A virtual power plant aggregation resource coordination method and system, medium and product

Abstract

A method, system, medium, and product for virtual power plant resource aggregation and coordination are disclosed, relating to the field of power system operation and control. Implementing this method, the control system first collects the real-time output and physical constraints of each resource unit, calculates the instantaneous adjustable capacity range, and then, combining the electrical topology and real-time power flow of the power grid, constructs a dynamic coupling matrix between units through disturbance response. Based on this, the capacity range is modified to form a feasible adjustment domain that balances equipment constraints and grid coupling safety, eliminating the risk of exceeding limits. Subsequently, within the feasible adjustment domain, with the goal of meeting the power demand of grid dispatch and maximizing the minimum remaining adjustment space of each resource unit, a coordinated output allocation solution is solved. Finally, commands are issued in ascending order of coupling influence strength to achieve safe, balanced, and stable multi-resource coordinated output, avoiding line congestion and voltage exceeding limits caused by synchronous adjustment of multiple resource units from the source, thus improving the response reliability of the virtual power plant and the operational safety of the power grid.

Description

Technical Field

[0001] This application relates to the field of power system operation control, and in particular to a method, system, medium and product for virtual power plant resource aggregation and coordination. Background Technology

[0002] With the continuous development of power systems, various energy sources, such as distributed power sources, energy storage devices, and flexible loads, are being connected to the power grid in large quantities. Virtual power plants, as a regional centralized energy management model, can integrate geographically dispersed energy sources, coordinate and optimize them, and participate in grid operation and dispatch as a unified power plant. In actual operation, the key to ensuring stable interaction between the virtual power plant and the power grid lies in how to rationally allocate the total dispatch power demand from the grid to various aggregated resources within the virtual plant, and achieve multi-resource collaborative output control.

[0003] For the power output allocation problem within a virtual power plant, most related technologies adopt an independent allocation strategy based on static capacity declaration. Each resource unit first reports its maximum and minimum output static operating range to the control center based on its rated equipment parameters and current operating status. The control center linearly superimposes these independent boundaries to obtain the overall adjustable capacity range of the virtual power plant. Upon receiving power dispatch instructions from the power grid, the control center typically performs optimization calculations with the goal of minimizing total operating costs or based on a fixed proportion of the declared capacity of each resource unit, deriving the output target for each resource unit, and then uniformly issues instructions to complete the power allocation.

[0004] However, the above method has revealed significant safety hazards in practical applications. Because each resource unit is treated as an electrically independent node when allocating power, relying entirely on its own static physical boundaries, when multiple resource units on the same feeder or close by electrical distance simultaneously respond to dispatch commands and adjust their output, their power changes will generate a strong physical superposition effect in the underlying distribution network. This physical superposition effect, during periods of high grid load or high proportion of renewable energy integration, can easily cause the power flow of local distribution lines to exceed thermal stability limits or node voltages to deviate from safe ranges, seriously threatening the safe and stable operation of the power grid. Summary of the Invention

[0005] This application provides a method, system, medium, and product for virtual power plant resource aggregation and collaboration, which can improve the response reliability of virtual power plants and the safety of power grid operation.

[0006] Firstly, this application provides a virtual power plant resource aggregation and coordination method applied to a control system. The method includes: collecting the actual output value and physical operating constraints of each resource unit; using the actual output value as the current operating point and combining it with the physical operating constraints, calculating the instantaneous adjustable capacity range of each resource unit, where the instantaneous adjustable capacity range represents the closed interval defined by the maximum output adjustment amount that the resource unit can adjust upwards and downwards; acquiring the electrical topology connection relationship of each resource unit connected to the power grid and the real-time power flow distribution data of the power grid; and calculating the disturbance response of the instantaneous adjustable capacity range of each resource unit based on the electrical topology connection relationship and the real-time power flow distribution data to obtain the inter-unit dynamic coupling matrix, where the inter-unit dynamic coupling matrix represents the effect of any change in the output of a resource unit on its... The influence of the instantaneous adjustable capacity range boundary of the resource unit is assessed; based on the inter-unit dynamic coupling matrix, the coupling constraint of the instantaneous adjustable capacity range is corrected to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. The feasible adjustment domain is used to exclude infeasible adjustment combinations that cause line capacity or voltage to exceed limits due to simultaneous adjustment by multiple resource units; power grid dispatch power demand constraints are introduced into the feasible adjustment domain to solve the collaborative output allocation solution that satisfies the power grid dispatch power demand and maximizes the minimum remaining adjustment space of each resource unit in the corresponding instantaneous adjustable capacity range; based on the inter-unit dynamic coupling matrix, the coupling influence strength of each resource unit is calculated, and the collaborative output allocation solution is sequentially distributed according to the order of low to high coupling influence strength.

[0007] By adopting the above technical solutions, the control system incorporates the grid coupling effect between resource units into the core link of collaborative optimization, fundamentally solving the problems of line power flow exceeding limits and voltage exceeding limits caused by the neglect of resource electrical coupling in traditional static allocation strategies. While meeting the power demand of grid dispatch, it maximizes the retention of adjustment redundancy of each resource unit, and improves the safety, stability and robustness of the virtual power plant aggregation response.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, based on electrical topology connections and real-time power flow distribution data, disturbance response calculations are performed on the instantaneous adjustable capacity range of each resource unit to obtain an inter-unit dynamic coupling matrix. This inter-unit dynamic coupling matrix represents the degree of influence of any resource unit's output change on the boundaries of other resource units' instantaneous adjustable capacity ranges. Specifically, this includes: identifying the core congested branch and voltage-sensitive node in the power grid closest to its operating limit based on electrical topology connections and real-time power flow distribution data; applying a unit output disturbance to each resource unit at the current operating point; calculating the sensitivity coefficient of the unit output disturbance to the power flow of the core congested branch and the voltage of the voltage-sensitive node; calculating the regulation capacity crowding-out ratio when different resource units jointly affect the same core congested branch or voltage-sensitive node based on the sensitivity coefficient; and using the regulation capacity crowding-out ratio as matrix elements to construct the inter-unit dynamic coupling matrix.

[0009] By adopting the above technical solutions, the control system can accurately quantify the impact of power output changes of each resource unit on weak links in the power grid and the adjustable capacity of other resource units. It transforms the abstract physical coupling of the power grid into calculable and applicable matrix data, providing a precise quantitative basis for subsequent coupling constraint correction. This allows the virtual power plant to better align its judgment on the coupling relationship between resources with the real-time operating status of the power grid, significantly improving the accuracy and relevance of coupling analysis.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, based on the inter-unit dynamic coupling matrix, the instantaneous adjustable capacity range is modified by coupling constraints to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. The feasible adjustment domain is used to exclude infeasible adjustment combinations that would cause line capacity or voltage to exceed limits due to simultaneous adjustment by multiple resource units. Specifically, this includes: extracting the adjustment capacity squeezing ratio in the inter-unit dynamic coupling matrix; for any two first and second resource units with a coupling relationship, determining whether the influence directions of the first and second resource units on the same core congestion branch or voltage-sensitive node are consistent; if so, using the adjustment capacity squeezing ratio, reducing and compressing the same-direction boundary of the instantaneous adjustable capacity range of the first and second resource units to obtain a safe boundary condition; and performing an intersection operation between the instantaneous adjustable capacity range of each resource unit and the safe boundary condition to generate a feasible adjustment domain, so as to ensure that any output combination within the feasible adjustment domain will not trigger the exceeding of limits of the core congestion branch and voltage-sensitive node.

[0011] By adopting the above technical solutions, the power grid security risks caused by the simultaneous regulation of multiple resources are avoided from the source. It not only strictly adheres to the physical operation boundaries of each resource unit, but also fully adapts to the overall physical coupling constraints of the power grid, achieving bidirectional compatibility between resource coordination within the virtual power plant and safe operation of the power grid.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, a power demand constraint for grid dispatch is introduced within the feasible adjustment domain. The solution is then used to find a coordinated output allocation solution that satisfies the power demand for grid dispatch and maximizes the minimum remaining adjustment space of each resource unit within its corresponding instantaneous adjustable capacity interval. Specifically, this includes: determining an auxiliary margin variable reflecting the remaining adjustment space of the resource unit; constructing an objective function that maximizes the auxiliary margin variable; setting a first constraint, a second constraint, and a third constraint. The first constraint limits the sum of the output allocation values ​​of each resource unit to equal the power demand for grid dispatch; the second constraint limits the output allocation values ​​of each resource unit to be within the feasible adjustment domain; and the third constraint limits the remaining adjustment space of any resource unit within its corresponding instantaneous adjustable capacity interval to be greater than or equal to the auxiliary margin variable. Under the premise of satisfying the first, second, and third constraints, the objective function is solved to obtain the output allocation values ​​of each resource unit as the coordinated output allocation solution.

[0013] By adopting the above technical solutions, under the premise of meeting the power dispatch command of the power grid, the minimum remaining adjustment space of each resource unit is maximized, the adjustment redundancy is evenly distributed, and the loss of response elasticity of a single resource unit due to the exhaustion of adjustment space is avoided. This effectively improves the continuous adjustment capability of the virtual power plant in response to sudden disturbances and continuous dispatch, and ensures that the collaborative power output allocation scheme has a stronger safety margin and anti-disturbance performance.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the coupling influence strength of each resource unit is calculated based on the inter-unit dynamic coupling matrix, and the coordinated output allocation solution is sequentially distributed according to the order of low to high coupling influence strength. Specifically, this includes: summing the row vectors or column vectors of the inter-unit dynamic coupling matrix to obtain the coupling influence strength of each resource unit; dividing each resource unit into multiple distribution batches according to the order of low to high coupling influence strength; when distributing the corresponding output allocation value to the resource unit of the current distribution batch, calculating the reserved grid crossing capacity required for the undistributed batches based on the inter-unit dynamic coupling matrix and the output allocation values ​​of the resource units in the undistributed batches; using the reserved grid crossing capacity as an additional constraint, verifying and dynamically correcting the output allocation value of the current distribution batch before distributing, until all distribution batches are distributed.

[0015] By adopting the above technical solutions, the coupled impact on the power grid caused by the simultaneous operation of multiple resource units can be reduced in an orderly manner, preventing line congestion and voltage over-limit caused by centralized regulation. While ensuring the accurate execution of dispatching instructions, the stability of the virtual power plant control process and the safety of power grid operation can be improved.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after calculating the coupling influence strength of each resource unit based on the inter-unit dynamic coupling matrix, and sequentially issuing control to the collaborative output allocation solution according to the order of low to high coupling influence strength, the method further includes: real-time monitoring of the actual response output value of each resource unit after executing the collaborative output allocation solution; calculating the output execution deviation between the actual response output value and the collaborative output allocation solution; when the absolute value of the output execution deviation is greater than a preset tolerance threshold, triggering a closed-loop compensation control mechanism, generating an error compensation allocation instruction based on the current remaining adjustment space of each resource unit and the inter-unit dynamic coupling matrix, and issuing it for execution.

[0017] By adopting the above technical solutions, a complete closed-loop control process is formed, from optimized allocation to instruction issuance to real-time monitoring and deviation compensation. This process promptly corrects output execution errors, ensuring that the overall output of the virtual power plant always aligns with the grid dispatch requirements, and significantly improves the accuracy of aggregated resource response and control reliability.

[0018] In some embodiments of the first aspect, when the absolute value of the output execution deviation exceeds a preset tolerance threshold, a closed-loop compensation control mechanism is triggered. Based on the current remaining adjustment space of each resource unit and the dynamic coupling matrix between units, an error compensation allocation instruction is generated and issued for execution. Specifically, this includes: identifying the defaulting resource unit that generates the output execution deviation and locking the current actual output state of the defaulting resource unit; selecting candidate compensation units with a current remaining adjustment space greater than zero from the resource units other than the defaulting resource units; evaluating the degree of secondary coupling impact of each candidate compensation unit on the core blocking branch and voltage-sensitive node when bearing the output execution deviation, based on the dynamic coupling matrix between units; and redistributing the output execution deviation within the feasible adjustment domain of the candidate compensation units with the goal of minimizing the degree of secondary coupling impact, thereby obtaining and issuing the error compensation allocation instruction.

[0019] By adopting the above technical solution, the deviation is redistributed within the feasible adjustment range with the goal of minimizing the impact of secondary coupling. This can not only quickly make up for the output gap, but also minimize the secondary disturbances and safety risks to weak links in the power grid during the compensation process. While achieving rapid error correction, the stability of the power grid operation is maintained, ensuring the safety and effectiveness of the closed-loop compensation control of the virtual power plant.

[0020] In a second aspect, embodiments of this application provide a control system comprising: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, wherein the one or more processors invoke the computer instructions to cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a control system, cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a control system, cause the control system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the control system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting the above technical solution, the control system incorporates the grid coupling effect between resource units into the core link of collaborative optimization, fundamentally solving the problems of line power flow exceeding limits and voltage exceeding limits caused by the neglect of resource electrical coupling in the traditional static allocation strategy. While meeting the power demand of grid dispatch, it maximizes the retention of adjustment redundancy of each resource unit, and improves the safety, stability and robustness of the virtual power plant aggregation response.

[0026] 2. By adopting the above technical solutions, the control system can accurately quantify the impact of power output changes of each resource unit on weak links of the power grid and the adjustable capacity of other resource units. It transforms the abstract physical coupling of the power grid into calculable and applicable matrix data, providing accurate quantitative basis for subsequent coupling constraint correction. This allows the virtual power plant to better align its judgment on the coupling relationship between resources with the real-time operating status of the power grid, significantly improving the accuracy and relevance of coupling analysis.

[0027] 3. By adopting the above technical solutions, under the premise of meeting the power dispatch command of the power grid, the remaining adjustment space of each resource unit is maximized to achieve the minimum value, the adjustment redundancy is evenly distributed, and the loss of response elasticity of a single resource unit due to the exhaustion of adjustment space is avoided. This effectively improves the continuous adjustment capability of the virtual power plant in response to sudden disturbances and continuous dispatch, and ensures that the collaborative power output allocation scheme has a stronger safety margin and anti-disturbance performance. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a virtual power plant resource aggregation and collaboration method in an embodiment of this application.

[0029] Figure 2 This is another flowchart illustrating the virtual power plant resource aggregation and collaboration method in this application embodiment;

[0030] Figure 3 This is a schematic diagram of the physical device structure of a control system in an embodiment of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a virtual power plant resource aggregation and collaboration method in an embodiment of this application.

[0034] S101. Collect the actual output value and physical operating constraints of each resource unit respectively;

[0035] In this context, a resource unit refers to various distributed energy devices managed by the virtual power plant, including distributed photovoltaic power stations, wind turbine generators, energy storage devices, and flexible adjustable loads. Each resource unit is connected to the power grid as an independent power regulation entity and is subject to unified scheduling by the control system. Actual output value represents the real-time active power that a resource unit is injecting into or absorbing from the grid at the current acquisition moment. For example, if an energy storage device is currently discharging 200kW into the grid, its actual output value is 200kW. Physical operating constraints refer to the set of operating boundary parameters determined by the resource unit's own equipment characteristics and safety regulations. These include hard constraints such as the upper limit of rated maximum output, the lower limit of rated minimum output, the maximum power change rate (ramp rate), the current state of charge (for energy storage devices), and the allowed continuous operating time of the equipment.

[0036] Specifically, when the power grid issues dispatch instructions or enters a periodic collaborative optimization control process, the control system first grasps the current operating status and equipment capacity boundaries of each resource unit. Through data channels established with intelligent terminals, SCADA systems, or communication gateways deployed in each resource unit, the control system reads the current active power output measurement value of each resource unit in real time, and simultaneously acquires the physical operating constraint parameters of the equipment reported by each resource unit or pre-registered in the database. The control system performs integrity verification and rationality screening on the collected data, eliminating invalid samples with communication anomalies or data exceeding limits.

[0037] S102. Using the actual output value as the current operating point, and in conjunction with the physical operating constraints, calculate the instantaneous adjustable capacity range of each resource unit. The instantaneous adjustable capacity range represents the closed interval defined by the maximum output adjustment amount that the resource unit can increase upward and decrease downward.

[0038] The current operating point represents the reference point for the actual output state of the resource unit at the moment of calculation, i.e., the operating state corresponding to the actual output value. Subsequent adjustment capabilities are all calculated based on this operating point. The instantaneous adjustable capacity range refers to the closed interval defined by the maximum adjustment amount that the resource unit can increase or decrease its output at the current moment, centered on the current operating point and taking into account the physical operating constraints of the resource unit. Its upper boundary is the adjustable increment between the current operating point and the maximum allowable output, and its lower boundary is the adjustable decrement between the current operating point and the minimum allowable output. For example, if a certain energy storage device currently has an actual output of 200kW, a rated maximum discharge power of 500kW, a rated minimum discharge power of 0kW, and the current remaining power can only support a maximum additional discharge power of 150kW, then the instantaneous adjustable capacity range of the energy storage device is [-200kW, +150kW], indicating that it can be reduced by a maximum of 200kW (down to 0kW) or increased by a maximum of 150kW (up to 350kW).

[0039] Specifically, after the control system collects the actual output value and physical operating constraints of each resource unit, it needs to transform the static equipment parameters into a dynamic range reflecting the actual available adjustable capacity at the current moment. The control system anchors the actual output value of each resource unit as the current operating point and compares this point with each boundary parameter in the physical operating constraints: For upward adjustment, the difference between the current operating point and the maximum output limit is taken, and this difference is compared with the minimum value among dynamic constraints such as the maximum allowable increment of the ramp rate constraint within the control cycle and the remaining discharge capacity of the energy storage device, to determine the actual adjustable upper limit; for downward adjustment, the difference between the current operating point and the minimum output limit is taken, and this difference is compared with the minimum value among dynamic constraints such as the maximum allowable decrease of the maximum descent rate constraint within the control cycle and the remaining rechargeable capacity of the energy storage device, to determine the actual adjustable lower limit. These two boundaries together constitute the instantaneous adjustable capacity range of the resource unit. The control system performs the above calculations for all resource units one by one, forming an independent instantaneous adjustable capacity range for each resource unit.

[0040] S103. Obtain the electrical topology connection relationship of each resource unit connected to the power grid and the real-time power flow distribution data of the power grid;

[0041] Electrical topology refers to the physical wiring structure and location information of each resource unit in the distribution network, including the bus node number to which each resource unit is connected, the feeder line it is connected to, the status of the transformers and switches it passes through, and the electrical path relationship with other resource units. For example, resource unit A is connected to the 3rd bus node of 10kV feeder F1, and resource unit B is connected to the 5th bus node of the same feeder F1. Both share the same upstream trunk line segment. Real-time power flow distribution data represents the measured or estimated data of active power, reactive power, voltage amplitude, and phase angle of each bus node and other electrical state quantities flowing through each branch of the power grid at the current operating moment. It is used to reflect the current power flow state and voltage level of the power grid. For example, the current power flow of the trunk line segment of feeder F1 is 800kW, while its thermal stability limit is 1000kW, and the voltage of the 3rd bus node is 10.15kV. The power grid refers to the distribution network system to which each resource unit is connected, and it is the physical carrier for the electrical coupling effect between resource units.

[0042] Specifically, after the control system completes the independent calculation of the instantaneous adjustable capacity range of each resource unit, in order to assess the coupling effects on the power grid caused by the simultaneous adjustment of multiple resource units, the control system needs to understand the physical connection relationships between resource units and the current operating status of the power grid. The control system reads the latest electrical topology connection data from the power grid dispatch management system or distribution management system, including network node numbers, branch connection relationships, transformer parameters, and current switch opening and closing states, to construct a topology model reflecting the actual operating wiring of the current power grid. Simultaneously, the control system acquires real-time power flow distribution data, such as active power flow, reactive power flow, and voltage amplitude at each node, through the SCADA system or state estimation calculations. The combination of these two types of data enables the control system to accurately identify the relative electrical positions of each resource unit in the power grid, determine which resource units share the same transmission channel or affect the same voltage node, and quantify the margin levels of each branch and node of the current power grid from their operating limits, providing necessary grid-side data support for subsequent disturbance response calculations and the construction of dynamic coupling matrices between units.

[0043] S104. Based on the electrical topology connection relationship and real-time power flow distribution data, the disturbance response of the instantaneous adjustable capacity range of each resource unit is calculated to obtain the dynamic coupling matrix between units. The dynamic coupling matrix between units represents the degree of influence of the output change of any resource unit on the boundary of the instantaneous adjustable capacity range of other resource units.

[0044] Optionally, under normal circumstances, based on the electrical topology connections and real-time power flow distribution data, disturbance response calculations are performed on the instantaneous adjustable capacity range of each resource unit to obtain the inter-unit dynamic coupling matrix. The inter-unit dynamic coupling matrix represents the degree of influence of any resource unit's output change on the boundary of the instantaneous adjustable capacity range of other resource units. This can be achieved in the following ways, without limitation: Based on the electrical topology connections and real-time power flow distribution data, identify the core congested branch and voltage-sensitive node in the power grid that are closest to the operating limit; at the current operating point, apply a unit output disturbance to each resource unit respectively; calculate the sensitivity coefficient of the unit output disturbance to the power flow of the core congested branch and the voltage of the voltage-sensitive node; based on the sensitivity coefficient, calculate the regulation capacity crowding ratio when different resource units jointly affect the same core congested branch or voltage-sensitive node, and use the regulation capacity crowding ratio as matrix elements to construct the inter-unit dynamic coupling matrix.

[0045] Disturbance response calculation refers to applying a small output change (i.e., a unit output disturbance) to each resource unit at the current operating point, and then analyzing the response changes to the power flow of each branch and the voltage of each node after the output change propagates in the power grid through power flow calculation, thereby quantifying the impact of resource unit output regulation on the power grid state. The inter-unit dynamic coupling matrix is ​​a square matrix with resource units as row and column indices. Each matrix element represents the degree of crowding out or release of the instantaneous adjustable capacity range boundary of another resource unit caused by a unit output change in one resource unit through physical propagation in the power grid. For example, matrix element M(i,j) represents the proportion by which the adjustable upper bound of resource unit j is compressed when resource unit i increases its output by 1kW due to the occupancy of shared line capacity. A core congested branch refers to the transmission line or transformer branch in the power grid whose current power flow level is closest to its thermal stability limit; that is, the branch with the smallest remaining transmission capacity margin and most prone to power flow exceeding limits due to resource unit output regulation. A voltage-sensitive node is a bus node in a power grid whose current voltage amplitude is closest to its allowable upper or lower operating limit. In other words, it is the node with the smallest voltage margin and most susceptible to voltage overshooting due to changes in power injection from resource units. The sensitivity coefficient is the ratio of the change in power flow in a specific branch or the change in voltage at a specific node caused by a unit change in active power injected by a resource unit at the current operating point. It reflects the linear mapping relationship between power changes and changes in grid state. For example, a sensitivity coefficient of 0.6 MW / MW for resource unit A means that for every 1 MW increase in A's output, the power flow in a core congested branch increases by 0.6 MW. The capacity occupancy ratio refers to the ratio by which the output adjustment of one resource unit, when two or more resource units jointly affect the same core congested branch or voltage-sensitive node, effectively compresses the actual usable adjustment capacity boundary of the other resource unit by occupying the shared remaining transmission capacity or voltage margin space of the line. For example, if resource units A and B share a line with a remaining capacity of 100kW, and A's sensitivity coefficient is 0.6 and B's sensitivity coefficient is 0.4, then every 1kW increase in A's capacity will occupy an equivalent space of 0.6 / 0.4 = 1.5kW of B's ​​adjustable capacity.

[0046] Specifically, after the control system acquires the electrical topology connections and real-time power flow distribution data, it needs to quantitatively evaluate the coupling effects between various resource units through the physical connection of the power grid. First, based on the electrical topology connections and real-time power flow distribution data, the control system compares the current power flow value of each branch with its thermal stability limit, and compares the current voltage amplitude of each node with its allowable operating range. It then selects the core congested branches with the smallest remaining margin and those closest to the operating limit as key monitoring objects for coupling analysis. Subsequently, at the current operating point, the control system sequentially applies a standard unit output disturbance to each resource unit. Using linearized power flow calculations or DC power flow approximation methods, it calculates the power flow increment caused by this unit disturbance on each core congested branch and the voltage offset caused by it on each voltage-sensitive node, obtaining the sensitivity coefficient of each resource unit to each key monitoring object. Based on this, the control system compares the sensitivity coefficients of different resource units to the same core congested branch or voltage-sensitive node, calculates the regulation capacity crowding ratio between them, that is, the proportional relationship in which one resource unit effectively compresses the adjustable capacity boundary of another resource unit by occupying the shared grid margin space when adjusting a unit output. These crowding ratios are then filled in as matrix elements to construct a complete dynamic coupling matrix between units. This matrix comprehensively reflects the capacity coupling relationship between all resource units through the physical channels of the grid, providing a precise quantitative basis for the subsequent correction of coupling constraints in the instantaneous adjustable capacity range.

[0047] S105. Based on the dynamic coupling matrix between units, the coupling constraint of the instantaneous adjustable capacity range is corrected to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. The feasible adjustment domain is used to exclude infeasible adjustment combinations that cause the line capacity or voltage to exceed the limit due to the simultaneous adjustment of multiple resource units.

[0048] Optionally, under normal circumstances, based on the inter-unit dynamic coupling matrix, the instantaneous adjustable capacity range is modified by coupling constraints to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. The feasible adjustment domain is used to exclude infeasible adjustment combinations that cause line capacity or voltage to exceed limits due to simultaneous adjustment by multiple resource units. This can be achieved in the following ways, without limitation: extract the adjustment capacity squeezing ratio in the inter-unit dynamic coupling matrix; for any two first and second resource units with coupling relationships, determine whether the influence directions of the first and second resource units on the same core congestion branch or voltage sensitive node are consistent; if so, use the adjustment capacity squeezing ratio to reduce and compress the same-direction boundary of the instantaneous adjustable capacity range of the first and second resource units to obtain the safety boundary condition; perform an intersection operation on the instantaneous adjustable capacity range of each resource unit and the safety boundary condition to generate a feasible adjustment domain, so as to ensure that any output combination within the feasible adjustment domain will not trigger the exceeding of limits of the core congestion branch and voltage sensitive node.

[0049] Among them, coupling constraint correction refers to using the capacity crowding relationship between resource units indicated by the inter-unit dynamic coupling matrix to further tighten or reduce the boundary of the instantaneous adjustable capacity range originally calculated by each resource unit based only on its own physical operation constraints, so that the corrected adjustment range simultaneously reflects the limitations of the equipment itself and the physical coupling constraints of the power grid. The physical operation constraints of the unit itself refer to the output boundary conditions determined by the equipment parameters and operating procedures of the resource unit itself, that is, the physical operation constraints collected in step S101, including maximum and minimum output limits, ramp rate limits, energy storage state of charge constraints, etc. The physical coupling constraints between units refer to the mutual constraints generated by multiple resource units sharing the physical channels of the power grid, that is, when multiple resource units adjust their output at the same time, their power changes are superimposed and propagated in the power grid, forming a joint security constraint on the shared line capacity and shared node voltage. The feasible adjustment domain refers to the set of safe output combinations that, after coupling constraint correction, simultaneously satisfy the physical operation constraints of each resource unit and the physical coupling constraints of the power grid between all resource units in the multi-dimensional space formed by the output adjustment amounts of all resource units. Any output combination within this domain will not cause any branch power flow to exceed its limit or any node voltage to exceed its limit in the power grid. An infeasible adjustment combination refers to an output combination scheme where, although the output adjustment amount of each resource unit is individually within its own instantaneous adjustable capacity range, the superposition effect of its power changes in the power grid when multiple resource units simultaneously utilize this adjustment amount would cause the power flow of a certain line to exceed the thermal stability limit or the voltage of a certain node to exceed the allowable operating range. The safety boundary condition refers to the linear inequality constraint obtained by reducing and compressing the instantaneous adjustable capacity range boundary of resource unit pairs with unidirectional coupling influence according to the adjustment capacity crowding ratio. It is used to limit the joint adjustment amount of coupled resource units to the safe carrying capacity of the shared power grid margin space. Consistent influence direction refers to the fact that the output adjustment of two resource units has the same effect on the same core congested branch or voltage-sensitive node. For example, if both increase their output simultaneously, it will lead to an increase in power flow on a certain line or a rise in voltage at a certain node, resulting in a superimposed deterioration effect. Reduction and compression refers to proportionally reducing the boundary values ​​in the instantaneous adjustable capacity range that are consistent with the direction of coupled influence, according to the regulation capacity occupancy ratio, to reserve shared grid margin space occupied by the regulation of other coupled resource units. Intersection operation refers to taking the common overlap between the reduced and compressed safety boundary conditions of each resource unit and the original instantaneous adjustable capacity range, ensuring that the final feasible regulation domain simultaneously meets the most stringent requirements of both types of constraints.

[0050] Specifically, after the control system completes the construction of the inter-unit dynamic coupling matrix, it needs to transform the coupling relationships between resource units revealed in the inter-unit dynamic coupling matrix into actual corrections to the instantaneous adjustable capacity range of each resource unit. The control system first extracts the regulation capacity squeeze ratio between each pair of resource units from the inter-unit dynamic coupling matrix. Then, the control system traverses all resource unit pairs with non-zero coupling relationships. For any two coupled first and second resource units, it determines whether their influence directions on the same core congested branch or voltage-sensitive node are consistent. If the output regulation of both will have a unidirectional superposition effect on the same weak link in the power grid, then the regulation capacity squeeze ratio is used to reduce and compress the unidirectional boundary of their instantaneous adjustable capacity ranges, generating a safety boundary condition reflecting the upper limit of joint regulation safety, i.e., limiting the total joint regulation of both in this direction to not exceed the carrying capacity of the shared power grid margin space. The control system summarizes all safety boundary conditions generated by coupling relationships, performs an intersection operation with the original instantaneous adjustable capacity range of each resource unit, and takes the strictest boundary as the final constraint, generating a feasible regulation domain in multi-dimensional space. This feasible adjustment domain ensures that any set of output adjustment combinations selected within its range will not violate the physical operating limits of each resource unit, and the output changes of multiple resource units, when superimposed in the power grid, will not trigger any power flow over-limit of any core congested branch or any voltage over-limit of any voltage-sensitive node. This eliminates infeasible adjustment combinations from the source and provides a safe and reliable solution space for subsequent coordinated output allocation optimization.

[0051] S106. Introduce power demand constraints for grid dispatch within the feasible adjustment domain, and solve for the coordinated output allocation solution that satisfies the power demand for grid dispatch and maximizes the minimum remaining adjustment space of each resource unit within the corresponding instantaneous adjustable capacity range.

[0052] Optionally, under normal circumstances, introducing power demand constraints for grid dispatch within the feasible adjustment domain, the solution for coordinating power allocation that satisfies the power demand for grid dispatch and maximizes the minimum remaining adjustment space of each resource unit within its corresponding instantaneous adjustable capacity interval can be achieved in the following way, without limitation: Determine an auxiliary margin variable reflecting the remaining adjustment space of the resource unit; construct an objective function that maximizes the auxiliary margin variable; set a first constraint, a second constraint, and a third constraint. The first constraint ensures that the sum of the power allocation values ​​of each resource unit equals the power demand for grid dispatch; the second constraint ensures that the power allocation values ​​of each resource unit are within the feasible adjustment domain; and the third constraint ensures that the remaining adjustment space of any resource unit within its corresponding instantaneous adjustable capacity interval is greater than or equal to the auxiliary margin variable. Under the premise of satisfying the first, second, and third constraints, solve the objective function to obtain the power allocation values ​​of each resource unit as the coordinating power allocation solution.

[0053] In this context, the power demand for grid dispatch refers to the total active power regulation command value issued by the grid to the virtual power plant. This represents the target power that the virtual power plant, as a whole, needs to provide or absorb from the grid. For example, the grid might require the virtual power plant to achieve a total output of 800kW in the current time period. The power demand constraint for grid dispatch refers to transforming the power demand for grid dispatch into an equality constraint in an optimization problem. This requires that the sum of the output allocation values ​​of all resource units must be exactly equal to the power demand for grid dispatch. The remaining adjustment space refers to the distance between a resource unit's output allocation value and the closer of its output allocation value to the upper or lower boundary of the instantaneous adjustable capacity range after receiving its allocation value. It reflects the remaining adjustable capacity margin that the resource unit retains under the current allocation scheme. For example, if a resource unit's instantaneous adjustable capacity range is [-200kW, +150kW], and its output regulation is allocated as +50kW, then it has a remaining capacity of 100kW upwards and 250kW downwards. The smaller of these remaining adjustment spaces is 100kW. The collaborative output allocation solution refers to the set of optimal output allocation values ​​for each resource unit obtained after satisfying all constraints within the feasible adjustment domain. This set serves as the power adjustment target issued to each resource unit for execution. The auxiliary margin variable is a scalar decision variable introduced into the optimization model to uniformly measure the minimum level of remaining adjustment space in all resource units. Maximizing this variable achieves a balanced allocation of adjustment redundancy among the resource units. The objective function is the mathematical expression that needs to be maximized in the optimization problem; in this step, it is maximizing the auxiliary margin variable. The first constraint is an equality constraint that limits the sum of the output allocation values ​​of all resource units to the power demand of the grid dispatch, ensuring that the overall output of the virtual power plant accurately meets the dispatch instructions. The second constraint is an inequality constraint that requires the output allocation value of each resource unit to fall within the feasible adjustment domain, ensuring that the allocation scheme does not violate equipment physical constraints and grid coupling safety constraints. The third constraint is an inequality constraint that requires each resource unit, after obtaining its output allocation value, to have both its distance from the upper boundary and its distance from the lower boundary of the instantaneously adjustable capacity range greater than or equal to the auxiliary margin variable, ensuring that each resource unit retains at least the minimum adjustment redundancy specified by the auxiliary margin variable.

[0054] Specifically, after the control system generates the feasible adjustment domain, it needs to determine the specific output target value of each resource unit within this safe domain, satisfying both grid dispatch requirements and maintaining optimal adjustment redundancy allocation. The control system first introduces an auxiliary margin variable as a scalar decision variable to be optimized, representing the minimum level of remaining adjustment space among all resource units. Then, the control system constructs a linear optimization problem with maximizing this auxiliary margin variable as the objective function, while setting three sets of constraints: The first constraint requires that the sum of the output allocation values ​​of all resource units must equal the grid dispatch power demand, ensuring that the overall delivery power of the virtual power plant meets the target; the second constraint requires that the output allocation value of each resource unit is within the safe range defined by the feasible adjustment domain, ensuring that the allocation scheme simultaneously meets the physical limitations of the equipment itself and the grid coupling safety limitations; the third constraint requires that the distance between the output allocation value of each resource unit and the upper and lower boundaries of its instantaneous adjustable capacity interval is not less than the auxiliary margin variable, thus binding the minimum remaining adjustment space of all resource units to the auxiliary margin variable. Under the combined constraints of the three sets of conditions mentioned above, the control system solves the objective function using a linear programming solver to obtain the output allocation values ​​for each resource unit that maximize the auxiliary margin variable. These output allocation values ​​are then used as the coordinated output allocation solution. This solution strategy ensures that the adjustment redundancy of each resource unit is distributed as evenly as possible, preventing any resource unit from losing its subsequent adjustment flexibility due to output allocation close to the capacity boundary. This enhances the virtual power plant's continuous response capability to subsequent continuous dispatch commands or sudden disturbances.

[0055] S107. Based on the dynamic coupling matrix between units, calculate the coupling influence strength of each resource unit, and distribute the collaborative output allocation solution in sequence according to the order of low to high coupling influence strength.

[0056] Optionally, under normal circumstances, the coupling influence strength of each resource unit is calculated based on the inter-unit dynamic coupling matrix, and the coordinated output allocation solution is sequentially distributed according to the order of low to high coupling influence strength. This can be achieved in the following way, without limitation: the row vectors or column vectors of the inter-unit dynamic coupling matrix are summed to obtain the coupling influence strength of each resource unit; each resource unit is divided into multiple distribution batches according to the order of low to high coupling influence strength; when distributing the corresponding output allocation value to the resource unit of the current distribution batch, the reserved grid crossing capacity required for the undistributed batches is calculated based on the inter-unit dynamic coupling matrix and the output allocation values ​​of the resource units in the undistributed batches; the reserved grid crossing capacity is used as an additional constraint, and the output allocation value of the current distribution batch is verified and dynamically corrected before distribution is executed until all distribution batches are completed.

[0057] The coupling influence strength refers to the quantitative measure of the comprehensive coupling influence of a resource unit's output change on the power grid and all other resource units. It is calculated by summing all elements of the corresponding row or column vectors in the dynamic coupling matrix between units. A larger value indicates a stronger disturbance to the power grid state and the adjustable capacity of other resource units caused by the output adjustment of that resource unit. For example, if the coupling influence strength of resource unit A is 2.8 and that of resource unit B is 0.5, it means that the coupling impact on the power grid when A adjusts its output is much greater than that of B. Sequential control means that the control system does not simultaneously issue the coordinated output allocation solution to all resource units for execution. Instead, it issues it in multiple batches according to a preset order. Each batch of resource units begins to execute output adjustment after receiving the instruction, and the next batch is issued only after the previous batch has been executed. This avoids drastic power grid fluctuations caused by the synchronous action of multiple highly coupled resource units. The batch issuance refers to the division of all resource units into multiple ordered groups based on the coupling influence strength. Each group serves as a control instruction issuance unit, with priority given to groups containing resource units with low coupling influence strength. Reserved grid ride-through capacity refers to the remaining safety margin space reserved in advance for core grid congestion branches and voltage-sensitive nodes of resource units that have not yet been issued batches, ensuring that the grid still has sufficient transmission and voltage carrying capacity when subsequent batches of resource units perform output regulation. Additional constraints refer to converting the reserved grid ride-through capacity into additional safety restrictions on the output allocation value of the current batch before issuing the output command for the current batch, preventing the current batch's regulation from excessively consuming grid margin and causing subsequent batches to be unable to execute safely. Dynamic correction refers to the control system performing real-time verification and necessary adjustments to the output allocation value of the current batch before issuing each batch, based on the actual grid status feedback of the executed batches and the reserved requirements of subsequent batches, ensuring the safety of the entire sequential issuance process.

[0058] Specifically, after the control system completes the solution for the coordinated output allocation, it needs to distribute the output allocation values ​​of each resource unit in a safe and orderly manner to avoid coupled impacts on the power grid caused by multiple resource units simultaneously and significantly adjusting their output. The control system first sums all the adjustment capacity occupancy ratio elements in the row or column vectors corresponding to each resource unit from the inter-unit dynamic coupling matrix to obtain the coupling influence strength value of that resource unit. This value comprehensively reflects the overall impact of the output change of that resource unit on all relevant branches and nodes in the power grid, as well as the adjustable capacity of other resource units. Subsequently, the control system divides all resource units into multiple distribution batches according to the coupling influence strength from low to high. Resource units with low coupling influence strength are included in the first batch with priority, while resource units with high coupling influence strength are included in the later batches. During the sequential distribution process, the control system processes data sequentially, starting with the first batch. Before distributing the corresponding output allocation value to the resource units in the current batch, the control system calculates the required transmission capacity of the grid core congestion branches and the voltage margin of voltage-sensitive nodes for subsequent batches based on the dynamic coupling matrix between units and the output allocation values ​​of each resource unit in the undistributed batches. This is then aggregated into a reserved grid crossing capacity. This reserved grid crossing capacity is then added as an additional constraint to the output allocation value verification of the current batch to verify whether the remaining grid margin after the current batch is executed is sufficient to support the safe regulation of subsequent batches. If the verification finds that the output allocation value of the current batch will excessively occupy the grid margin, the output allocation value of the current batch is dynamically corrected to ensure sufficient reserved space. After the correction is completed, the distribution is executed. The control system proceeds batch by batch according to this logic until all output allocation instructions for all batches are distributed, achieving safe, orderly, and stable execution of the entire coordinated output allocation solution.

[0059] By adopting the above technical solutions, the control system incorporates the grid coupling effect between resource units into the core link of collaborative optimization, fundamentally solving the problems of line power flow exceeding limits and voltage exceeding limits caused by the neglect of resource electrical coupling in traditional static allocation strategies. While meeting the power demand of grid dispatch, it maximizes the retention of adjustment redundancy of each resource unit, and improves the safety, stability and robustness of the virtual power plant aggregation response.

[0060] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the virtual power plant resource aggregation and collaboration method in this application embodiment.

[0061] After step S107, the following steps may or may not be performed; this is not limited here:

[0062] S201. Real-time monitoring of the actual response output value of each resource unit after executing the collaborative output allocation solution.

[0063] The actual response output value refers to the measured value of the active power that each resource unit actually outputs or absorbs after receiving the power adjustment command corresponding to the collaborative output allocation solution and executing the action. This value is obtained by real-time sampling of the power metering device or smart terminal deployed on each resource unit side. For example, if an energy storage device is instructed to output 350kW, but only outputs 330kW due to reasons such as increased battery internal resistance or reduced inverter efficiency, then its actual response output value is 330kW.

[0064] Specifically, after the control system completes the sequential distribution control of the coordinated power allocation solution, each resource unit begins to adjust its own power output according to the received power allocation value. Due to factors such as equipment aging, environmental changes, communication delays, and controller accuracy deviations during actual operation, the actual output power of resource units often deviates from the target value. Therefore, the control system immediately enters the closed-loop monitoring phase after the command is issued and executed. It maintains real-time communication with the intelligent terminals, power metering devices, or SCADA data channels of each resource unit, continuously collecting the current actual active power output measurement value of each resource unit according to a preset sampling period, forming time-series data of the actual response output value of each resource unit. The control system performs data quality verification on the collected actual response output values, including range rationality checks and communication timescale consistency verification, to ensure that the measurement data used for subsequent deviation calculations is accurate and reliable.

[0065] S202. Calculate the output execution deviation between the actual response output value and the cooperative output allocation solution.

[0066] Among them, the output execution deviation refers to the difference between the actual response output value of each resource unit and the corresponding output allocation value in the collaborative output allocation solution issued by the control system. It is used to quantify the command execution accuracy of each resource unit and the degree of deviation between the overall power delivery and dispatch requirements of the virtual power plant. For example, if the output allocation value of a resource unit is 350kW and the actual response output value is 330kW, then the output execution deviation of the resource unit is -20kW, which means that the actual output is 20kW less than the command target.

[0067] Specifically, after the control system completes real-time acquisition of the actual response output values ​​of each resource unit, it calculates the difference between the actual response output value of each resource unit and the corresponding output allocation value in the coordinated output allocation solution to obtain the output execution deviation of each resource unit. A positive value indicates that the actual output exceeds the limit, and a negative value indicates that the actual output is insufficient. Simultaneously, the control system sums up the output execution deviations of all resource units to obtain the total output execution deviation at the overall virtual power plant level, reflecting the total deviation between the actual delivered power of the virtual power plant and the power demand of the grid dispatch. The control system compares the absolute values ​​of the output execution deviations of each resource unit and the absolute value of the total output execution deviation with preset tolerance thresholds to determine whether the deviation is within an acceptable range. The preset tolerance threshold refers to the upper limit of acceptable output execution deviation set by the control system. When the absolute value of the deviation does not exceed this threshold, it is considered normal execution fluctuation and no compensation mechanism is triggered; when the absolute value of the deviation exceeds this threshold, it is determined to be a significant deviation, requiring the activation of closed-loop compensation control. For example, the preset tolerance threshold can be set to 5% of the rated capacity of a single resource unit or an absolute value of 10kW.

[0068] S203. Identify the defaulting resource unit that has generated an output execution deviation, and lock the current actual output status of the defaulting resource unit.

[0069] Among them, a defaulting resource unit refers to a resource unit whose absolute value of output execution deviation exceeds a preset tolerance threshold during the execution of the coordinated output allocation solution. In other words, it fails to accurately complete the power regulation task according to the output allocation value issued by the control system. For example, if a photovoltaic power station experiences a sudden drop in output due to cloud cover and cannot maintain the command target value, then the photovoltaic power station is identified as a defaulting resource unit. Locking the current actual output state means that in subsequent error compensation calculations, the control system fixes the output value of the defaulting resource unit to its current actual response output value and no longer assigns it additional adjustment tasks. That is, during the compensation phase, the defaulting resource unit is treated as an unadjustable fixed output node.

[0070] Specifically, after the control system confirms an output execution deviation exceeding a preset tolerance threshold, it needs to accurately locate the source of the deviation and isolate it to enable error compensation without relying on faulty resources. The control system checks the absolute value of the output execution deviation for each resource unit, marking all resource units with absolute deviations exceeding the preset tolerance threshold as defaulting resource units and recording their deviation direction and magnitude. Subsequently, the control system performs a state locking operation on these defaulting resource units. That is, in subsequent compensation optimization calculations, the output value of the defaulting resource unit is fixed to its current actual response output value rather than its original output allocation value, and it is no longer included in the adjustable resource pool. This processing logic is based on the following judgment: the reason why defaulting resource units fail to execute instructions accurately is usually due to their own reasons such as equipment failure, resource fluctuations, or controller anomalies, which impair or render their actual adjustment capabilities unreliable. Continuing to issue adjustment instructions to them will not only fail to improve the deviation but may also exacerbate system uncertainty. By locking the state of defaulting resource units, the control system explicitly transfers the error compensation task to other normally operating resource units with remaining adjustment capabilities, laying the foundation for the selection of subsequent candidate compensation units.

[0071] S204. Among the resource units other than the defaulted resource units, select candidate compensation units with a current remaining adjustment space greater than zero.

[0072] Among them, candidate compensation units refer to resource units that are still in normal operation after excluding defaulting resource units and that currently have available adjustment capabilities and can undertake part or all of the output to perform deviation compensation tasks. The current remaining adjustment space refers to the available adjustment margin between the actual output value of each resource unit and the upper or lower boundary of the instantaneous adjustable capacity range after the current output allocation value has been executed. The specific direction depends on the deviation direction that needs to be compensated. If it is necessary to compensate for a positive power gap (i.e., it is necessary to increase the total output), then the remaining space of each resource unit in the upward adjustment direction is examined; if it is necessary to compensate for a negative power surplus (i.e., it is necessary to reduce the total output), then the remaining space of each resource unit in the downward adjustment direction is examined. For example, if the current actual output of an energy storage device is 300kW and the maximum output corresponding to the upper boundary of its instantaneous adjustable capacity range is 450kW, then its current remaining upward adjustment space is 150kW.

[0073] Specifically, after the control system identifies and locks the status of defaulting resource units, it needs to select units with actual compensation capabilities from the remaining normally operating resource units. The control system first determines the direction of the deviation to be compensated: if the overall actual output of the virtual power plant is lower than the grid dispatch power demand, resource units with upward adjustment capabilities need to be selected; if the overall actual output of the virtual power plant is higher than the grid dispatch power demand, resource units with downward adjustment capabilities need to be selected. Subsequently, the control system iterates through all resource units except for the defaulting resource units, calculating the difference between the current actual response output value of each resource unit and the boundary value of its instantaneous adjustable capacity range in the deviation compensation direction to obtain the current remaining adjustment space of that resource unit in the compensation direction. The control system includes resource units with a current remaining adjustment space greater than zero in the candidate compensation unit set, and excludes resource units with a current remaining adjustment space equal to zero, i.e., those already operating at the corresponding boundary limit position. Each resource unit in the final candidate compensation unit set is confirmed to have actual usable adjustment capacity, capable of undertaking part of the output to perform deviation compensation tasks in subsequent compensation allocation optimization.

[0074] S205. Combine the dynamic coupling matrix between units to evaluate the degree of secondary coupling impact of each candidate compensation unit on the core blocking branch and voltage sensitive node when bearing the output execution deviation.

[0075] The degree of secondary coupling impact refers to the magnitude of the additional disturbance to the power flow of core congested branches and the voltage of voltage-sensitive nodes caused by the output adjustment of candidate compensation units to compensate for the deviation when the output of defaulting resource units deviates from the expected output, resulting in a change in the power grid state. In other words, it is the secondary cascading coupling effect triggered by the compensation action itself in the power grid. For example, if the output of defaulting resource unit A decreases by 20kW, causing a change in the power flow distribution of a certain line, and if candidate compensation unit B increases its output by 20kW to compensate, the output change of candidate compensation unit B will cause changes in the power flow of that line and other lines, as well as voltage fluctuations of related nodes, through the power grid. These additional effects caused by the compensation action are the secondary coupling impact.

[0076] Specifically, after the control system completes the screening of candidate compensation units, it cannot simply allocate the output execution deviation to the candidate compensation units according to the capacity ratio. This is because the output adjustment of the compensation units themselves will also have a coupling effect on core congested branches and voltage-sensitive nodes through the physical channels of the power grid. Improper allocation may cause new line power flow exceeding limits or voltage exceeding limits. Therefore, the control system needs to evaluate the power grid security impact of each candidate compensation unit when it performs compensation adjustment before allocating compensation tasks. The control system, combined with the inter-unit dynamic coupling matrix constructed in step S104, extracts the sensitivity coefficient and regulation capacity crowding ratio corresponding to each candidate compensation unit, and calculates the power flow increment caused on each core congested branch and the voltage offset caused on each voltage-sensitive node when the candidate compensation unit undertakes a unit compensation output. At the same time, the control system considers that the output deviation of the defaulting resource unit has changed the power flow distribution state of the power grid, and evaluates the superposition effect produced by the compensation action of the candidate compensation unit based on this corrected power grid state. The control system comprehensively summarizes the impact of each candidate compensation unit on the power flow of all core congested branches and the voltage impact of all voltage-sensitive nodes, and obtains a quantitative value of the degree of secondary coupling impact of each candidate compensation unit, which provides an evaluation basis for subsequent compensation allocation optimization with the goal of minimizing the secondary coupling impact.

[0077] S206. Taking the minimum degree of secondary coupling as the optimization objective, the output execution deviation is redistributed within the feasible adjustment domain of the candidate compensation unit to obtain the error compensation allocation command and issue it.

[0078] The error compensation allocation instruction refers to the set of compensatory power adjustment instructions generated by the control system in response to output execution deviations. It includes the additional power increase or decrease required for each selected candidate compensation unit. After the instruction is issued and executed, the overall output of the virtual power plant returns to the power demand level of the power grid dispatch. Reallocation refers to the process of redistributing the power difference that should have been completed by the defaulting resource unit but was not delivered due to its execution deviation among the candidate compensation units according to the optimization objective. The optimization objective is to minimize the total secondary coupling impact caused by the compensation actions of all candidate compensation units in the compensation allocation solution, selecting the allocation scheme that minimizes the disturbance to power grid security while meeting the deviation compensation requirements.

[0079] Specifically, after the control system completes the assessment of the secondary coupling impact of each candidate compensation unit, it needs to reasonably allocate the output execution deviation to the candidate compensation units for compensation under the premise of ensuring grid safety. The control system constructs a compensation allocation optimization problem with the goal of minimizing the secondary coupling impact: the objective function is to minimize the weighted sum of the secondary coupling impact caused by the compensation output of all participating candidate compensation units; the constraints include that the sum of the compensation output of all candidate compensation units must be equal to the total output execution deviation to be compensated, ensuring that the overall output of the virtual power plant recovers to the grid dispatch power demand level; the compensation output value of each candidate compensation unit must be within its current feasible adjustment range and must not exceed the physical operation limits of the equipment itself and the grid coupling safety limits; after compensation, the power flow of each core congested branch and the voltage of each voltage-sensitive node should still remain within the safe operating range. By solving this optimization problem, the control system obtains the optimal compensation output allocation scheme of each candidate compensation unit that minimizes the secondary coupling disturbance of the grid, encapsulates it as an error compensation allocation instruction, and issues it for execution in order of increasing coupling impact strength of each candidate compensation unit. After receiving the instruction, the candidate compensation unit adjusts its own output to make up for the power gap or surplus caused by the defaulting resource unit, so that the overall output of the virtual power plant can be accurately matched with the power demand of the grid dispatch, and the closed-loop compensation control process is completed.

[0080] The control system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of the control system in an embodiment of this application.

[0081] It should be noted that, Figure 3 The structure of the control system shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0082] like Figure 3 As shown, the control system includes a CPU 301, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 302 or a program loaded from the storage section 308 into the random access memory RAM 303, such as executing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0083] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0084] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0085] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0086] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0087] Specifically, the control system of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, it implements the virtual power plant aggregation resource coordination method provided in the above embodiment.

[0088] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the control system described in the above embodiments; or it may exist independently and not incorporated into the control system. The storage medium carries one or more computer programs that, when executed by a processor of the control system, cause the control system to implement the virtual power plant aggregation resource coordination method provided in the above embodiments.

[0089] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0090] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0091] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A virtual power plant aggregation resource coordination method, characterized in that, Applied to a control system, the method includes: Collect the actual output value and physical operating constraints of each resource unit separately; Using the actual output value as the current operating point and combining it with the physical operating constraints, the instantaneous adjustable capacity range of each resource unit is calculated respectively. The instantaneous adjustable capacity range represents the closed interval defined by the maximum output adjustment amount that the resource unit can adjust upward and downward. Obtain the electrical topology connection relationship of each resource unit connected to the power grid and the real-time power flow distribution data of the power grid; Based on the electrical topology connection relationship and the real-time power flow distribution data, the disturbance response of the instantaneous adjustable capacity range of each resource unit is calculated to obtain the inter-unit dynamic coupling matrix. The inter-unit dynamic coupling matrix represents the degree of influence of any resource unit's output change on the boundary of the instantaneous adjustable capacity range of other resource units. Based on the inter-unit dynamic coupling matrix, the coupling constraint of the instantaneous adjustable capacity range is corrected to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. The feasible adjustment domain is used to exclude infeasible adjustment combinations that cause the line capacity or voltage to exceed the limit due to the simultaneous adjustment of multiple resource units. Introduce power demand constraints for grid dispatch within the feasible adjustment domain, and solve for a coordinated output allocation solution that satisfies the power demand for grid dispatch and maximizes the minimum remaining adjustment space of each resource unit within the corresponding instantaneous adjustable capacity range. Based on the dynamic coupling matrix between the units, the coupling influence strength of each resource unit is calculated, and the coordinated output allocation solution is sequentially distributed according to the order of the coupling influence strength from low to high.

2. The method of claim 1, wherein, The disturbance response calculation is performed on the instantaneous adjustable capacity range of each resource unit based on the electrical topology connection relationship and the real-time power flow distribution data to obtain the inter-unit dynamic coupling matrix. The inter-unit dynamic coupling matrix represents the degree of influence of any resource unit's output change on the boundary of the instantaneous adjustable capacity range of other resource units, specifically including: Based on the electrical topology connections and the real-time power flow distribution data, identify the core congested branches and voltage-sensitive nodes in the power grid that are closest to their operating limits. At the current operating point, a unit output disturbance is applied to each of the resource units; Calculate the sensitivity coefficient of the unit output disturbance to the power flow of the core congested branch and the voltage of the voltage-sensitive node; Based on the sensitivity coefficient, the regulation capacity crowding ratio of different resource units when they jointly affect the same core blocking branch or voltage-sensitive node is calculated, and the regulation capacity crowding ratio is used as matrix elements to construct the dynamic coupling matrix between the units.

3. The method of claim 2, wherein, Based on the inter-unit dynamic coupling matrix, the instantaneous adjustable capacity range is modified by coupling constraints to generate a feasible adjustment domain that simultaneously satisfies the physical operation constraints of the unit itself and the physical coupling constraints of the power grid between units. This feasible adjustment domain is used to exclude infeasible adjustment combinations that would cause line capacity or voltage exceedances due to simultaneous adjustments by multiple resource units. Specifically, it includes: Extract the adjustment capacity squeezing ratio from the dynamic coupling matrix between the units; For any two resource units and resource units that are coupled, determine whether the influence directions of the first resource unit and the second resource unit on the same core blocking branch or voltage-sensitive node are consistent. If so, the adjusted capacity occupancy ratio is used to reduce and compress the same-direction boundary of the instantaneous adjustable capacity range of the first resource unit and the second resource unit to obtain the safety boundary condition. The intersection operation of the instantaneous adjustable capacity range of each resource unit with the safety boundary condition is performed to generate the feasible adjustment domain, so as to ensure that any output combination within the feasible adjustment domain will not trigger the over-limit of the core blocking branch and voltage sensitive node.

4. The method of claim 3, wherein, The process of introducing power demand constraints for grid dispatch within the feasible adjustment domain, and solving for a coordinated output allocation solution that satisfies the power demand for grid dispatch and maximizes the minimum remaining adjustment space of each resource unit within its corresponding instantaneous adjustable capacity range, specifically includes: Determine the auxiliary margin variable that reflects the remaining adjustment space of the resource unit; Construct an objective function that maximizes the auxiliary margin variable; The first constraint, the second constraint, and the third constraint are set. The first constraint is used to limit the sum of the output allocation values ​​of each resource unit to be equal to the power grid dispatching power demand. The second constraint is used to limit the output allocation values ​​of each resource unit to be within the feasible adjustment range. The third constraint is used to limit the remaining adjustment space of any resource unit in the corresponding instantaneous adjustable capacity range to be greater than or equal to the auxiliary margin variable. Under the premise of satisfying the first constraint, the second constraint, and the third constraint, the objective function is solved to obtain the output allocation value of each resource unit as the collaborative output allocation solution.

5. The method of claim 4, wherein, The step of calculating the coupling influence strength of each resource unit based on the inter-unit dynamic coupling matrix, and then distributing the collaborative output allocation solution in a sequential manner according to the order of the coupling influence strength, specifically includes: The coupling influence strength of each resource unit is obtained by summing the row vectors or column vectors of the dynamic coupling matrix between the units. According to the order of the coupling influence strength from low to high, the resource units are divided into multiple distribution batches; When issuing the corresponding power allocation value to the resource unit in the current batch, the reserved grid crossing capacity required for the unissued batch is calculated based on the dynamic coupling matrix between the units and the power allocation value of the resource unit in the unissued batch. The reserved grid crossing capacity is used as an additional constraint. The output allocation value of the current batch is verified and dynamically corrected before the batch is issued, and the issuance is carried out until all batches are issued.

6. The method of claim 1, wherein, After the steps of calculating the coupling influence strength of each resource unit based on the inter-unit dynamic coupling matrix, and distributing the coordinated output allocation solution in sequence according to the order of the coupling influence strength, the method further includes: Real-time monitoring of the actual response output value of each resource unit after executing the collaborative output allocation solution; Calculate the output execution deviation between the actual response output value and the cooperative output allocation solution; When the absolute value of the output execution deviation is greater than the preset tolerance threshold, the closed-loop compensation control mechanism is triggered. Based on the current remaining adjustment space of each resource unit and the dynamic coupling matrix between the units, an error compensation allocation instruction is generated and issued for execution.

7. The method according to claim 6, characterized in that, When the absolute value of the output execution deviation exceeds a preset tolerance threshold, a closed-loop compensation control mechanism is triggered. Based on the current remaining adjustment space of each resource unit and the dynamic coupling matrix between the units, an error compensation allocation instruction is generated and issued for execution, specifically including: Identify the defaulting resource unit that caused the output execution deviation, and lock the current actual output status of the defaulting resource unit; Among the resource units other than the defaulted resource units, candidate compensation units with a current remaining adjustment space greater than zero are selected. Based on the dynamic coupling matrix between the units, the degree of secondary coupling impact of each candidate compensation unit on the core blocking branch and voltage-sensitive node when bearing the output execution deviation is evaluated; With the goal of minimizing the impact of the secondary coupling, the output execution deviation is redistributed within the feasible adjustment range of the candidate compensation unit to obtain the error compensation allocation instruction and issue it.

8. A control system, characterized in that, The control system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the control system to perform the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the control system, it causes the control system to perform the method as described in any one of claims 1-7.

10. A computer program product, characterized in that, When the computer program product is run on the control system, the control system performs the method as described in any one of claims 1-7.

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