0015] Based on the linearization result, a linear constraint group for the nonlinear relationship between active current and terminal voltage is constructed by introducing a first auxiliary binary variable and adopting the Big-M strategy.

[0016] The available limit of active current under the reactive power priority principle is determined by a quadratic constraint; based on the available limit, an active current output constraint group is constructed by introducing a second auxiliary binary variable and adopting the Big-M strategy.

[0017] Based on the current components of the active current output constraint group, the inverter power injection current constraint in the power system coordinate system is obtained by transforming the injection current from the dq coordinate system back to the power system coordinate system.

[0018] As a preferred embodiment of an integrable power system short-circuit current constraint modeling method, the network equation constraints include node current balance constraints and zero voltage constraints;

[0019] The node current balance constraint is constructed by ensuring that the injected current of any node is equal to the outflow current, and that the total injected current is the algebraic sum of the external current sources of all connected nodes, taking into account the fault current.

[0020] The zero-voltage constraint is constructed by forcing the voltage of the faulty node to zero.

[0021] This invention also provides an integrable power system short-circuit current constraint modeling device, based on the above-mentioned integrable power system short-circuit current constraint modeling method, comprising:

[0022] The Norton equivalent circuit model building module is used to construct the Norton equivalent circuit model of the synchronous generator by obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault.

[0023] The nonlinear control logic conversion module is used to convert the nonlinear control logic of the inverter power supply into mixed integer constraints through a multi-dimensional constraint conversion strategy, thereby obtaining the inverter power supply injection current constraint in the power system coordinate system.

[0024] The network equation constraint construction module is used to construct the node admittance matrix of the power system based on the node current injection information of the synchronous generator and the power injection current constraint of the inverter; and to construct the network equation constraints of the power system based on the node admittance matrix.

[0025] The mixed-integer quadratic constraint optimization model construction and solution module is used to integrate the Norton equivalent circuit model, the mixed-integer constraints, and the network equation constraints to construct a mixed-integer quadratic constraint optimization model; by solving the mixed-integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

[0026] As a preferred embodiment of an integrable power system short-circuit current constraint modeling device, the Norton equivalent circuit model construction module includes a parallel admittance and an equivalent current source. When constructing the power system node admittance matrix, the parallel admittance is added to the self-admittance corresponding to the physical connection node of the synchronous generator. The components of the equivalent current source are added as known injected current terms to the node current balance equation of the physical connection node of the synchronous generator.

[0027] As a preferred embodiment of an integrable power system short-circuit current constraint modeling device, the nonlinear control logic conversion module, in the process of converting the nonlinear control logic of the inverter power supply into the mixed integer constraint through the multi-dimensional constraint conversion strategy, includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive priority principle.

[0028] As a preferred embodiment of an integrable power system short-circuit current constraint modeling device, the nonlinear control logic conversion module includes a sub-module that converts the nonlinear control logic into the mixed integer constraints, comprising:

[0029] The linearization processing submodule is used to linearize the nonlinear curves in the reactive current control, active current control and low-voltage power control logic by using a piecewise linearization constraint group to obtain the linearization processing result.

[0030] A submodule for constructing a linear constraint group for the nonlinear relationship between active current and terminal voltage is used to construct a linear constraint group for the nonlinear relationship between active current and terminal voltage based on the linearization processing result by introducing a first auxiliary binary variable and adopting the Big-M strategy.

[0031] An active current output constraint group construction submodule is used to determine the available limit of active current under the reactive priority principle through secondary constraints; based on the available limit, an active current output constraint group is constructed by introducing a second auxiliary binary variable and adopting the Big-M strategy.

[0032] The inverter power injection current constraint acquisition submodule is used to obtain the inverter power injection current constraint in the power system coordinate system by transforming the injection current in the dq coordinate system back to the power system coordinate system based on the current component of the active current output constraint group.

[0033] As a preferred embodiment of an integrable power system short-circuit current constraint modeling device, the network equation constraint construction module includes node current balance constraints and zero voltage constraints.

[0034] The node current balance constraint is constructed by ensuring that the injected current of any node is equal to the outflow current, and that the total injected current is the algebraic sum of the external current sources of all connected nodes, taking into account the fault current.

[0035] The zero-voltage constraint is constructed by forcing the voltage of the faulty node to zero.

[0036] This invention has the following advantages: It constructs a Norton equivalent circuit model of the synchronous generator by obtaining the electromotive force and subtransient reactance parameters of the synchronous generator before a fault; it transforms the nonlinear control logic of the inverter power supply into mixed integer constraints through a multi-dimensional constraint transformation strategy, obtaining the inverter power supply injection current constraint in the power system coordinate system; based on the node current injection information of the synchronous generator and the inverter power supply injection current constraint, it constructs the node admittance matrix of the power system; based on the node admittance matrix, it constructs the network equation constraints of the power system; it integrates the Norton equivalent circuit model, the mixed integer constraints, and the network equation constraints to construct a mixed integer quadratic constraint optimization model; and it solves the mixed integer quadratic constraint optimization model to obtain the short-circuit current value required for power system optimization. This method innovatively solves the limitations of traditional short-circuit current calculation methods being unsuitable and existing iterative solvers being difficult to directly embed into higher-level optimization problems by constructing a unified short-circuit current MIQCP model. Compared with existing iterative methods, the core advantage of the method proposed in this invention lies in constructing the IBG nonlinear control logic and system network equations into a unified and integrable MIQCP model. The key value of this invention is that the proposed model can be directly embedded as a complete subproblem into higher-level optimization problems such as SCUC or OPF, providing an efficient and integrable technical solution for applying precise system strength constraints and maintaining system safety and stability. Attached Figure Description

[0037] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.

[0038] The structures, proportions, sizes, etc. illustrated in this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed herein, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0039] Figure 1 This is a flowchart illustrating an integrable power system short-circuit current constraint modeling method provided in Embodiment 1 of the present invention.

[0040] Figure 2 This is a schematic diagram of the low-voltage power logic of a GE 2.5MW wind turbine in an integrable power system short-circuit current constraint modeling method provided in Embodiment 1 of the present invention.

[0041] Figure 3 This is a schematic diagram of an improved IEEE 39-node computing system in one possible embodiment of Embodiment 1 of the present invention;

[0042] Figure 4 This is a schematic diagram of the architecture of an integrable power system short-circuit current constraint modeling device provided in Embodiment 2 of the present invention. Detailed Implementation

[0043] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1

[0045] See Figure 1 Embodiment 1 of the present invention provides an integrable power system short-circuit current constraint modeling method, comprising the following steps:

[0046] S1. By obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault, a Norton equivalent circuit model of the synchronous generator is constructed.

[0047] S2. By using a multi-dimensional constraint transformation strategy, the nonlinear control logic of the inverter power supply is transformed into mixed integer constraints to obtain the inverter power supply injection current constraint in the power system coordinate system.

[0048] S3. Based on the node current injection information of the synchronous generator and the power injection current constraints of the inverter, construct the node admittance matrix of the power system; based on the node admittance matrix, construct the network equation constraints of the power system:

[0049] S4. Integrate the Norton equivalent circuit model, the mixed integer constraints, and the network equation constraints to construct a mixed integer quadratic constraint optimization model; solve the mixed integer quadratic constraint optimization model to obtain the short-circuit current value required for power system optimization.

[0050] In this embodiment, in step S1, the Norton equivalent circuit model of the synchronous generator is constructed by obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault.

[0051] Specifically, in short-circuit calculations, a synchronous generator (SG) is typically modeled as a constant voltage source connected in series with a subtransient reactance. This voltage source This refers to the internal electromotive force of the synchronizing machine calculated before the fault. To account for this model within the framework of the nodal admittance matrix equation, this paper uses the Norton equivalent circuit of the m-th SG for modeling. This equivalent circuit consists of a parallel admittance and an equivalent current source.

[0052] The expression for the parallel admittance is:

[0053]

[0054] In the formula, For parallel admittance; j is the imaginary unit. For subtransient reactance;

[0055] The expression for the equivalent current source is:

[0056]

[0057] In the formula, It is an equivalent current source; It is a voltage source.

[0058] In this embodiment, the system node admittance matrix is ​​constructed. At that time, admittance Added to its physical connection node Corresponding self-admittance Above. Simultaneously, the equivalent current source... The component is added to the node as a known injected current term. The nodal current balance equation.

[0059] In this embodiment, in step S2, the nonlinear control logic of the inverter power supply is transformed into mixed integer constraints through a multi-dimensional constraint transformation strategy to obtain the inverter power supply injection current constraint in the power system coordinate system.

[0060] The nonlinear control logic includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive power priority principle.

[0061] Specifically, the steps for converting the nonlinear control logic into the mixed integer constraints are as follows:

[0062] S21. For the nonlinear curves in the reactive current control, active current control and low-voltage power control logic, the nonlinear curves are linearized by a piecewise linearization constraint group to obtain the linearization result.

[0063] Specifically, for the nonlinear curves in the reactive current droop control and active current low-voltage power control, a piecewise linear (PWL) constraint set is used to accurately linearize them.

[0064] No. Terminal voltage of IBG and its amplitude These are all decision variables in the model, and are related by the following quadratic constraints:

[0065]

[0066] In the formula, This is the real part of the terminal voltage; This represents the imaginary part of the terminal voltage.

[0067] The reactive current control logic of IBG is shown in the following equation:

[0068]

[0069]

[0070] In the formula, Output reactive current for IBG; This is the rated current value of IBG; For IBG pre-fault reactive current; For reactive power output of generators in case of pre-fault conditions; This refers to the amplitude of the generator terminal voltage in the event of a pre-fault. , and These represent the terminal voltage amplitude when the IBG connection point fails, the voltage amplitude before the fault, and the rated voltage, respectively. This is the droop factor for IBG reactive current control.

[0071] No. Taiwan IBG Shaft current reference value Before taking into account the saturation limit, it is expressed as the pre-fault steady-state component. With dynamic response components Superposition:

[0072]

[0073]

[0074] In the formula, This represents the reactive power before the fault. The voltage amplitude is the terminal voltage; the voltage deviation is the voltage deviation. Defined as Dynamic response components yes A nonlinear function, denoted as This function is used to implement reactive power droop control, and its characteristics strictly adhere to power grid specifications: when voltage deviation... Located at the voltage dead zone threshold At that time, =0; outside the dead zone, Follow by The gain changes linearly.

[0075] To make this nonlinear The function is embedded in a mixed-integer programming model, precisely expressed as a set of piecewise linear constraints. This PWL function is derived from its... A turning point As defined, where represent sampling points, Represents the corresponding Values. By introducing a set of non-negative continuous weight variables. and a set of binary variables This nonlinear relationship It is equivalently transformed into the following set of linear constraints:

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083] This set of constraints is fully defined. Shaft current reference value This value will be related to Shaft current reference value They are all affected by the maximum current amplitude of the inverter. Saturation limit.

[0084] Low-voltage power control logic The maximum allowable active current at different voltage levels is specified. .Should The curves are also modeled accurately using the same PWL constraint set.

[0085] S22. Based on the linearization result, by introducing a first auxiliary binary variable and adopting the Big-M strategy, a linear constraint group for the nonlinear relationship between active current and terminal voltage is constructed.

[0086] Specifically, to address the nonlinear relationship between active current and terminal voltage, an auxiliary binary variable is introduced and a Big-M strategy is employed to establish a linear constraint set.

[0087] No. Taiwan IBG Shaft current reference value From the active power before the fault It is determined together with the IBG low-voltage power control logic.

[0088] For robust processing Shaft current and active power before fault Relationships (especially) (singularity of time), the model introduces a voltage threshold. and an auxiliary binary variable The following constraints are established using the Big-M method:

[0089] when hour, Forced to 1, at this time Shaft active component It is constrained to 0.

[0090] when ( When (is a very small positive number), Forced to 0, at this time constrained as .

[0091] This logic is implemented through the following set of linear constraints (where... (for a sufficiently large constant)

[0092]

[0093]

[0094]

[0095]

[0096]

[0097]

[0098] It is constrained to be the smaller of the two values ​​mentioned above. To achieve... The model introduces an auxiliary binary variable and a sufficiently large constant, and imposes the following set of linear constraints:

[0099]

[0100]

[0101]

[0102]

[0103] In the formula, It is a sufficiently large constant; For auxiliary binary variables.

[0104] like Figure 2 The diagram shown is the low-voltage power logic diagram of the GE 2.5MW wind turbine, which illustrates the active power output limitation relationship of IBG under different terminal voltage conditions. It intuitively presents the nonlinear characteristics of low-voltage power control and provides a direct basis for transforming this nonlinear logic into mixed integer constraints through piecewise linear (PWL) constraint groups.

[0105] S23. Determine the available limit of active current under the reactive priority principle through secondary constraints; based on the available limit, construct an active current output constraint group by introducing a second auxiliary binary variable and adopting the Big-M strategy.

[0106] Specifically, for the current limit calculation and minimum value selection logic under the reactive power priority principle, a quadratic constraint is adopted to determine the available limit of active current, and an auxiliary binary variable and Big-M strategy are introduced to realize the final active current output constraint.

[0107] dq axis current reference value and The maximum current amplitude limit of the inverter must be met. And follow the principle of prioritizing reactive power.

[0108] first, shaft current constrained as After saturation limiting, the output is restricted to the value. Within the interval. This saturation element is achieved through a set of (PWL) constraints, the form of which is similar to... The PWL implementations of the functions are completely identical.

[0109] Secondly, following the principle of prioritizing reactive power, based on the already determined... The maximum current amplitude of the inverter Limited availability Axis current limit Determined by the following quadratic constraints:

[0110]

[0111] Finally, the ultimate shaft current constrained as Axis reference value With available Axis current limit The smaller value between. To achieve The model introduces a second auxiliary binary variable and a sufficiently large constant. And apply the following set of linear constraints:

[0112]

[0113]

[0114]

[0115]

[0116] In the formula, For auxiliary binary variables.

[0117] S24. Based on the current components of the active current output constraint group, transform the injection current from the dq coordinate system back to the power system coordinate system to obtain the inverter power supply injection current constraint in the power system coordinate system.

[0118] Specifically, in order to inject IBG as a controlled current source into the system network equations, it is necessary to... Final current components in coordinate system Transform back Injected current in system coordinate system .assumed With the axis and terminal voltage phase aligned, the coordinate transformation is as follows:

[0119]

[0120] In the formula, This is the terminal voltage.

[0121] In this embodiment, in step S3, the node admittance matrix of the power system is constructed based on the node current injection information of the synchronous generator and the power injection current constraint of the inverter; and the network equation constraint of the power system is constructed based on the node admittance matrix.

[0122] Specifically, the core of the short-circuit current calculation model constructed in this invention is based on the nodal admittance matrix. The network equations are as follows. These equations strictly adhere to nodal current balance constraints, ensuring that at any node in the system... Injection current This is equivalent to the current flowing out of the node through the network.

[0123]

[0124]

[0125]

[0126] In the formula, For nodes Voltage phasors; and These are nodes The real and imaginary parts of the total injected current. This total injected current... It is all connected to the node The algebraic sum of the contributions from external current sources, taking into account fault current.

[0127]

[0128]

[0129] In the formula, and Connected to the nodes respectively The index set of synchronous generators and IBG. For index The SG connects to its nodes Norton equivalent injected current component. For index IBG's connection nodes The injected current component is determined by the IBG internal model. For a binary variable, when (Fault node) ,when hour . It is a fault node The fault current component at the location.

[0130] In this embodiment, a specified node is simulated. When a three-phase ground fault occurs, the model applies a zero-voltage constraint, forcing the voltage of that node to zero.

[0131]

[0132]

[0133] In the formula, This represents the real part of the voltage at the fault point. This represents the imaginary part of the voltage at the fault point.

[0134] In this embodiment, in step S4, the Norton equivalent circuit model, the mixed integer constraints, and the network equation constraints are integrated to construct a mixed integer quadratic constraint optimization model; by solving the mixed integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

[0135] Specifically, optimization solvers that support MIQCP problems, such as Gurobi and CPLEX, are used to solve the problem and obtain the short-circuit current values ​​required for power system optimization.

[0136] In one possible embodiment, a specific verification example is provided as follows:

[0137] This embodiment uses an improved IEEE 39-node system for simulation verification. For example... Figure 3 As shown, the synchronous generators located on buses 34 and 36 in the standard 39-node case are replaced with the inverter power supply (IBG) described in this invention, and the remaining generators (such as buses 30-33, 35, 37-39, etc.) are modeled as synchronous generators (SG).

[0138] The verification method of this invention is as follows: a three-phase ground fault is applied to a series of buses in the system (buses 1 to 29 in this embodiment), and the fault current is calculated using two methods: one is the iterative fault current solution method proposed in existing research as a benchmark method; the other is the method proposed in this invention. Finally, by comparing the calculation results of the two methods, the relative error is used as an indicator to verify the accuracy of the method proposed in this invention. The simulation results of this embodiment are shown in Table 1:

[0139] Table 1. Implementation results of this invention on the improved IEEE 39-node system.

[0140] As shown in the table above, the fault current amplitude calculated by the method of this invention is highly consistent with the results of the benchmark iterative method, and the relative error is within a small range at all test fault points. This fully demonstrates the effectiveness and accuracy of the unified MIQCP model proposed in this invention in accurately evaluating the short-circuit current of systems containing IBG.

[0141] The application scenarios of this invention are as follows:

[0142] In grid planning and design scenarios with a high proportion of wind power / solar power connected to the grid, this is used for preliminary verification of the grid connection of new energy bases. By accurately calculating the short-circuit current level under different access schemes, it optimizes the location of power access points, grid topology and transmission channel capacity configuration, avoids equipment selection problems caused by excessive short-circuit current, and ensures the safety and economy of grid planning.

[0143] In the daily operation and dispatching scenarios of power systems, upper-level dispatching models such as unit combination optimization (SCUC) and optimal power flow calculation (OPF) are embedded to evaluate the system strength under the current operating mode in real time. By applying short-circuit current constraints, the power output allocation of units, reactive power compensation configuration and grid operation status are optimized, thereby improving the renewable energy absorption capacity and operation economy while ensuring system safety and stability.

[0144] In power grid fault prevention and equipment configuration scenarios, it is used for relay protection setting and current limiting device optimization configuration. By accurately simulating the magnitude and distribution of short-circuit current under different node faults, the action threshold and time limit of relay protection are determined, and the installation position and parameters of current limiting reactors and fault current limiters are reasonably selected to improve the power grid fault rapid isolation capability and reduce the risk of fault expansion.

[0145] In the management and control scenarios of microgrids and distributed power generation clusters, for microgrids containing a large number of distributed photovoltaic and energy storage inverters, the short-circuit current assessment and operation optimization are coordinated. When the microgrid switches between grid connection and off-grid and when the output of distributed power generation fluctuates, the short-circuit current level is dynamically verified, the power control strategy within the microgrid is optimized, and the safe and stable operation of the local power grid is ensured.

[0146] In power grid upgrade and renovation scenarios, this is used for system performance verification after upgrading old power grids and replacing traditional power sources with new energy sources. By comparing the changes in short-circuit current before and after the renovation, the effectiveness of the renovation plan is evaluated, and the upgrade selection of key equipment such as transformers and circuit breakers is optimized to ensure that the upgraded power grid meets the system strength requirements and long-term operation needs.

[0147] It should be noted that the method of this disclosure embodiment can be executed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario, where multiple devices cooperate to complete the task. In such a distributed scenario, one of these devices may execute only one or more steps of the method of this disclosure embodiment, and the multiple devices will interact with each other to complete the method described.

[0148] It should be noted that the above description describes some embodiments of this disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in a different order than that shown in the above embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0149] Example 2

[0150] See Figure 4 Embodiment 2 of the present invention also provides an integrable power system short-circuit current constraint modeling device, comprising:

[0151] Norton equivalent circuit model construction module 001 is used to construct the Norton equivalent circuit model of the synchronous generator by obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault.

[0152] The nonlinear control logic conversion module 002 is used to convert the nonlinear control logic of the inverter power supply into mixed integer constraints through a multi-dimensional constraint conversion strategy, so as to obtain the inverter power supply injection current constraint in the power system coordinate system.

[0153] The network equation constraint construction module 003 is used to construct the node admittance matrix of the power system based on the node current injection information of the synchronous generator and the power injection current constraint of the inverter; and to construct the network equation constraints of the power system based on the node admittance matrix.

[0154] The mixed-integer quadratic constraint optimization model construction and solution module 004 is used to integrate the Norton equivalent circuit model, the mixed-integer constraints, and the network equation constraints to construct a mixed-integer quadratic constraint optimization model; by solving the mixed-integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

[0155] In this embodiment, the Norton equivalent circuit model construction module 001 includes a parallel admittance and an equivalent current source. When constructing the power system node admittance matrix, the parallel admittance is added to the self-admittance corresponding to the physical connection node of the synchronous generator. The component of the equivalent current source is added as a known injected current term to the node current balance equation of the physical connection node of the synchronous generator.

[0156] In this embodiment, in the nonlinear control logic conversion module 002, during the process of converting the nonlinear control logic of the inverter power supply into the mixed integer constraints through the multi-dimensional constraint conversion strategy, the nonlinear control logic includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive priority principle.

[0157] In this embodiment, the sub-module in the nonlinear control logic conversion module 002 that converts the nonlinear control logic into the mixed integer constraint includes:

[0158] Linearization processing submodule 021 is used to linearize the nonlinear curves in the reactive current control, active current control and low voltage power control logic by using a piecewise linearization constraint group to obtain the linearization processing result.

[0159] The linear constraint group construction submodule 022 for the nonlinear relationship between active current and terminal voltage is used to construct a linear constraint group for the nonlinear relationship between active current and terminal voltage based on the linearization processing result by introducing a first auxiliary binary variable and adopting the Big-M strategy.

[0160] Active current output constraint group construction submodule 023 is used to determine the available limit of active current under the reactive priority principle through secondary constraints; based on the available limit, active current output constraint group is constructed by introducing a second auxiliary binary variable and adopting the Big-M strategy.

[0161] The inverter power injection current constraint acquisition submodule 024 is used to obtain the inverter power injection current constraint in the power system coordinate system by transforming the injection current in the dq coordinate system back to the power system coordinate system based on the current component of the active current output constraint group.

[0162] In this embodiment, the network equation constraint construction module 003 includes node current balance constraints and zero voltage constraints.

[0163] The node current balance constraint is constructed by ensuring that the injected current of any node is equal to the outflow current, and that the total injected current is the algebraic sum of the external current sources of all connected nodes, taking into account the fault current.

[0164] The zero-voltage constraint is constructed by forcing the voltage of the faulty node to zero.

[0165] It should be noted that the information interaction and execution process between the modules of the above system are based on the same concept as the method embodiment in Embodiment 1 of this application, and the resulting technical effects are the same as those in the method embodiment of this application. For details, please refer to the description in the method embodiment shown above in this application, and it will not be repeated here.

[0166] Example 3

[0167] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium storing program code of an integrable power system short-circuit current constraint modeling method. The program code includes instructions for executing the integrable power system short-circuit current constraint modeling method of Embodiment 1 or any possible implementation thereof.

[0168] Computer-readable storage media can be any available medium that a computer can access, or a data storage device such as a server or data center that integrates one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0169] Example 4

[0170] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0171] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor can execute an integrable power system short-circuit current constraint modeling method according to Embodiment 1 or any possible implementation thereof by calling the program instructions.

[0172] Specifically, a processor can be implemented in hardware or software. When implemented in hardware, the processor can be a logic circuit, an integrated circuit, etc. When implemented in software, the processor can be a general-purpose processor that reads software code stored in memory. This memory can be integrated into the processor or located outside the processor and exist independently.

[0173] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0174] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing systems. They can be centralized on a single computing system or distributed across a network of multiple computing systems. Optionally, they can be implemented using program code executable by a computing system, thereby storing them in a storage system for execution by the computing system. In some cases, the steps shown or described can be performed in a different order than those presented herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0175] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. An integrated power system short circuit current constraint modeling method, characterized in that, include: By obtaining the electromotive force and subtransient reactance parameters of the synchronous generator before the fault, a Norton equivalent circuit model of the synchronous generator is constructed. By using a multi-dimensional constraint transformation strategy, the nonlinear control logic of the inverter power supply is transformed into mixed integer constraints, thereby obtaining the inverter power supply injection current constraint in the power system coordinate system. Based on the node current injection information of the synchronous generator and the power injection current constraint of the inverter, the node admittance matrix of the power system is constructed. Based on the node admittance matrix, the network equation constraints of the power system are constructed as follows: The Norton equivalent circuit model, the mixed integer constraints, and the network equation constraints are integrated to construct a mixed integer quadratic constraint optimization model. By solving the mixed integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

2. The integrable power system short-circuit current constraint modeling method according to claim 1, characterized in that, The Norton equivalent circuit model includes parallel admittance and equivalent current source; when constructing the power system node admittance matrix, the parallel admittance is added to the self-admittance corresponding to the physical connection node of the synchronous generator; the component of the equivalent current source is added as a known injected current term to the node current balance equation of the physical connection node of the synchronous generator.

3. The integrable power system short-circuit current constraint modeling method according to claim 2, characterized in that, In the process of transforming the nonlinear control logic of the inverter power supply into the mixed integer constraints through the multi-dimensional constraint transformation strategy, the nonlinear control logic includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive priority principle.

4. The integrable power system short-circuit current constraint modeling method according to claim 3, characterized in that, The steps to transform the nonlinear control logic into the mixed integer constraints are as follows: For the nonlinear curves in the reactive current control, active current control, and low-voltage power control logic, the nonlinear curves are linearized by a piecewise linearization constraint group to obtain the linearization result. Based on the linearization result, a linear constraint group for the nonlinear relationship between active current and terminal voltage is constructed by introducing a first auxiliary binary variable and adopting the Big-M strategy. The available limit of active current under the reactive power priority principle is determined by secondary constraints; Based on the available limits, an active current output constraint group is constructed by introducing a second auxiliary binary variable and adopting the Big-M strategy. Based on the current components of the active current output constraint group, the inverter power injection current constraint in the power system coordinate system is obtained by transforming the injection current from the dq coordinate system back to the power system coordinate system.

5. The integrable power system short-circuit current constraint modeling method according to claim 4, characterized in that, The network equation constraints include node current balance constraints and zero voltage constraints; The node current balance constraint is constructed by ensuring that the injected current of any node is equal to the outflow current, and that the total injected current is the algebraic sum of the external current sources of all connected nodes, taking into account the fault current. The zero-voltage constraint is constructed by forcing the voltage of the faulty node to zero.

6. An integrable power system short-circuit current constraint modeling device, employing the integrable power system short-circuit current constraint modeling method according to any one of claims 1-5, characterized in that, include: The Norton equivalent circuit model building module is used to construct the Norton equivalent circuit model of the synchronous generator by obtaining the internal potential and subtransient reactance parameters of the synchronous generator before the fault. The nonlinear control logic conversion module is used to convert the nonlinear control logic of the inverter power supply into mixed integer constraints through a multi-dimensional constraint conversion strategy, thereby obtaining the inverter power supply injection current constraint in the power system coordinate system. The network equation constraint construction module is used to construct the node admittance matrix of the power system based on the node current injection information of the synchronous generator and the power injection current constraint of the inverter. Based on the node admittance matrix, the network equation constraints of the power system are constructed as follows: The mixed-integer quadratic constraint optimization model construction and solution module is used to integrate the Norton equivalent circuit model, the mixed-integer constraints, and the network equation constraints to construct a mixed-integer quadratic constraint optimization model; by solving the mixed-integer quadratic constraint optimization model, the short-circuit current value required for power system optimization is obtained.

7. An integrable power system short-circuit current constraint modeling device according to claim 6, characterized in that, In the Norton equivalent circuit model construction module, the Norton equivalent circuit model includes parallel admittance and equivalent current source; when constructing the power system node admittance matrix, the parallel admittance is added to the self-admittance corresponding to the physical connection node of the synchronous generator; the component of the equivalent current source is added as a known injected current term to the node current balance equation of the physical connection node of the synchronous generator.

8. An integrable power system short-circuit current constraint modeling device according to claim 7, characterized in that, In the nonlinear control logic conversion module, during the process of converting the nonlinear control logic of the inverter power supply into the mixed integer constraints through the multi-dimensional constraint conversion strategy, the nonlinear control logic includes: reactive current control, active current control, low-voltage power control logic, current saturation limitation and reactive priority principle.

9. An integrable power system short-circuit current constraint modeling device according to claim 8, characterized in that, The nonlinear control logic conversion module includes a submodule that converts the nonlinear control logic into the mixed integer constraints, comprising: The linearization processing submodule is used to linearize the nonlinear curves in the reactive current control, active current control and low-voltage power control logic by using a piecewise linearization constraint group to obtain the linearization processing result. A submodule for constructing a linear constraint group for the nonlinear relationship between active current and terminal voltage is used to construct a linear constraint group for the nonlinear relationship between active current and terminal voltage based on the linearization processing result by introducing a first auxiliary binary variable and adopting the Big-M strategy. An active current output constraint group construction submodule is used to determine the available limit of active current under the reactive priority principle through secondary constraints; based on the available limit, an active current output constraint group is constructed by introducing a second auxiliary binary variable and adopting the Big-M strategy. The inverter power injection current constraint acquisition submodule is used to obtain the inverter power injection current constraint in the power system coordinate system by transforming the injection current in the dq coordinate system back to the power system coordinate system based on the current component of the active current output constraint group.

10. An integrable power system short-circuit current constraint modeling device according to claim 9, characterized in that, In the network equation constraint construction module, the network equation constraints include node current balance constraints and zero voltage constraints; The node current balance constraint is constructed by ensuring that the injected current of any node is equal to the outflow current, and that the total injected current is the algebraic sum of the external current sources of all connected nodes, taking into account the fault current. The zero-voltage constraint is constructed by forcing the voltage of the faulty node to zero.

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