Unit commitment method considering new energy limit and grid connection strength constraint

Abstract

The present application belongs to the field of new energy cluster grid connection technology, especially relates to a unit start-up mode optimization method considering new energy limit grid connection strength constraint; the present application establishes a unit minimum start-up mode optimization model with new energy maximum consumption as the target based on a coupling relationship model under the premise of meeting the limit grid connection strength requirement of new energy equipment, and the coupling relationship between different unit start-up modes and new energy station grid strength is decoupled by introducing an intermediate variable to obtain a double-layer optimization model, and a hybrid strategy combining a genetic algorithm and a CPLEX solver is used to solve the double-layer optimization model; so that the conventional unit start-up optimization method provided by the present application takes into account the new energy consumption problem and meets the requirement of grid strength.

Description

Technical Field

[0001] This invention belongs to the field of new energy cluster grid connection technology, and in particular relates to an optimization method for unit start-up mode considering the limit grid connection intensity constraint of new energy. Background Technology

[0002] Under the "dual carbon" background, clean energy represented by wind power and photovoltaics has shown an explosive growth trend, promoting the development of new power systems. However, the uncertainty and intermittency of wind and photovoltaic power output are not conducive to the stable operation of the power grid; moreover, the large-scale grid connection of new energy sources has squeezed the available space of conventional units, resulting in insufficient system inertia and voltage support capacity, and weak grid strength; in particular, the grid strength of the sending end of the new energy cluster is extremely weak, and stability problems such as transient voltage instability and wide-frequency oscillation are prominent. Common AC faults and DC commutation failures can easily trigger cascading faults, which seriously restricts the capacity for new energy consumption and transmission.

[0003] Currently, optimization of conventional power generation start-up methods mainly focuses on peak shaving, frequency regulation, and voltage constraints, with most algorithms focusing on multi-decision-variable, multi-constraint, and multi-objective unit combination optimization. However, there is limited research on conventional minimum start-up optimization models that consider the limit grid connection strength constraints of renewable energy. Furthermore, current conventional unit start-up optimization methods cannot simultaneously meet the requirements of renewable energy consumption and grid strength. Summary of the Invention

[0004] In order to solve the technical problems existing in the prior art, the present invention provides a method for optimizing the start-up mode of generating units that takes into account the constraints of the maximum grid connection intensity of new energy sources, and aims to solve the problem that the current conventional method for optimizing the start-up of generating units cannot simultaneously meet the requirements of new energy consumption and grid strength.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] A method for optimizing the start-up mode of generating units considering the constraints of the maximum grid connection intensity of new energy sources, characterized by the following steps:

[0007] Establish a coupling relationship model between the unit start-up mode and the grid strength at the renewable energy grid connection point;

[0008] Establish a power grid intensity constraint model for new energy power plants;

[0009] Under the premise of meeting the requirements of the maximum grid connection strength of new energy equipment, an optimization model of the minimum start-up mode of the unit with the goal of maximizing the absorption of new energy is established based on the coupling relationship model.

[0010] The nonlinear constraints in the minimum start-up mode optimization model of the generating units are linearized. By introducing intermediate variables, the coupling relationship between different generating unit start-up modes and the grid strength of new energy power plants is decoupled, resulting in a two-level optimization model. The two-level optimization model is solved by a hybrid strategy combining genetic algorithm and CPLEX solver.

[0011] This invention, while meeting the requirements of the maximum grid connection strength of new energy equipment, establishes an optimization model for the minimum start-up mode of generating units based on a coupling relationship model, with the goal of maximizing the absorption of new energy. Furthermore, by introducing intermediate variables, the coupling relationship between different unit start-up modes and the grid strength of new energy power plants is decoupled, resulting in a two-layer optimization model. A hybrid strategy combining genetic algorithms and CPLEX solvers is then used to solve this two-layer optimization model. This ensures that the conventional unit start-up optimization method provided in this application takes into account both the absorption of new energy and the requirements of grid strength.

[0012] Furthermore, the coupling relationship model includes:

[0013] The unit start-up state matrix and the unit subtransient reactance matrix are constructed based on the unit start-up state and the unit subtransient impedance value;

[0014] The system impedance matrix is ​​calculated using the unit start-up state matrix and the unit subtransient reactance matrix.

[0015] Calculate the short-circuit capacity of each new energy grid connection point based on the system impedance matrix;

[0016] The grid strength of each renewable energy grid connection point is calculated using the short-circuit ratio calculation formula; based on this, the grid strength of renewable energy grid connection points under different unit start-up modes is obtained.

[0017] Furthermore, the specific expression of the coupling relationship model is as follows:

[0018] Z sys =f1(X,X″) d );

[0019]

[0020]

[0021]

[0022] In the formula: Z sys The system impedance matrix; X represents the self-impedance of node i; X is the unit start-up state matrix, a binary variable where 0 indicates the unit is not in operation and 1 indicates the unit is in operation; X″ d S is the subtransient reactance matrix of the unit;ac,i Let f1 be the short-circuit capacity of the new energy power station i; function f1 represents the implicit functional relationship between the unit's start-up state and the system impedance matrix; SCR-X represents the formula for calculating the short-circuit ratio associated with the unit's operating state. Contribute to the development of new energy power stations; Contributing to the active power of the new energy power station; ji Z is the interaction factor between new energy field i and j; ji and Z ii These are the system's self-impedance and mutual impedance, respectively.

[0023] Furthermore, the power grid strength constraint model for new energy power plants uses a critical short-circuit ratio of 2 as the boundary condition for judging the strength of the new energy grid connection system. When the calculated short-circuit ratio of the new energy grid connection is greater than or equal to 2, the new energy grid connection is considered to meet the power grid strength constraint. The specific expression is as follows:

[0024]

[0025] In the formula: S ac,i Z represents the short-circuit capacity of new energy power station i; sys The system impedance matrix; Let be the self-impedance of node i; Contribute to the development of new energy power stations; Contributing to the active power of the new energy power station; ji Z is the interaction factor between new energy field i and j; ii X represents the system mutual impedance; X is the unit start-up state matrix, a binary variable, where 0 indicates the unit is not in operation and 1 indicates the unit is in operation; X″ d is the subtransient reactance matrix of the unit; function f1 represents the implicit functional relationship between the unit's start-up state and the system impedance matrix.

[0026] Furthermore, the constraints of the unit minimum start-up mode optimization model include power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, grid strength constraints for new energy power plants, output constraints for conventional units, and new energy processing constraints.

[0027] Furthermore, the linearization process for the nonlinear constraints includes:

[0028] Using the critical short-circuit ratio of 2 as the boundary condition, the maximum active power output limit of each new energy power station is obtained;

[0029] By changing the unit start-up method, the system short-circuit capacity can be increased, thereby increasing the maximum active power output limit of each renewable energy power station and improving the renewable energy absorption capacity.

[0030] By using the maximum active power output limit of the improved new energy power station as an intermediate variable, the grid intensity constraint model of the new energy power station is transformed into a maximum output limit constraint. This decouples the coupling relationship between different unit start-up modes and the grid intensity of the new energy power station, resulting in a two-layer optimization model.

[0031] Furthermore, the two-layer optimization model includes an upper-layer model and a lower-layer model;

[0032] The objective function of the upper-level model is to maximize the absorption of new energy sources.

[0033] The constraints of the upper-level model are power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, conventional unit output constraints, and renewable energy output constraints.

[0034] The objective function of the lower-level model is to maximize the active power output limit P of the renewable energy power station. newmax ;

[0035] The lower-level model constraint is the power grid strength constraint for new energy power plants.

[0036] Furthermore, the new energy output constraints of the upper-level model include:

[0037] The active power output of the renewable energy power station is less than the theoretical maximum active power output of the corresponding renewable energy power station and the objective function value P of the lower-level model. newmax :

[0038]

[0039]

[0040] In the formula: The active power output of the new energy power station at time t; This represents the theoretical maximum active power output of renewable energy power station i at time t; Let t be the objective function value of the lower-level model of the new energy power station i under the power grid strength constraint of the new energy power station at time t.

[0041] Furthermore, the expression for the lower-level model is as follows:

[0042]

[0043]

[0044] In the formula: T is the simulation running time of the lower-level model, taken as 8760h; n ew Indicates the number of new energy power stations; Let t be the active power output limit of renewable energy power station i at time t; S represents the active power output of the renewable energy power station j at time t;ac,i Z represents the short-circuit capacity of new energy power station i; sys , Let be the system impedance matrix and the self-impedance of node i, respectively; Y be the system admittance matrix; and the function f represents the functional relationship between different unit start-up modes and the system admittance matrix. For the installed capacity of new energy power station i; X, X″ d These are the unit start-up state matrix and the unit subtransient reactance matrix, respectively, where X is a binary variable, 0 indicates that the conventional unit is not in operation, and 1 indicates that the conventional unit is in operation.

[0045] Furthermore, the genetic algorithm optimizes the unit start-up mode variable on a daily basis, and obtains the minimum start-up mode of the unit throughout the year under the extreme grid connection intensity requirement of new energy equipment through rolling optimization.

[0046] The sum of the maximum output of the operating units represented by the variables in the genetic algorithm is greater than the maximum value of the load for the day, and the sum of the minimum output of the operating units is less than the minimum value of the load for the day.

[0047] The beneficial effects of this invention include:

[0048] This invention, while meeting the requirements of the maximum grid connection strength of new energy equipment, establishes an optimization model for the minimum start-up mode of generating units based on a coupling relationship model, with the goal of maximizing the absorption of new energy. Furthermore, by introducing intermediate variables, the coupling relationship between different unit start-up modes and the grid strength of new energy power plants is decoupled, resulting in a two-layer optimization model. A hybrid strategy combining genetic algorithms and CPLEX solvers is then used to solve this two-layer optimization model. This ensures that the conventional unit start-up optimization method provided in this application takes into account both the absorption of new energy and the requirements of grid strength. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the overall process of the present invention.

[0050] Figure 2 This is a flowchart of the computer software program of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0052] The following is in conjunction with the appendix Figure 1-2 The present invention will be further described in detail below:

[0053] See appendix Figure 1 As shown, the method for optimizing the start-up mode of generating units considering the limit grid connection intensity constraint of new energy sources is characterized by the following steps:

[0054] Establish a coupling relationship model between the unit start-up mode and the grid strength at the renewable energy grid connection point;

[0055] The coupling relationship model includes:

[0056] The unit start-up state matrix and the unit subtransient reactance matrix are constructed based on the unit start-up state and the unit subtransient impedance value;

[0057] The system impedance matrix is ​​calculated using the unit start-up state matrix and the unit subtransient reactance matrix.

[0058] Calculate the short-circuit capacity of each new energy grid connection point based on the system impedance matrix;

[0059] The grid strength of each renewable energy grid connection point is calculated using the short-circuit ratio calculation formula; based on this, the grid strength of renewable energy grid connection points under different unit start-up modes is obtained.

[0060] The specific expression of the coupling relationship model is as follows:

[0061] Z sys =f1(X,X″) d );

[0062]

[0063]

[0064]

[0065] In the formula: Z sys The system impedance matrix; X represents the self-impedance of node i; X is the unit start-up state matrix, a binary variable where 0 indicates the unit is not in operation and 1 indicates the unit is in operation; X″ d S is the subtransient reactance matrix of the unit; ac,i Let f1 be the short-circuit capacity of the new energy power station i; function f1 represents the implicit functional relationship between the unit's start-up state and the system impedance matrix; SCR-X represents the formula for calculating the short-circuit ratio associated with the unit's operating state. Contribute to the development of new energy power stations; Contributing to the active power of the new energy power station; ji Z is the interaction factor between new energy field i and j; ji and Z ii These are the system's self-impedance and mutual impedance, respectively.

[0066] Establish a power grid intensity constraint model for new energy power plants;

[0067] The power grid strength constraint model for new energy power plants uses a critical short-circuit ratio of 2 as the boundary condition for judging the strength of the new energy grid connection system. When the calculated short-circuit ratio of the new energy grid connection is greater than or equal to 2, the new energy grid connection is considered to meet the power grid strength constraint. The specific expression is as follows:

[0068]

[0069] In the formula: S ac,i Z represents the short-circuit capacity of new energy power station i; sys The system impedance matrix; Let be the self-impedance of node i; Contribute to the development of new energy power stations; Contributing to the active power of the new energy power station; ji Z is the interaction factor between new energy field i and j; ii X represents the system mutual impedance; X is the unit start-up state matrix, a binary variable, where 0 indicates the unit is not in operation and 1 indicates the unit is in operation; X″ d is the subtransient reactance matrix of the unit; function f1 represents the implicit functional relationship between the unit's start-up state and the system impedance matrix.

[0070] Under the premise of meeting the requirements of the maximum grid connection strength of new energy equipment, an optimization model of the minimum start-up mode of the unit with the goal of maximizing the absorption of new energy is established based on the coupling relationship model.

[0071] The constraints of the unit minimum start-up mode optimization model include power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, grid strength constraints for new energy power plants, output constraints for conventional units, and new energy processing constraints.

[0072] The methods for linearizing the nonlinear constraints include:

[0073] Using the critical short-circuit ratio of 2 as the boundary condition (i.e., the limit of grid connection strength of new energy equipment), the maximum active power output limit of each new energy power station is obtained;

[0074] By changing the unit start-up method, the system short-circuit capacity can be increased, thereby increasing the maximum active power output limit of each renewable energy power station and improving the renewable energy absorption capacity.

[0075] By using the maximum active power output limit of the improved new energy power station as an intermediate variable, the grid intensity constraint model of the new energy power station is transformed into a maximum output limit constraint. This decouples the coupling relationship between different unit start-up modes and the grid intensity of the new energy power station, resulting in a two-layer optimization model.

[0076] The nonlinear constraints (i.e., the grid strength constraints of new energy power plants, which are nonlinear constraints) in the minimum start-up mode optimization model of the generating units are linearized. By introducing intermediate variables, the coupling relationship between different start-up modes of generating units and the grid strength of new energy power plants is decoupled, resulting in a two-level optimization model. A hybrid strategy combining genetic algorithm and CPLEX solver is used to solve the two-level optimization model.

[0077] The two-layer optimization model includes an upper-layer model and a lower-layer model;

[0078] The objective function of the upper-level model is to maximize the absorption of new energy sources.

[0079] The constraints of the upper-level model are power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, conventional unit output constraints, and renewable energy output constraints.

[0080] Power balance constraints:

[0081]

[0082] Conventional unit ramp-up constraints:

[0083]

[0084] Rotational spare constraint:

[0085]

[0086] Output constraints of conventional units:

[0087]

[0088] Constraints on new energy output:

[0089]

[0090] In the above formula: n ew n gen This indicates the number of new energy power plants and the number of conventional generating units; Let i and j be the active power output values ​​of the renewable energy power station at time t; Let t be the total system load at time t; P represents the active power output of conventional unit i at time t. i up , These represent the maximum uphill and downhill ramp rates of conventional unit i, respectively. These represent the maximum and minimum active power outputs of unit i at time t; X t,i P is a binary variable representing the operating state of unit i at time t, where 1 indicates the unit is in operation and 0 indicates the unit is shut down; re For system rotation standby; S ac,i Z represents the short-circuit capacity of new energy power station i; sys , Let X and X″ be the system impedance matrix and the self-impedance of node i, respectively; d These are the unit start-up state matrix and the unit subtransient reactance matrix, respectively, where X is a binary variable, 0 indicates that the conventional unit is not in operation, and 1 indicates that the conventional unit is in operation; the function f1 represents the implicit functional relationship between the unit start-up state and the system impedance matrix; Let i and t represent the theoretical maximum active power output of the renewable energy power station i at time t.

[0091] The expression for the upper-level model is as follows:

[0092]

[0093] In the formula, n ew This represents the number of new energy power stations; T is the total simulation running time of the production simulation, which is taken as 8760h in this paper. Let i be the active power output of the renewable energy power station at time t.

[0094] The objective function of the lower-level model is to maximize the active power output limit P of the renewable energy power station. newmax ;

[0095] The lower-level model constraint is the power grid strength constraint for new energy power plants.

[0096] The new energy output constraints of the upper-level model include:

[0097] The active power output of the renewable energy power station is less than the theoretical maximum active power output of the corresponding renewable energy power station and the objective function value P of the lower-level model. newmax :

[0098]

[0099]

[0100] In the formula: The active power output of the new energy power station at time t; This represents the theoretical maximum active power output of renewable energy power station i at time t; Let t be the objective function value of the lower-level model of the new energy power station i under the power grid strength constraint of the new energy power station at time t.

[0101] The expression for the lower-level model is as follows:

[0102]

[0103]

[0104] In the formula: T is the simulation running time of the lower-level model, taken as 8760h; n ew Indicates the number of new energy power stations; Let t be the active power output limit of renewable energy power station i at time t; S represents the active power output of the renewable energy power station j at time t; ac,i Z represents the short-circuit capacity of new energy power station i; sys , Let be the system impedance matrix and the self-impedance of node i, respectively; Y be the system admittance matrix; and the function f represents the functional relationship between different unit start-up modes and the system admittance matrix. For the installed capacity of new energy power station i; X, X″ d These are the unit start-up state matrix and the unit subtransient reactance matrix, respectively, where X is a binary variable, 0 indicates that the conventional unit is not in operation, and 1 indicates that the conventional unit is in operation.

[0105] In this embodiment, the genetic algorithm input variables include the unit start-up mode variable optimized on a daily basis, taking into account the actual situation that the downtime and operation time of conventional units in engineering applications are both long. The minimum start-up mode of the unit throughout the year under the limit grid connection intensity requirement of new energy equipment is obtained by rolling optimization solution.

[0106] In this embodiment, the genetic algorithm input variables include those required to ensure that the unit start-up mode variables provided by the genetic algorithm can meet the power balance constraints of the system in the upper-level model. Specifically, the sum of the maximum output of the operating units represented by the genetic algorithm input variables (i.e., the unit start-up mode variables) must be greater than the maximum load of the day, and the sum of the minimum output of the operating units must be less than the minimum load of the day. The specific mathematical model is as follows:

[0107]

[0108] In the formula: These represent the maximum and minimum load values ​​for a given day, respectively; X i This indicates the operating status of unit i, where 1 represents operation and 0 represents shutdown; n gen P represents the total number of conventional generating units; i gmax P i gmin These represent the maximum and minimum output of conventional unit i, respectively.

[0109] This invention, while meeting the requirements of the maximum grid connection strength of new energy equipment, establishes an optimization model for the minimum start-up mode of generating units based on a coupling relationship model, with the goal of maximizing the absorption of new energy. Furthermore, by introducing intermediate variables, the coupling relationship between different unit start-up modes and the grid strength of new energy power plants is decoupled, resulting in a two-layer optimization model. A hybrid strategy combining genetic algorithms and CPLEX solvers is then used to solve this two-layer optimization model. This ensures that the conventional unit start-up optimization method provided in this application takes into account both the absorption of new energy and the requirements of grid strength.

[0110] See appendix Figure 2 As shown, the computer software flow execution steps of the present invention are as follows:

[0111] S1. Input parameters of the input model: system grid structure, relevant parameters of conventional units, and annual time-series curves of new energy sources / load;

[0112] S2, Initial population size generated by the algorithm;

[0113] S3, Input the normal unit start-up method;

[0114] S4. Handle nonlinear constraints and decouple the model to obtain the upper and lower layer models;

[0115] S5. Update the system admittance matrix;

[0116] S6. Call the CPLEX solver to solve the lower-level model;

[0117] S7. Return the objective function value of the lower-level model to the upper-level model;

[0118] S8. Call the CPLEX solver to solve the upper-level model;

[0119] S9. Set the crossover and mutation parameters of the computer genetic algorithm program, change the start-up mode of the conventional unit, and repeat the above S1 to S8.

[0120] S10. When the above step S9 iterates to the maximum number of generations, the optimization result is output, and the minimum start-up mode of the conventional units in the system is obtained under the constraint of the limit grid connection intensity of new energy.

[0121] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A method for optimizing unit start-up modes considering the constraints of renewable energy grid connection limits, characterized in that, Includes the following steps: Establish a coupling relationship model between the unit start-up mode and the grid strength at the renewable energy grid connection point; Establish a power grid intensity constraint model for new energy power plants; Under the premise of meeting the requirements of the maximum grid connection strength of new energy equipment, an optimization model of the minimum start-up mode of the unit with the goal of maximizing the absorption of new energy is established based on the coupling relationship model. The nonlinear constraints in the minimum start-up mode optimization model of the generating units are linearized. The coupling relationship between different start-up modes of generating units and the grid strength of new energy power plants is decoupled by introducing intermediate variables, resulting in a two-level optimization model. The two-level optimization model is solved by a hybrid strategy combining genetic algorithm and CPLEX solver. The methods for linearizing the nonlinear constraints include: Using the critical short-circuit ratio of 2 as the boundary condition, the maximum active power output limit of each new energy power station is obtained; By changing the unit start-up method, the system short-circuit capacity can be increased, thereby increasing the maximum active power output limit of each renewable energy power station and improving the renewable energy absorption capacity. By using the enhanced maximum active power output limit of the renewable energy power station as an intermediate variable, the grid intensity constraint model of the renewable energy power station is transformed into a maximum output limit constraint. This decouples the coupling relationship between different unit start-up modes and the grid intensity of the renewable energy power station, resulting in a two-layer optimization model.

2. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 1, characterized in that, The coupling relationship model includes: The unit start-up state matrix and the unit subtransient reactance matrix are constructed based on the unit start-up state and the unit subtransient impedance value; The system impedance matrix is ​​calculated using the unit start-up state matrix and the unit subtransient reactance matrix. Calculate the short-circuit capacity of each new energy grid connection point based on the system impedance matrix; The grid strength of each renewable energy grid connection point is calculated using the short-circuit ratio calculation formula; based on this, the grid strength of renewable energy grid connection points under different unit start-up modes is obtained.

3. The method for optimizing unit start-up mode considering the limit of new energy grid connection intensity as described in claim 2, characterized in that, The specific expression of the coupling relationship model is as follows: ； ； ； ； In the formula: Z sys The system impedance matrix; For nodes i The self-impedance; X is the unit start-up state matrix, which is a binary variable, where 0 indicates that the unit is not in operation and 1 indicates that the unit is in operation; The subtransient reactance matrix of the unit; For new energy power stations i Short-circuit capacity; function This represents the implicit functional relationship between the unit's start-up state and the system impedance matrix; The formula for calculating the short-circuit ratio in relation to the unit's operating status; For new energy power stations i Contribute your efforts and merits; For new energy power stations j Those who have made meritorious contributions; For new energy fields i , j Interaction factors between them; and These are the system's self-impedance and mutual impedance, respectively.

4. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 1, characterized in that, The power grid strength constraint model for new energy power plants uses a critical short-circuit ratio of 2 as the boundary condition for judging the strength of the new energy grid connection system. When the calculated short-circuit ratio of the new energy grid connection is greater than or equal to 2, the new energy grid connection is considered to meet the power grid strength constraint. The specific expression is as follows: ； In the formula: Indicates new energy power station i The short-circuit capacity; Z sys The system impedance matrix; For nodes i Self-impedance; For new energy power stations i Contribute your efforts and merits; For new energy power stations j Contributions made; For new energy fields i , j Interaction factors between them; X represents the system mutual impedance; X is the unit start-up state matrix, a binary variable, where 0 indicates the unit is not in operation and 1 indicates the unit is in operation. The subtransient reactance matrix of the unit; function This represents the implicit functional relationship between the unit's start-up state and the system impedance matrix.

5. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 1, characterized in that, The constraints of the unit minimum start-up mode optimization model include power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, grid strength constraints for new energy power plants, output constraints for conventional units, and new energy processing constraints.

6. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 1, characterized in that, The two-layer optimization model includes an upper-layer model and a lower-layer model; The objective function of the upper-level model is to maximize the absorption of new energy sources. The constraints of the upper-level model are power balance constraints, conventional unit ramp-up constraints, spinning reserve constraints, conventional unit output constraints, and renewable energy output constraints. The objective function of the lower-level model is to maximize the active power output limit of the renewable energy power station. P newmax; The lower-level model constraint is the power grid strength constraint for new energy power plants.

7. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 6, characterized in that, The new energy output constraints of the upper-level model include: The active power output of the renewable energy power station is less than the theoretical maximum active power output of the corresponding renewable energy power station and the objective function value of the lower-level model. P newmax: ； ； In the formula: For new energy power stations i exist t Contributing effort at all times; Indicates new energy power station i exist t The theoretical maximum value of active power output at any given moment; for t Shike New Energy Power Station i Objective function value of the lower-level model under the power grid strength constraint of new energy power plants.

8. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 6, characterized in that, The expression for the lower-level model is as follows: ； ； In the formula: T The simulation runtime for the lower-level model is set to 8760 hours. Indicates the number of new energy power stations; for t Shike New Energy Power Station i The limit of active power output; for t Shike New Energy Power Station The effective output value; Indicates new energy power station i Short-circuit capacity; , These are the system impedance matrix and the nodes, respectively. i Self-impedance; Y The system admittance matrix; function f This represents the functional relationship between different unit start-up methods and the system admittance matrix; For new energy power stations i The installed capacity; X , These are the unit start-up state matrix and the unit subtransient reactance matrix, respectively. X This is a binary variable; 0 indicates that the conventional unit is not in operation, and 1 indicates that the conventional unit is in operation.

9. The method for optimizing unit start-up mode considering the limit grid connection intensity constraint of new energy sources according to claim 1, characterized in that, The genetic algorithm optimizes the unit start-up mode variable on a daily basis, and obtains the minimum start-up mode of the unit throughout the year under the extreme grid connection intensity requirement of new energy equipment through rolling optimization. The sum of the maximum output of the operating units represented by the variables in the genetic algorithm is greater than the maximum value of the load for the day, and the sum of the minimum output of the operating units is less than the minimum value of the load for the day.

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