A medium and long term power margin calculation method and system

Abstract

The application provides a kind of medium and long term power margin calculation method and system, comprising: according to the basic data collected, the power grid topology of medium and long term margin evaluation time is constructed;Coupling relationship between each subject is constructed based on power grid topology;Based on the coupling relationship between each subject and the multi-level power margin model constructed in advance, the power margin of each subject is obtained;The medium and long term power margin is obtained by summarizing the power margin of each subject.The method and system make the unit, unit group, branch and section form an associated and interactive whole through the coupling relationship between each subject, calculate the medium and long term power margin of each branch and section after solving the medium and long term power margin of generator unit and unit group, provide data support for the medium and long term power safety check of distribution network, provide reference for power grid operation and planning management department's power grid operation maintenance management and power grid construction planning, provide auxiliary decision basis for electric energy transaction in capacity quota for electric power market participants.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system dispatching plan, and in particular relates to a medium- and long-term electricity margin calculation method and system. Background Art

[0002] In the electricity market, grid transmission capacity plays a crucial role in the smooth operation of the entire power market and is a key technical reference indicator that all market participants must understand when conducting transactions. Existing research and applications focus on short-term power flows. However, assessing and analyzing medium- and long-term power margins to meet the requirements of a rigid transition to medium- and long-term power regulation is a pressing issue.

[0003] With the advancement of market-oriented reforms, the need for medium- and long-term power safety verification has become increasingly urgent. The medium- and long-term power capacity of units, groups of units, branches, and sections is the foundation for conducting these verifications and also provides the executable boundaries for these verifications. Therefore, how to adapt to the development of the power market and the characteristics of power grid operation, taking into account various constraints on power grid safe operation, and implementing medium- and long-term power margin analysis are key issues that must be addressed and resolved to ensure the smooth operation of power market transactions. Summary of the Invention

[0004] To overcome the shortcomings of the aforementioned existing technologies, the present invention proposes a method and system for calculating medium- and long-term energy margins. This method and system, based on safety-constrained unit combinations, considers constraints such as network security, unit characteristics, and operating modes. With the objective function of maximizing the transmission margin space for units, groups of units, branches, and sections, it establishes energy margin analysis models for each entity (hydropower units and groups of units, thermal power units and groups of units, branches, and sections). This method and system lays the foundation for conducting medium- and long-term energy security verifications, provides a reference for power grid operations and planning management departments that rely on power grid transmission capacity as a key operational guide, and provides a basis for market participants who use power grid transmission capacity as an auxiliary decision-making tool for energy trading.

[0005] The solutions adopted to achieve the above objectives are:

[0006] A method for calculating medium- and long-term power margin, the improvement of which includes:

[0007] Construct the grid topology at the time of mid- to long-term margin assessment based on the collected basic data;

[0008] Building coupling relationships between entities based on the grid topology;

[0009] Obtaining the power margin of each subject based on the coupling relationship between the subjects and a pre-built multi-level power margin model;

[0010] Summarizing the power margins of the various entities to obtain a medium- and long-term power margin;

[0011] The main body includes hydropower units and unit groups, thermal power units and unit groups, and branches and sections;

[0012] The coupling relationship between the various entities includes: the coupling relationship between units, unit groups, branches and sections;

[0013] The multi-level power margin model includes: a power margin model for hydropower units and units, a power margin model for thermal power units and units, and a branch and section power margin model.

[0014] The first preferred technical solution provided by the present invention is improved in that the construction of the power grid topology at the mid- to long-term evaluation time based on the collected basic data includes:

[0015] Obtain unit information, unit group information, section information, load forecast information, network model, medium- and long-term power grid change information, and load physical parameters as basic data through the dispatching agency;

[0016] Based on the basic data, a grid topology at the time of grid constraint and margin assessment is generated.

[0017] The second preferred technical solution provided by the present invention is improved in that the coupling relationship between the entities is established based on the power grid topology, including:

[0018] According to the power grid topology, the relationship matrices between units, between groups of units and units, between branches and units, and between sections and units are calculated respectively;

[0019] The coupling relationship between the subjects is represented based on the relationship matrix.

[0020] The third preferred technical solution provided by the present invention is improved in that the relationship matrix between the units is as follows:

[0021]

[0022] Among them, K u Represents the relationship matrix between units, subscript u represents the unit, k u11 、k u12 ,…,k umm Respectively represent the proportional coefficients between units;

[0023] The relationship matrix between the group of units and the units is shown below:

[0024]

[0025] Among them, K ug Represents the relationship matrix between the unit group and the units, the subscript ug represents the unit group, kug11 、k ug12 ,…,k ugnm Respectively represent the proportional coefficients between the group of units and the units;

[0026] The relationship matrix between the branches and the units is shown in the following formula:

[0027]

[0028] Among them, K b Represents the relationship matrix between branches and units, subscript b represents branch, k b11 、k b12 ,…,k bim Respectively represent the proportional coefficient between the branch and the unit;

[0029] The relationship matrix between the section and the unit is shown in the following formula:

[0030]

[0031] Among them, K s Represents the relationship matrix between the section and the unit, the subscript s represents the section, k s11 、k s12 ,…,k sjm They represent the proportional coefficients between the section and the unit respectively.

[0032] The fourth preferred technical solution provided by the present invention is improved in that the establishment of the power margin model of the hydropower unit and the unit group includes:

[0033] Taking the maximization of the power margin space value of hydropower units and unit groups as the objective function, and taking the unit operation constraints, system balance constraints, network constraints, water balance constraints of hydropower plants, water level constraints, output constraints of hydropower units or unit groups and watershed associations as constraints, a power margin model for hydropower units and unit groups is established.

[0034] The fifth preferred technical solution provided by the present invention is improved in that the establishment of the power margin model of the thermal power unit and the unit group includes:

[0035] Taking the maximization of the power margin space value of thermal power units and unit groups as the objective function, and taking the unit operation constraints, system balance constraints, network constraints, the three publics of thermal power units, voltage support, startup maintenance, overhaul, unit or unit group output constraints and minimum start-up and shutdown time constraints as constraints, a power margin model for thermal power units and unit groups is established.

[0036] The sixth preferred technical solution provided by the present invention is improved in that the establishment of the branch and section power margin model includes:

[0037] Taking the maximization of branch and section electricity margin space value as the objective function, and taking group electricity declaration information, load forecast information, trading plan information, and unit and grid operation constraints as constraints, a branch and section electricity margin model is established.

[0038] A medium- and long-term electricity margin calculation system is improved in that it includes: a power grid topology module, a coupling relationship module, a main body margin module and an electricity margin module;

[0039] The power grid topology module is used to construct the power grid topology at the time of medium and long-term margin assessment based on the collected basic data;

[0040] The coupling relationship module is used to establish the coupling relationship between the various entities based on the power grid topology;

[0041] The subject margin module is used to obtain the power margin of each subject based on the coupling relationship between the subjects and a pre-built multi-level power margin model;

[0042] The power margin module is used to aggregate the power margins of the various entities to obtain a medium- and long-term power margin;

[0043] The main body includes hydropower units and unit groups, thermal power units and unit groups, and branches and sections;

[0044] The coupling relationship between the various entities includes: the coupling relationship between units, unit groups, branches and sections;

[0045] The multi-level power margin model includes: a power margin model for hydropower units and units, a power margin model for thermal power units and units, and a branch and section power margin model.

[0046] The seventh preferred technical solution provided by the present invention is improved in that the power grid topology module includes a data acquisition unit and a topology generation unit;

[0047] The data acquisition unit is used to obtain unit information, unit group information, section information, load forecast information, network model, medium- and long-term power grid change information, and load physical parameters as basic data through the dispatching agency;

[0048] The topology generating unit is configured to generate a power grid topology at a power grid constraint and margin assessment moment based on the basic data.

[0049] The eighth preferred technical solution provided by the present invention is improved in that the coupling relationship module includes: a matrix calculation unit and a coupling relationship unit;

[0050] The matrix calculation unit is used to calculate the relationship matrices between units, between groups of units and units, between branches and units, and between sections and units according to the power grid topology;

[0051] The coupling relationship unit is used to represent the coupling relationship between the subjects based on the relationship matrix.

[0052] Compared with the closest prior art, the present invention has the following beneficial effects:

[0053] The present invention constructs a power grid topology at the time of medium- and long-term margin assessment based on collected basic data; constructs a coupling relationship between various entities based on the power grid topology; obtains the power margin of each entity based on the coupling relationship between various entities and a pre-constructed multi-level power margin model; and summarizes the power margin of each entity to obtain the medium- and long-term power margin. Through the coupling relationship between various entities, the units, unit groups, branches, and sections form an associated and interactive whole. After solving the medium- and long-term power margin of the generator units and unit groups, the medium- and long-term power margin of each branch and section is calculated, providing data support for the medium- and long-term power safety verification of the distribution network, providing a reference for the power grid operation and planning management departments of the power grid operation and maintenance management and power grid construction planning, and providing power market participants with an auxiliary decision-making basis for power energy trading in terms of capacity quota.

[0054] In this application, the coupling relationship between units, unit groups, branches and sections is represented by a relationship matrix, and according to different equipment attributes, the power margin analysis model of hydropower units and unit groups, the power margin analysis model of thermal power units and unit groups, and the power margin analysis model of branches and sections are established respectively. The power margin of hydropower units, hydropower groups, thermal power units, thermal power groups, branches and sections can be obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flow chart of a method for calculating medium- and long-term power margin provided by the present invention;

[0056] Figure 2 A flow chart of an embodiment of a method for calculating medium- and long-term power margin provided by the present invention;

[0057] Figure 3 A schematic diagram of the basic structure of a medium- and long-term power margin calculation system provided by the present invention;

[0058] Figure 4 A detailed structural diagram of a medium- and long-term electricity margin calculation system provided by the present invention. DETAILED DESCRIPTION

[0059] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0060] Example 1:

[0061] The flow chart of a method for calculating medium and long term power margin provided by the present invention is as follows: Figure 1 Shown, including:

[0062] Step 1: Construct the grid topology at the time of medium- and long-term margin assessment based on the collected basic data;

[0063] Step 2: Construct the coupling relationship between each subject based on the power grid topology;

[0064] Step 3: Based on the coupling relationship between the entities and the pre-built multi-level power margin model, the power margin of each entity is obtained;

[0065] Step 4: Summarize the power margin of each entity to obtain the medium- and long-term power margin;

[0066] The main body includes hydropower units and unit groups, thermal power units and unit groups, as well as branches and sections;

[0067] The coupling relationship between each subject includes: the coupling relationship between units, unit groups, branches and sections;

[0068] The multi-level power margin model includes: power margin model for hydropower units and units, power margin model for thermal power units and units, and power margin model for branches and sections.

[0069] Specifically, the medium and long-term power margin calculation method process is as follows: Figure 2 Shown, including:

[0070] Step 101: Prepare basic data. Obtain basic data such as unit information, unit group information, section information, load forecast information, network models, medium- and long-term equipment change information, and load physical parameters from the dispatching organization to provide data for boundary condition processing. Medium- and long-term equipment change information includes plans for changing the grid topology, such as medium- and long-term equipment maintenance plans and equipment addition plans.

[0071] Step 102: Processing boundary conditions: Integrate data, obtain system data boundary conditions, and form various grid constraints based on basic parameters and generate a future grid topology model, i.e., the grid topology at the time of mid- to long-term margin assessment.

[0072] Step 103: Constructing a relationship matrix. There are coupling relationships among the units, unit groups, branches, and sections. The relationship matrix K can represent the coupling relationships among the units, unit groups, branches, and sections.

[0073] Assume a simple network consists of m units, n unit groups, i branches and j sections. The relationship matrix K between units is u , the relationship matrix K between the unit group and the units ug , the relationship matrix K between branches and units b , the relationship matrix K between sections and units sThe expressions are as follows respectively.

[0074] The relationship matrix K between units u :

[0075]

[0076] Among them, k u11 、k u12 ,…,k umm Respectively represent the proportional coefficients between units, such as k u11 It represents the proportional relationship between the current unit (unit 1) and unit 1. There is a proportional relationship of 0 or 1 between the unit and its own unit, that is, k u11 、k u22 ,…,k umm The value is 0 or 1, which is related to the start and stop status of the unit. There is a proportional relationship of 0 between the unit and other units, that is, the residual coefficient k u12 ,…k u1m ,…are all 0.

[0077] The relationship matrix K between the unit group and the units ug :

[0078]

[0079] Among them, k ug11 、k ug12 ,…,k ugnm Respectively represent the proportional coefficients between the unit group and the unit, such as k ug11 It represents the proportional relationship between group 1 and unit 1. The power of each group is determined by the start and stop status of the units it contains, so k ug11 、k ug12 ,…,k ugnm The value is 0 or 1.

[0080] Relationship matrix K between branches and units b :

[0081]

[0082] Among them, k b11 、k b12 ,…,k bim Respectively represent the proportional coefficients between the branch and the unit, such as k b11 It indicates the proportional relationship between branch 1 and unit 1. From the sensitivity calculation, we know that the branch power and the power between units have a proportional relationship of -1 to 1, so k b11 、k b12 ,…,k bim The value is between [-1, 1].

[0083] Relationship matrix K between sections and units s :

[0084]

[0085] Among them, k s11 、k s12 ,…,k sjm Respectively represent the proportional coefficient between the section and the unit, such as k s11 It indicates the proportional relationship between section 1 and unit 1. From the sensitivity calculation, it can be known that the proportional relationship between the section power and the power between units is -1 to 1, so k s11 、k s12 ,…,k sjm The value is between [-1, 1].

[0086] The above relationship matrix K u , K ug , K b and K s The specific value can be calculated from the future power grid topology model.

[0087] Step 104: constructing a power margin model for the hydropower units and the hydropower unit groups.

[0088] Step 104-1, model optimization objective: maximize the power margin space of hydropower units and generator groups, including the upper and lower limits of the power margin of hydropower units and generator groups, that is, the optimization objective is:

[0089] max C wu (5)

[0090] Where C wu Indicates the power margin space value of hydropower units and unit groups.

[0091] Step 104-2, model constraints: In addition to satisfying constraints such as unit operation constraints, system balance constraints, and network constraints, the power margin analysis model of a hydropower unit or unit group should also satisfy constraints such as the hydropower plant's water balance constraints, water level constraints, hydropower unit or unit group output constraints, and watershed association constraints.

[0092] Step 105: Constructing a power margin model for the thermal power units and the power unit groups.

[0093] Step 105-1. Model optimization objective: maximize the power margin space of thermal power units and generator groups, including the upper and lower limits of the power margin of thermal power units and generator groups.

[0094] max C fu (6)

[0095] Where C fu Indicates the power margin space value of thermal power units and unit groups.

[0096] Step 105-2, model constraints: In addition to meeting constraints such as unit operation constraints, system balance constraints, and network constraints, the power margin analysis model of a thermal power unit or unit group should also meet constraints such as the three publics, voltage support, startup maintenance, overhaul, unit or unit group output constraints, and minimum start-up and shutdown time constraints of the thermal power unit.

[0097] Step 106: Construct branch and section power margin models.

[0098] Step 106-1. Model optimization objective: maximize the branch and section power margin space, including the upper and lower limits of the branch and section power margin space.

[0099] max C bs (7)

[0100] Where C bs Indicates the branch and section power margin space value.

[0101] Step 106-2, model constraints: group power declaration information, load forecast information, transaction plan information, and unit and grid operation constraints are used as constraints.

[0102] Step 107: Summarize the power margins of each entity. Based on the safety-constrained unit combination technology, the power margins of each entity are calculated using the power margin models of hydropower units and units, thermal power units and units, branches and sections, and the relationship matrix. The power margins of each entity are then summarized to provide data support for medium- and long-term power safety verification.

[0103] After step 107, the application of medium- and long-term power margin is also included, namely:

[0104] Step 108: Check the power plan based on the medium- and long-term power margin.

[0105] That is, the medium- and long-term electricity plan is broken down into entities such as units, unit groups, branches, and sections, and the electricity plan and electricity margin of each entity are compared. When the electricity plan exceeds the limit, the electricity plan is adjusted and revised. Step 108 can also include judging whether the power grid operation and maintenance plan and power grid construction plan, such as maintenance, are within the medium- and long-term electricity margin based on the medium- and long-term electricity margin. If not, the power grid operation and maintenance plan and power grid construction plan are revised. At the same time, step 108 can also include providing power market participants with auxiliary decision-making basis for capacity quota of electricity transactions, that is, judging whether the electricity transaction quota is within the medium- and long-term electricity margin. If not, the electricity transaction is modified according to the long-term electricity margin.

[0106] Example 2:

[0107] Based on the same inventive concept, the present invention also provides a medium- and long-term electricity margin calculation system. Since the principles of these devices in solving technical problems are similar to the medium- and long-term electricity margin calculation method, the repeated parts will not be repeated.

[0108] The basic structure of the system is as follows Figure 3 Shown, including:

[0109] Grid topology module, coupling relationship module, main body margin module and power margin module;

[0110] Among them, the power grid topology module is used to construct the power grid topology at the time of medium and long-term margin assessment based on the collected basic data;

[0111] The coupling relationship module is used to build the coupling relationship between various entities based on the power grid topology;

[0112] The subject margin module is used to obtain the power margin of each subject based on the coupling relationship between the subjects and the pre-built multi-level power margin model;

[0113] The power margin module is used to summarize the power margin of each entity to obtain the medium- and long-term power margin;

[0114] The main body includes hydropower units and unit groups, thermal power units and unit groups, as well as branches and sections;

[0115] The coupling relationship between each subject includes: the coupling relationship between units, unit groups, branches and sections;

[0116] The multi-level power margin model includes: power margin model for hydropower units and units, power margin model for thermal power units and units, and power margin model for branches and sections.

[0117] The detailed structure of the medium and long term power margin calculation system is as follows: Figure 4 shown.

[0118] Among them, the power grid topology module includes a data acquisition unit and a topology generation unit;

[0119] The data acquisition unit is used to obtain unit information, unit group information, section information, load forecast information, network model, medium- and long-term power grid change information, and load physical parameters as basic data through the dispatching agency;

[0120] The topology generation unit is used to generate the power grid topology at the time of power grid constraint and margin evaluation based on basic data.

[0121] Wherein, the coupling relationship module includes: a matrix calculation unit and a coupling relationship unit;

[0122] Matrix calculation unit, used to calculate the relationship matrix between units, between groups of units and units, between branches and units, and between sections and units according to the power grid topology;

[0123] The coupling relationship unit is used to represent the coupling relationship between entities based on the relationship matrix.

[0124] Among them, the medium- and long-term electricity margin calculation system also includes a hydropower model module;

[0125] The hydropower model module is used to establish a hydropower unit and unit group power margin model with the objective function of maximizing the power margin space value of the hydropower unit and unit group, and with the unit operation constraints, system balance constraints, network constraints, hydropower plant water balance constraints, water level constraints, hydropower unit or unit group output constraints and watershed association as constraints.

[0126] Among them, the medium- and long-term electricity margin calculation system also includes a thermal power model module;

[0127] The thermal power model module is used to establish a power margin model for thermal power units and unit groups with the objective function of maximizing the power margin space value of thermal power units and unit groups, and with the unit operation constraints, system balance constraints, network constraints, the three publics of thermal power units, voltage support, startup maintenance, overhaul, unit or unit group output constraints and minimum start-up and shutdown time constraints as constraints.

[0128] Among them, the medium and long-term power margin calculation system also includes branch and section model modules;

[0129] The branch and section model module is used to establish branch and section power margin models with the maximization of branch and section power margin space value as the objective function and group power declaration information, load forecast information, trading plan information, and unit and grid operation constraints as constraints.

[0130] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0131] 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 produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. 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.

[0132] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device 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.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit its scope of protection. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that after reading this application, those skilled in the art may still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, but these changes, modifications or equivalent substitutions are all within the scope of protection of the pending claims of the application.

Claims

1. A method for calculating medium- and long-term power margin, characterized in that: include: Construct the grid topology at the time of mid- to long-term margin assessment based on the collected basic data; Establishing coupling relationships between entities based on the power grid topology; Obtaining the power margin of each subject based on the coupling relationship between the subjects and a pre-built multi-level power margin model; Summarizing the power margins of the various entities to obtain a medium- and long-term power margin; The main body includes hydropower units and unit groups, thermal power units and unit groups, and branches and sections; The coupling relationship between the various entities includes: the coupling relationship between units, unit groups, branches and sections; The multi-level power margin model includes: a power margin model for hydropower units and units, a power margin model for thermal power units and units, and a power margin model for branches and sections; The construction of the power grid topology at the mid- to long-term evaluation time based on the collected basic data includes: Obtain unit information, unit group information, section information, load forecast information, network model, medium- and long-term power grid change information, and load physical parameters as basic data through the dispatching agency; generating a grid topology at the time of grid constraint and margin assessment based on the basic data; The establishing of coupling relationships between entities based on the power grid topology includes: According to the power grid topology, the relationship matrices between units, between groups of units and units, between branches and units, and between sections and units are calculated respectively; The coupling relationship between the subjects is represented based on the relationship matrix.

2. The method according to claim 1, wherein The relationship matrix between the units is shown below: Among them, K u Represents the relationship matrix between units, subscript u represents the unit, k u11 、k u12 ,…,k umm Respectively represent the proportional coefficients between units; The relationship matrix between the group of units and the units is shown below: Among them, K ug Represents the relationship matrix between the unit group and the units, the subscript ug represents the unit group, k ug11 、k ug12 ,…,k ugnm Respectively represent the proportional coefficients between the group of units and the units; The relationship matrix between the branches and the units is shown in the following formula: Among them, K b Represents the relationship matrix between branches and units, subscript b represents branch, k b11 、k b12 ,…,k bim Respectively represent the proportional coefficients between the branch and the unit; The relationship matrix between the section and the unit is shown in the following formula: Among them, K s Represents the relationship matrix between the section and the unit, the subscript s represents the section, k s11 、k s12 ,…,k sjm They represent the proportional coefficients between the section and the unit respectively.

3. The method according to claim 1, wherein The establishment of the power margin model of the hydropower unit and unit group includes: Taking the maximization of the power margin space value of hydropower units and unit groups as the objective function, and taking the unit operation constraints, system balance constraints, network constraints, water balance constraints of hydropower plants, water level constraints, output constraints of hydropower units or unit groups and watershed associations as constraints, a power margin model for hydropower units and unit groups is established.

4. The method according to claim 1, wherein The establishment of the power margin model of the thermal power unit and the unit group includes: Taking the maximization of the power margin space value of thermal power units and unit groups as the objective function, and taking the unit operation constraints, system balance constraints, network constraints, the three publics of thermal power units, voltage support, startup maintenance, overhaul, unit or unit group output constraints and minimum start-up and shutdown time constraints as constraints, a power margin model for thermal power units and unit groups is established.

5. The method according to claim 1, wherein The establishment of the branch and section power margin model includes: Taking the maximization of branch and section electricity margin space value as the objective function, and taking group electricity declaration information, load forecast information, trading plan information, and unit and grid operation constraints as constraints, a branch and section electricity margin model is established.

6. A medium- and long-term power margin calculation system, characterized in that: include: Grid topology module, coupling relationship module, main body margin module and power margin module; The power grid topology module is used to construct the power grid topology at the time of medium and long-term margin assessment based on the collected basic data; The coupling relationship module is used to establish the coupling relationship between the various entities based on the power grid topology; The subject margin module is used to obtain the power margin of each subject based on the coupling relationship between the subjects and a pre-built multi-level power margin model; The power margin module is used to aggregate the power margins of the various entities to obtain a medium- and long-term power margin; The main body includes hydropower units and unit groups, thermal power units and unit groups, and branches and sections; The coupling relationship between the various entities includes: the coupling relationship between units, unit groups, branches and sections; The multi-level power margin model includes: a power margin model for hydropower units and units, a power margin model for thermal power units and units, and a power margin model for branches and sections; The power grid topology module includes a data acquisition unit and a topology generation unit; The data acquisition unit is used to obtain unit information, unit group information, section information, load forecast information, network model, medium- and long-term power grid change information, and load physical parameters as basic data through the dispatching agency; The topology generating unit is configured to generate a power grid topology at the time of power grid constraint and margin assessment based on the basic data; The coupling relationship module includes: a matrix calculation unit and a coupling relationship unit; The matrix calculation unit is used to calculate the relationship matrices between units, between groups of units and units, between branches and units, and between sections and units according to the power grid topology; The coupling relationship unit is used to represent the coupling relationship between the subjects based on the relationship matrix.

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