Scheduling information determination method and device and electronic equipment

Abstract

The invention discloses a scheduling information determination method and device and electronic equipment. Relates to the power system field. The method comprises the following steps: acquiring system parameters required for constructing a multi-energy system scheduling model; constructing a multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, adjusting the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplifying the first scheduling model to a matrix form to obtain a second scheduling model; initializing a preset parameter in the second scheduling model, calculating a residual value of the second scheduling model, and adjusting the preset parameter according to the residual value to obtain a target scheduling model; and solving the target scheduling model to obtain scheduling information of the multi-energy system. According to the method and the device, the problem of relatively low accuracy of the scheduling method for processing the optimal scheduling problem of the electrical multi-energy system in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the field of power systems, and in particular to a method, device and electronic device for determining dispatching information. Background Art

[0002] With the widespread application of low-carbon and high-efficiency gas-fired generators, the coupling between the electricity and natural gas systems has become increasingly stronger, forming an electricity-gas multi-energy system. This system has shown great potential in improving energy efficiency and promoting low-carbon emissions.

[0003] However, the complexity and dynamics of multi-energy systems place higher demands on optimal scheduling. Existing scheduling methods mostly focus on the optimization of a single system, which makes it difficult to fully utilize the complementary advantages between the electricity and gas systems, resulting in insufficient energy utilization and high operating costs. Therefore, there is an urgent need for an optimal scheduling method that can comprehensively consider the mutual influence of the electricity and natural gas systems to achieve coordinated optimization of multi-energy systems and improve overall operating efficiency and economy.

[0004] There is currently no effective solution to the problem of low accuracy in the scheduling methods used in related technologies for dealing with the optimization scheduling problem of electrical multi-energy systems. Summary of the invention

[0005] The present application provides a method, device and electronic device for determining scheduling information to solve the problem of low accuracy of scheduling methods in related technologies in dealing with the optimization scheduling problem of electrical multi-energy systems.

[0006] According to one aspect of the present application, a method for determining scheduling information is provided. The method includes: obtaining system parameters required for constructing a multi-energy system scheduling model; constructing a multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, and adjusting the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplifying the first scheduling model to a matrix form to obtain a second scheduling model; initializing preset parameters in the second scheduling model, and calculating the residual value of the second scheduling model, adjusting the preset parameters according to the residual value to obtain a target scheduling model; solving the target scheduling model to obtain scheduling information of the multi-energy system.

[0007] Optionally, the system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters. A multi-energy system scheduling model is constructed according to the system parameters, and the initial scheduling model includes: constructing a power system operation scheduling sub-model based on the power system parameters, gas-electricity coupling equipment parameters and price parameters; constructing a natural gas system operation scheduling sub-model based on the natural gas system parameters and price parameters; constructing constraints of the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model according to the power system parameters, the natural gas system parameters and the gas-electricity coupling equipment parameters; combining the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model to obtain the objective function, and combining the objective function and the constraints to obtain the initial scheduling model.

[0008] Optionally, the initial scheduling model includes the Weymouth equation, and the initial scheduling model is adjusted by a linear relaxation method to obtain a first scheduling model, including: obtaining multiple points on a function curve obtained by the Weymouth equation, and obtaining the tangent of each point on the function curve to obtain multiple tangents; performing a linear relaxation operation on the Weymouth equation through multiple tangents to obtain a linearized Weymouth equation; using the linearized Weymouth equation to replace the Weymouth equation in the initial scheduling model to obtain the first scheduling model.

[0009] Optionally, the second scheduling model includes M preset parameters, and calculating the residual value of the second scheduling model includes: obtaining the partial derivative of the Lagrangian function of the second scheduling model with respect to each preset parameter to obtain M partial derivatives, where M is a positive integer; obtaining the infinite norm of each partial derivative to obtain M infinite norms; obtaining the maximum value among the M infinite norms to obtain the residual value.

[0010] Optionally, the system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters, and the preset parameters are adjusted according to the residual value to obtain the target scheduling model, including: determining whether the residual value is less than a preset tolerance value; when the residual value is greater than or equal to the preset tolerance value, calculating the correction amount of each preset parameter according to the power system parameters, the natural gas system parameters and the gas-electricity coupling equipment parameters to obtain M correction amounts, and adjusting each preset parameter in the second scheduling model by the M correction amounts to obtain the adjusted second scheduling model, and re-executing the step of determining whether the residual value is less than the preset tolerance value until the residual value is less than the preset tolerance value, wherein M is a positive integer; when the residual value is less than the preset tolerance value, terminating the operation of adjusting the preset parameters, and determining the adjusted second scheduling model as the target scheduling model.

[0011] Optionally, each preset parameter in the second scheduling model is adjusted by M correction amounts to obtain the adjusted second scheduling model, including: calculating the original step size and the dual step size according to the M preset parameters; calculating each correction amount by the original step size and the dual step size to obtain M updated correction amounts; adding each preset parameter to the corresponding updated correction amount to obtain M updated preset parameters, and using each updated preset parameter to replace the corresponding preset parameter in the second scheduling model to obtain the adjusted second scheduling model.

[0012] Optionally, after obtaining the first scheduling model, the method also includes: generating a penalty term based on the natural gas system parameters, and adding the penalty term to the objective function to obtain an updated first scheduling model; and performing the step of simplifying the first scheduling model to a matrix form according to the updated first scheduling model to obtain a second scheduling model.

[0013] According to another aspect of the present application, a device for determining scheduling information is provided. The device includes: an acquisition unit, which is used to acquire system parameters required for constructing a multi-energy system scheduling model; a first adjustment unit, which is used to construct a multi-energy system scheduling model according to the system parameters, obtain an initial scheduling model, and adjust the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplify the first scheduling model to a matrix form to obtain a second scheduling model; a second adjustment unit, which is used to initialize the preset parameters in the second scheduling model, and calculate the residual value of the second scheduling model, and adjust the preset parameters according to the residual value to obtain a target scheduling model; a calculation unit, which is used to solve the target scheduling model to obtain scheduling information of the multi-energy system.

[0014] According to another aspect of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, a method for determining scheduling information in the present application is implemented.

[0015] According to another aspect of the present invention, an electronic device is provided, comprising one or more processors and a memory; the memory stores computer-readable instructions, and the processor is used to execute the computer-readable instructions, wherein a method for determining scheduling information is executed when the computer-readable instructions are executed.

[0016] Through this application, the following steps are adopted: obtaining the system parameters required for constructing a multi-energy system scheduling model; constructing a multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, and adjusting the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplifying the first scheduling model to a matrix form to obtain a second scheduling model; initializing the preset parameters in the second scheduling model, and calculating the residual value of the second scheduling model, adjusting the preset parameters according to the residual value to obtain a target scheduling model; solving the target scheduling model to obtain the scheduling information of the multi-energy system. The problem of low accuracy of the scheduling method in the related art in processing the optimization scheduling problem of the electrical multi-energy system is solved. By constructing a multi-energy system scheduling model, linearly relaxing the formula content in the multi-energy system scheduling model, and simplifying the multi-energy system scheduling model to a matrix form, the calculation complexity of the multi-energy system scheduling model is reduced, the calculation accuracy is improved, and at the same time, the preset parameters in the model are adjusted by calculating the residual value, the calculation accuracy of the multi-energy system scheduling model is improved, and the technical effect of improving the accuracy of processing the scheduling of the multi-energy system through the multi-energy system scheduling model is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a flowchart of a method for determining scheduling information provided in an embodiment of the present application;

[0019] Figure 2 is a flowchart of an optional preset parameter updating method provided according to an embodiment of the present application;

[0020] Figure 3 is a schematic diagram of a device for determining scheduling information provided in an embodiment of the present application;

[0021] Figure 4 It is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] It should be noted that the method, device and electronic device for determining the scheduling information determined in the present disclosure can be used in the field of power systems, and can also be used in any field other than the field of power systems. The application field of the method, device and electronic device for determining the scheduling information determined in the present disclosure is not limited.

[0026] It should be noted that the collected information, user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) used in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated. Corresponding operation portals are provided for users to choose to authorize or refuse to use. For example, an interface is set up between this system and relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0027] For the convenience of description, some nouns or terms involved in the embodiments of the present application are explained below:

[0028] Multi-energy system: A multi-energy system refers to a system that uses a variety of different energy sources to meet energy needs. By combining multiple energy sources, it is possible to improve energy efficiency, reduce energy costs, reduce dependence on a single energy source, and also help reduce the impact on the environment. Multi-energy systems usually include energy production, conversion, storage and utilization. Through reasonable planning and management, efficient energy utilization and sustainable development can be achieved.

[0029] According to an embodiment of the present application, a method for determining scheduling information is provided.

[0030] Figure 1 is a flow chart of a method for determining scheduling information according to an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0031] Step S101, obtaining system parameters required for constructing a multi-energy system scheduling model.

[0032] It should be noted that the multi-energy system scheduling model can be a mathematical model established according to the parameters of the multi-energy system. The model can take into account the complementarity and substitutability between different energy sources, as well as the operating constraints and objective functions of the system, and optimize the allocation, scheduling and control of various energy resources to achieve efficient operation of the system and reduce energy costs. Therefore, when constructing a multi-energy system scheduling model, it is necessary to first obtain the system parameters required to construct the multi-energy system scheduling model, so as to construct the multi-energy system scheduling model according to the system parameters.

[0033] Specifically, the parameters of the multi-energy system may include power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters. The power system parameters may include: bus parameters, branch parameters, coal-fired generator set parameters, wind farm parameters and electric load parameters; the natural gas system parameters may include: node parameters, pipeline parameters, thermal boiler parameters and thermal load parameters; the gas-electricity coupling equipment parameters may include gas generator set operating parameters.

[0034] Step S102, constructing a multi-energy system scheduling model according to system parameters to obtain an initial scheduling model, adjusting the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplifying the first scheduling model to a matrix form to obtain a second scheduling model.

[0035] Specifically, when establishing a multi-energy system optimization scheduling model, the multi-energy system optimization scheduling model can be expressed as follows:

[0036] (1)

[0037] (2)

[0038] (3)

[0039] (4)

[0040] (5)

[0041] (6)

[0042] (7)

[0043] (8)

[0044] (9)

[0045] (10)

[0046] (11)

[0047] (12)

[0048] (13)

[0049] (14)

[0050] (15)

[0051] Among them, formula (1) is the objective function. Solving formula (1) can obtain the multi-energy scheduling cost. is the active output of the generator set, wherein the active output of the generator set includes the active output of the coal-fired generator set and the active output of the gas-fired generator set; , and is the cost coefficient of the generator set; is the carbon emission factor of the generator set; The gas supply from the natural gas source; is the price coefficient of natural gas source; is the carbon emission factor of natural gas source; is the price of carbon emission quota; is the electrical load of the bus; is the line power; is the voltage phase angle of bus i at time t; is the voltage phase angle of bus j at time t; is the line reactance; is the voltage phase angle of the reference bus ref at time t; is the line capacity; , are the maximum and minimum technical outputs of the generator sets, respectively; , They are the maximum downward and upward climbing power of the generator set respectively; , are the air flow rates at the compressor outlet and inlet respectively; is the natural gas load of the node; is the gas flow rate of the natural gas pipeline; The flow rate of natural gas consumed by the gas-fired generator set; is the Weymouth coefficient for natural gas pipelines; is the difference between the square of gas pressure at node m and node n of the natural gas pipeline; is the square of the air pressure at node m; is the square of the air pressure at node n; is the square of the outlet pressure of compressor c at time t; is the square of the inlet pressure of compressor c at time t; is the compressor gas consumption ratio; is the maximum compression ratio of the compressor; , are the maximum and minimum gas pressures at the natural gas node, respectively; , are the maximum and minimum gas supply of the natural gas source respectively; is the efficiency of the gas generator set; is the calorific value of natural gas; is a collection of scheduling periods; It is a collection of coal-fired power generation units; A collection of gas generator sets; A collection of natural gas sources; is the set of coal-fired generating units connected to bus i; is the collection of gas-fired generator sets connected to bus i; is the set of other buses connected to bus i; is the set of natural gas sources connected to node m; is the set of compressors connected to node m; is the set of gas generator sets connected to node m; is the set of other nodes connected to node m.

[0052] Furthermore, after obtaining the multi-energy system optimization scheduling model, it is necessary to bring the above multi-energy system parameters into the multi-energy system optimization scheduling model to obtain the initial scheduling model. In addition, since the Weymouth equation (Formula (11)) describing the steady-state gas flow of natural gas in the multi-energy system optimization scheduling model is nonlinear and non-convex, it is difficult to obtain the global optimal solution for the optimization scheduling problem of the multi-energy system. Therefore, it is necessary to perform linear relaxation operation on the Weymouth equation (Formula (11)) in the initial scheduling model through a linear relaxation method to obtain the first scheduling model.

[0053] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, after obtaining the first scheduling model, the method also includes: generating a penalty term based on the natural gas system parameters, and adding the penalty term to the objective function to obtain an updated first scheduling model; and performing the step of simplifying the first scheduling model to a matrix form according to the updated first scheduling model to obtain a second scheduling model.

[0054] Specifically, in order to tighten the constraint of the objective function (Formula (1)), a penalty term can be added to the objective function to obtain an updated objective function, where the penalty term can be shown as Formula (16):

[0055] (16)

[0056] in, is the penalty term coefficient, A collection of natural gas pipelines. is the difference between the square of gas pressure at node m and node n of the natural gas pipeline; A collection of scheduling periods.

[0057] The updated objective function can be shown as formula (17):

[0058] (17)

[0059] After obtaining the updated objective function, the updated objective function can be used to replace the original objective function to obtain the first scheduling function. Furthermore, in order to simplify the first scheduling model, the first scheduling model can be organized into a more concise matrix form of quadratic programming as shown in formula (18) and formula (21), thereby obtaining a more concise second scheduling model, and then solving the second scheduling model to obtain scheduling information.

[0060] (18)

[0061] (19)

[0062] (20)

[0063] (twenty one)

[0064] in: is the decision variable of the power system, including the active output of the generator set , Line power and voltage phase angle ; is the decision variable of the natural gas system, including the gas supply from the natural gas source , compressor outlet and inlet air flow , , Gas pipeline flow , Natural gas flow consumed by gas generator sets and gas flow in natural gas pipelines ; is the power system quadratic cost coefficient matrix, including the generator set quadratic cost coefficient ; is the cost coefficient matrix of the quadratic term of the natural gas system, which is a zero matrix; is the primary cost coefficient vector of the power system, including the primary cost coefficient of the generator set and carbon emission cost coefficient ; is the primary cost coefficient vector of the natural gas system, including the natural gas source price coefficient , Carbon emission cost coefficient and the penalty coefficient ; and are the operating costs of the power system and the natural gas system respectively; Formula (18) is the matrix form of Formula (17); Represent the coefficient matrices of the power system equality constraints (2)~(4), inequality constraints (5)~(7) and coupling constraints (15); They represent the right-hand side vectors of the power system equality constraints (2)~(4) and inequality constraints (5)~(7); Represent the coefficient matrices of the natural gas system equality constraints (8)~(10), inequality constraints (11)~(14) and coupling constraints (15); They represent the right-hand side vectors of the natural gas system equality constraints (8)~(10) and inequality constraints (11)~(14); represents the right-hand side vector of the coupling constraint (15); and They represent the matrix forms of the equation constraints (2) to (4) and the inequality constraints (5) to (7) in the power system constraints respectively; and They represent the matrix forms of the equation constraints (8)~(10) and inequality constraints (11)~(14) in the natural gas system constraints respectively; The matrix form representing the gas generator coupling constraint (15).

[0065] Step S103: Initialize preset parameters in the second scheduling model, calculate the residual value of the second scheduling model, and adjust the preset parameters according to the residual value to obtain the target scheduling model.

[0066] Specifically, since the second scheduling model, in addition to the system parameters related to electricity and natural gas, also contains preset parameters carried by the model, in order to ensure that the calculated result is the optimal solution, it is also necessary to adjust the parameters in the model to obtain a target scheduling model that can calculate the optimal solution.

[0067] It should be noted that when adjusting the preset parameters, the parameters in the model can be updated based on the decomposition-coordination interior point method, that is, the residual value is calculated through the preset parameters, and the relationship between the residual value and the preset threshold is used to determine whether the current model output is the optimal solution, and then determine whether the preset parameters need to be further adjusted.

[0068] Step S104, solving the target scheduling model to obtain scheduling information of the multi-energy system.

[0069] Specifically, after obtaining the target scheduling model, the target scheduling model can be solved directly according to the preset parameters and system parameters to obtain the scheduling information of the multi-energy system, wherein the output scheduling information may include: the output of coal-fired power generation units, the output of gas-fired power generation units and the consumed natural gas flow, the gas supply of natural gas sources, the gas pressure of natural gas nodes, the pipeline gas flow, and the scheduling cost of the multi-energy system.

[0070] The method for determining the scheduling information provided in the embodiment of the present application is to obtain the system parameters required for constructing the multi-energy system scheduling model; construct the multi-energy system scheduling model according to the system parameters to obtain the initial scheduling model, and adjust the initial scheduling model by the linear relaxation method to obtain the first scheduling model, and simplify the first scheduling model to the matrix form to obtain the second scheduling model; initialize the preset parameters in the second scheduling model, and calculate the residual value of the second scheduling model, and adjust the preset parameters according to the residual value to obtain the target scheduling model; solve the target scheduling model to obtain the scheduling information of the multi-energy system. The problem of low accuracy of the scheduling method in the related art in processing the optimization scheduling problem of the electrical multi-energy system is solved. By constructing the multi-energy system scheduling model, linearly relaxing the formula content in the multi-energy system scheduling model, and simplifying the multi-energy system scheduling model to the matrix form, the calculation complexity of the multi-energy system scheduling model is reduced, the calculation accuracy is improved, and the preset parameters in the model are adjusted by calculating the residual value, the calculation accuracy of the multi-energy system scheduling model is improved, and the technical effect of improving the accuracy of the scheduling of the multi-energy system through the multi-energy system scheduling model is achieved.

[0071] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters, and a multi-energy system scheduling model is constructed according to the system parameters to obtain an initial scheduling model including: constructing a power system operation scheduling sub-model based on power system parameters, gas-electricity coupling equipment parameters and price parameters; constructing a natural gas system operation scheduling sub-model based on natural gas system parameters and price parameters; constructing constraints for the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model according to the power system parameters, natural gas system parameters and gas-electricity coupling equipment parameters; combining the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model to obtain an objective function, and combining the objective function and the constraints to obtain an initial scheduling model.

[0072] Specifically, in formula (1), For the power system operation dispatch sub-model part, Run the dispatch sub-model section for the natural gas system.

[0073] Furthermore, formula (2) to formula (15) are constraints constructed based on power system parameters, natural gas system parameters and gas-electricity coupling equipment parameters, thereby determining formula (1) to formula (15) as the initial dispatch model.

[0074] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, the initial scheduling model includes the Weymouth equation, and the initial scheduling model is adjusted by a linear relaxation method to obtain a first scheduling model, including: obtaining multiple points on the function curve obtained by the Weymouth equation, and obtaining the tangent of each point on the function curve to obtain multiple tangents; performing a linear relaxation operation on the Weymouth equation through multiple tangents to obtain a linearized Weymouth equation; using the linearized Weymouth equation to replace the Weymouth equation in the initial scheduling model to obtain the first scheduling model.

[0075] Specifically, the process of the linear relaxation multi-energy system optimization dispatch model is as follows: Since the Weymouth equation (Formula (11)) The second-order derivative of is less than zero. According to Taylor's formula with Lagrange residual term, at point You can get:

[0076] (twenty two)

[0077] Therefore, a series of points on the function curve obtained by the Weymouth equation can be selected to approximate , using a cluster of tangent linear relaxation curves, we obtain the linearized Weymouth equation, as shown in formula (23):

[0078] (twenty three)

[0079] Then, the Weymouth equation after linear relaxation is obtained. After that, the linearized Weymouth equation can be used to replace the Weymouth equation in the initial scheduling model to obtain the first scheduling model, thereby completing the update operation of the scheduling model.

[0080] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, the second scheduling model includes M preset parameters, and calculating the residual value of the second scheduling model includes: obtaining the partial derivative of the Lagrangian function of the second scheduling model with respect to each preset parameter to obtain M partial derivatives, where M is a positive integer; obtaining the infinite norm of each partial derivative to obtain M infinite norms; obtaining the maximum value among the M infinite norms to obtain the residual value.

[0081] Specifically, when calculating the residual value, it is first necessary to obtain the preset parameters in the second scheduling model, where the preset parameters include: the original variable , dual variable ; Set disturbance parameters Therefore, the residual value can be calculated by preset parameters, and the calculation formula is shown in formula (24) to formula (30):

[0082] (twenty four)

[0083] (25)

[0084] (26)

[0085] (27)

[0086] (28)

[0087] (29)

[0088] (30)

[0089] in, are the Lagrangian functions of the second scheduling model (18)~(21) for the primal and dual variables respectively. , The partial derivative of .

[0090] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, the system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters, and the preset parameters are adjusted according to the residual value to obtain the target scheduling model, including: determining whether the residual value is less than a preset tolerance value; when the residual value is greater than or equal to the preset tolerance value, calculating a correction amount of each preset parameter according to the power system parameters, the natural gas system parameters and the gas-electricity coupling equipment parameters to obtain M correction amounts, and adjusting each preset parameter in the second scheduling model by the M correction amounts to obtain an adjusted second scheduling model, and re-executing the step of determining whether the residual value is less than the preset tolerance value until the residual value is less than the preset tolerance value, where M is a positive integer; when the residual value is less than the preset tolerance value, terminating the operation of adjusting the preset parameters, and determining the adjusted second scheduling model as the target scheduling model.

[0091] Specifically, after obtaining the residual value, it is also necessary to set a preset tolerance value, so as to determine whether the model output result is the optimal solution according to the size relationship between the preset tolerance value and the residual value. The preset tolerance value can be set to

[0092] When the residual value is greater than or equal to the preset tolerance value, it indicates that the preset parameters need to be adjusted. At this time, the correction amount of each preset parameter can be calculated first, and the preset parameters can be adjusted using the correction amount so that the residual value of the model is less than the preset tolerance value. The preset parameters are adjusted to obtain the target scheduling model, ensuring that the output result of the target scheduling model is the optimal solution.

[0093] It should be noted that when calculating the correction amount of the preset parameters, it can be calculated by the following formula:

[0094] First, the power system calculation and , natural gas system calculation and ,in,

[0095] (31)

[0096] (32)

[0097] (33)

[0098] (34)

[0099] (35)

[0100] Furthermore, the coupled constraint dual variables are solved by the following formula (36): The correction amount .

[0101] (36)

[0102] Furthermore, the power system calculation correction is calculated by the following formula (37) to formula (42): , , , natural gas system calculation correction .

[0103] (37)

[0104] (38)

[0105] (39)

[0106] (40)

[0107] (41)

[0108] (42)

[0109] Optionally, in the method for determining scheduling information provided in an embodiment of the present application, each preset parameter in the second scheduling model is adjusted by M correction amounts, and the adjusted second scheduling model includes: calculating the original step size and the dual step size according to the M preset parameters; calculating each correction amount by the original step size and the dual step size to obtain M updated correction amounts; adding each preset parameter to the corresponding updated correction amount to obtain M updated preset parameters, and using each updated preset parameter to replace the corresponding preset parameter in the second scheduling model to obtain the adjusted second scheduling model.

[0110] Specifically, when adjusting the preset parameters by the correction amount, the step length needs to be calculated first, where the step length includes the original step length and dual step length , thus ensuring that the slack variables and Lagrange multipliers Non-negative. The step length calculation formula is shown in formula (43)-formula (44):

[0111] (43)

[0112] (44)

[0113] Furthermore, after obtaining the original step length and the dual step length, each correction value can be calculated by the original step length and the dual step length to obtain M updated correction values, and each preset parameter is added to the corresponding updated correction value to obtain M updated preset parameters, as shown in formula (45) to formula (48), where the original and dual variables of the power system need to be updated , update the primal-dual variables of the natural gas system , , update the coupled dual variables and disturbance factor .

[0114] (45)

[0115] (46)

[0116] (47)

[0117] (48)

[0118] After obtaining the updated preset parameters, each updated preset parameter can be used to replace the corresponding preset parameter in the second scheduling model to obtain the adjusted second scheduling model, thereby completing the update operation of the parameters in the second scheduling model.

[0119] Figure 2 is a flowchart of an optional preset parameter updating method provided according to an embodiment of the present application, such as Figure 2 As shown, the method includes:

[0120] First, after the second scheduling model, the preset parameters in the second scheduling model can be initialized, that is, the preset parameters are set to the initial values, and the residual value of the second scheduling model is calculated. When the residual value is greater than or equal to the preset tolerance value, it indicates that the preset parameters need to be adjusted. At this time, the correction amounts of the original variables and dual variables of the power system and the natural gas system can be calculated respectively, and the original step size and the dual step size can be calculated. The original step size and the dual step size are used to update the original variables and the dual variables, and the coupled dual variables and the disturbance factor are updated to obtain the updated preset parameters, and the residual value is recalculated until the residual value is less than the preset tolerance value.

[0121] When the residual value is less than the preset tolerance value, the target scheduling model after solving the updated preset parameters is obtained to obtain the optimal solution of the multi-energy system scheduling model, thereby improving the calculation accuracy of the multi-energy system scheduling model, thereby achieving the technical effect of improving the accuracy of multi-energy system scheduling through the multi-energy system scheduling model.

[0122] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0123] The embodiment of the present application also provides a device for determining scheduling information. It should be noted that the device for determining scheduling information in the embodiment of the present application can be used to execute the method for determining scheduling information provided in the embodiment of the present application. The following introduces the device for determining scheduling information provided in the embodiment of the present application.

[0124] Figure 3 Schematic diagram of a device for determining scheduling information according to an embodiment of the present application. Figure 3 As shown, the device includes: an acquisition unit 31, a first adjustment unit 32, a second adjustment unit 33, and a calculation unit 34.

[0125] The acquisition unit 31 is used to acquire system parameters required for building a multi-energy system scheduling model.

[0126] The first adjustment unit 32 is used to construct a multi-energy system scheduling model according to system parameters to obtain an initial scheduling model, and adjust the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplify the first scheduling model to a matrix form to obtain a second scheduling model.

[0127] The second adjustment unit 33 is used to initialize the preset parameters in the second scheduling model, calculate the residual value of the second scheduling model, and adjust the preset parameters according to the residual value to obtain the target scheduling model.

[0128] The calculation unit 34 is used to solve the target scheduling model and obtain the scheduling information of the multi-energy system.

[0129] The device for determining scheduling information provided in the embodiment of the present application obtains the system parameters required for constructing a multi-energy system scheduling model through an acquisition unit 31; the first adjustment unit 32 constructs the multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, and adjusts the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplifies the first scheduling model to a matrix form to obtain a second scheduling model; the second adjustment unit 33 initializes the preset parameters in the second scheduling model, and calculates the residual value of the second scheduling model, and adjusts the preset parameters according to the residual value to obtain a target scheduling model; the calculation unit 34 solves the target scheduling model to obtain the scheduling information of the multi-energy system. The problem of low accuracy of scheduling methods in related technologies in handling optimal scheduling problems of electrical multi-energy systems is solved. By constructing a multi-energy system scheduling model, linear relaxation adjustment is made to the formula content in the multi-energy system scheduling model, and simplifying the multi-energy system scheduling model to a matrix form, the computational complexity of the multi-energy system scheduling model is reduced and the computational accuracy is improved. At the same time, the preset parameters in the model are adjusted by calculating the residual values, which improves the computational accuracy of the multi-energy system scheduling model, thereby achieving the technical effect of improving the accuracy of scheduling of multi-energy systems through the multi-energy system scheduling model.

[0130] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, the system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters, and the first adjustment unit 32 includes: a first construction module, used to construct a power system operation scheduling sub-model based on the power system parameters, gas-electricity coupling equipment parameters and price parameters; a second construction module, used to construct a natural gas system operation scheduling sub-model based on the natural gas system parameters and price parameters; a third construction module, used to construct constraints of the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model according to the power system parameters, the natural gas system parameters and the gas-electricity coupling equipment parameters; a combination module, used to combine the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model to obtain an objective function, and combine the objective function and the constraints to obtain an initial scheduling model.

[0131] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, the initial scheduling model includes the Weymouth equation, and the first adjustment unit 32 includes: a first acquisition module, used to obtain multiple points on the function curve obtained by the Weymouth equation, and obtain the tangent of each point on the function curve to obtain multiple tangents; a processing module, used to perform a linear relaxation operation on the Weymouth equation through multiple tangents to obtain a linearized Weymouth equation; a replacement module, used to replace the Weymouth equation in the initial scheduling model with the linearized Weymouth equation to obtain a first scheduling model.

[0132] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, the second scheduling model includes M preset parameters, and the second adjustment unit 33 includes: a second acquisition module, used to obtain the partial derivative of the Lagrangian function of the second scheduling model with respect to each preset parameter, and obtain M partial derivatives, where M is a positive integer; a third acquisition module, used to obtain the infinite norm of each partial derivative, and obtain M infinite norms; and a fourth acquisition module, used to obtain the maximum value among the M infinite norms to obtain a residual value.

[0133] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, the system parameters include: power system parameters, natural gas system parameters, gas-electric coupling equipment parameters and price parameters, and the second adjustment unit 33 includes: a judgment module, used to judge whether the residual value is less than a preset tolerance value; a calculation module, used to calculate the correction amount of each preset parameter according to the power system parameters, the natural gas system parameters and the gas-electric coupling equipment parameters when the residual value is greater than or equal to the preset tolerance value, to obtain M correction amounts, and adjust each preset parameter in the second scheduling model by the M correction amounts to obtain the adjusted second scheduling model, and re-execute the step of judging whether the residual value is less than the preset tolerance value until the residual value is less than the preset tolerance value, wherein M is a positive integer; a determination module, used to terminate the operation of adjusting the preset parameters when the residual value is less than the preset tolerance value, and determine the adjusted second scheduling model as the target scheduling model.

[0134] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, the calculation module includes: a first calculation submodule, used to calculate the original step size and the dual step size based on M preset parameters; a second calculation submodule, used to calculate each correction amount through the original step size and the dual step size to obtain M updated correction amounts; a third calculation submodule, used to add each preset parameter to the corresponding updated correction amount to obtain M updated preset parameters, and use each updated preset parameter to replace the corresponding preset parameter in the second scheduling model to obtain an adjusted second scheduling model.

[0135] Optionally, in the device for determining scheduling information provided in an embodiment of the present application, after obtaining the first scheduling model, it further includes: an adding unit, used to generate a penalty term based on the natural gas system parameters, and add the penalty term to the objective function to obtain an updated first scheduling model; an execution unit, used to execute the step of simplifying the first scheduling model to a matrix form according to the updated first scheduling model to obtain a second scheduling model.

[0136] The above-mentioned scheduling information determination device includes a processor and a memory. The above-mentioned acquisition unit 31, the first adjustment unit 32, the second adjustment unit 33, the calculation unit 34, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize the corresponding functions.

[0137] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the problem of low accuracy of the scheduling method in the related art in dealing with the optimization scheduling problem of the electrical multi-energy system is solved by adjusting the kernel parameters.

[0138] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0139] An embodiment of the present invention provides a computer-readable storage medium on which a program is stored. When the program is executed by a processor, the method for determining the scheduling information is implemented.

[0140] An embodiment of the present invention provides a processor, which is used to run a program, wherein the method for determining scheduling information is executed when the program is running.

[0141] Figure 4 is a schematic diagram of an electronic device provided according to an embodiment of the present application, such as Figure 4 As shown, an embodiment of the present invention provides an electronic device, the electronic device 40 includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the steps of the above-mentioned method for determining scheduling information when executing the program. The device in this article can be a server, a PC, a PAD, a mobile phone, etc.

[0142] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the steps of the above-mentioned scheduling information determination method.

[0143] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0144] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0145] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0146] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0147] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0148] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0149] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0150] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0151] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for determining scheduling information, characterized in that: include: Obtain the system parameters required to build a multi-energy system dispatch model; Constructing the multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, adjusting the initial scheduling model by a linear relaxation method to obtain a first scheduling model, and simplifying the first scheduling model to a matrix form to obtain a second scheduling model; Initializing preset parameters in the second scheduling model, calculating residual values ​​of the second scheduling model, and adjusting the preset parameters according to the residual values ​​to obtain a target scheduling model; Solve the target scheduling model to obtain scheduling information of the multi-energy system.

2. The method according to claim 1, characterized in that The system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters. The multi-energy system scheduling model is constructed according to the system parameters, and the initial scheduling model includes: Constructing a power system operation dispatch sub-model based on the power system parameters, the gas-electricity coupling equipment parameters and the price parameters; Constructing a natural gas system operation scheduling sub-model based on the natural gas system parameters and the price parameters; Constructing constraint conditions of the power system operation scheduling sub-model and the natural gas system operation scheduling sub-model according to the power system parameters, the natural gas system parameters and the gas-electricity coupling equipment parameters; The power system operation scheduling sub-model and the natural gas system operation scheduling sub-model are combined to obtain an objective function, and the objective function and the constraint conditions are combined to obtain the initial scheduling model.

3. The method according to claim 1, characterized in that The initial scheduling model includes the Weymouth equation, and the initial scheduling model is adjusted by a linear relaxation method to obtain a first scheduling model including: Obtaining a plurality of points on the function curve obtained by the Weymouth equation, and obtaining a tangent line of each point on the function curve to obtain a plurality of tangent lines; Performing a linear relaxation operation on the Weymouth equation through the multiple tangent lines to obtain a linearized Weymouth equation; The linearized Weymouth equations are used to replace the Weymouth equations in the initial scheduling model to obtain the first scheduling model.

4. The method according to claim 1, characterized in that: The second scheduling model includes M preset parameters, and calculating the residual value of the second scheduling model includes: Obtaining the partial derivative of the Lagrangian function of the second scheduling model with respect to each preset parameter to obtain M partial derivatives, where M is a positive integer; Get the infinite norm of each partial derivative and get M infinite norms; The maximum value of the M infinite norms is obtained to obtain the residual value.

5. The method according to claim 1, characterized in that The system parameters include: power system parameters, natural gas system parameters, gas-electricity coupling equipment parameters and price parameters. The preset parameters are adjusted according to the residual value to obtain the target scheduling model including: Determine whether the residual value is less than a preset tolerance value; In the case where the residual value is greater than or equal to the preset tolerance value, a correction amount of each preset parameter is calculated according to the power system parameter, the natural gas system parameter and the gas-electric coupling device parameter to obtain M correction amounts, and each preset parameter in the second scheduling model is adjusted by the M correction amounts to obtain an adjusted second scheduling model, and the step of determining whether the residual value is less than the preset tolerance value is re-executed until the residual value is less than the preset tolerance value, wherein M is a positive integer; When the residual value is less than the preset tolerance value, the operation of adjusting the preset parameters is terminated, and the adjusted second scheduling model is determined as the target scheduling model.

6. The method according to claim 5, characterized in that Each preset parameter in the second scheduling model is adjusted by the M correction amounts to obtain the adjusted second scheduling model, including: Calculate the original step size and the dual step size according to M preset parameters; Calculate each correction amount by using the original step length and the dual step length to obtain M updated correction amounts; Each preset parameter is added to the corresponding updated correction amount to obtain M updated preset parameters, and each updated preset parameter is used to replace the corresponding preset parameter in the second scheduling model to obtain the adjusted second scheduling model.

7. The method according to claim 2, characterized in that After obtaining the first scheduling model, the method further includes: generating a penalty term according to the natural gas system parameter, and adding the penalty term to the objective function to obtain an updated first scheduling model; The step of simplifying the first scheduling model to a matrix form to obtain a second scheduling model is performed according to the updated first scheduling model.

8. A device for determining scheduling information, characterized in that: include: An acquisition unit, used to acquire system parameters required for building a multi-energy system scheduling model; A first adjustment unit is used to construct the multi-energy system scheduling model according to the system parameters to obtain an initial scheduling model, and adjust the initial scheduling model through a linear relaxation method to obtain a first scheduling model, and simplify the first scheduling model to a matrix form to obtain a second scheduling model; a second adjustment unit, configured to initialize preset parameters in the second scheduling model, calculate a residual value of the second scheduling model, and adjust the preset parameters according to the residual value to obtain a target scheduling model; A computing unit is used to solve the target scheduling model and obtain the scheduling information of the multi-energy system.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for determining scheduling information according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for determining scheduling information as described in any one of claims 1 to 7.

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