A capacity self-adaptive collaborative balance power flow solving method and system for slow process simulation of a power grid island system

Abstract

The application discloses a capacity self-adaptive collaborative balance power flow solving method and system for slow process simulation of a power grid island system, and belongs to the technical field of power system power flow analysis and energy coordination control. The method comprises the following steps: obtaining system parameters of a flexible direct-current island sending-end system to be solved; based on the system parameters, constructing an augmented power flow equation group comprising a reference station, a sharing station and a global relaxation variable lambda; when the adjustment capacity of the reference station is insufficient, based on the augmented power flow equation group, performing capacity self-adaptive collaborative balance power flow solving for slow process simulation of the flexible direct-current island sending-end system to be solved. The implementation of the application solves the problem of how to realize adaptive collaborative sharing of active power, smooth processing of operation boundary switching and consistent power factor control of each station when the adjustment capacity of the reference station is insufficient in a high-proportion new energy flexible direct-current island sending-end system.

Description

Technical Field

[0001] This invention relates to the field of power system power flow analysis and energy coordination control technology, and more specifically, to a capacity-adaptive cooperative balance power flow solution method for slow process simulation of islanded power grid systems. Background Technology

[0002] my country's new power system has entered a stage of comprehensive development and accelerated construction. It is estimated that by 2030, the renewable energy capacity in the State Grid's operating area will reach nearly 3 billion kilowatts (1.15 billion kilowatts of wind power and 1.81 billion kilowatts of solar power), accounting for more than 50%. With the high proportion of renewable energy connected, new scenarios such as the construction of large-scale bases in desert and Gobi areas and the development of offshore wind power are constantly emerging. The power grid operation faces multiple new risks and challenges, such as the system stability risks caused by the slow process of handling long-term and large fluctuations in renewable energy under extreme weather conditions.

[0003] Simulation technology is an important means of understanding the characteristics of the power grid and ensuring the stable operation of the power system. Currently, slow process simulation is mainly based on two technical approaches. One approach is to realize slow process simulation by stitching together power flow calculations at different time sections. The other approach is to carry out time-domain simulation of slow transient processes at the minute to hour level based on converged power flow results. Both approaches require a converged power flow result.

[0004] The construction of large-scale power bases in the desert and the development of offshore wind power largely rely on flexible DC islanding for power transmission. In this scenario, the DC power transmission is typically locked as a scheduling plan value, while the active power imbalance, network losses, and operational deviations within the AC system need to be absorbed or shared by the sending-end power plants. This scenario differs significantly from traditional synchronous machine-dominated power grids.

[0005] Existing traditional power flow calculation methods include: establishing a mathematical model: based on the power grid topology and parameters, forming a node admittance matrix, and establishing a set of nonlinear equations describing the balance of active and reactive power.

[0006] Set initial values ​​and iteratively solve: Set initial values ​​for the unknown node voltages, and gradually correct the voltage amplitude and phase angle by repeatedly calculating the correction equation (Jacobi matrix) until the power deviation is less than the set accuracy.

[0007] Output results: After the calculation converges, the voltage amplitude and phase angle of each node in the entire network, as well as the active and reactive power flow and network loss of all branches are obtained.

[0008] In traditional power grids, a single balancing node typically handles the power imbalance across the entire grid. However, in renewable energy islanded sending-end systems, this single-node balancing method is often not physically feasible.

[0009] The disadvantages of the existing methods described above include: 1. Directly allocating system imbalances statically based on participation factors lacks a hierarchical control logic of "prioritizing reference stations and then allocating after exceeding limits," thus making it difficult to reflect the adjustment priorities in actual operation.

[0010] 2. The default is that nodes participating in the cost-sharing are always available, and there is a lack of a unified description of the reference site boundary switching, the exit of cost-sharing sites due to exceeding limits, and the reallocation of remaining nodes.

[0011] 3. The switching chattering problem near the boundary was not explicitly considered in the solution framework. When the nodal output approaches the upper or lower limit, the numerical truncation error can easily cause the state to jump back and forth on both sides of the boundary, which can lead to non-convergence or oscillation.

[0012] 4. When allocating the active power imbalance, only the active power equation is corrected, but the reactive power follow-up problem of new energy power plants operating at constant power factor is not addressed simultaneously, which leads to the actual power factor of each power plant deviating from the set value in the final calculation results.

[0013] 5. When all allocated resources reach their limits, existing methods often lack clear infeasibility determination logic, and are prone to continuing to output distorted power flow results instead of reporting the fact that "regulatory resources are exhausted and there is no feasible solution under the current constraints" to the scheduler or computing personnel. Summary of the Invention

[0014] To address the above problems, this invention proposes a capacity-adaptive cooperative balancing power flow solution method for slow process simulation of islanded power grid systems, comprising: Obtain the system parameters of the flexible DC islanded sending-end system to be solved; Based on the system parameters, an augmented power flow equation set is constructed, including: reference station, shared station, and global relaxation variable λ. When the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balance power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved.

[0015] Optional system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

[0016] Optionally, the global slack variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

[0017] Optionally, based on the system parameters, an augmented power flow equation set is constructed, including: a reference station, shared stations, and a global relaxation variable λ, comprising: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: Nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

[0018] Optionally, when the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

[0019] Optionally, when the reference station has not exceeded its limits, the global relaxation variable λ = 0, allowing the reference station to preferentially bear the system imbalance, thus bringing the system to a natural equilibrium mode, including: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

[0020] Optionally, when the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered to lock the reference station at the corresponding boundary value and enter the cooperative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the direction of exceeding the limit and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

[0021] Optionally, when any allocation station reaches the boundary, the allocation station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factor of the remaining allocation stations is then renormalized and allocation continues. This also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

[0022] Optionally, when the activity set is empty and the remaining amount to be assigned still exceeds the threshold, an infeasibility decision is output, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting for resource depletion; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

[0023] Furthermore, this invention also proposes a capacity-adaptive cooperative balancing power flow solution system for slow process simulation of islanded power grid systems, comprising: The parameter acquisition unit is used to acquire the system parameters of the flexible DC islanding sending-end system to be solved. The modeling unit is used to construct an augmented power flow equation set including: a reference station, a shared station, and a global relaxation variable λ, based on the system parameters. The solution unit is used to perform capacity-adaptive cooperative power flow solution based on the augmented power flow equations and the slow process simulation of the flexible DC islanded sending-end system to be solved when the reference station's regulation capacity is insufficient.

[0024] Optional system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

[0025] Optionally, the global slack variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

[0026] Optionally, based on the system parameters, an augmented power flow equation set is constructed, including: a reference station, shared stations, and a global relaxation variable λ, comprising: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: Nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

[0027] Optionally, when the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

[0028] Optionally, when the reference station has not exceeded its limits, the global relaxation variable λ = 0, allowing the reference station to preferentially bear the system imbalance, thus bringing the system to a natural equilibrium mode, including: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

[0029] Optionally, when the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered to lock the reference station at the corresponding boundary value and enter the cooperative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the over-limit direction and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

[0030] Optionally, when any allocation station reaches the boundary, the allocation station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factor of the remaining allocation stations is then renormalized and allocation continues. This also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

[0031] Optionally, when the activity set is empty and the remaining amount to be assigned still exceeds the threshold, output an infeasibility decision, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting resources until they are exhausted; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

[0032] In another aspect, the present invention also provides a computing device, comprising: one or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described above is implemented.

[0033] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the method described above.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a capacity-adaptive cooperative power flow solution method for slow-process simulation of islanded DC power grid systems. The method includes: obtaining system parameters of the flexible DC islanded sending-end system to be solved; constructing an augmented power flow equation set based on the system parameters, including a reference power station, shared power stations, and a global relaxation variable λ; and, when the reference power station's regulation capacity is insufficient, performing a capacity-adaptive cooperative power flow solution based on the augmented power flow equation set for the slow-process simulation of the flexible DC islanded sending-end system. This invention solves the problem of how to achieve adaptive cooperative sharing of active power by multiple power stations, smooth handling of operational boundary switching, and maintenance of consistent power factor control among power stations in a high-proportion renewable energy flexible DC islanded sending-end system when the reference power station's regulation capacity is insufficient. It achieves a smooth and reliable transition from "single-station-dominated regulation" to "multi-station intelligent cooperation." Attached Figure Description

[0035] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a structural diagram of the system of the present invention. Detailed Implementation

[0036] Exemplary embodiments of the invention will now be described with reference to the accompanying drawings. However, the invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to fully and completely disclose the invention and to fully convey its scope to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the drawings is not intended to limit the invention. In the drawings, the same units / elements are referred to by the same reference numerals.

[0037] Unless otherwise stated, the terms used herein (including technical terms) have their common meaning as understood by one of ordinary skill in the art. Furthermore, it is understood that terms defined in commonly used dictionaries should be understood to have a meaning consistent with the context of their relevant field, and not to be interpreted as having an idealized or overly formal meaning.

[0038] Example 1: This invention proposes a capacity-adaptive cooperative balancing power flow solution method S100 for slow process simulation of islanded power grid systems, such as... Figure 1 As shown, it includes: S101, Obtain the system parameters of the flexible DC islanding sending-end system to be solved; S102, Based on the system parameters, construct an augmented power flow equation set including: reference station, shared station and global relaxation variable λ; S103, When the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balance power flow solution is performed for the slow process simulation of the flexible DC islanded sending-end system to be solved.

[0039] The system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

[0040] Among them, the global slack variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

[0041] Based on the system parameters, an augmented power flow equation set is constructed, comprising: a reference station, shared stations, and a global relaxation variable λ, including: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: Nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

[0042] Optionally, when the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

[0043] Specifically, when the reference station has not exceeded its limits, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, bringing the system to a natural equilibrium mode, including: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

[0044] Specifically, when the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering a collaborative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the over-limit direction and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

[0045] Specifically, when any participating station reaches its boundary, the station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The remaining participating stations are then re-normalized for participation factors before further allocation. This also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

[0046] When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, an infeasibility decision is output, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting resources until they are exhausted; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

[0047] The present invention will be further described below with reference to specific embodiments: The specific implementation steps include: Step 1: Obtain the node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value of the flexible DC islanded sending-end system to be solved; Step 2: Construct an augmented power flow equation set that includes the reference station, the shared station, and the global slack variable λ; A global scalar λ is introduced to characterize the total active power imbalance of the system. Its physical meaning is the power correction ratio of each adjustable point relative to the baseline scheduling plan.

[0048] Define the set of system nodes as Ω, and the set of nodes with active power regulation capability as Ω. adj , and Ω adj ⊂Ω; and for each node i∈Ω adj Allocation normalized participation factor β i It satisfies the following: Where, β i This represents the weighting of unbalanced active power among adjustable resources. Based on different engineering assumptions, three typical setting methods can be adopted: 1) Proportional allocation, meaning each participating node bears the same share; 2) Fixed ratio allocation, that is, allocation according to a pre-given station weight or scheduling ratio; The active power injection equation for node i is modified to be a function of the global relaxation variable λ, as follows: Among them, P i base S is the baseline scheduling power for node i. base β is the system baseline capacity. i Let be the participation factor of node i.

[0049] Reactive power servo guarantee based on equation coupling In traditional distributed relaxation methods, if only the active power equation is modified while the reactive power equation remains unchanged, the active power of renewable energy units will adjust with λ while the reactive power remains constant, thus violating the power factor constraint. Therefore, this paper uses embedded coupled modeling to simultaneously incorporate renewable energy nodes into both the active power balance equation and the power factor constraint equation: Although the slack variable λ appears only explicitly in the work equation, the joint solution mechanism of the NR method guarantees that both of the above equations are satisfied at the convergence point, thus necessarily having: Therefore, without the need for manual adjustment of the reactive power setpoint, the algorithm can automatically find a new equilibrium point, ensuring that reactive power accurately follows changes in active power after including network loss amortization. Mathematically, this process fully preserves the total differential properties of the coupled equations with respect to V and θ, physically guarantees a constant power factor, and numerically inherits the convergence advantages under weak network conditions.

[0050] Step 3: When the reference station has not exceeded the limit, set λ = 0, and the reference station shall take priority in bearing the system imbalance, and the system shall be in a natural equilibrium mode. The system's active power balance is entirely absorbed by the calculated active power results from the reference station, while the allocated stations maintain their base planned output. This mode is suitable for operating conditions where the system imbalance is small and the reference station has not yet reached its upper or lower limits.

[0051] If the active power calculation value of the reference station is denoted as P r c The criterion under the natural equilibrium model is: Where ε is the hysteresis threshold. When the above conditions are met, the system continues to maintain the natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus the hysteresis threshold or falls below the lower limit minus the hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the cooperative amortization mode; When a node touches or exceeds the boundary, its output is locked at the boundary value, and the remaining imbalance is shared collaboratively by activating distributed resources across the entire network according to the participation factor.

[0052] like If so, it is determined that the reference station has exceeded the upper limit; like If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: After switching to collaborative sharing mode, the reference station will no longer absorb new imbalances, but will instead maintain: In the natural equilibrium mode, if the reference station exceeds the boundary and satisfies the hysteresis criterion, it enters the cooperative sharing mode. In the cooperative sharing mode, the system is only allowed to return to the natural equilibrium mode when the sign of λ is opposite to the direction of exceeding the limit and crosses the hysteresis threshold.

[0053] For example, in the case of exceeding the upper limit, when the system is in cooperative sharing mode and d = +1, it only applies if: Only then did it exit the collaborative cost-sharing mode and revert to the natural balance mode.

[0054] For the lower bound scenario, when the system is in cooperative amortization mode and d = -1, it only applies if: Only then did they exit the collaborative cost-sharing mode.

[0055] Introducing the aforementioned hysteresis threshold can effectively prevent the reference station from repeatedly switching between “entering amortization – exiting amortization – re-entering amortization” near the boundary due to numerical errors, thereby improving the smoothness and numerical stability of the iteration process.

[0056] Step 5: Allocate the remaining active power deviation according to the participation factor of the allocating stations, and detect in real time whether each station has reached the boundary during the allocation process; Step 6: When any participating station reaches the boundary, remove it from the activity set and lock it at the boundary value. Then, renormalize the participation factor for the remaining activity stations and continue to allocate them. If all adjustable points reach their upper and lower limits, there is no feasible steady-state solution under fixed power transmission and constraints. In this case, further coordination is required through manual adjustment of the operating mode or constraint relaxation mechanism.

[0057] In the k-th iteration, the state update rule is as follows: (1) Criteria for entering the apportionment state; (2) Criteria for exiting the sharing status; When the system is in a shared state and the sign of the global relaxation variable λ is opposite to the direction of exceeding the limit, it is considered that the system imbalance has fallen back to the equipment capacity range, the lock on the active power of the reference station is released, and natural balance is restored. (3) Dynamic rearrangement of Jacobian matrix rows; In the augmented equations, the constraint rows related to power balance and their corresponding Jacobian row vectors are dynamically switched to achieve a smooth transition between single-node load-bearing and distributed relaxation. in, θ, , are the derivative vectors of the active power of the reference node with respect to the voltage phase angle and voltage magnitude, respectively.

[0058] Step 7: Solve the power factor constraint of the shared power station and the active power balance equation containing λ simultaneously, and keep the reactive power following the action. For renewable energy power plants that participate in the power factor sharing, their reactive power cannot remain unchanged after the active power changes, otherwise it will violate the constant power factor operation requirements. Therefore, this invention maintains the power factor constraint simultaneously in addition to active power sharing.

[0059] Let the target power factor of the distribution station s_i be cosφ_i, and the corresponding coupling coefficient be: During the cost-sharing process, the station satisfies the following: Or it can be written in residual form during the solution process: By combining the residual with the active power balance equation containing λ into the augmented equation system for simultaneous solution, it can be ensured that the reactive power of the power station is automatically adjusted while it undertakes the shared active power, thereby maintaining the target power factor unchanged at the convergence point.

[0060] Step 8: When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

[0061] If, after all distribution stations have reached their boundaries, there are still unabsorbed or unallocated active power deviations, then there is no feasible steady-state solution under the current fixed power transmission and capacity constraints. In this case, the present invention no longer forcibly outputs a distorted power flow solution, but instead provides an infeasibility determination.

[0062] Specifically, when the activity set is empty and the remaining amount to be allocated satisfies: The output will be: 1. Regulating resource depletion; 2. There is no feasible solution under the current boundary conditions; 3. It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

[0063] This infeasibility decision logic can prevent existing methods from continuing to produce results that lack physical meaning after resources are exhausted.

[0064] Example 2: Furthermore, this invention also proposes a capacity-adaptive cooperative balancing power flow solution system 200 for slow process simulation of islanded power grid systems, such as... Figure 2 As shown, it includes: The parameter acquisition unit 201 is used to acquire the system parameters of the flexible DC islanding sending-end system to be solved. Modeling unit 202 is used to construct an augmented power flow equation set including: reference station, shared station and global relaxation variable λ based on the system parameters; The solver unit 203 is used to perform capacity-adaptive cooperative balance power flow solution based on the augmented power flow equations and the slow process simulation of the flexible DC islanding sending-end system to be solved when the reference station's regulation capacity is insufficient.

[0065] The system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

[0066] Among them, the global slack variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

[0067] Based on the system parameters, an augmented power flow equation set is constructed, comprising: a reference station, shared stations, and a global relaxation variable λ, including: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i, via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

[0068] Optionally, when the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

[0069] Specifically, when the reference station has not exceeded its limits, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, bringing the system to a natural equilibrium mode, including: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

[0070] Specifically, when the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering a collaborative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the over-limit direction and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

[0071] Specifically, when any participating station reaches its boundary, the station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The remaining participating stations are then re-normalized for participation factors before further allocation. This also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

[0072] When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, an infeasibility decision is output, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting resources until they are exhausted; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

[0073] The implementation of this invention solves the problem of how to achieve adaptive collaborative sharing of active power among multiple stations, smooth handling of operational boundary switching, and maintaining the consistency of power factor control among stations when the reference station's regulation capability is insufficient in a high-proportion flexible DC islanded sending system. It realizes a smooth and reliable transition from "single station-dominated regulation" to "multi-station intelligent collaboration".

[0074] Example 3: Based on the same inventive concept, this invention also provides a computer device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement corresponding method flows or corresponding functions, thereby implementing the steps of the methods in the above embodiments.

[0075] Example 4: Based on the same inventive concept, this invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiments.

[0076] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0077] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0078] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0079] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0080] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0081] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A capacity-adaptive cooperative balanced power flow solution method for slow process simulation of islanded power grid systems, characterized in that, include: Obtain the system parameters of the flexible DC islanded sending-end system to be solved; Based on the system parameters, an augmented power flow equation set is constructed, including: reference station, shared station, and global relaxation variable λ. When the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balance power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved.

2. The capacity-adaptive cooperative balanced power flow solution method according to claim 1, characterized in that, The system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

3. The capacity-adaptive cooperative balanced power flow solution method according to claim 1, characterized in that, The global relaxation variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

4. The capacity adaptive cooperative balanced power flow solution method according to claim 1, characterized in that, Based on the system parameters, an augmented power flow equation set is constructed, comprising: a reference station, shared stations, and a global relaxation variable λ, including: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: Nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

5. The capacity-adaptive cooperative balanced power flow solution method according to claim 1, characterized in that, When the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

6. The capacity-adaptive cooperative balanced power flow solution method according to claim 5, characterized in that, The step of setting the global relaxation variable λ = 0 when the reference station has not exceeded its limits, allowing the reference station to take priority in bearing the system imbalance and bringing the system to a natural equilibrium mode, includes: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

7. The capacity adaptive cooperative balanced power flow solution method according to claim 5, characterized in that, When the active power calculated by the reference power station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered to lock the reference power station at the corresponding boundary value and enter the cooperative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the over-limit direction and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

8. The capacity-adaptive cooperative balanced power flow solution method according to claim 5, characterized in that, The step of removing a participating station from the activity set and locking it at the corresponding boundary value when any participating station reaches the boundary, and then re-normalizing the participation factor for the remaining participating stations before continuing allocation, also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

9. The capacity adaptive cooperative balanced power flow solution method according to claim 5, characterized in that, When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, the infeasibility decision is output, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting resources until they are exhausted; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

10. A capacity-adaptive cooperative balanced power flow solution system for slow process simulation of islanded power grid systems, characterized in that, include: The parameter acquisition unit is used to acquire the system parameters of the flexible DC islanding sending-end system to be solved. The modeling unit is used to construct an augmented power flow equation set based on the system parameters, including: a reference station, a shared station, and a global relaxation variable λ. The solution unit is used to perform capacity-adaptive cooperative power flow solution based on the augmented power flow equations and the slow process simulation of the flexible DC islanded sending-end system to be solved when the reference station's regulation capacity is insufficient.

11. The capacity-adaptive cooperative balanced power flow solution system according to claim 10, characterized in that, The system parameters include: node parameters, branch parameters, reference station capacity boundary, allocated station capacity boundary, participation factor, and DC transmission plan value.

12. The capacity-adaptive cooperative balanced power flow solution system according to claim 10, characterized in that, The global relaxation variable λ is used to characterize the total active power imbalance of the system, and is physically defined as the power correction ratio of each adjustable point relative to the baseline scheduling plan.

13. The capacity-adaptive cooperative balanced power flow solution system according to claim 10, characterized in that, Based on the system parameters, an augmented power flow equation set is constructed, comprising: a reference station, shared stations, and a global relaxation variable λ, including: Define the system node set as Among them, the set of nodes with active power regulation capability is: , and for each node Assignment of normalized participation factors , The following conditions must be met: node The active power injection equation is modified to The function is as follows: in, As the baseline scheduling power, As the system's baseline capacity, Let be the participation factor of node i; Based on embedded coupling modeling: Nodes Simultaneously incorporating the active power balance equation and the power factor constraint equation, the expression is as follows: At the convergence point, the active power balance equation and the power factor constraint equation together satisfy the following follow-up relationship: in, Let i be the active power balance residual. The power factor coupling residual of the i-th cosφ-θ node; For node i via global slack variables The corrected active power setpoint; and These are respectively the current voltage magnitude vector and voltage phase angle vector The calculated values ​​of active and reactive power injection at node i are obtained from the following calculations. The active-reactive coupling coefficient is obtained by converting the target power factor.

14. The capacity-adaptive cooperative balanced power flow solution system according to claim 10, characterized in that, When the reference station's regulation capacity is insufficient, based on the augmented power flow equations, a capacity-adaptive cooperative balanced power flow solution is performed for the slow-process simulation of the flexible DC islanded sending-end system to be solved, including: When the reference station does not exceed the limit, the global relaxation variable λ = 0, and the reference station takes priority in bearing the system imbalance, so that the system is in a natural equilibrium mode. When the active power calculated by the reference station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered, locking the reference station at the corresponding boundary value and entering the collaborative sharing mode. The remaining active power deviation is allocated based on the participation factor of the allocating stations, and each station is monitored in real time during the allocation process to see if it reaches the boundary. When any sub-station reaches the boundary, the sub-station that reached the boundary is removed from the activity set and locked at the corresponding boundary value. The participation factors of the remaining sub-stations are then re-normalized and the allocation continues. Solve the power factor constraints of the remaining allocated power stations and the active power balance equations containing λ in a unified manner, while maintaining reactive power responsiveness. When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, output an infeasibility decision; otherwise, output the power flow calculation result when the convergence condition is met.

15. The capacity-adaptive cooperative balanced power flow solution system according to claim 14, characterized in that, The step of setting the global relaxation variable λ = 0 when the reference station has not exceeded its limits, allowing the reference station to take priority in bearing the system imbalance and bringing the system to a natural equilibrium mode, includes: If the active power calculation value of the reference station is denoted as The hysteresis criterion under the natural equilibrium mode is: in, The hysteresis threshold, For reference, the lower limit of active power at the station. For reference, the maximum active power capacity of the station; If the hysteresis criterion is met, the system continues to maintain its natural equilibrium mode.

16. The capacity-adaptive cooperative balanced power flow solution system according to claim 14, characterized in that, When the active power calculated by the reference power station exceeds the upper limit plus hysteresis threshold or falls below the lower limit minus hysteresis threshold, a state machine switch is triggered to lock the reference power station at the corresponding boundary value and enter the cooperative allocation mode, including: When the reference station reaches or exceeds the boundary, the output of the reference station will be locked at the boundary value. The remaining imbalance will be shared by activating the distributed resources of the entire network and coordinating according to the participation factor. like > + If so, it is determined that the reference station has exceeded the upper limit; like < - If so, it is determined that the reference station has exceeded the lower limit; When an upper limit violation occurs, the reference station will be locked at the upper boundary: When a lower limit breach occurs, the reference station will be locked at the lower boundary: Once the system is in collaborative sharing mode, the reference station will no longer absorb any new imbalances. In the natural equilibrium mode, if the reference station exceeds the boundary and meets the hysteresis criterion, it will enter the collaborative sharing mode. In the cooperative sharing mode, when the sign of λ is opposite to the over-limit direction and crosses the hysteresis threshold, the system is allowed to return to the natural equilibrium mode.

17. The capacity-adaptive cooperative balanced power flow solution system according to claim 14, characterized in that, The step of removing a participating station from the activity set and locking it at the corresponding boundary value when any participating station reaches the boundary, and then re-normalizing the participation factor for the remaining participating stations before continuing allocation, also includes: If all adjustable distribution stations reach their upper and lower limits, then there is no feasible steady-state solution under the fixed power transmission and constraints. In this case, the relaxation mechanism can be further coordinated by adjusting the system operation mode or constraints.

18. The capacity-adaptive cooperative balanced power flow solution system according to claim 14, characterized in that, When the activity set is empty and the remaining amount to be allocated still exceeds the threshold, the infeasibility decision is output, including: When the activity set is empty and the remaining amount to be allocated satisfies: The output will be: Adjusting resources until they are exhausted; There is no feasible solution under the current boundary conditions; It is necessary to adjust the operating mode, relax constraints, or modify the delivery plan.

19. A computer device, characterized in that, include: One or more processors; A processor is used to execute one or more programs; When the one or more programs are executed by the one or more processors, the method described in any one of claims 1-9 is implemented.

20. A computer-readable storage medium, characterized in that, It contains a computer program, which, when executed, implements the method as described in any one of claims 1-9.

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