Uncertainty power grid preventive control measure optimization method and system and storage medium

Abstract

The application discloses the technical field of power system automation control, and relates to an uncertainty power grid preventive control measure optimization method and system and a storage medium, which comprises the following steps: constructing a power grid operation mode uncertainty domain; constructing a power grid operation stability domain; constructing a power grid preventive control model according to the power grid operation mode uncertainty domain and the power grid operation stability domain and solving the model; and performing time domain simulation checking on the power grid preventive control model to obtain optimized uncertainty power grid preventive control measures. The application improves the ability of the power grid to cope with uncertainty risk scenarios and improves the utilization rate of power transmission equipment.

Description

Technical Field

[0001] This invention belongs to the field of power system automation control technology, specifically relating to an optimization method, system, and storage medium for uncertain power grid prevention and control measures. Background Technology

[0002] Traditional prevention and control measures are based on real-time / planned operation mode for various safety and stability situational awareness and active defense measures. By using time-domain simulation methods and control measures sequencing, the correlation and nonlinearity between control measures are ignored. However, by pre-setting a measure table according to the instability mode, the problem of selecting control measures under different instability modes is solved, and an active defense strategy suitable for engineering is given.

[0003] Uncertainty is an inherent characteristic of new energy sources, whose guaranteed output is almost zero. As the proportion of new energy sources continues to increase, uncertainty has gradually shifted from quantitative to qualitative change. Taking the State Grid as an example, in 2019, the maximum daily power fluctuation of new energy sources within the State Grid's network exceeded 100 million kilowatts, and the daily fluctuation of some important transmission sections in the Northwest Power Grid reached tens of millions of kilowatts. On a minute-level time scale, the power change rate can reach about 1% of the installed capacity.

[0004] First, such extreme uncertainty makes it difficult for traditional operation and control strategies, primarily based on typical deterministic operating modes, to cover all high-risk scenarios. Second, the increasingly complex and volatile characteristics of power grid security and stability limit the utilization rate of transmission equipment based on single deterministic operating modes. Finally, considering the uncertainty of new energy sources, time-domain simulations using massive methods struggle to meet computational time requirements, increasing the dimensionality of control measure optimization and potentially rendering traditional methods unusable. Therefore, there is an urgent need to develop more scientific and rational preventive and control measures. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method, system, and storage medium for optimizing uncertain power grid prevention and control measures, which improves the power grid's ability to cope with uncertain risk scenarios and increases the utilization rate of transmission equipment.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] Firstly, a method for optimizing uncertain power grid prevention and control measures is provided, including: constructing an uncertainty domain of power grid operation mode; constructing a stability domain of power grid operation mode; constructing and solving a power grid prevention and control model based on the uncertainty domain of power grid operation mode and the stability domain of power grid operation mode to obtain power grid prevention and control measures; and performing time-domain simulation verification on the power grid prevention and control measures to obtain optimized uncertain power grid prevention and control measures.

[0008] Furthermore, the construction of the uncertainty domain of the power grid operation mode includes: obtaining the power output information of the power grid at the current moment, including: the current number of conventional generating units N in the power grid, and the power output P of conventional generating unit i in the power grid. i ,P i ≥0,,i=1,2....N, the current number of renewable energy generating units M in the power grid, and the power output P of renewable energy generating unit j in the power grid. j ,P j ≥0,,j=1,2....M; Obtain the predicted power output of the power grid at the next moment; Based on the current power output information and the predicted power output information at the next moment, construct the uncertainty domain of the power grid operation mode, including: calculating and generating the number N of power grid operation modes. G and the power grid operation mode k, k=1,2....N G All units output,

[0009]

[0010] Among them, P L2 P represents the upper limit of the power grid load forecast range. L1 P represents the lower limit of the power grid load forecast range. Lacc P represents the random precision of the power grid load. j2 P represents the upper limit of the predicted output range of the new energy generating unit j in the power grid. j1 P represents the lower limit of the predicted output range of the new energy generating unit j in the power grid. jacc Indicates the random precision of new energy sources in the power grid; based on the generated power grid N G The operating mode is used to obtain the output range of conventional power unit i in the power grid [P]. i1 ,P i2 ], Where k = 1, 2, ..., N G P iK This represents the output of conventional generating unit i in grid operation mode k.

[0011] Furthermore, the power grid operation mode k, k = 1, 2, ..., N G The calculation method for the output of all units includes:

[0012] 1-4-1) in [P L1 ,P L2 Randomly and uniformly generate grid load P within the range Lk ;

[0013] 1-4-2) in [P j1 ,P j2 The output P of the new energy generating unit j of the power grid is randomly and uniformly generated within the range. jk Then the total output of new energy units in the power grid

[0014] 1-4-3) Obtain the allowable output range of conventional generating unit i in the power grid [P] imin ,P imax The inertia M of conventional generating unit i in the power grid i ;

[0015] 1-4-4) Output P of conventional generating unit i in the power grid ik The calculation method is as follows:

[0016]

[0017] 1-4-5) If the output P of conventional unit i is ik <P imin (i∈A), where A is the set of conventional generators with output less than the set value, then P ik =P imin (i∈A), increase output

[0018] 1-4-6) If the output P of conventional unit i is ik >P imax (i∈B), where B is the set of conventional generators with output greater than the set value, then P ik =P imax (i∈B), reduce output

[0019] 1-4-7) Recalculate the conventional generating units of the power grid Output P ik The calculation method is as follows:

[0020]

[0021] Repeat steps 1-4-5), 1-4-6), and 1-4-7) until all units i in the non-grid conventional mode do not meet the conditions described in 1-4-5) and 1-4-6), and complete the output calculation for all units in grid operation mode k.

[0022] Furthermore, the construction of the power grid operation stability domain includes: constructing the output vector P of the power grid operation mode h. h =[P 1h ,P 2h ...P ih ...P Nh ,P 1h ,P 2h ...P jh ...P Mh ], Grid Operation Mode Matrix Among them, the power grid operation modes h = 1, 2, ..., N H N HThis represents the number of power grid operation modes over a one-year period, where P is the output of conventional unit i under power grid operation mode h. ih The output of the grid's new energy unit j is P. jh Construct a column vector of stability results for power grid fault f. Where f = 1, 2...F, F represents the number of power grid lines, and R... hf This represents the power angle stability result of the power grid operating mode h under power grid fault f; it constructs the power grid operating mode matrix S and the column vector R of the stability results under power grid fault f. f The mapping is specifically as follows: The SVM function from the sklearn library in Python is used to construct a mapping between the power grid operation mode matrix S and the stability results of the power grid fault f; the Kernel parameter uses poly, the gamma parameter uses auto, the degree value is 2, and other parameters are default. The stability SVM result R of the power grid fault f is... svmf =S rf ∑P i1 P i2 , where P i1 P i2 It provides power to both conventional and renewable energy generating units in the power grid; P i1 ,P i2 ∈{P1,P2,...,P i ,...,P N P1, P2..., P j ,...,P M}, S rf The parameters are calculated for the SVM function.

[0023] Furthermore, when the work angle is stable, the work angle stability result R hf =0, otherwise R hf =1.

[0024] Furthermore, the construction and solution of the power grid prevention and control model includes: constructing the power grid prevention and control objective function as follows:

[0025]

[0026] Among them, X i This indicates that the power output of conventional generating units i in the power grid is reduced, and k i k represents the power adjustment cost coefficient of conventional generating unit i in the power grid. i X i Represent the adjustment cost of conventional generating unit i in the power grid; construct the stability constraints as follows:

[0027] R svmf =S rf ∑((P α +x α )×(Pβ +x β ))≤0 (5)

[0028] Where α, β are the unit serial numbers, P α P β For the output of conventional or renewable energy units in the power grid, when it is a conventional unit, α and β are represented by the unit number i, α,β = i, P i ∈[P i1 ,P i2 ], x i =X i When the generator is a new energy unit, a and β are represented by the unit number j, a,β = j, P j ∈[P j1 ,P j2 ], x j =0; the power balance constraint is constructed as follows:

[0029]

[0030] Solve for the objective function of power grid prevention and control to obtain X. i The value of .

[0031] Furthermore, by calling the commercial software CPLEX to solve the objective function of power grid prevention and control, X was calculated. i The value of .

[0032] Furthermore, the time-domain simulation verification includes: generating the operating mode k after prevention and control. p Calculate the power grid operation mode k p SVM results R svmkf ; Regarding the power grid operation mode k p SVM results R svmkf Sort the data and then filter the top N from smallest to largest. C A power grid scenario, the power grid scenario including power grid operation mode k p 1. Grid fault f; 2. Calculate the stability reliability value of the grid scenario; 3. Modify the stability constraints based on the stability reliability value of the grid scenario. The modified stability constraints are as follows:

[0033] R svmf =S rf ∑((P i1 +x i1 )×(P i2 +x i2 ))≤ε f (7)

[0034] Where, ε f Let f represent the reliability value of the power grid fault; based on the modified stability constraints, solve for the power grid prevention and control objective function to obtain X. iThe value of is used to obtain optimized uncertain power grid prevention and control measures.

[0035] Furthermore, the stability reliability value of the power grid scenario is calculated, including: the stability reliability value of the power grid operation mode k. p 1. Perform time-domain simulation verification of power grid fault f; 2. If the power grid operation mode k p The time-domain verification of the power grid fault f is unstable, R svmkf Based on the stability assessment results at this time, obtain the stability reliability value ε. kf =R svmkf If the power grid operates in mode k p The stability of the power grid fault f in the time domain is verified, and the stability reliability value ε is obtained. kf =0; the reliability value ε of the power grid fault f. f =max(ε kf ).

[0036] Secondly, an optimization system for uncertain power grid prevention and control measures is provided, comprising: an uncertainty domain construction module for constructing an uncertainty domain of power grid operation mode; a stability domain construction module for constructing a stability domain of power grid operation; a power grid prevention and control model construction module for constructing and solving a power grid prevention and control model based on the uncertainty domain of power grid operation mode and the stability domain of power grid operation to obtain power grid prevention and control measures; and an optimization module for performing time-domain simulation verification of the power grid prevention and control measures to obtain optimized uncertain power grid prevention and control measures.

[0037] Thirdly, a computer-readable storage medium is provided, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed by a processor, it controls the device in which the storage medium is located to perform the method described in the first aspect.

[0038] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0039] (1) This invention constructs an uncertainty domain and a stability domain for power grid operation; constructs and solves a power grid prevention and control model based on the uncertainty domain and the stability domain; performs time-domain simulation verification on the power grid prevention and control model to obtain optimized uncertain power grid prevention and control measures, thereby improving the power grid's ability to cope with uncertain risk scenarios and increasing the utilization rate of transmission equipment.

[0040] (2) The present invention is based on a data-driven stability assessment method, which solves the problem of difficult power grid stability processing;

[0041] (3) This invention solves the problem of difficulty in solving control measures by constructing an optimization model for control measures;

[0042] (4) This invention solves the contradiction between computational efficiency and long computation time in massive operation mode by using time-domain simulation verification. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of the main process of an optimization method for uncertain power grid prevention and control measures provided in an embodiment of the present invention. Detailed Implementation

[0044] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0045] Example 1:

[0046] like Figure 1 As shown, an optimization method for uncertain power grid prevention and control measures includes: constructing an uncertainty domain of power grid operation mode; constructing a stability domain of power grid operation; constructing and solving a power grid prevention and control model based on the uncertainty domain and the stability domain of power grid operation mode; and performing time-domain simulation verification on the power grid prevention and control model to obtain optimized uncertain power grid prevention and control measures.

[0047] Step 1: Construct the uncertainty domain of power grid operation mode.

[0048] 1-1) Obtain the power output information of the power grid at the current moment.

[0049] Obtain the current number N of conventional generating units in the power grid, and the output P of conventional generating units i (i = 1, 2, ..., N). i (P i ≥0). Obtain the current number M of renewable energy generating units in the power grid, and the output P of renewable energy generating units j (j=1,2....M) in the power grid. j (P j ≥0). Then the total power generation of the power grid Total load of the power grid P L Total power generation P of grid units G If they are equal, then P L =P G .

[0050] 1-2) Obtain the predicted power output of the power grid at the next time point t (t = 15 min). Power grid load prediction range [P] L1 ,P L2 [P] Obtain the output prediction range of the new energy generating unit j in the power grid. j1 ,P j2 ].

[0051] Based on the power output information of the power grid at the current moment and the predicted power output information of the power grid at the next moment, an uncertainty domain of the power grid operation mode is constructed.

[0052] 1-3) Calculate the number N of power grid operation modes generated. G N G The calculation method is as follows:

[0053]

[0054] Among them, P L2 P represents the upper limit of the power grid load forecast range. L1 P represents the lower limit of the power grid load forecast range. Lacc P represents the random accuracy of power grid load, typically ranging from 100MW to 500MW. j2 P represents the upper limit of the predicted output range of the new energy generating unit j in the power grid. j1 P represents the lower limit of the predicted output range of the new energy generating unit j in the power grid. jacc This indicates the random precision of new energy generation in the power grid, and its value is generally between 0.5MW and 2MW. M represents the number of new energy generating units in the power grid.

[0055] 1-4) Generate the power grid operation mode k, k = 1, 2, ..., N G All generating units output power. The specific method is as follows:

[0056] 1-4-1) Randomly generate grid load P Lk P Lk In [P] L1 ,P L2 Randomly and uniformly generated within the range;

[0057] 1-4-2) Randomly generate the output P of the new energy generating unit j in the power grid. jk P jk In [P] j1 ,P j2 The energy is generated randomly and uniformly within the specified range. Therefore, the total output of the new energy source is...

[0058] 1-4-3) Obtain the allowable output range of conventional generating unit i in the power grid [P] imin ,P imax The inertia M of conventional generating unit i in the power grid i ;

[0059] 1-4-4) Output P of conventional generating unit i in the power grid ik The calculation method is as follows:

[0060]

[0061] 1-4-5) If the output P of conventional unit i is ik <P imin (i∈A), where A is the set of conventional generators with output less than the set value, then Pik =P imin (i∈A), increase output

[0062] 1-4-6) If the output P of conventional unit i is ik >P imax (i∈B), where B is the set of conventional generators with output greater than the set value, then P ik =P imax (i∈B), reduce output

[0063] 1-4-7) Recalculate the conventional generating units of the power grid Output P ik The calculation method is as follows:

[0064]

[0065] Repeat steps 1-4-5), 1-4-6), and 1-4-7) until all units i in the grid-free conventional generating unit do not meet the conditions described in steps 1-4-5) and 1-4-6), and complete the output calculation for all units in grid operation mode k;

[0066] 1-5) Calculate the output range of conventional generating unit i in the power grid. Based on the generated power grid N G The operating mode is used to obtain the output range of conventional power unit i in the power grid [P]. i1 ,P i2 ]. P i1 =min(P iK ), P i2 =max(P iK ), where k (k=1,2....N) G ).

[0067] Step 2: Construct the power grid operation stability domain.

[0068] 2-1) Obtain the power grid operation mode N for one year of power grid history. H There are several. Then the power grid operation mode h (h=1,2....N) H The output of conventional unit i is P. ih The power output P of the new energy generating unit j in the power grid jh Construct the output vector P of the power grid operating mode h. h =[P 1h ,P 2h ...P ih ...P Nh ,P 1h ,P 2h ...P jh ...P Mh ], Grid Operation Mode Matrix

[0069] 2-2) Given F power grid lines, there are F types of faulty power grid lines. Simulate and calculate the power angle stability of the power grid operating mode h under power grid fault f (f = 1, 2...F). The stability result R when the power angle is stable is... hf =0, otherwise R hf =1. Construct a column vector of stability results for grid fault f.

[0070] 2-3) Calculate the mapping between operating modes and stability. The SVM function from the sklearn library in Python is used to construct a mapping between the power grid operating mode matrix S and the stability results of power grid faults f. The Kernel parameter is set to poly, the gamma parameter to auto, the degree parameter to 2, and the other parameters are default.

[0071] Stability SVM results for grid fault f: R svmf =S rf ∑P i1 P i2 , where P i1 P i2 It provides power to both conventional and renewable energy generating units in the power grid. i1 ,P i2 ∈{P1,P2,...,P i ,...,P N P1, P2..., P j ,...,P M}, S r The parameters are calculated for the SVM function.

[0072] Step 3: Based on the uncertainty domain and stability domain of the power grid operation mode, construct the power grid prevention and control model and solve it.

[0073] 3-1) Construct the control objective function. The power output of conventional generating unit i in the power grid is reduced by adjustment X. i The adjustment cost for conventional generating unit i in the power grid is k. i X i The objective function for power grid prevention and control is:

[0074]

[0075] k i The power adjustment cost coefficient for conventional generating unit i in the power grid can be obtained from the operating unit of generating unit i.

[0076] 3-2) Constructing stability constraints. The stability constraint f is constructed as follows:

[0077] R svmf =S rf∑((P α +x α )×(P β +x β ))≤0 (5)

[0078] Where α, β are the unit serial numbers, P α P β For the output of conventional or renewable energy units in the power grid, when it is a conventional unit, α and β are represented by the unit number i, α,β = i, P i ∈[P i1 ,P i2 ], x i =X i When the generator is a new energy unit, a and β are represented by the unit number j, a,β = j, P j ∈[P j1 ,P j2 ], x j =0;

[0079] 3-3) Construct the power balance constraints as follows:

[0080]

[0081] 3-4) Use the commercial software CPLEX to solve for X. i The value of .

[0082] Step 4: Perform time-domain simulation verification on the power grid prevention and control model to obtain optimized uncertain power grid prevention and control measures.

[0083] 4-1) Generation of the operating mode after preventive control. The power grid operating mode k becomes the new power grid operating mode k after preventive control. p Calculate the power grid operation mode k p SVM results R svmkf .

[0084] 4-2) Sort and filter power grid scenarios (power grid operation mode k) p Power grid faults (f) are collectively referred to as power grid scenarios. For R... svmkf The results are sorted in ascending order, and the top N are selected. C A power grid scenario. N C The value is selected based on the computing power, and is generally within the range of [20, 200].

[0085] 4-3) Calculate the stability reliability value of the power grid scenario. For the power grid operation mode k... p The power grid fault f is verified using time-domain simulation. If the power grid operation mode k... p The power grid fault f is unstable in the time domain, and the stability reliability value ε is obtained. kf =Rsvmkf If the power grid operates in mode k p The stability of the power grid fault f in the time domain is verified, and the stability reliability value ε is obtained. kf =0.

[0086] 4-4) Calculate the confidence value ε of the power grid fault f. f =max(ε kf ).

[0087] 4-5) Modify the stability constraint in step 3-2). The stability constraint f is constructed as follows:

[0088] R svmf =S rf ∑((P i1 +x i1 )×(P i2 +x i2 ))≤ε f (7)

[0089] 4-6) Repeat step 3-4) to calculate X. i The value of is used to solve for the prevention and control measures.

[0090] Example 2:

[0091] Based on the method for optimizing uncertain power grid prevention and control measures described in Embodiment 1, this embodiment provides a system for optimizing uncertain power grid prevention and control measures, including:

[0092] The uncertainty domain construction module is used to construct the uncertainty domain of power grid operation.

[0093] The stability domain construction module is used to construct the stability domain for power grid operation.

[0094] The power grid prevention and control model construction module is used to construct and solve the power grid prevention and control model based on the uncertainty domain and stability domain of power grid operation.

[0095] The optimization module is used to perform time-domain simulation verification of the power grid prevention and control model, and to obtain optimized uncertain power grid prevention and control measures.

[0096] Example 3:

[0097] Based on the method for optimizing uncertain power grid prevention and control measures described in Embodiment 1, this embodiment provides a computer-readable storage medium, which includes a stored computer program. When the computer program is run by a processor, it controls the device where the storage medium is located to execute the method described in Embodiment 1.

[0098] Embodiments of this application may be provided as methods, systems, or computer program products. Therefore, this application may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application may take 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 code. The solutions in the embodiments of this application may be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0103] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for optimizing uncertain power grid prevention and control measures, characterized in that, include: Constructing the uncertainty domain of power grid operation modes; Construct the power grid operation stability domain; Based on the uncertainty domain and stability domain of power grid operation, a power grid prevention and control model is constructed and solved to obtain power grid prevention and control measures. Time-domain simulation verification of power grid prevention and control measures is performed to obtain optimized uncertain power grid prevention and control measures; The uncertainty domain of the power grid operation mode includes: Obtain the current power output information of the power grid, including: the current number of conventional generating units in the power grid. Conventional generating units in the power grid contribution , , The current number of new energy generating units in the power grid New energy generating units in power grid contribution , , ; Obtain forecast information on the power grid's output at the next moment; Based on the current power output information and the predicted power output information for the next moment, an uncertainty domain for power grid operation modes is constructed, including: calculating and generating the number of power grid operation modes. and power grid operation mode , All units output, （1） in, This indicates the upper limit of the power grid load forecast range. This indicates the lower limit of the power grid load forecast range. Indicates the random precision of power grid load. Indicates new energy generating units in the power grid The upper limit of the output prediction range, Indicates new energy generating units in the power grid The lower limit of the output prediction range, Indicates the random precision of new energy sources in the power grid; According to the generated power grid One operating mode, obtain the conventional generating units of the power grid Output range , , ,in, , Indicates the power grid operation mode Conventional power grid units contribution; The construction and solution of the power grid prevention and control model includes: The objective function for power grid prevention and control is constructed as follows: （4） in, Indicates conventional generating units in the power grid Adjust the power reduction. Indicates conventional generating units in the power grid The power adjustment cost coefficient, Indicates conventional generating units in the power grid Adjustment costs; The stability constraints are constructed as follows: （5） in, For unit serial number, , For the output of conventional generating units or new energy generating units in the power grid, when it is a conventional generating unit... Unit number express, , , When it is a new energy unit, Unit number express, , , ; The power balance constraints are constructed as follows: （6） Solving for the objective function of power grid prevention and control, we obtain... The value of .

2. The method for optimizing uncertain power grid prevention and control measures according to claim 1, characterized in that, Power grid operation mode The calculation method for the output of all units includes: 1-4-1) in Randomly and uniformly generate power grid load within the range ; 1-4-2) in Randomly and uniformly generate new energy generating units for the power grid within the specified range contribution Then the total output of new energy units in the power grid ; 1-4-3) Obtain information on conventional generating units in the power grid Permissible output range Conventional generating units in the power grid inertia ; 1-4-4) Conventional generating units in the power grid contribution The calculation method is as follows: （2） 1-4-5) If conventional units contribute , If the set value is a collection of conventional generating units with output less than the set value, then Increase output ; 1-4-6) If conventional units contribute , If the set value is a collection of conventional generating units, then Reduce output ; 1-4-7) Recalculate the conventional generating units of the power grid contribution The calculation method is as follows: （3） Repeat steps 1-4-5), 1-4-6), and 1-4-7) until the grid-connected conventional generating units are de-grided. None of the conditions described in 1-4-5) and 1-4-6) are met, thus completing the power grid operation mode. Calculate the output of all generating units.

3. The method for optimizing uncertain power grid prevention and control measures according to claim 2, characterized in that, The construction of the power grid operation stability domain includes: Constructing power grid operation mode Output vector Grid operation mode matrix Among them, power grid operation mode , This indicates the number of power grid operation modes over a one-year period. conventional units The output is New energy generating units in power grid The output is ; Constructing power grid faults Stability result column vector ,in, , Indicates the number of power grid lines. Indicates the power grid operation mode In power grid failure The results of the work angle stability; Constructing a power grid operation mode matrix and power grid failure Stability result column vector The mapping is specifically as follows: A power grid operation mode matrix is ​​constructed using the SVM function of the sklearn library in Python. and power grid failure Mapping of stability results; Kernel parameter uses poly, gamma parameter uses auto, degree is set to 2, and other parameters are default; power grid faults. Stability SVM results ,in , It provides power to both conventional and new energy generating units in the power grid; , The parameters are calculated for the SVM function.

4. The method for optimizing uncertain power grid prevention and control measures according to claim 3, characterized in that, When the angle of work is stable, the results of the angle of work stability ,otherwise .

5. The method for optimizing uncertain power grid prevention and control measures according to claim 3, characterized in that, By calling the commercial software CPLEX to solve the objective function of power grid prevention and control, the following was calculated: The value of .

6. The method for optimizing uncertain power grid prevention and control measures according to claim 3, characterized in that, The time-domain simulation verification includes: Operation mode after generating prevention and control Calculate the power grid operation mode SVM results ; Power grid operation mode SVM results Sort and filter from smallest to largest before proceeding. A power grid scenario, the power grid scenario including power grid operation mode Power grid faults ; Calculate the stability reliability value for the power grid scenario; The stability constraints are modified based on the stability reliability value of the power grid scenario. The modified stability constraints are as follows: （7） in, Indicates a power grid fault The credibility value; Based on the modified stability constraints, the objective function for power grid prevention and control is solved to obtain... The value of is used to obtain optimized uncertain power grid prevention and control measures.

7. The method for optimizing uncertain power grid prevention and control measures according to claim 6, characterized in that, Calculate the stability reliability value of the power grid scenario, including: Power grid operation mode Power grid faults Perform time-domain simulation verification; if the power grid operation mode Power grid faults Time-domain verification is unstable. Based on the stability assessment results at this time, obtain the stability reliability value. If the power grid operates in the following way Power grid faults Time-domain verification shows stability and a stable reliability value. ; Power grid fault Credibility value .

8. An optimization system for uncertain power grid prevention and control measures, characterized in that, include: The uncertainty domain construction module is used to construct the uncertainty domain of power grid operation. The stability domain construction module is used to construct the stability domain for power grid operation. The power grid prevention and control model construction module is used to construct and solve the power grid prevention and control model based on the uncertainty domain and stability domain of power grid operation mode, and obtain power grid prevention and control measures. The optimization module is used to perform time-domain simulation verification of power grid prevention and control measures to obtain optimized uncertain power grid prevention and control measures. The uncertainty domain of the power grid operation mode includes: Obtain the current power output information of the power grid, including: the current number of conventional generating units in the power grid. Conventional generating units in the power grid contribution , , The current number of new energy generating units in the power grid New energy generating units in power grid contribution , , ; Obtain forecast information on the power grid's output at the next moment; Based on the current power output information and the predicted power output information for the next moment, an uncertainty domain for power grid operation modes is constructed, including: calculating and generating the number of power grid operation modes. and power grid operation mode , All units output, （1） in, This indicates the upper limit of the power grid load forecast range. This indicates the lower limit of the power grid load forecast range. Indicates the random precision of power grid load. Indicates new energy generating units in the power grid The upper limit of the output prediction range, Indicates new energy generating units in the power grid The lower limit of the output prediction range, Indicates the random precision of new energy sources in the power grid; According to the generated power grid One operating mode, obtain the conventional generating units of the power grid Output range , , ,in, , Indicates the power grid operation mode Conventional power grid units contribution; The construction and solution of the power grid prevention and control model includes: The objective function for power grid prevention and control is constructed as follows: （4） in, Indicates conventional generating units in the power grid Adjust the power reduction. Indicates conventional generating units in the power grid The power adjustment cost coefficient, Indicates conventional generating units in the power grid Adjustment costs; The stability constraints are constructed as follows: （5） in, For unit serial number, , For the output of conventional generating units or new energy generating units in the power grid, when it is a conventional generating unit... Unit number express, , , When it is a new energy unit, Unit number express, , , ; The power balance constraints are constructed as follows: （6） Solving for the objective function of power grid prevention and control, we obtain... The value of .

9. The optimization system for uncertain power grid prevention and control measures according to claim 8, characterized in that, Power grid operation mode The calculation method for the output of all units includes: 1-4-1) in Randomly and uniformly generate power grid load within the range ; 1-4-2) in Randomly and uniformly generate new energy generating units for the power grid within the specified range contribution Then the total output of new energy units in the power grid ; 1-4-3) Obtain information on conventional generating units in the power grid Permissible output range Conventional generating units in the power grid inertia ; 1-4-4) Conventional generating units in the power grid contribution The calculation method is as follows: （2） 1-4-5) If conventional units contribute , If the set value is a collection of conventional generating units with output less than the set value, then Increase output ; 1-4-6) If conventional units contribute , If the set value is a collection of conventional generating units, then Reduce output ; 1-4-7) Recalculate the conventional generating units of the power grid contribution The calculation method is as follows: （3） Repeat steps 1-4-5), 1-4-6), and 1-4-7) until the grid-connected conventional generating units are de-grided. None of the conditions described in 1-4-5) and 1-4-6) are met, thus completing the power grid operation mode. Calculate the output of all generating units.

10. The optimization system for uncertain power grid prevention and control measures according to claim 9, characterized in that, The construction of the power grid operation stability domain includes: Constructing power grid operation mode Output vector Grid operation mode matrix Among them, power grid operation mode , This indicates the number of power grid operation modes over a one-year period. conventional units The output is New energy generating units in power grid The output is ; Constructing power grid faults Stability result column vector ,in, , Indicates the number of power grid lines. Indicates the power grid operation mode In power grid failure The results of the work angle stability; Constructing a power grid operation mode matrix and power grid failure Stability result column vector The mapping is specifically as follows: A power grid operation mode matrix is ​​constructed using the SVM function of the sklearn library in Python. and power grid failure Mapping of stability results; Kernel parameter uses poly, gamma parameter uses auto, degree is set to 2, and other parameters are default; power grid faults. Stability SVM results ,in , It provides power to both conventional and new energy generating units in the power grid; , The parameters are calculated for the SVM function.

11. The optimization system for uncertain power grid prevention and control measures according to claim 10, characterized in that, The time-domain simulation verification includes: Operation mode after generating prevention and control Calculate the power grid operation mode SVM results ; Power grid operation mode SVM results Sort and filter from smallest to largest before proceeding. A power grid scenario, the power grid scenario including power grid operation mode Power grid faults ; Calculate the stability reliability value for the power grid scenario; The stability constraints are modified based on the stability reliability value of the power grid scenario. The modified stability constraints are as follows: （7） in, Indicates a power grid fault The credibility value; Based on the modified stability constraints, the objective function for power grid prevention and control is solved to obtain... The value of is used to obtain optimized uncertain power grid prevention and control measures.

12. The optimization system for uncertain power grid prevention and control measures according to claim 11, characterized in that, Calculate the stability reliability value of the power grid scenario, including: Power grid operation mode Power grid faults Perform time-domain simulation verification; if the power grid operation mode Power grid faults Time-domain verification is unstable. Based on the stability assessment results at this time, obtain the stability reliability value. If the power grid operates in the following way Power grid faults Time-domain verification shows stability and a stable reliability value. ; Power grid fault Credibility value .

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed by a processor, it controls the device in which the storage medium is located to perform the method according to any one of claims 1 to 7.

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