Electric power economic dispatching model solving method and device, storage medium, program product and computer equipment

Abstract

The invention discloses an electric power economic dispatching model solving method and device, a storage medium, a program product and computer equipment, and the method comprises the steps: constructing a safety constraint mathematical model based on an overload generator tripping type electric power system safety and stability control device, and determining an original feasible region of an overload generator tripping type condition section according to the safety constraint mathematical model; reconstructing the original feasible region through the introduced cut plane to obtain a reconstructed feasible region; solving is carried out based on power monitoring and data acquisition SCADA real-time acquisition data, market clearing data and a reconstructed feasible region to generate a new cut plane through iteration, so that on the premise of guaranteeing precision, power market intra-day real-time rolling clearing can be rapidly solved, and the efficiency is improved. The method effectively guarantees the speed and precision requirements of power market construction for safety constraint economic dispatching, ensures that the market clearing result has the actual performability of a power grid, and especially solves the problem that the real-time clearing of the power market is difficult due to overload generator tripping type condition sections.

Description

Technical Field

[0001] This application relates to the field of power dispatching technology, and in particular to a method, apparatus, storage medium, program product, and computer equipment for solving power economic dispatching models. Background Technology

[0002] With the rapid advancement of power market reforms and the massive integration of new energy sources into the grid, the uncertainty and scale of variables in the power market have increased significantly. Safety-constrained economic dispatch is a core issue in the real-time power market; the quality of its solution determines the safety and economy of the power grid. Furthermore, grid operation also needs to consider conditional sections coupled with optimization variables.

[0003] In related technologies, the following three approaches are commonly used to solve optimization problems related to economic scheduling with safety constraints: First, model simplification strategies, which reduce complexity by linearizing constraints, but this can lead to errors; second, decomposition algorithms, which use decomposition methods such as the Benders algorithm to achieve efficient convergence of solutions through iteration, but this algorithm is not adaptable to conditional sections; and third, heuristic algorithms, which combine heuristic algorithms such as genetic algorithms with traditional optimization algorithms such as interior-point methods to screen feasible solution spaces, but global optimality is difficult to guarantee. Summary of the Invention

[0004] To address the aforementioned technical issues, this application proposes a method, apparatus, storage medium, program product, and computer equipment for solving a power economic dispatch model. This method enables rapid calculation of real-time rolling clearing of the power market within a day, while ensuring accuracy. It effectively guarantees the speed and accuracy requirements of power market construction for safety-constrained economic dispatch and ensures that the market clearing results are actually feasible for the power grid.

[0005] In a first aspect, embodiments of this application provide a method for solving a power economic dispatch model, including:

[0006] A safety constraint mathematical model based on the overload tripping type power system safety and stability control device is constructed, and the original feasible region of the overload tripping type condition section is determined according to the safety constraint mathematical model.

[0007] The original feasible region is reconstructed by introducing a cutting plane to obtain a reconstructed feasible region;

[0008] The solution is based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region, in order to iteratively generate a new cutting plane.

[0009] Optionally, the construction of the safety constraint mathematical model based on the overload tripping type power system safety and stability control device includes:

[0010] Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines;

[0011] Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value.

[0012] Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

[0013] Optionally, the number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The reconstruction of the original feasible region through the introduced cutting planes to obtain the reconstructed feasible region includes:

[0014] Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively.

[0015] Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively;

[0016] Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region.

[0017] The two superimposed regions are combined to form the reconstructed feasible region.

[0018] Optionally, the step of solving based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region to iteratively generate a new cutting plane includes:

[0019] During the first iteration, based on the data corresponding to the first round of clearing in the real-time SCADA data, the position of the power grid operating point in the reconstructed feasible region is determined, and the reconstructed feasible region is adjusted according to the position determined in the first iteration to obtain the new cutting plane generated in the first iteration.

[0020] During the nth iteration, based on the (n-1)th round of clearing data in the market clearing data, the position of the power grid operating point in the feasible region generated by the new cutting plane in the (n-1)th iteration is determined, and the new cutting plane in the (n-1)th iteration is adjusted according to the position determined in the nth iteration to obtain the new cutting plane generated in the nth iteration, where n is an integer greater than 1.

[0021] Secondly, embodiments of this application provide a power economic dispatch model solving device, comprising:

[0022] The safety constraint modeling module is used to construct a safety constraint mathematical model based on the safety and stability control device for overload tripping power systems, and to determine the original feasible region of the overload tripping condition section based on the safety constraint mathematical model.

[0023] The reconstruction module is used to reconstruct the original feasible region by introducing a cutting plane to obtain a reconstructed feasible region.

[0024] The iterative module is used to solve the problem based on real-time data collected by SCADA (Supervisory Control and Data Acquisition), market clearing data, and the reconstructed feasible region, so as to iteratively generate a new cutting plane.

[0025] Optionally, the construction of the safety constraint mathematical model based on the overload tripping type power system safety and stability control device includes:

[0026] Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines;

[0027] Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value.

[0028] Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

[0029] Optionally, the number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The reconstruction of the original feasible region through the introduced cutting planes to obtain the reconstructed feasible region includes:

[0030] Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively.

[0031] Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively;

[0032] Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region.

[0033] The two superimposed regions are combined to form the reconstructed feasible region.

[0034] Thirdly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any of the above-mentioned embodiments.

[0035] Fourthly, embodiments of this application provide a computer program product, including computer instructions that, when executed by a processor, implement the steps of the method described in any of the above-described embodiments.

[0036] Fifthly, embodiments of this application provide a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the steps of the method described in any of the preceding claims.

[0037] In summary, the embodiments of this application have at least the following beneficial effects:

[0038] By employing the embodiments of this application, a safety constraint mathematical model based on an overload tripping type power system safety and stability control device is constructed, and the original feasible region of the overload tripping type condition section is determined according to the safety constraint mathematical model. The original feasible region is reconstructed by introducing a cutting plane to obtain a reconstructed feasible region. Based on real-time data collected by power monitoring and data acquisition SCADA, market clearing data, and the reconstructed feasible region, a new cutting plane is iteratively generated. This enables the rapid solution of intraday real-time rolling clearing of the power market while ensuring accuracy, effectively guaranteeing the speed and accuracy requirements of power market construction for safety constraint economic dispatch, ensuring that the market clearing results are actually executable by the power grid, and especially solving the problem of difficulty in real-time clearing of the power market caused by overload tripping type condition sections. Attached Figure Description

[0039] Figure 1 This is a flowchart illustrating the method for solving the power economic dispatch model provided in the embodiments of this application;

[0040] Figure 2 This is a schematic diagram of the AC / DC hybrid power grid topology provided in the embodiments of this application;

[0041] Figure 3 This is a schematic diagram of the feasible region of the overload shearing machine condition section formula provided in the embodiments of this application;

[0042] Figure 4 This is a schematic diagram of the feasible region reconstructed by the cutting plane algorithm according to an embodiment of this application;

[0043] Figure 5 This is a flowchart illustrating the calculation process for clearing a single time period in the real-time electricity market, as provided in this application embodiment.

[0044] Figure 6 This is a schematic diagram of the power economic dispatch model solving device provided in the embodiments of this application;

[0045] Figure 7 This is a schematic diagram of the computer device provided in the embodiments of this application. Detailed Implementation

[0046] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0047] In the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first," "second," "third," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more. In the description of this application, the term "comprising" and its variations are open-ended, meaning "including but not limited to." The term "based on" means "at least partially based on." The term "according to" means "at least partially according to." The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments."

[0048] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; 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; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0049] In the description of this application, it should be noted that, unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this application is for the purpose of describing specific embodiments only and is not intended to limit the application. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0050] The following explains some terms and concepts used in the embodiments of this application:

[0051] SCADA (Supervisory Control and Data Acquisition) systems are important tools for the automation control of power systems. They utilize computer technology, network communication technology, and automatic control technology to perform real-time monitoring, data acquisition, remote control, and management of the power system's operating status.

[0052] In some cases, related technologies introduce 0-1 variables into the safety-constrained economic dispatch model because grid operation also considers conditional sections coupled with optimization variables, increasing constraint complexity. One type of constraint is the safety constraints on grid operation conditions caused by overload tripping and other safety and stability automatic devices, which significantly increases constraint complexity.

[0053] Firstly, see [the following] Figure 1 The diagram shows a flowchart of a power economic dispatch model solution method provided in this application embodiment. The method includes steps S101-S103, as follows:

[0054] S101, construct a safety constraint mathematical model based on the overload tripping type power system safety and stability control device, and determine the original feasible region of the overload tripping type condition section according to the safety constraint mathematical model.

[0055] S102, the original feasible region is reconstructed by introducing a cutting plane to obtain a reconstructed feasible region.

[0056] S103, based on real-time data collected by power monitoring and data acquisition SCADA, market clearing data and the reconstructed feasible region, a new cutting plane is iteratively generated.

[0057] In some examples, according to existing regulations (such as the "Implementation Rules for Spot Electricity Trading in the Southern Regional Electricity Market"), real-time electricity market security-constrained economic dispatch typically needs to meet various constraints, including load balance constraints, positive and negative reserve capacity constraints, primary frequency regulation reserve capacity constraints, contingency reserve capacity constraints, unit output upper and lower limit constraints, unit ramping constraints, cross-sectional power flow constraints, hydropower plant power output upper and lower limit constraints, hydropower plant water level constraints, DC optimized power modeling, new energy output constraints, and inter-provincial priority planning constraints. Among these, overload shedding condition cross-sectional constraints have a crucial impact on clearing efficiency. Therefore, this application will conduct a detailed analysis of this type of condition cross-sectional constraint and derive its generalized mathematical model. For example, according to the "Guidelines for Power System Security and Stability" (GB38755-2019), to avoid power grid security and stability issues, security and stability cross-sectional constraints will be superimposed on the original line design current carrying capacity when arranging operating modes.

[0058] In this embodiment, the cutting plane method adjusts the feasible region of the original problem by constructing a cutting plane, which can efficiently handle some 0-1 variable problems while ensuring accuracy. The 0-1 variable fixing technique reduces the problem dimensionality by pre-setting variable values ​​based on historical solutions. The 0-1 variable hot-start technique uses the 0-1 variables of the previously cleared optimal solution as the initial values ​​for optimization, which significantly improves the efficiency of the next clearing calculation.

[0059] This new cutting plane can be used for one or more of the following in power systems: safety-constrained economic dispatch, safety-constrained unit combination, network constraint processing, and cross-sectional power flow modeling.

[0060] In one optional implementation, the construction of a safety constraint mathematical model based on an overload tripping type power system safety and stability control device includes:

[0061] Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines;

[0062] Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value.

[0063] Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

[0064] In some examples, specifically, see [link to relevant documentation]. Figure 2 It illustrates a hybrid AC / DC power grid topology, which will be discussed below. Figure 2 This section is used to illustrate overload tripping conditions. The relationship between the two local power grids at the sending and receiving ends is shown. Nodes B1 and B2 are connected via a DC tie line (red), and nodes B3 and B4 are connected via an AC tie line (black solid line). The electrical topology within the local power grid is omitted (black dashed lines). In this basic model, the DC lines consider the upper and lower limits of the converter's operating power, and the AC lines consider the upper and lower limits of the thermal stability current limiting value.

[0065]

[0066] Among them, P DC This refers to the transmission power of a DC line in actual operation. These are the minimum allowable transmission power and the maximum allowable transmission power of the DC line, respectively, both of which are determined by the converter design.

[0067] Among them, P AC This refers to the transmission power of the AC line in actual operation. These are the minimum allowable transmission power and the maximum allowable transmission power of an AC line, respectively. It is mainly determined by the thermal stability current limiting value.

[0068] Based on the constraints above, consider a common line thermal stability problem: a situation where one line trips while another line is overloaded. To avoid AC line overload after DC line tripping, a power flow transfer coefficient 'a' after DC line tripping is introduced into the constraints above, thus further extending the above formula to the following formula.

[0069]

[0070] To avoid frequency stability issues in the sending-end grid caused by DC line tripping during high-power operation, further consideration is given to the deployment of safety and stability devices (i.e., overload tripping power system safety and stability control devices). These devices can disconnect generating units exceeding the grid's capacity to achieve overload tripping. When the DC line trips, the power P... DC Less than the safe and stable power operating threshold value At that time, maintain the line thermal stability constraint after the power flow transfer in the previous section; when P DC Greater than the safe and stable power threshold When considering only the power flow transfer to the AC line below the threshold value that satisfies the thermal stability constraint, the following formula can be derived.

[0071]

[0072] The lower constraint in the above equation is a convex constraint, which will not be discussed here. Analyzing only the upper constraint in the above equation, it can be simplified as follows:

[0073]

[0074] The above equation can be transformed into a general form containing 0-1 variables using the Big M method, thus obtaining the final mathematical model of safety constraints. It should be understood that this introduces a sufficiently large constant M containing 0-1 variables and a sufficiently small constant ε.

[0075]

[0076] In one optional implementation, the number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The reconstruction of the original feasible region through the introduced cutting planes to obtain the reconstructed feasible region includes:

[0077] Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively.

[0078] Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively;

[0079] Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region.

[0080] The two superimposed regions are combined to form the reconstructed feasible region.

[0081] In some examples, specifically, see [link to relevant documentation]. Figure 3 It shows that by Figure 2 A schematic diagram of the feasible region for the overload shearing type condition section formula derived under the given conditions; wherein the feasible region of the overload shearing type condition section can be P DC The region is divided into two subsets by a boundary. Both subsets are convex sets, but the merged region is a non-convex set.

[0082] This embodiment reconstructs the feasible region by introducing cutting planes. The conditional cross-section forms two cutting planes through the extension of the dashed lines, naturally dividing the feasible region into three regions: an intersection region and two non-intersection regions. The intersection region is the intersection of the feasible regions of the two cutting planes, and the coordinates in this region satisfy the constraints of both cutting planes. The coordinates of the two non-intersection regions satisfy the constraints of only one cutting plane.

[0083]

[0084] Where d1 and d2 represent the Euclidean distances from each point to the two cutting planes (i.e., the angle bisectors formed by the conditional sections), so that the intersection of the feasible regions of the two cutting planes can be reconstructed into two regions based on the Euclidean distance, each of which is close to the two non-intersecting regions and superimposed.

[0085] Accordingly, you can refer to Figure 4 This diagram illustrates the feasible region reconstructed using the cutting plane algorithm after applying the overload shearing machine condition section formula. The original condition section, reconstructed through the feasible region, satisfies the following condition: the A+B+C region satisfies the cutting plane constraint. Regions A+B+D satisfy the cutting plane constraint. Region A is located within the cutting plane constraint. When the constraint center and the running point are located in region A, using this constraint to clear the constraint is more conducive to reducing the loss of optimality; the logic is similar in region B.

[0086] In one optional implementation, the step of solving based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region to iteratively generate a new cutting plane includes:

[0087] During the first iteration, based on the data corresponding to the first round of clearing in the real-time SCADA data, the position of the power grid operating point in the reconstructed feasible region is determined, and the reconstructed feasible region is adjusted according to the position determined in the first iteration to obtain the new cutting plane generated in the first iteration.

[0088] During the nth iteration, based on the (n-1)th round of clearing data in the market clearing data, the position of the power grid operating point in the feasible region generated by the new cutting plane in the (n-1)th iteration is determined, and the new cutting plane in the (n-1)th iteration is adjusted according to the position determined in the nth iteration to obtain the new cutting plane generated in the nth iteration, where n is an integer greater than 1.

[0089] In some examples, leveraging the process characteristics of at least two rounds of clearing and the reconstruction results of the feasible region in the above embodiments, the overload shearing type condition section generates a cutting plane for calculation during the first round of clearing. Then, based on the clearing calculation results, a new cutting plane is generated for the next round of clearing.

[0090] First, the real-time data collected by the power grid SCADA system (P' DC ,P′ AC By substituting the values ​​into the cutting plane expression, the location of the power grid operating point in the optimization space can be determined, specifically whether it is located in the intersection region or the non-intersection region of the two cutting planes. The specific calculation methods can be obtained by substituting these values ​​into the formulas listed below.

[0091] If the landing point is located on the cutting plane The non-intersecting parts satisfy the following formula.

[0092]

[0093] If the landing point is located on the cutting plane The corresponding non-intersection parts satisfy the following formula.

[0094]

[0095] If it is located at the intersection of two secant planes, then select the secant plane with the greater Euclidean distance according to the following formula.

[0096]

[0097] Through the above process, the conditional constraints during the first round of clearing are transformed into common convex constraints. The strategy for generating the cutting plane before subsequent rolling clearing is similar to the above process, the main difference being that the landing point data used for cutting plane generation is no longer the real-time SCADA data collected during the first round of clearing, but rather a new cutting plane generated based on the results of each time period in the previous round of clearing (refer to the embodiments related to the reconstruction of the feasible region in this application, where reconstruction is used to adjust the cutting plane). Finally, the cutting plane constraints selected in each time period in the above embodiments replace the original conditional cross-sections and are substituted into the new round of clearing. That is, in different time periods, the original 0-1 variable constraints are transformed into common linear cutting plane constraints in both rounds of clearing. Here, it can be understood that the results of each time period in the previous round of clearing can refer to generator output, cross-sectional power flow, etc., in each time period.

[0098] See in some examples Figure 5 The flowchart illustrates the calculation process for clearing a single case in the real-time electricity market.

[0099] Secondly, correspondingly, this application also provides a power economic dispatch model solving device, which can realize all the processes of the power economic dispatch model solving method provided in the above embodiments.

[0100] See Figure 6 The diagram shows a schematic of the power economic dispatch model solving device provided in this application embodiment. The power economic dispatch model solving device includes:

[0101] The safety constraint modeling module 601 is used to construct a safety constraint mathematical model based on the safety and stability control device of the overload tripping type power system, and to determine the original feasible region of the overload tripping type condition section according to the safety constraint mathematical model.

[0102] The reconstruction module 602 is used to reconstruct the original feasible region by introducing a cutting plane to obtain a reconstructed feasible region;

[0103] The iteration module 603 is used to solve the problem based on real-time data collected by power monitoring and data acquisition SCADA, market clearing data, and the reconstructed feasible region, so as to iteratively generate a new cutting plane.

[0104] In one optional implementation, the construction of a safety constraint mathematical model based on an overload tripping type power system safety and stability control device includes:

[0105] Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines;

[0106] Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value.

[0107] Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

[0108] In one optional implementation, the number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The reconstruction of the original feasible region through the introduced cutting planes to obtain the reconstructed feasible region includes:

[0109] Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively.

[0110] Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively;

[0111] Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region.

[0112] The two superimposed regions are combined to form the reconstructed feasible region.

[0113] In one optional implementation, the step of solving based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region to iteratively generate a new cutting plane includes:

[0114] During the first iteration, based on the data corresponding to the first round of clearing in the real-time SCADA data, the position of the power grid operating point in the reconstructed feasible region is determined, and the reconstructed feasible region is adjusted according to the position determined in the first iteration to obtain the new cutting plane generated in the first iteration.

[0115] During the nth iteration, based on the (n-1)th round of clearing data in the market clearing data, the position of the power grid operating point in the feasible region generated by the new cutting plane in the (n-1)th iteration is determined, and the new cutting plane in the (n-1)th iteration is adjusted according to the position determined in the nth iteration to obtain the new cutting plane generated in the nth iteration, where n is an integer greater than 1.

[0116] Thirdly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method described in any of the above-mentioned embodiments.

[0117] Fourthly, embodiments of this application provide a computer program product, including computer instructions that, when executed by a processor, implement the steps of the method described in any of the above-described embodiments.

[0118] Fifthly, embodiments of this application provide a computer device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the steps of the method described in any of the preceding claims.

[0119] See Figure 7The computer device in this embodiment includes a processor 701, a memory 702, and a computer program stored in the memory 702 and executable on the processor 701, such as a power economic dispatch model solver. When the processor 701 executes the computer program, it implements the steps in the various power economic dispatch model solver embodiments described above, for example... Figure 1 The steps S101-S103 are shown.

[0120] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 702 and executed by the processor 701 to complete this application. The one or more modules / units 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 computer device.

[0121] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device may include, but is not limited to, a processor 701 and a memory 702. Those skilled in the art will understand that the schematic diagram is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than illustrated, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0122] The processor 701 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. The general-purpose processor can be a microprocessor, or processor 701 can be any conventional processor. The processor 701 is the control center of the computer device, connecting various parts of the entire computer device through various interfaces and lines.

[0123] The memory 702 can be used to store the computer programs and / or modules. The processor 701 implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 702 and calling the data stored in the memory 702. The memory 702 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 702 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital card (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0124] Wherein, if the modules / units integrated into the computer device are implemented as software functional units and sold or used as independent products, they 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 the processor 701, it can implement the steps of the various method embodiments described above. Wherein, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0125] In summary, the embodiments of this application have at least the following beneficial effects:

[0126] By employing the embodiments of this application, a safety constraint mathematical model based on an overload tripping type power system safety and stability control device is constructed, and the original feasible region of the overload tripping type condition section is determined according to the safety constraint mathematical model. The original feasible region is reconstructed by introducing a cutting plane to obtain a reconstructed feasible region. Based on real-time data collected by power monitoring and data acquisition SCADA, market clearing data, and the reconstructed feasible region, a new cutting plane is iteratively generated. This enables the rapid solution of intraday real-time rolling clearing of the power market while ensuring accuracy, effectively guaranteeing the speed and accuracy requirements of power market construction for safety constraint economic dispatch, ensuring that the market clearing results are actually executable by the power grid, and especially solving the problem of difficulty in real-time clearing of the power market caused by overload tripping type condition sections.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary hardware platforms, and of course, it can also be implemented entirely by hardware. Based on this understanding, all or part of the technical solutions of this application that contribute to the background technology can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0128] The above description is the preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications are also considered to be within the scope of protection of this application.

Claims

1. A method for solving a power economic dispatch model, characterized in that, include: A safety constraint mathematical model based on the overload tripping type power system safety and stability control device is constructed, and the original feasible region of the overload tripping type condition section is determined according to the safety constraint mathematical model. The original feasible region is reconstructed by introducing a cutting plane to obtain a reconstructed feasible region; The solution is based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region, in order to iteratively generate a new cutting plane.

2. The method according to claim 1, characterized in that, The construction of the safety constraint mathematical model based on the overload tripping type power system safety and stability control device includes: Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines; Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value. Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

3. The method according to claim 1, characterized in that, The number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The original feasible region is reconstructed using the introduced cutting planes to obtain the reconstructed feasible region, including: Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively. Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively; Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region. The two superimposed regions are combined to form the reconstructed feasible region.

4. The method according to claim 1, characterized in that, The process of solving for a new cutting plane based on real-time data collected by SCADA (Supervisory Control and Data Acquisition) for power monitoring and data acquisition, market clearing data, and the reconstructed feasible region includes: During the first iteration, based on the data corresponding to the first round of clearing in the real-time SCADA data, the position of the power grid operating point in the reconstructed feasible region is determined, and the reconstructed feasible region is adjusted according to the position determined in the first iteration to obtain the new cutting plane generated in the first iteration. During the nth iteration, based on the (n-1)th round of clearing data in the market clearing data, the position of the power grid operating point in the feasible region generated by the new cutting plane in the (n-1)th iteration is determined, and the new cutting plane in the (n-1)th iteration is adjusted according to the position determined in the nth iteration to obtain the new cutting plane generated in the nth iteration, where n is an integer greater than 1.

5. A power economic dispatch model solving device, characterized in that, include: The safety constraint modeling module is used to construct a safety constraint mathematical model based on the safety and stability control device for overload tripping power systems, and to determine the original feasible region of the overload tripping condition section based on the safety constraint mathematical model. The reconstruction module is used to reconstruct the original feasible region by introducing a cutting plane to obtain a reconstructed feasible region. The iterative module is used to solve the problem based on real-time data collected by SCADA (Supervisory Control and Data Acquisition), market clearing data, and the reconstructed feasible region, so as to iteratively generate a new cutting plane.

6. The apparatus according to claim 5, characterized in that, The construction of the safety constraint mathematical model based on the overload tripping type power system safety and stability control device includes: Construct upper and lower limits of operating power constraints for DC lines, and upper and lower limits of thermal stability current limiting values ​​for AC lines; Based on the upper and lower limits of the operating power, the upper and lower limits of the thermal stability current limiting value, the safety and stability power action threshold value corresponding to the overload tripping type power system safety and stability control device, and the preset power flow transfer coefficient, a constraint model is constructed. The power flow transfer coefficient is used to characterize the power flow transfer caused by the tripping of the DC line, and the overload tripping type power system safety and stability control device is used to perform the corresponding overload tripping operation according to the safety and stability power action threshold value. Using the Big M method, the upper limit constraint part of the constraint model is converted into a 0-1 variable form to obtain the safety constraint mathematical model.

7. The apparatus according to claim 5, characterized in that, The number of introduced cutting planes is two, and the introduced cutting planes are determined by the overload shearing machine type condition section. The original feasible region is reconstructed using the introduced cutting planes to obtain the reconstructed feasible region, including: Based on the two introduced cutting planes, the original feasible region is divided into an intersection region and two non-intersection regions. The intersection region is the intersection between the corresponding regions of the two introduced cutting planes in the original feasible region, and the two non-intersection regions correspond to the two introduced cutting planes respectively. Using the Euclidean distance between each point in the intersection region and the two introduced cutting planes as the criterion, the intersection region is reconstructed into two sub-regions, wherein the two sub-regions correspond to the two non-intersection regions respectively; Each non-intersection region is superimposed on its corresponding sub-region, such that the superimposed region satisfies the constraint of the introduced cutting plane corresponding to the non-intersection region. The two superimposed regions are combined to form the reconstructed feasible region.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-4.

9. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the method described in any one of claims 1-4.

10. A computer device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the method of any one of claims 1-4.

Images