Cooperative scheduling method and system based on system unbalance, and medium

Abstract

The invention discloses a cooperative scheduling method and system based on system unbalance, and a medium. The method comprises the following steps: acquiring the system unbalance, AC / DC iteration return information, section basic information, sensitivity information of various devices associated with a section, a system total load and a bus load prediction value; on the basis of the total load of the system and the predicted value of the bus load, calculating to obtain an unbalance allocation coefficient of each bus, and determining a to-be-corrected section set on the basis of the section basic information, the sensitivity information, the unbalance allocation coefficient and a preset system unbalance sensitivity threshold; inputting the to-be-corrected section set, the system unbalance amount, the alternating current and direct current iteration return information and the sensitivity information into the transformed network security constraint model to obtain an optimal scheduling result; and a scheduling instruction is generated based on the optimized scheduling result to perform power system scheduling control, so that accurate and efficient power scheduling control is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power dispatch automation, and in particular to a collaborative dispatching method and system based on system imbalance and a medium. BACKGROUND

[0002] In the operation of a power system, system imbalance is an inevitable phenomenon, which is essentially a mismatch between the actual operating power of the power grid and the calculation model. This imbalance can be caused by various factors, including deviations in generation plan execution, load prediction errors, network loss estimation distortion, etc. If not effectively handled, system imbalance can cause the flow deviation of alternating current and direct current iterations to exceed the standard, causing the calculated value of the key section flow to deviate from the actual operating condition. This not only reduces the efficiency of the power system, but also can cause safety problems such as section over-limit, and even threatens the stable operation of the entire power grid. Therefore, it is crucial to achieve accurate and efficient power dispatching control, especially in the presence of system imbalance, to ensure the safe, reliable and efficient operation of the power system.

[0003] The existing methods for handling system imbalance mainly include manual intervention, global slack variable, uniform allocation and decoupling verification. However, these methods have many defects. Among them, the manual intervention method cannot adapt to real-time clearing scenarios due to response delay; the global slack variable method adds a penalty term to the objective function, which may blur the safety boundary and cause a sharp increase in the risk of section over-limit; the uniform allocation method ignores the load distribution characteristics, which can easily lead to an increase in the probability of node voltage over-limit; and the decoupling verification method causes the deviation to accumulate out of control due to the separation of the optimization model and the power flow calculation. These methods cannot simultaneously solve the three major demands of imbalance elimination, flow deviation suppression and physical executability maintenance while ensuring the timeliness of real-time clearing, thereby limiting the accuracy and efficiency of power dispatching control. SUMMARY

[0004] The present application provides a collaborative dispatching method and system based on system imbalance, which can achieve accurate and efficient power dispatching control in the presence of system imbalance.

[0005] An embodiment of the present application provides a collaborative dispatching method based on system imbalance, comprising:

[0006] obtaining the system imbalance, alternating current and direct current iteration return information, section basic information, sensitivity information of various devices associated with the section, system total load and bus load prediction value that occurred in the previous iteration;

[0007] Based on the total system load and the predicted bus load, the unbalance allocation coefficient of each bus is calculated. Based on the basic cross-sectional information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold, the set of cross-sections to be corrected is determined.

[0008] The set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information are input into the modified network security constraint model to obtain the optimized scheduling result.

[0009] Based on the optimized scheduling results, generator power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies are generated for power system dispatch control.

[0010] This application's embodiments, by calculating the imbalance sharing coefficients of each bus and determining the set of sections to be corrected, can accurately locate the sections requiring correction, avoiding indiscriminate processing of all sections. This not only improves computational efficiency but also ensures the targetedness and accuracy of subsequent dispatch control, enabling dispatch instructions to precisely solve practical problems. Through the modified network security constraint model, system imbalance and its impact are incorporated into the dispatch optimization process, allowing the optimized dispatch results to more accurately reflect the actual operation of the power grid. This helps generate dispatch schemes that meet safety constraints while considering system imbalance, ensuring the accuracy and reliability of dispatch control. By generating specific dispatch instructions and control strategies based on the optimized dispatch results, the optimized decisions can be transformed into actual power grid operations, ensuring the accuracy and executability of dispatch instructions. This enables the power grid to operate safely and efficiently according to the optimized scheme even with system imbalance. Compared with existing technologies, this application can achieve accurate and efficient power dispatch control even with system imbalance.

[0011] Further, the step of determining the set of cross-sections to be corrected based on the basic cross-sectional information, the sensitivity information, the imbalance sharing coefficient, and a preset system imbalance sensitivity threshold specifically involves:

[0012] Traverse the associated busbars of the target section, multiply the unbalance allocation coefficient corresponding to the associated busbar by the sensitivity of the node load to the section, and sum the multiplication of all associated busbars to obtain the unbalance sensitivity of the section association system. The associated busbars are obtained by analyzing the basic information of the section, and the sensitivity of the node load to the section is determined according to the sensitivity information.

[0013] The imbalance sensitivity is compared with a preset system imbalance sensitivity threshold to filter out sections that are greater than or equal to the system imbalance sensitivity threshold, forming a set of sections to be corrected.

[0014] By calculating the bus imbalance allocation coefficient and determining the set of sections to be corrected, the sections that need correction can be accurately located, avoiding indiscriminate processing of all sections. This not only improves calculation efficiency but also ensures the pertinence and accuracy of subsequent scheduling control, enabling scheduling instructions to accurately solve practical problems.

[0015] Furthermore, the product of the unbalance allocation coefficient corresponding to the associated bus and the sensitivity of the nodal load to the cross-section, and the sum of the products of all associated buses, yields the relevant formula for the unbalance sensitivity of the cross-section associated system, specifically:

[0016]

[0017] In the formula, s is the cross-section number, t is the time period, k is the busbar number, and K is the total number of buses. For the unbalance sensitivity of the cross-sectional correlation system, G k-s The sensitivity of the nodal load to the cross section; This is the unbalanced allocation coefficient corresponding to the associated bus.

[0018] Furthermore, if the imbalance sensitivity is lower than the system imbalance sensitivity threshold, it is determined that the impact of the system imbalance on the cross-sectional power flow is zero, and the system imbalance is not allocated in the network security constraint modification of the corresponding cross-section.

[0019] By selecting sections that are insensitive to system imbalances and ignoring the imbalance distribution of these sections during network security constraint modifications, unnecessary calculations and adjustments are effectively reduced, dispatching efficiency is improved, and error accumulation due to over-correction is avoided. This ensures both computational efficiency and the accuracy and reliability of power dispatching.

[0020] Furthermore, the system imbalance sensitivity threshold is set according to the power grid operation scenario, section safety margin and historical power flow data, and the value range is a floating-point number between [0,1].

[0021] Furthermore, the step of inputting the set of cross-sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result specifically involves:

[0022] The lower and upper transmission limits of each section in the set of sections to be corrected are used as constraint boundaries.

[0023] The product of the system imbalance and the corresponding imbalance sensitivity is used as the power flow correction term. The output of market units, the planned output of non-market units, the power of DC tie lines, the power of AC tie lines, the bus load and the total output of the system balancing machine in the AC / DC iterative return information are used as basic parameters. Based on the constraint boundary and the basic parameters, the modified network constraint model is determined.

[0024] The sensitivity information is used as the power flow calculation coefficient and substituted into the network security constraint model. The network security constraint model is solved by a mixed integer linear programming algorithm to obtain the unit output plan value, tie line power plan value and power flow calculation result of each section to be corrected, which together constitute the optimized scheduling result.

[0025] By incorporating system imbalances and their sensitivity into the network security constraint model and solving it using a mixed-integer linear programming algorithm, it is possible to precisely adjust unit output and DC tie-line power even in the presence of system imbalances. This ensures that the safety constraints of each section to be corrected are met, thereby achieving accurate and efficient power dispatch control, guaranteeing the safe and stable operation of the power grid, and ensuring the physical executability of real-time market clearing results.

[0026] Furthermore, the expression for the modified network security constraint model is as follows:

[0027]

[0028] In the formula, These represent the lower and upper transmission limits for section s, respectively; t represents the time period information; I represents the total number of market units; J represents the total number of non-market units; H represents the total number of DC tie lines; R represents the total number of AC tie lines; K represents the total number of buses; P i,t Contribute to the market units; Planned output value for non-market units; For the injected power of the DC tie line; TL r,t For the injected power of the AC tie line; L k,t For the bus load; PSG t c0 represents the total output of the system balancing machine; c0 represents the AC / DC iterative return information; L imb G represents the system imbalance. i-s G j-s G h-s G r-s G k-s and These are, respectively, the output sensitivity of market units, the output sensitivity of non-market units, the DC tie line injected power sensitivity, the AC tie line injected power sensitivity, the node load sensitivity to the cross section, and the imbalance sensitivity. This represents the positive relaxation amount of the cross-sectional limit; This represents the negative relaxation amount of the cross-sectional limit.

[0029] Furthermore, the generation of unit power adjustment commands, DC tie-line power modulation commands, and over-limit section control strategies based on the optimized scheduling results for power system dispatch control specifically includes:

[0030] Based on the difference between the optimized unit output and the current actual output in the optimized scheduling results, and combined with the unit regulation rate and capacity limit, a unit power adjustment command is generated.

[0031] Based on the deviation between the optimized transmission power of the DC tie line and the current operating power in the optimized scheduling results, a DC tie line power modulation command is generated in combination with the tie line power adjustment range.

[0032] For the over-limit section information in the optimized scheduling results, based on the sensitivity information, determine the associated units, loads or tie lines that need to be adjusted, and formulate an over-limit section control strategy that includes power transfer path, adjustment amount and execution timing.

[0033] Based on the unit power adjustment command, the DC tie line power modulation command, and the over-limit section control strategy, the accurate power flow output by the optimized scheduling result is used as the verification basis for the verification. After the feasibility is confirmed by online safety verification, the command is sent to the automatic generation control system of the power plant or the DC control and protection system of the converter station for execution.

[0034] By generating specific dispatch instructions and control strategies based on the optimized dispatch results, the optimized decisions can be transformed into actual power grid operations, ensuring the accuracy and executability of the dispatch instructions and enabling the power grid to operate safely and efficiently according to the optimized scheme even in the presence of system imbalances.

[0035] Another embodiment of the present invention provides a cooperative scheduling system based on system imbalance, comprising: an acquisition module, a determination module, a solution module, and a scheduling module;

[0036] The acquisition module is used to acquire the system imbalance, AC / DC iteration return information, basic section information, sensitivity information of various equipment associated with the section, total system load, and predicted bus load from the previous iteration.

[0037] The determining module is used to calculate the unbalance allocation coefficient of each bus based on the total system load and the predicted bus load, and to determine the set of sections to be corrected based on the basic section information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold.

[0038] The solution module is used to input the set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result;

[0039] The scheduling module is used to generate unit power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies based on the optimized scheduling results, so as to carry out power system scheduling and control.

[0040] This application's embodiments, by calculating the bus imbalance allocation coefficient and determining the set of sections to be corrected, can accurately locate the sections requiring correction, avoiding indiscriminate processing of all sections. This not only improves computational efficiency but also ensures the targetedness and accuracy of subsequent dispatch control, enabling dispatch instructions to precisely address practical problems. Through the modified network security constraint model, system imbalance and its impact are incorporated into the dispatch optimization process, allowing the optimized dispatch results to more accurately reflect the actual operation of the power grid. This helps generate dispatch schemes that comply with safety constraints while considering system imbalance, ensuring the accuracy and reliability of dispatch control. By generating specific dispatch instructions and control strategies based on the optimized dispatch results, the optimized decisions can be transformed into actual power grid operations, ensuring the accuracy and executability of dispatch instructions. This enables the power grid to operate safely and efficiently according to the optimized scheme even with system imbalance. Compared with existing technologies, this application can achieve accurate and efficient power dispatch control even with system imbalance.

[0041] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform steps of the cooperative scheduling method based on system imbalance as described in the present invention. Attached Figure Description

[0042] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating an embodiment of the collaborative scheduling method based on system imbalance provided in this application;

[0044] Figure 2 This is a schematic diagram of an embodiment of the collaborative scheduling system based on system imbalance provided in this application. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0047] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0048] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0049] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0050] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0051] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0052] System imbalance is a phenomenon where the actual power output of the power grid differs from the calculated power model during power system operation. It can be caused by factors such as generation plan deviations, load forecasting errors, and distorted network loss estimations. If left unaddressed, it can lead to excessive AC / DC iterative power flow deviations, causing safety issues such as exceeding capacity limits and threatening the stable operation of the power grid. Existing methods, such as manual intervention, global relaxation variable methods, uniform allocation methods, and decoupling verification methods, all have shortcomings. These methods cannot simultaneously ensure real-time clearing while addressing imbalance elimination, power flow deviation suppression, and physical feasibility maintenance, thus limiting the accuracy and efficiency of dispatch control.

[0053] See Figure 1 To achieve accurate and efficient power dispatch control, an embodiment of the present invention provides a collaborative dispatch method based on system imbalance, including steps S101 to S104.

[0054] Step S101: Obtain the system imbalance, AC / DC iteration return information, basic section information, sensitivity information of various equipment associated with the section, total system load, and predicted bus load from the previous iteration.

[0055] In some embodiments, the system imbalance after the previous iteration is obtained by calling the real-time data interface (such as API interface) with the dispatch control center. The system imbalance is the return value of the system imbalance that occurred in the previous AC / DC iteration, which reflects the deviation between the actual operating power of the power grid and the calculation model. Generally, the dispatch control center will record these imbalances, which usually exist in the form of power difference.

[0056] It should be noted that Security-Constrained Economic Dispatch (SCED), as the core technology for real-time power market clearing, directly determines the security and physical executability of the unit output commands and tie-line power control commands issued by the dispatch center. Currently, the industry employs multi-round AC / DC iterative algorithms to coordinate security and economy: the first round optimizes and clears the generation of unit combinations and DC transmission plans, and subsequent rounds correct the security constraint boundaries through AC power flow verification. However, due to deviations in generation plan execution, load forecasting errors, and distortions in network loss estimation, system imbalances can occur during the AC iterative verification process.

[0057] In some embodiments, AC / DC iteration return information is obtained by reading the output file or database record of the optimization calculation module. The AC / DC iteration return information includes the unit output, tie line power, and cross-sectional power flow of the previous iteration. This information is the output of the multi-round AC / DC iteration algorithm and is used for subsequent safety constraint optimization.

[0058] In some embodiments, basic section information is obtained from the power grid topology database using SQL queries. This basic section information includes the section number, the lower and upper transmission limits of the section, and a list of devices associated with the section. This information is part of the power grid topology and is stored in the power grid topology database.

[0059] In some embodiments, by calling the interface of the sensitivity analysis module, sensitivity information of various devices associated with the cross-section is obtained. Device sensitivity information refers to a quantitative description of how sensitive the power flow (i.e., the power flow through that cross-section) of a specific cross-section in a power system is to parameter changes (such as output changes, impedance changes, etc.) of various devices (such as generators, transformers, transmission lines, etc.) in the system. This sensitivity information is usually expressed in numerical form, reflecting the direct impact of device parameter changes on the power flow of the cross-section.

[0060] In some embodiments, the total load of the current system is obtained by calling the interface of the real-time monitoring system; and the bus load forecast value is obtained by calling the interface of the load forecast module, wherein the bus load forecast value is calculated by the load forecast module and reflects the load situation of the bus in the future.

[0061] It should be noted that this also includes obtaining time period information to determine the current operating period, which may affect the calculation of the bus load forecast and the total system load, thereby indirectly affecting the subsequent sensitivity calculation.

[0062] Step S102: Based on the total system load and the predicted bus load, calculate the unbalance allocation coefficient of each bus, and determine the set of sections to be corrected based on the basic cross-sectional information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold.

[0063] In some embodiments, the unbalance allocation coefficient of each bus is calculated based on the total system load and the predicted bus load. Specifically, firstly, all sections in the system are traversed to determine whether each section needs to respond to unbalance correction. If a section needs to respond to unbalance correction, the unbalance sensitivity of the system associated with that section is initialized. The purpose of initialization is to set initial values ​​for subsequent sensitivity calculations to ensure the smooth progress of the calculation process. Then, each bus in the system is traversed, and its unbalance allocation coefficient is calculated one by one. For each bus, its unbalance allocation coefficient is calculated according to the following... The calculation formula is: In the formula, This is the allocation factor for the load imbalance of the busbar. For the load forecast of this bus, L total Let be the total load of the system; using the above formula, the unbalanced allocation coefficient of each bus can be obtained, which reflects the proportion of each bus in the total load of the system.

[0064] By selecting the sections that require imbalance correction, unnecessary calculations for all sections can be avoided, thus improving the overall system's computational efficiency. Calculating the bus imbalance allocation coefficient allows for more precise distribution of system imbalance, preventing calculation errors caused by improper allocation.

[0065] In some embodiments, determining the set of cross-sections to be corrected based on the basic cross-sectional information, the sensitivity information, the unbalance allocation coefficient, and a preset system unbalance sensitivity threshold includes: traversing the associated buses of the target cross-section, multiplying the unbalance allocation coefficient corresponding to the associated bus with the sensitivity of the node load to the cross-section, and summing the multiplications of all associated buses to obtain the unbalance sensitivity of the cross-section associated system, wherein the associated bus is obtained by analyzing the basic cross-sectional information, and the sensitivity of the node load to the cross-section is determined according to the sensitivity information; comparing the unbalance sensitivity with the preset system unbalance sensitivity threshold to filter out cross-sections that are greater than or equal to the system unbalance sensitivity threshold, thus forming the set of cross-sections to be corrected. Specifically, firstly, a list of buses directly related to the cross-section is extracted from the basic information of the cross-section. Then, by analyzing the cross-section's topology and electrical connections, it is determined which buses are directly related to the power flow calculation of that cross-section, i.e., the associated buses are identified. Next, the sensitivity value of each associated bus is extracted from the sensitivity information of various equipment associated with the cross-section. For each associated bus, the sensitivity of its nodal load to the cross-section is determined based on its sensitivity information. Finally, for each target cross-section, all buses associated with that cross-section are traversed, and for each associated bus, its unbalanced allocation coefficient is calculated. Sensitivity G of nodal load to cross section k-sThe product of these products is used to obtain the product of several associated busbars; subsequently, the products of all associated busbars are summed to obtain the unbalance sensitivity of the cross-sectional associated system. That is, the sensitivity of each cross-section; finally, the calculated sensitivity of each cross-section is... If the system imbalance sensitivity threshold is compared with the preset system imbalance sensitivity threshold, then the section is added to the set of sections to be corrected.

[0066] In some embodiments, the formula for obtaining the unbalance sensitivity of the cross-section association system by multiplying the unbalance allocation coefficient corresponding to the associated bus with the sensitivity of the nodal load to the cross-section, and summing the products of all associated buses, is as follows:

[0067]

[0068] In the formula, s is the cross-section number, t is the time period, k is the busbar number, and K is the total number of buses. For the unbalance sensitivity of the cross-sectional correlation system, G k-s The sensitivity of the nodal load to the cross section; This is the unbalanced allocation coefficient corresponding to the associated bus.

[0069] In some embodiments, the system imbalance sensitivity threshold is set according to the power grid operation scenario, section safety margin and historical power flow data, and the value range is a floating-point number between [0,1].

[0070] By calculating the bus imbalance allocation coefficient and determining the set of sections to be corrected, the sections that need correction can be accurately located, avoiding indiscriminate processing of all sections. This not only improves calculation efficiency but also ensures the pertinence and accuracy of subsequent scheduling control, enabling scheduling instructions to accurately solve practical problems.

[0071] In some embodiments, if the sensitivity of the imbalance is lower than the system imbalance sensitivity threshold, the impact of the system imbalance on the cross-sectional power flow is determined to be zero, and the system imbalance is not allocated in the network security constraint modification of the corresponding cross-section. Specifically, if the sensitivity value of a certain cross-section is lower than the system imbalance sensitivity threshold, the impact of the system imbalance on its power flow is determined to be zero. For cross-sections with sensitivity lower than the threshold, the system imbalance is not allocated in its network security constraint modification, that is, the impact of the system imbalance is not considered, and the original network security constraints remain unchanged.

[0072] It should be noted that an external interface can be set to provide the method with preference information for allocating system imbalances. By setting relevant parameters, the method can automatically distinguish the adjustment range and type.

[0073] By selecting sections that are insensitive to system imbalances and ignoring the imbalance distribution of these sections during network security constraint modifications, unnecessary calculations and adjustments are effectively reduced, dispatching efficiency is improved, and error accumulation due to over-correction is avoided. This ensures both computational efficiency and the accuracy and reliability of power dispatching.

[0074] Step S103: Input the set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result;

[0075] In some embodiments, the step of inputting the set of sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result specifically involves: using the lower and upper transmission limits of each section in the set of sections to be corrected as constraint boundaries; using the product of the system imbalance and the corresponding imbalance sensitivity as a power flow correction term; using the market unit output, non-market unit planned output, DC tie line power, AC tie line power, bus load, and total output of the system balancing machine in the AC / DC iterative return information as basic parameters; and determining the modified network constraint model based on the constraint boundaries and the basic parameters; using the sensitivity information as power flow calculation coefficients, substituting them into the network security constraint model, and solving the network security constraint model using a mixed integer linear programming algorithm to obtain the planned unit output value, planned tie line power value, and power flow calculation results of each section to be corrected, which together constitute the optimized scheduling result.

[0076] In some embodiments, for the target section to be corrected, the system imbalance and its sensitivity information are incorporated into the network security constraint model. The expression of the modified network security constraint model is as follows:

[0077] In the formula, These represent the lower and upper transmission limits for section s, respectively; t represents the time period information; I represents the total number of market units; J represents the total number of non-market units; H represents the total number of DC tie lines; R represents the total number of AC tie lines; K represents the total number of buses; P i,t Contribute to the market units; Planned output value for non-market units; For the injected power of the DC tie line; TL r,t For the injected power of the AC tie line; Lk,t For the bus load; PSG t c0 represents the total output of the system balancing machine; c0 represents the AC / DC iterative return information; L imb G represents the system imbalance. i-s G j-s G h-s G r-s G k-s and These are, respectively, the output sensitivity of market units, the output sensitivity of non-market units, the DC tie line injected power sensitivity, the AC tie line injected power sensitivity, the node load sensitivity to the cross section, and the imbalance sensitivity. This represents the positive relaxation amount of the cross-sectional limit; This represents the negative relaxation amount of the cross-sectional limit.

[0078] It should be noted that the model modified with network security constraints is a mixed-integer linear programming model, which can be solved directly by calling existing optimization algorithm software packages (such as Gurobi or CPLEX). After solving, the results such as unit output, tie line power, and cross-sectional relaxation can be obtained, and the relevant cross-sectional power flow can be calculated based on the solution results.

[0079] It should be noted that the optimized scheduling results include, but are not limited to, unit output and tie-line power information after considering system imbalance, cross-sectional power flow information after considering system imbalance, information on cross-sectional sections where the slack is still greater than 0 after optimization and adjustment, and cross-sectional associated system imbalance information. Specifically, the cross-sectional associated system imbalance information is the sum of the system imbalance sensitivity of the cross-sectional section considering system imbalance, the absolute value of the system bus load, and the sum of the absolute value of the cross-sectional associated bus load multiplied by the sensitivity.

[0080] By incorporating system imbalances and their sensitivity into the network security constraint model and solving it using a mixed-integer linear programming algorithm, it is possible to precisely adjust unit output and DC tie-line power even in the presence of system imbalances. This ensures that the safety constraints of each section to be corrected are met, thereby achieving accurate and efficient power dispatch control, guaranteeing the safe and stable operation of the power grid, and ensuring the physical executability of real-time market clearing results.

[0081] Step S104: Based on the optimized scheduling results, generate unit power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies to perform power system dispatch control.

[0082] In some embodiments, the step of generating unit power adjustment commands, DC tie-line power modulation commands, and over-limit section control strategies based on the optimized scheduling results for power system dispatch control specifically involves: generating unit power adjustment commands based on the difference between the optimized unit output and the current actual output in the optimized scheduling results, combined with unit regulation rates and capacity limits; generating DC tie-line power modulation commands based on the deviation between the optimized transmission power and the current operating power of the DC tie-line in the optimized scheduling results, combined with the tie-line power regulation range; determining the associated units, loads, or tie-lines requiring adjustment based on the sensitivity information for over-limit sections in the optimized scheduling results, and formulating an over-limit section control strategy including power transfer paths, adjustment amounts, and execution sequences; and verifying the precise power flow output from the optimized scheduling results as the verification basis, and after confirming feasibility through online safety verification, issuing the commands to the automatic generation control system of the power plant or the DC control and protection system of the converter station for execution. Specifically, firstly, for each generating unit, the difference between the optimized output in the optimized scheduling result and the current actual output is calculated. Based on the unit's regulation rate and capacity limitations, this output difference is adjusted to ensure the adjustment command is within the unit's regulation capacity and range. For example, if the regulation rate limit is 10MW per minute, and the calculated output difference is 50MW, the adjustment command needs to be executed gradually over 5 minutes. Based on the adjusted output difference, a unit power adjustment command is generated, including the adjustment direction (increase or decrease), adjustment amount, and execution time. Secondly, for each DC tie line, the deviation between the optimized transmission power in the optimized scheduling result and the current operating power is calculated. Based on the tie line's power regulation range, the power deviation is adjusted to ensure the adjustment command is within the tie line's regulation capacity. For example, if the regulation range is ±50MW, and the calculated power deviation is 60MW, the adjustment command needs to be executed twice. Based on the adjusted power deviation, a DC tie line power modulation command is generated, including the adjustment direction (increase or decrease), adjustment amount, and execution time. Then, based on the over-limit section information and sensitivity information, the associated units, loads, or tie lines that need adjustment are determined. Sensitivity information is used to assess which equipment has the greatest impact on the over-limit section, thus prioritizing the adjustment of these equipment. An over-limit section control strategy, including power transfer paths, adjustment amounts, and execution timing, is formulated, and the formulated control strategy is translated into specific control commands, including the name of the equipment to be adjusted, the direction of adjustment, the adjustment amount, and the execution time. Subsequently, the generated scheduling commands are input into the fast safety analysis module built into the scheduling system (such as online static safety analysis). The accurate power flow output of the optimized scheduling results is used as the verification basis for safety verification. The verification content includes whether the execution of the command will cause new over-limit problems and whether the execution of the command will lead to equipment overload or voltage over-limit.Finally, if the verification result shows that the instruction is not feasible, the instruction needs to be readjusted and verified again. If the verification result shows that the instruction is feasible, the instruction is confirmed as an executable instruction and sent to the corresponding physical execution unit such as the power plant (automatic generation control AGC system acting on generator sets) or converter station (acting on DC control and protection system) through the power system dedicated communication network.

[0083] It should be noted that the specific steps for formulating an over-limit section control strategy, including power transfer paths, adjustment amounts, and execution timing, are as follows: First, determine the power transfer path from the sending end to the receiving end of the over-limit section to ensure that power adjustments do not trigger new over-limit issues. Second, calculate the required power adjustment amount based on the power flow value of the over-limit section and the lower and upper transmission limits of the section. Third, formulate the adjustment execution timing based on the equipment's regulation rate and power adjustment path to ensure the smoothness and safety of the adjustment process.

[0084] It should be noted that the dispatch instructions received by the power plant will control the output of the generator units, adjust the transmission power of the DC tie line, etc., thereby actually changing the power flow distribution in the power grid.

[0085] By generating specific dispatch instructions and control strategies based on the optimized dispatch results, the optimized decisions can be transformed into actual power grid operations, ensuring the accuracy and executability of the dispatch instructions and enabling the power grid to operate safely and efficiently according to the optimized scheme even in the presence of system imbalances.

[0086] This application's embodiments, by calculating the imbalance sharing coefficients of each bus and determining the set of sections to be corrected, can accurately locate the sections requiring correction, avoiding indiscriminate processing of all sections. This not only improves computational efficiency but also ensures the targetedness and accuracy of subsequent dispatch control, enabling dispatch instructions to precisely solve practical problems. Through the modified network security constraint model, system imbalance and its impact are incorporated into the dispatch optimization process, allowing the optimized dispatch results to more accurately reflect the actual operation of the power grid. This helps generate dispatch schemes that meet safety constraints while considering system imbalance, ensuring the accuracy and reliability of dispatch control. By generating specific dispatch instructions and control strategies based on the optimized dispatch results, the optimized decisions can be transformed into actual power grid operations, ensuring the accuracy and executability of dispatch instructions. This enables the power grid to operate safely and efficiently according to the optimized scheme even with system imbalance. Compared with existing technologies, this application can achieve accurate and efficient power dispatch control even with system imbalance.

[0087] like Figure 2 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided;

[0088] One embodiment of the present invention provides a cooperative scheduling device based on system imbalance, comprising: an acquisition module 100, a determination module 200, a solution module 300, and a scheduling module;

[0089] The acquisition module is used to acquire the system imbalance, AC / DC iteration return information, basic section information, sensitivity information of various equipment associated with the section, total system load, and predicted bus load from the previous iteration.

[0090] The determining module is used to calculate the unbalance allocation coefficient of each bus based on the total system load and the predicted bus load, and to determine the set of sections to be corrected based on the basic section information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold.

[0091] The solution module is used to input the set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result;

[0092] The scheduling module is used to generate unit power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies based on the optimized scheduling results, so as to carry out power system scheduling and control.

[0093] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the cooperative scheduling method based on system imbalance provided by any of the above-described method embodiments of the present invention.

[0094] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0095] Based on the above embodiments of the cooperative scheduling method based on system imbalance, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the cooperative scheduling method based on system imbalance of any embodiment of the present invention.

[0096] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0097] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0098] The processor can 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. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting various parts of the terminal device via various interfaces and lines.

[0099] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the cooperative scheduling method based on system imbalance described in any of the above-described method embodiments of the present invention.

[0100] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0101] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A cooperative scheduling method based on system imbalance, characterized in that, include: Obtain the system imbalance, AC / DC iteration return information, basic section information, sensitivity information of various equipment associated with the section, total system load, and predicted bus load from the previous iteration. Based on the total system load and the predicted bus load, the unbalance allocation coefficient of each bus is calculated. Based on the basic cross-sectional information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold, the set of cross-sections to be corrected is determined. The set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information are input into the modified network security constraint model to obtain the optimized scheduling result. Based on the optimized scheduling results, generator power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies are generated for power system dispatch control.

2. The cooperative scheduling method based on system imbalance as described in claim 1, characterized in that, The determination of the set of cross-sections to be corrected based on the basic cross-sectional information, the sensitivity information, the imbalance sharing coefficient, and the preset system imbalance sensitivity threshold is specifically as follows: Traverse the associated busbars of the target section, multiply the unbalance allocation coefficient corresponding to the associated busbar by the sensitivity of the node load to the section, and sum the multiplication of all associated busbars to obtain the unbalance sensitivity of the section association system. The associated busbars are obtained by analyzing the basic information of the section, and the sensitivity of the node load to the section is determined according to the sensitivity information. The imbalance sensitivity is compared with a preset system imbalance sensitivity threshold to filter out sections that are greater than or equal to the system imbalance sensitivity threshold, forming a set of sections to be corrected.

3. The cooperative scheduling method based on system imbalance as described in claim 2, characterized in that, The formula for the sensitivity of the unbalance quantity of the cross-section association system is obtained by multiplying the unbalance allocation coefficient corresponding to the associated bus with the sensitivity of the nodal load to the cross-section, and summing the products of all associated buses. Specifically: In the formula, s is the cross-section number, t is the time period, k is the busbar number, and K is the total number of buses. For the unbalance sensitivity of the cross-sectional correlation system, G k-s The sensitivity of the nodal load to the cross section; This is the unbalanced allocation coefficient corresponding to the associated bus.

4. The cooperative scheduling method based on system imbalance as described in claim 2, characterized in that, If the sensitivity of the imbalance is lower than the sensitivity threshold of the system imbalance, it is determined that the impact of the system imbalance on the cross-sectional power flow is zero, and the system imbalance is not allocated in the network security constraint modification of the corresponding cross-section.

5. The cooperative scheduling method based on system imbalance as described in claim 1, characterized in that, The system imbalance sensitivity threshold is set according to the power grid operation scenario, section safety margin and historical power flow data, and the value range is a floating-point number between [0,1].

6. The cooperative scheduling method based on system imbalance as described in claim 1, characterized in that, The process involves inputting the set of cross-sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result. Specifically: The lower and upper transmission limits of each section in the set of sections to be corrected are used as constraint boundaries. The product of the system imbalance and the corresponding imbalance sensitivity is used as the power flow correction term. The output of market units, the planned output of non-market units, the power of DC tie lines, the power of AC tie lines, the bus load and the total output of the system balancing machine in the AC / DC iterative return information are used as basic parameters. Based on the constraint boundary and the basic parameters, the modified network constraint model is determined. The sensitivity information is used as the power flow calculation coefficient and substituted into the network security constraint model. The network security constraint model is solved by a mixed integer linear programming algorithm to obtain the unit output plan value, tie line power plan value and power flow calculation result of each section to be corrected, which together constitute the optimized scheduling result.

7. The cooperative scheduling method based on system imbalance as described in claim 6, characterized in that, The modified expression for the network security constraint model is as follows: In the formula, These represent the lower and upper transmission limits for section s, respectively; t represents the time period information; I represents the total number of market units; J represents the total number of non-market units; H represents the total number of DC tie lines; R represents the total number of AC tie lines; K represents the total number of buses; P i,t Contribute to the market units; Planned output value for non-market units; For the injected power of the DC tie line; TL r,t For the injected power of the AC tie line; L k,t For the bus load; PSG t c0 represents the total output of the system balancing machine; c0 represents the AC / DC iterative return information; L imb G represents the system imbalance. i-s G j-s G h-s G r-s G k-s and These are, respectively, the output sensitivity of market units, the output sensitivity of non-market units, the DC tie line injected power sensitivity, the AC tie line injected power sensitivity, the node load sensitivity to the cross section, and the imbalance sensitivity. This represents the positive relaxation amount of the cross-sectional limit; This represents the negative relaxation amount of the cross-sectional limit.

8. The cooperative scheduling method based on system imbalance as described in claim 1, characterized in that, The process of generating unit power adjustment commands, DC tie-line power modulation commands, and over-limit section control strategies based on the optimized scheduling results for power system dispatch control specifically includes: Based on the difference between the optimized unit output and the current actual output in the optimized scheduling results, and combined with the unit regulation rate and capacity limit, a unit power adjustment command is generated. Based on the deviation between the optimized transmission power of the DC tie line and the current operating power in the optimized scheduling results, a DC tie line power modulation command is generated in combination with the tie line power adjustment range. For the over-limit section information in the optimized scheduling results, based on the sensitivity information, determine the associated units, loads or tie lines that need to be adjusted, and formulate an over-limit section control strategy that includes power transfer path, adjustment amount and execution timing. Based on the unit power adjustment command, the DC tie line power modulation command, and the over-limit section control strategy, the accurate power flow output by the optimized scheduling result is used as the verification basis for the verification. After the feasibility is confirmed by online safety verification, the command is sent to the automatic generation control system of the power plant or the DC control and protection system of the converter station for execution.

9. A cooperative scheduling system based on system imbalance, characterized in that, include: The module includes an acquisition module, a determination module, a solution module, and a scheduling module. The acquisition module is used to acquire the system imbalance, AC / DC iteration return information, basic section information, sensitivity information of various equipment associated with the section, total system load, and predicted bus load from the previous iteration. The determining module is used to calculate the unbalance allocation coefficient of each bus based on the total system load and the predicted bus load, and to determine the set of sections to be corrected based on the basic section information, the sensitivity information, the unbalance allocation coefficient and the preset system unbalance sensitivity threshold. The solution module is used to input the set of cross sections to be corrected, the system imbalance, the AC / DC iterative return information, and the sensitivity information into the modified network security constraint model to obtain the optimized scheduling result; The scheduling module is used to generate unit power adjustment commands, DC tie line power modulation commands, and over-limit section control strategies based on the optimized scheduling results, so as to carry out power system scheduling and control.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the steps of the cooperative scheduling method based on system imbalance as described in any one of claims 1-8.

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