Power grid inter-provincial collaborative power supply guarantee dispatching method and related device

Abstract

The application belongs to the field of power systems, and discloses a power grid cross-provincial and cross-regional collaborative power supply guarantee scheduling method and related devices, which comprises the following steps: obtaining the supply balance margin of each region in the power grid and the new energy prediction error; obtaining the power supply guarantee capability coefficient of each region according to the supply balance margin and the new energy prediction error, and determining the upper limit of the support capability of each region according to the power supply guarantee capability coefficient; obtaining the maximum supportable support capability of the power grid according to the upper limit of the support capability of each region combined with the power grid transmission capability limit; taking the maximum supportable support capability as the distribution reference, and performing power supply guarantee scheduling with the minimum difference of the power supply guarantee capability coefficient of the power gap region in each region as the optimization target to obtain the power grid collaborative scheduling interactive power of each region. The application realizes the unified representation of the balancing capability considering the differences of new energy in different regions, reasonably allocates the limited resources among different regions, realizes the power grid collaborative balancing in the new power system, and guarantees the stability of power supply.

Description

Technical Field

[0001] This invention belongs to the field of power systems and relates to a method and related devices for cross-provincial collaborative power supply dispatching. Background Technology

[0002] With the increasing proportion of renewable energy generation and the rapid growth of load demand, power shortages frequently occur during peak electricity consumption periods due to regional power imbalances, posing a significant challenge to ensuring power supply. Therefore, the electricity spot market, based on multiple bids and clearing transactions according to price differences, enables cross-regional electricity trading to balance surpluses and shortages, reducing the risk of supply disruptions.

[0003] However, in scenarios with high power shortage risks, regions experiencing shortages often quote ceiling prices, leading to market failures. Furthermore, to mitigate risk, exporting regions tend to submit conservative electricity sales declarations, further increasing the supply pressure on provinces facing power shortages. Simultaneously, the high proportion of renewable energy in the new power system introduces significant uncertainty. While the existing dispatch system employs interval forecasting methods with varying confidence levels to describe this uncertainty, it fails to accurately assess the supply risk and external support capabilities of each region in power balance calculations. This results in a lack of accurate data describing the supply and demand situation in grid-coordinated supply dispatch, preventing limited power export resources from reaching their full potential. Moreover, in extreme scenarios of severe power shortages, current methods still rely on teleconferences conducted by dispatch center technicians. Regions with power gaps submit their gaps and corresponding timeframes during the negotiation phase. Technicians then subjectively assess the export capacity of relevant regions based on the upper limits and plans of other regions' power generation, negotiating a certain scale of power supply. Furthermore, the allocation of all secured export capacity among regions with gaps is still based on subjective judgment, making it difficult to achieve a completely rational allocation and resulting in low balance in grid-coordinated supply decision-making. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method and related apparatus for cross-provincial collaborative power supply scheduling.

[0005] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for cross-provincial coordinated power grid supply guarantee scheduling, comprising: obtaining the supply balance margin and new energy prediction error of each region within the power grid; obtaining the supply guarantee capacity coefficient of each region based on the supply balance margin and new energy prediction error, and determining the upper limit of the support capacity of each region based on the supply guarantee capacity coefficient; obtaining the maximum available support capacity of the power grid based on the upper limit of the support capacity of each region and the power grid transmission capacity limit; performing supply guarantee scheduling with the maximum available support capacity as the allocation benchmark and with the minimum difference in the supply guarantee capacity coefficient of the power shortage region in each region as the optimization objective, thereby obtaining the power grid coordinated scheduling interaction power of each region.

[0006] Optionally, the supply balance margin is obtained by the following formula:

[0007] in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

[0008] Optionally, the new energy prediction error is obtained by: acquiring historical prediction data and actual data of various types of new energy in each region of the power grid, and obtaining the standard deviation of the prediction error of each type of new energy in each region of the power grid based on the historical prediction data and actual data; and obtaining the new energy prediction error of each region using the following formula:

[0009] in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

[0010] Optionally, the supply capacity coefficient of each region is obtained by the following formula:

[0011] in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

[0012] Optionally, determining the upper limit of support capacity for each region based on the supply capacity coefficient includes obtaining the upper limit of support capacity for each region using the following formula:

[0013] in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ,

[0014] in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

[0015] Optionally, obtaining the maximum power transmission capacity of the power grid based on the upper limit of the support capacity of each region and the power grid transmission capacity limit includes: solving a preset maximum power transmission capacity optimization model based on the upper limit of the support capacity of each region to obtain the maximum power transmission capacity of the power grid; wherein, the objective function of the maximum power transmission capacity optimization model is:

[0016] in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage.

[0017] The constraints of the maximum deliverable support capacity optimization model include: Supply guarantee risks and constraints in areas with power shortages:

[0018] in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage scheduling.

[0019] Power supply support areas face supply risk constraints:

[0020] in, For the region At any moment The upper limit of support capabilities.

[0021] Transmission limit constraints for tie lines:

[0022] in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A.

[0023] Tie line and regional power balance constraints:

[0024] in, For the region At any moment Power grid coordinated dispatch interaction power.

[0025] Power balance constraints on both the supply and demand sides:

[0026] Regulation rate constraints on regional power grids:

[0027] in, For the region At any moment The margin of climbing ability; For the region At any moment Power grid coordinated dispatch interaction power.

[0028] and regulation rate constraints under regional power grids:

[0029] in, For the region At any moment The landslide capacity margin.

[0030] Optionally, the step of using the maximum available support capacity as the allocation benchmark and minimizing the difference in the supply capacity coefficient between power shortage areas in each region as the optimization objective to obtain the grid coordinated dispatch interaction power for each region includes: using the maximum available support capacity as the allocation benchmark, solving a preset supply coordination dispatch model to obtain the grid coordinated dispatch interaction power for each region; wherein, the objective function of the supply coordination dispatch model is:

[0031] in, To ensure supply, regional scheduling and region At any moment The difference in the supply capacity coefficient.

[0032] The constraints of the supply guarantee scheduling model include: Non-negative constraint on supply capacity coefficient difference:

[0033]

[0034]

[0035] in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment The error in new energy prediction.

[0036] Maximum support capacity constraint:

[0037] In addition, there are constraints on supply risk in power shortage areas, constraints on supply risk in power support areas, constraints on transmission limits for interconnection lines, constraints on power balance between interconnection lines and regions, constraints on power balance between supply and demand, constraints on the upward regulation rate of regional power grids, and constraints on the downward regulation rate of regional power grids.

[0038] Optionally, it also includes: obtaining the supply guarantee scenario coverage rate of each region within the power grid using the following formula. :

[0039] in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient.

[0040] The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. :

[0041] in, To ensure supply, regional scheduling At any moment The supply capacity coefficient.

[0042] The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. :

[0043] in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

[0044] In a second aspect, the present invention provides a cross-provincial collaborative power grid supply guarantee dispatch system, comprising: a data acquisition module for acquiring the supply balance margin and new energy prediction error of each region within the power grid; a capacity assessment module for obtaining the supply guarantee capacity coefficient of each region based on the supply balance margin and new energy prediction error, and determining the upper limit of the support capacity of each region based on the supply guarantee capacity coefficient; a support analysis module for obtaining the maximum available support capacity of the power grid based on the upper limit of the support capacity of each region and the power grid transmission capacity limit; and a supply guarantee dispatch module for performing supply guarantee dispatch based on the maximum available support capacity and with the goal of minimizing the difference in the supply guarantee capacity coefficient of the power shortage areas in each region, thereby obtaining the interactive power of the power grid collaborative dispatch in each region.

[0045] Optionally, the supply balance margin is obtained by the following formula:

[0046] in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

[0047] Optionally, the new energy prediction error is obtained by: acquiring historical prediction data and actual data of various types of new energy in each region of the power grid, and obtaining the standard deviation of the prediction error of each type of new energy in each region of the power grid based on the historical prediction data and actual data; and obtaining the new energy prediction error of each region using the following formula:

[0048] in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

[0049] Optionally, the supply capacity coefficient of each region is obtained by the following formula:

[0050] in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

[0051] Optionally, determining the upper limit of support capacity for each region based on the supply capacity coefficient includes: The maximum support capacity for each region can be obtained using the following formula:

[0052] in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ,

[0053] in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

[0054] Optionally, the support analysis module is specifically used to: solve a preset maximum transmittable support capacity optimization model based on the upper limit of support capacity for each region, to obtain the maximum transmittable support capacity of the power grid; wherein, the objective function of the maximum transmittable support capacity optimization model is:

[0055] in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage.

[0056] The constraints of the maximum deliverable support capacity optimization model include: Supply guarantee risks and constraints in areas with power shortages:

[0057] in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage scheduling.

[0058] Power supply support areas face supply risk constraints:

[0059] in, For the region At any moment The upper limit of support capabilities.

[0060] Transmission limit constraints for tie lines:

[0061] in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A.

[0062] Tie line and regional power balance constraints:

[0063] in, For the region At any moment Power grid coordinated dispatch interaction power.

[0064] Power balance constraints on both the supply and demand sides:

[0065] Regulation rate constraints on regional power grids:

[0066] in, For the region At any moment The margin of climbing ability; For the region At any moment Power grid coordinated dispatch interaction power.

[0067] and regulation rate constraints under regional power grids:

[0068] in, For the region At any moment The landslide capacity margin.

[0069] Optionally, the supply guarantee scheduling module is specifically used to: solve a preset supply guarantee scheduling model based on the maximum available support capacity, and obtain the power grid coordinated scheduling interaction power of each region; wherein, the objective function of the supply guarantee scheduling model is:

[0070] in, To ensure supply, regional scheduling and region At any moment The difference in the supply capacity coefficient.

[0071] The constraints of the supply guarantee scheduling model include: Non-negative constraint on supply capacity coefficient difference:

[0072]

[0073]

[0074] in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment The error in new energy prediction.

[0075] Maximum support capacity constraint:

[0076] In addition, there are constraints on supply risk in power shortage areas, constraints on supply risk in power support areas, constraints on transmission limits for interconnection lines, constraints on power balance between interconnection lines and regions, constraints on power balance between supply and demand, constraints on the upward regulation rate of regional power grids, and constraints on the downward regulation rate of regional power grids.

[0077] Optionally, a scheduling analysis module may also be included, for: The following formula is used to obtain the supply guarantee scenario coverage rate for each region within the power grid. :

[0078] in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient.

[0079] The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. :

[0080] in, To ensure supply, regional scheduling At any moment The supply capacity coefficient.

[0081] The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. :

[0082] in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

[0083] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described inter-provincial collaborative supply guarantee dispatching method for power grids.

[0084] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described inter-provincial collaborative power grid supply guarantee scheduling method.

[0085] Compared with the prior art, the present invention has the following beneficial effects: This invention presents a cross-provincial collaborative power grid supply guarantee dispatching method. By dynamically calculating a supply guarantee capacity coefficient that quantifies regional risk and capacity using supply balance margin and new energy prediction errors, and using this coefficient as a unified risk benchmark, it achieves an objective comparison of cross-regional balance capacity. This accurately describes the balance situation brought about by new energy uncertainty and changes in both supply and demand, and provides a unified representation of balance capacity considering the differences in new energy in different regions. Furthermore, the maximum available support capacity is determined by the upper limit of the support capacity determined by this coefficient, combined with the power grid transmission capacity limit, ensuring the safety and feasibility of the dispatching scheme. Then, using the maximum available support capacity as the allocation benchmark, and with the optimization objective of minimizing the difference in supply guarantee capacity coefficients between power shortage areas in each region, supply guarantee dispatching is carried out. This allows limited transmission resources to systematically prioritize reducing the highest risk and promote a fair and efficient equilibrium of risk levels in all shortage areas. Thus, in a highly uncertain environment, it transforms the originally decentralized and subjective supply guarantee decision-making into a collaborative, quantitative optimization process that considers safety, fairness, and overall efficiency, effectively improving the decision-making capability and reliability of collaborative power grid supply guarantee in the new power system and ensuring stable power supply. Attached Figure Description

[0086] Figure 1 This is a flowchart of the cross-provincial collaborative power supply scheduling method according to an embodiment of the present invention.

[0087] Figure 2 This is a structural block diagram of the inter-provincial collaborative power supply dispatching system according to an embodiment of the present invention. Detailed Implementation

[0088] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0089] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0090] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 1 In one embodiment of the present invention, a method for cross-provincial collaborative power grid dispatch is provided, which realizes a unified representation of the balancing capacity considering the differences in new energy sources in different regions, enables the rational allocation of limited resources among different regions, achieves grid collaborative balance in the new power system, and ensures stable power supply.

[0091] Specifically, the cross-provincial collaborative power supply dispatching method of the present invention includes the following steps: S1: Obtain the supply balance margin of each region within the power grid and the prediction error of new energy sources.

[0092] S2: Based on the supply balance margin and the new energy forecast error, obtain the supply guarantee capacity coefficient for each region, and determine the upper limit of the support capacity for each region based on the supply guarantee capacity coefficient.

[0093] S3: Based on the upper limit of support capacity in each region and the power grid transmission capacity limit, the maximum support capacity that the power grid can transmit is obtained.

[0094] S4: Based on the maximum available support capacity, and with the goal of minimizing the difference in the supply capacity coefficient between power shortage areas in each region, supply guarantee scheduling is carried out to obtain the power grid collaborative scheduling interaction power in each region.

[0095] This invention presents a cross-provincial collaborative power grid supply guarantee dispatching method. By dynamically calculating a supply guarantee capacity coefficient that quantifies regional risk and capacity using supply balance margin and new energy prediction errors, and using this coefficient as a unified risk benchmark, it achieves an objective comparison of cross-regional balance capacity. This accurately describes the balance situation brought about by new energy uncertainty and changes in both supply and demand, and provides a unified representation of balance capacity considering the differences in new energy in different regions. Furthermore, the upper limit of support capacity determined by this coefficient, combined with grid transmission capacity limitations, determines the maximum transmittable support capacity, ensuring the safety and feasibility of the dispatching scheme. Then, using the maximum transmittable support capacity as the allocation benchmark, and minimizing the difference in supply guarantee capacity coefficients among power shortage areas in each region as the optimization objective, supply guarantee dispatching is performed. This allows limited transmission resources to systematically prioritize reducing the highest risk and promote a fair and efficient equilibrium of risk levels in all shortage areas. Thus, in a highly uncertain environment, it transforms the originally decentralized and subjective supply guarantee decision-making into a collaborative, quantitative optimization process that considers safety, fairness, and overall efficiency, effectively improving the decision-making capability and reliability of collaborative power grid supply guarantee in the new power system and ensuring stable power supply.

[0096] In one possible implementation, the supply balance margin is obtained by the following formula:

[0097] in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

[0098] Interpretive data is obtained for each region at each time point the following day, including renewable energy forecasts, system load forecasts, tie-line plans, conventional unit generating capacity limits, and reserve data, to calculate the supply balance margin for each region at each time point. Among these, the regional... At any moment The reserve power is for the area At any moment The sum of the load reserved and the emergency reserve power as required by the "Technical Guidelines for Power Systems".

[0099] In one possible implementation, the new energy prediction error is obtained by: acquiring historical prediction data and actual data of various types of new energy in each region of the power grid, and obtaining the standard deviation of the prediction error of each type of new energy in each region of the power grid based on the historical prediction data and actual data; and obtaining the new energy prediction error of each region using the following formula:

[0100] in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

[0101] For example, wind power and photovoltaic power are used as examples in this embodiment. Specifically, (1) based on the predicted and actual wind power of each region over the past three years, the standard deviation of the wind power prediction error for each region at each time is calculated. , For area code, (2) Based on the total photovoltaic power prediction and actual power of each region over the past three years, the standard deviation of photovoltaic power prediction error for each region at each time point is calculated. (3) Calculate the standard deviation of the new energy prediction error for each region at each time. .

[0102] In one possible implementation, the supply capacity coefficient of each region is obtained by the following formula:

[0103] in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

[0104] Interpretively, this paper combines the supply balance margin reflecting certain adjustable resources with the standard deviation of prediction errors characterizing the uncertainty of new energy sources to construct a dimensionless index with unified dimensions that simultaneously reflects "resource sufficiency" and "risk volatility." The larger this index, the greater the available adjustment margin in the region at the current moment relative to the predicted fluctuations in new energy sources, indicating stronger supply guarantee capacity and lower risk; conversely, the smaller the index, the weaker the capacity and the higher the risk. Based on the supply guarantee capacity coefficient, on the one hand, horizontal and vertical comparability of power balance capacity across different regions and at different times is achieved, providing an objective and quantitative unified benchmark for network-wide collaborative decision-making; on the other hand, it enables dispatch decisions to simultaneously respond to resource sufficiency and volatility risk, thereby more scientifically identifying support capacity and power shortage risk in an environment of strong uncertainty in new energy sources.

[0105] In one possible implementation, determining the upper limit of support capacity for each region based on the supply capacity coefficient includes obtaining the upper limit of support capacity for each region using the following formula:

[0106] in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ,

[0107] in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

[0108] Explanatory, based on the supply capacity coefficient, the power shortage area, the power shortage time, the power support area, and the upper limit of the support capacity are determined. Specifically, (1) the supply capacity coefficient limit required for each area is set. This allows us to obtain the power shortage flags for each region at each time. 1 indicates the presence of a gap, and 0 indicates the absence of a gap. If for any region there exists When the value equals 1, that region is designated as a power shortage region. This allows us to statistically identify all power shortage regions and form a set. .

[0109] (2) Count the time markers of any time when there is a power shortage. 1 indicates the presence of a gap, and 0 indicates the absence of a gap. This allows us to statistically determine the set of times of power shortage. Furthermore, due to the constraints of ramp-up and ramp-down rates on generator units, power balance is coupled between time periods. Therefore, the final determined dispatch time should be from... The moment when the smallest gap exists has arrived The set of all consecutive time points at which the largest power gap exists, denoted as the power gap scheduling time set. express.

[0110] (3) Set a supply capacity limit for areas with support capabilities. This allows us to obtain the power support capability flags for each region during the dispatch time. 1 indicates that support capability exists, and 0 indicates that support capability does not exist. If for any region there exists When the value equals 1, that region is designated as a power support region, allowing for the statistical analysis of all power support provinces to form a set. .

[0111] (4) Finally, calculate the upper limit of support capacity for each region during the scheduling time. .

[0112] In one possible implementation, obtaining the maximum power transmission capacity of the power grid based on the upper limit of the support capacity of each region and the power grid transmission capacity limit includes: solving a preset maximum power transmission capacity optimization model based on the upper limit of the support capacity of each region to obtain the maximum power transmission capacity of the power grid.

[0113] The objective function of the maximum deliverable support capability optimization model is:

[0114] in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage.

[0115] Interpretive calculations are performed to optimize the total maximum available support capacity of power support areas considering the grid's transmission capacity. The objective function is to maximize the total support capacity of all support areas at each time point. This method can accurately determine the maximum available support capacity of the grid while ensuring that the safety risks of all power support areas do not exceed the limits. This provides a global capacity ceiling and safety boundary for subsequent cross-regional supply guarantee scheduling.

[0116] The constraints of the maximum available support capacity optimization model include: supply risk constraints in power shortage areas, supply risk constraints in power support areas, transmission limit constraints of tie lines, power balance constraints between tie lines and regions, power balance constraints on both supply and demand sides, regulation rate constraints of regional grids, and regulation rate constraints of regional grids.

[0117] Among them, the supply guarantee risk constraint for power shortage areas means that after large-scale coordinated dispatch, the supply guarantee risk of any power shortage area at any dispatch time cannot increase. Specifically:

[0118] in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage scheduling.

[0119] The power supply guarantee risk constraint for power support areas means that after large-scale power grid coordinated dispatch, the support capacity of any support area at any dispatch time cannot exceed the upper limit of that area's support capacity at that time. Specifically:

[0120] in, For the region At any moment The upper limit of support capabilities.

[0121] The tie-line transmission limit constraint indicates that the transmission between different areas cannot exceed the corresponding limit, specifically:

[0122] in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A.

[0123] The tie-line and regional power balance constraint means that the external interactive power of any region at any time is equal to the sum of the external tie-line interactive power of that region, specifically:

[0124] in, For the region At any moment Power grid coordinated dispatch interaction power.

[0125] The power balance constraint on both the supply and demand sides means that at any given time, the sum of the power received by the power deficit region is equal to the sum of the power transmitted by the power supplied to the support region. Specifically:

[0126] The specific regulation rate constraints on regional power grids are as follows:

[0127] in, For the region At any moment The margin of climbing ability; For the region At any moment The power grid coordinated dispatch interaction. Specifically, , For the region At any moment The climbing ability of conventional units, For the region At any moment System load forecasting For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line (if the power output is negative).

[0128] Regulation rate constraints under regional power grid:

[0129] in, For the region At any moment The landslide capacity margin.

[0130] Specifically, ,in, For the region At any moment The landslide capacity of conventional generating units.

[0131] In one possible implementation, the step of using the maximum available support capacity as the allocation benchmark and minimizing the difference in the supply capacity coefficient between power shortage areas in each region as the optimization objective to obtain the power grid collaborative scheduling interaction power of each region includes: using the maximum available support capacity as the allocation benchmark, solving a preset supply guarantee scheduling model to obtain the power grid collaborative scheduling interaction power of each region.

[0132] The objective function of the supply guarantee scheduling model is:

[0133] in, To ensure supply, regional scheduling and region At any moment The difference in the supply capacity coefficient.

[0134] Explanatory calculations were performed to optimize the cross-provincial collaborative power grid supply guarantee scheduling scheme. The objective function was to minimize the difference in the supply guarantee capacity coefficient at different times in the power shortage area. This improved the average scenario coverage and prioritized the reduction of high risks. It is helpful to carry out large-scale power grid collaborative scheduling when power supply is tight. The optimization results take into account both fairness and efficiency and improve a key link in the new power system scheduling system.

[0135] The constraints of the supply guarantee dispatch model include the non-negativity constraint of the supply guarantee capacity coefficient difference, the maximum support capacity sum constraint, the supply guarantee risk constraint of the power shortage area, the supply guarantee risk constraint of the power support area, the tie line transmission limit constraint, the tie line and regional power balance constraint, the supply and demand dual-side power balance constraint, the regional grid upward regulation rate constraint, and the regional grid downward regulation rate constraint.

[0136] Specifically, the non-negativity constraint on the supply capacity coefficient difference is as follows:

[0137]

[0138]

[0139] in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment The error in new energy prediction.

[0140] The maximum total support capability constraint is as follows: This indicates that the power shortage area must be fully allocated the maximum power supply support capacity of the power grid determined in the previous step.

[0141] In one possible implementation, the cross-provincial collaborative power grid supply guarantee dispatch method further includes: The following formula is used to obtain the supply guarantee scenario coverage rate for each region within the power grid. :

[0142] in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient.

[0143] The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. :

[0144] in, To ensure supply, regional scheduling At any moment The supply capacity coefficient.

[0145] The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. :

[0146] in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

[0147] Explanatoryly, based on the interactive power of grid collaborative scheduling in each region, the improvement in the coverage of grid supply guarantee scenarios is calculated to characterize the role of the grid cross-provincial collaborative supply guarantee scheduling method of the present invention and guide the optimization process.

[0148] Specifically, (1) Calculate the coverage rate of supply guarantee scenarios before grid coordinated dispatch. Based on the supply guarantee capacity coefficient of each region before dispatch, calculate the coverage rate of supply guarantee scenarios of each region at each time before dispatch. ,in, The cumulative distribution function of the standard normal distribution can be obtained by referring to the standard normal distribution probability table. (2) Calculate the supply guarantee capacity coefficient and supply guarantee scenario coverage rate after grid coordinated dispatch. Based on the formula Calculate the supply capacity coefficient of each region after scheduling, and based on... Calculate the coverage rate of supply guarantee scenarios in each region after scheduling. (3) Calculate the improvement in the coverage rate of supply guarantee scenarios in each region. The cross-provincial collaborative supply guarantee scheduling method of the power grid results in the average change in the scenario coverage rate of the sending and receiving areas being By quantifying and comparing the coverage rate of supply guarantee scenarios in each region before and after coordinated scheduling and their average improvement, this invention provides an objective and intuitive probabilistic performance evaluation of the practical application effect of the method, proving that it can systematically improve the overall power supply security level of the entire network.

[0149] In summary, this invention presents a cross-provincial collaborative power grid supply guarantee dispatching method. Addressing the strong uncertainties of new energy sources in the new power system, it constructs a supply guarantee capacity coefficient that considers the spatiotemporal differences of new energy sources and the characteristics of power supply and demand. This provides a unified representation of supply balance capacity, quantifies the balance risk in each region, and enables horizontal and vertical comparisons of balance capacity across different regions at different times, facilitating collaborative decision-making within the large power grid. Furthermore, the supply guarantee capacity coefficient serves as a key basis for inter-regional power transmission decisions, allowing for the rational allocation of limited resources across different regions. This achieves collaborative balance within the large power grid in the new power system, ensuring power supply and reducing balance risks. When high supply risks cause market-based mechanisms such as inter-provincial spot markets to fail, this invention optimizes inter-regional interconnection plans, providing high-quality decision-making for dispatchers and enabling collaborative supply guarantee across the large power grid.

[0150] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0151] See Figure 2 In another embodiment of the present invention, a cross-provincial collaborative supply guarantee dispatching system for power grids is provided, which can be used to implement the above-mentioned cross-provincial collaborative supply guarantee dispatching method for power grids. Specifically, the cross-provincial collaborative supply guarantee dispatching system for power grids includes a data acquisition module, a capacity assessment module, a support analysis module, and a supply guarantee dispatching module.

[0152] The data acquisition module is used to acquire the supply balance margin and new energy prediction error of each region within the power grid; the capacity assessment module is used to obtain the supply guarantee capacity coefficient of each region based on the supply balance margin and new energy prediction error, and to determine the upper limit of the support capacity of each region based on the supply guarantee capacity coefficient; the support analysis module is used to obtain the maximum available support capacity of the power grid based on the upper limit of the support capacity of each region and the power grid transmission capacity limit; the supply guarantee scheduling module is used to perform supply guarantee scheduling based on the maximum available support capacity and with the goal of minimizing the difference in the supply guarantee capacity coefficient of the power shortage areas in each region, and to obtain the power grid collaborative scheduling interaction power of each region.

[0153] In one possible implementation, the supply balance margin is obtained by the following formula:

[0154] in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

[0155] In one possible implementation, the new energy prediction error is obtained by: acquiring historical prediction data and actual data of various types of new energy in each region of the power grid, and obtaining the standard deviation of the prediction error of each type of new energy in each region of the power grid based on the historical prediction data and actual data; and obtaining the new energy prediction error of each region using the following formula:

[0156] in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

[0157] In one possible implementation, the supply capacity coefficient of each region is obtained by the following formula:

[0158] in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

[0159] In one possible implementation, determining the upper limit of support capacity for each region based on the supply capacity coefficient includes obtaining the upper limit of support capacity for each region using the following formula:

[0160] in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ,

[0161] in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

[0162] In one possible implementation, the support analysis module is specifically used to: solve a preset maximum transmittable support capacity optimization model based on the upper limit of support capacity for each region, to obtain the maximum transmittable support capacity of the power grid; wherein, the objective function of the maximum transmittable support capacity optimization model is:

[0163] in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage.

[0164] The constraints of the maximum deliverable support capacity optimization model include: Supply guarantee risks and constraints in areas with power shortages:

[0165] in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage scheduling.

[0166] Power supply support areas face supply risk constraints:

[0167] in, For the region At any moment The upper limit of support capabilities.

[0168] Transmission limit constraints for tie lines:

[0169] in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A.

[0170] Tie line and regional power balance constraints:

[0171] in, For the region At any moment Power grid coordinated dispatch interaction power.

[0172] Power balance constraints on both the supply and demand sides:

[0173] Regulation rate constraints on regional power grids:

[0174] in, For the region At any moment The margin of climbing ability; For the region At any moment Power grid coordinated dispatch interaction power.

[0175] and regulation rate constraints under regional power grids:

[0176] in, For the region At any moment The landslide capacity margin.

[0177] In one possible implementation, the supply guarantee scheduling module is specifically used to: solve a preset supply guarantee scheduling model based on the maximum available support capacity, to obtain the power grid coordinated scheduling interaction power in each region; wherein, the objective function of the supply guarantee scheduling model is:

[0178] in, To ensure supply, regional scheduling and region At any moment The difference in the supply capacity coefficient.

[0179] The constraints of the supply guarantee scheduling model include: Non-negative constraint on supply capacity coefficient difference:

[0180]

[0181]

[0182] in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment The error in new energy prediction.

[0183] Maximum support capacity constraint:

[0184] In addition, there are constraints on supply risk in power shortage areas, constraints on supply risk in power support areas, constraints on transmission limits for interconnection lines, constraints on power balance between interconnection lines and regions, constraints on power balance between supply and demand, constraints on the upward regulation rate of regional power grids, and constraints on the downward regulation rate of regional power grids.

[0185] In one possible implementation, the inter-provincial collaborative power grid supply guarantee dispatch system further includes a dispatch analysis module, used to: obtain the supply guarantee scenario coverage rate of each region within the power grid using the following formula. :

[0186] in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient.

[0187] The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. :

[0188] in, To ensure supply, regional scheduling At any moment The supply capacity coefficient.

[0189] The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. :

[0190] in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

[0191] All relevant content of each step involved in the aforementioned embodiment of the cross-provincial collaborative supply guarantee dispatching method for power grids can be referenced to the functional description of the corresponding functional module of the cross-provincial collaborative supply guarantee dispatching system for power grids in the embodiments of the present invention, and will not be repeated here.

[0192] The module division in this embodiment of the invention is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in the various embodiments of the invention can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0193] In another embodiment of the present invention, a computer device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions from the computer storage medium to achieve corresponding method flows or corresponding functions. The processor described in this embodiment of the present invention can be used in the operation of a cross-provincial collaborative supply guarantee dispatching method for power grids.

[0194] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). This computer-readable storage medium is a memory device within a computer device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium of the computer device and extended storage media supported by the computer device. The computer-readable storage medium provides storage space containing the terminal's operating system. Furthermore, this storage space also contains one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the inter-provincial coordinated supply guarantee scheduling method for power grids in the above embodiments.

[0195] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0196] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0197] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0198] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0199] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for cross-provincial collaborative power grid dispatch to ensure supply, characterized in that, include: Obtain the supply balance margin and new energy forecasting error in various regions of the power grid; Based on the supply balance margin and the new energy forecast error, the supply guarantee capacity coefficient of each region is obtained, and the upper limit of the support capacity of each region is determined based on the supply guarantee capacity coefficient. Based on the upper limit of support capacity in each region and the power grid transmission capacity limit, the maximum support capacity that the power grid can send is obtained. Based on the maximum available support capacity, and with the goal of minimizing the difference in the supply capacity coefficient between power shortage areas in each region, the power grid coordinated dispatch interaction power of each region is obtained.

2. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, The supply balance margin is obtained by the following formula: in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

3. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, The new energy prediction error is obtained in the following way: Historical forecast data and actual data of various types of new energy sources in various regions of the power grid are obtained, and the standard deviation of the forecast error of various types of new energy sources in various regions of the power grid is obtained based on the historical forecast data and actual data. The new energy prediction error for each region is obtained using the following formula: in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

4. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, The supply capacity coefficients for each region are obtained using the following formula: in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

5. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, The determination of the upper limit of support capacity for each region based on the supply capacity coefficient includes: The maximum support capacity for each region can be obtained using the following formula: in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ， in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

6. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, The maximum power grid transmission capacity, calculated by combining the upper limit of support capacity in each region with the power grid transmission capacity limit, includes: Based on the upper limit of support capacity in each region, a preset optimization model for the maximum power transmission support capacity is solved to obtain the maximum power transmission support capacity of the power grid; wherein, the objective function of the optimization model for the maximum power transmission support capacity is: in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage. The constraints of the maximum deliverable support capacity optimization model include: Supply guarantee risks and constraints in areas with power shortages: in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage dispatching; Power supply support areas face supply risk constraints: in, For the region At any moment The upper limit of support capabilities; Transmission limit constraints for tie lines: in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A; Tie line and regional power balance constraints: in, For the region At any moment Power grid coordinated dispatch interaction power; Power balance constraints on both supply and demand sides: Regulation rate constraints on regional power grids: in, For the region At any moment The margin of climbing ability; For the region At any moment Power grid coordinated dispatch interaction power; and regulation rate constraints under regional power grids: in, For the region At any moment The landslide capacity margin.

7. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 6, characterized in that, The allocation based on the maximum available support capacity and the optimization objective of minimizing the difference in supply capacity coefficients between power shortage areas in each region, results in the following power grid collaborative dispatch interaction power for each region: Using the maximum available support capacity as the allocation benchmark, a pre-defined supply guarantee scheduling model is solved to obtain the power grid coordinated scheduling interaction power in each region; the objective function of the supply guarantee scheduling model is: in, To ensure supply, regional scheduling and region At any moment The difference in supply capacity coefficient; The constraints of the supply guarantee scheduling model include: Non-negative constraint on supply capacity coefficient difference: in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment New energy prediction error; Maximum support capacity constraint: In addition, there are constraints on supply risk in power shortage areas, constraints on supply risk in power support areas, constraints on transmission limits for interconnection lines, constraints on power balance between interconnection lines and regions, constraints on power balance between supply and demand, constraints on the upward regulation rate of regional power grids, and constraints on the downward regulation rate of regional power grids.

8. The inter-provincial collaborative power grid supply guarantee dispatching method according to claim 1, characterized in that, Also includes: The following formula is used to obtain the supply guarantee scenario coverage rate for each region within the power grid. : in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient; The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. : in, To ensure supply, regional scheduling At any moment The supply capacity coefficient; The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. : in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

9. A cross-provincial collaborative power grid dispatching system for ensuring power supply, characterized in that: include: The data acquisition module is used to obtain the supply balance margin of each region within the power grid and the prediction error of new energy sources; The capacity assessment module is used to obtain the supply guarantee capacity coefficient of each region based on the supply balance margin and the new energy forecast error, and to determine the upper limit of the support capacity of each region based on the supply guarantee capacity coefficient. The support analysis module is used to obtain the maximum available support capacity of the power grid based on the upper limit of support capacity of each region and the power grid transmission capacity limit. The supply guarantee scheduling module is used to allocate resources based on the maximum available support capacity and optimize the supply guarantee capacity coefficient difference between power shortage areas in each region, thereby obtaining the power grid collaborative scheduling interaction power in each region.

10. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, The supply balance margin is obtained by the following formula: in, For the region At any moment Supply balance margin, For the region At any moment New energy power forecast, For the region At any moment The power input plan for the connection line For the region At any moment The upper limit of the power generation capacity of conventional generating units, For the region At any moment System load forecasting For the region At any moment Backup power.

11. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, The new energy prediction error is obtained in the following way: Historical forecast data and actual data of various types of new energy sources in various regions of the power grid are obtained, and the standard deviation of the forecast error of various types of new energy sources in various regions of the power grid is obtained based on the historical forecast data and actual data. The new energy prediction error for each region is obtained using the following formula: in, For the region At any moment New energy prediction error For the region At any moment Type The standard deviation of the prediction error for new energy sources This refers to the number of new energy types.

12. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, The supply capacity coefficients for each region are obtained using the following formula: in, For the region At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment The error in new energy prediction.

13. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, The determination of the upper limit of support capacity for each region based on the supply capacity coefficient includes: The maximum support capacity for each region can be obtained using the following formula: in, For the region At any moment The upper limit of support capabilities, For the region At any moment Supply capacity coefficient The supply capacity limit for areas with power shortages. For the region At any moment New energy prediction error The set of times for power shortage scheduling includes all times from the minimum to the maximum time when the power shortage time flag is 1. The power shortage time flag is obtained by the following formula: ， in, For a moment The power shortage time marker, For the region At any moment The power shortage marker, For the region At any moment Supply capacity coefficient The limit for the power supply capacity coefficient of the power support area.

14. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, The support analysis module is specifically used for: Based on the upper limit of support capacity in each region, a preset optimization model for the maximum power transmission support capacity is solved to obtain the maximum power transmission support capacity of the power grid; wherein, the objective function of the optimization model for the maximum power transmission support capacity is: in, This represents the maximum power grid's ability to provide support. For the region At any moment Power grid coordinated dispatch interaction power, For the collection of power support areas, This is the set of moments when there is a power shortage. The constraints of the maximum deliverable support capacity optimization model include: Supply guarantee risks and constraints in areas with power shortages: in, For the region At any moment Power grid coordinated dispatch interaction power, This is a collection of areas with power shortages. This is the set of times for power shortage dispatching; Power supply support areas face supply risk constraints: in, For the region At any moment The upper limit of support capabilities; Transmission limit constraints for tie lines: in, For transmission line A at time By region To the region The transmission power, transmission line A is the area and region Directly connected inter-regional power transmission lines For a set of regions, This refers to the additional transmission power required on transmission line A; This is the lower limit of the transmission power of transmission line A. This represents the upper limit of the transmission power of transmission line A; Tie line and regional power balance constraints: in, For the region At any moment Power grid coordinated dispatch interaction power; Power balance constraints on both supply and demand sides: Regulation rate constraints on regional power grids: in, For the region At any moment The margin of climbing ability; For the region At any moment Power grid coordinated dispatch interaction power; and regulation rate constraints under regional power grids: in, For the region At any moment The landslide capacity margin.

15. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 14, characterized in that, The supply guarantee scheduling module is specifically used for: Using the maximum available support capacity as the allocation benchmark, a pre-defined supply guarantee scheduling model is solved to obtain the power grid coordinated scheduling interaction power in each region; the objective function of the supply guarantee scheduling model is: in, To ensure supply, regional scheduling and region At any moment The difference in supply capacity coefficient; The constraints of the supply guarantee scheduling model include: Non-negative constraint on supply capacity coefficient difference: in, To ensure supply, regional scheduling At any moment Supply capacity coefficient To ensure supply, regional scheduling At any moment Supply capacity coefficient For the region At any moment Supply balance margin, For the region At any moment Supply balance margin, For the region At any moment New energy prediction error For the region At any moment New energy prediction error; Maximum support capacity constraint: In addition, there are constraints on supply risk in power shortage areas, constraints on supply risk in power support areas, constraints on transmission limits for interconnection lines, constraints on power balance between interconnection lines and regions, constraints on power balance between supply and demand, constraints on the upward regulation rate of regional power grids, and constraints on the downward regulation rate of regional power grids.

16. The inter-provincial collaborative power grid supply guarantee dispatching system according to claim 9, characterized in that, It also includes a scheduling analysis module, used for: The following formula is used to obtain the supply guarantee scenario coverage rate for each region within the power grid. : in, The cumulative distribution function of the standard normal distribution. For the region At any moment The supply capacity coefficient; The following formula is used to obtain the coverage rate of supply guarantee scenarios in various regions of the power grid after supply guarantee dispatch. : in, To ensure supply, regional scheduling At any moment The supply capacity coefficient; The average change in scenario coverage for supply guarantee scheduling is obtained using the following formula. : in, This is the sum of the number of areas with power shortages and the number of areas with power support. For the number of moments, This is a collection of areas with power shortages. For the collection of power support areas, This is the set of times for power shortage scheduling.

17. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the inter-provincial collaborative supply guarantee scheduling method for power grids as described in any one of claims 1 to 8.

18. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the inter-provincial collaborative supply guarantee scheduling method for power grids as described in any one of claims 1 to 8.

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