High-proportion new energy power grid reliability evaluation method and system considering AGC system operation risk

Abstract

The invention discloses a high-proportion new energy power grid reliability evaluation method and system considering AGC system operation risks, and the method comprises the steps: building a power grid fault probability model through employing the fault probability of an AGC function, the fault probability of a dispatching instruction, the fault probability of a line, the fault probability of a new energy unit, and the fault probability of a conventional unit; iteratively solving a power flow model, a power flow constraint condition and an operation risk constraint of an AGC control unit of the high-proportion new energy power grid in different fault scenes to obtain a minimum load reduction amount of the power grid in each fault scene; based on the minimum load reduction amount of the power grid under all random faults, calculating a variance coefficient expected by a reliability index of the high-proportion new energy power grid; and when the variance coefficient is not greater than 0.01, quantitatively evaluating the reliability of the high-proportion new energy power grid under the superposition of the operation risk of the AGC system and the operation risk of the power grid equipment by taking the expected value of power shortage as a reliability evaluation result of the high-proportion new energy power grid considering the operation risk of the AGC system.

Description

Technical Field

[0001] The present invention relates to the technical field of new power systems, and in particular to a reliability assessment method and system for a high-proportion new energy power grid taking into account the operating risks of an automatic generation control (AGC) system. Background Art

[0002] The control system of power dispatching is of great significance to the safe and stable operation of the power grid. The defects and risks of the control system will directly lead to large power shortages in the power grid, large fluctuations in the power of the interconnection lines, frequency anomalies, DC blocking, voltage collapse and other events, which seriously affect the safe and stable operation of the physical power grid. In the actual operation of the power grid, there have been many accidents caused by the failure of the AGC control link of the automatic control system and human errors that led to the wrong system command values, resulting in power grid operation risks. First, due to defects in the AGC system software's anti-error strategy, the AGC of a regional power grid erroneously lowered the unit output for more than an hour, forcing another connected regional power grid to increase its output, causing significant fluctuations in the UHV line current and the power grid frequency to remain below 50 Hz, posing a huge safety risk to the power grid operation; second, due to defects in the AGC anti-error strategy and the lack of necessary control measures for software upgrades, during the AGC software upgrade process, the AGC issued erroneous control instructions to the provincial power grid's new energy plants and stations, causing the new energy power generation output to drop rapidly by more than 1 million kilowatts, and the regional AC power grid frequency where the provincial power grid is located fell to a minimum of 49.75 Hz; third, due to operational errors and unreasonable AGC adjustment limit settings, the new energy power generation output suddenly increased by more than 2.5 million kilowatts, and the power grid frequency exceeded the limit by a large margin.

[0003] The above accidents all show that while the AGC system supports the safe and stable operation of the power grid, it also introduces new uncertainties. The power grid equipment and information system influence each other. Faults occurring in a single system will couple and spread, seriously threatening the safety of the power system. Therefore, it is urgent to carry out reliability assessment research on high-proportion renewable energy power grids that consider the automatic power control risk model.

[0004] In the existing technology, the reliability assessment of power grids with a high proportion of renewable energy currently focuses on the operating risks of power grid equipment (such as risks of power grid, renewable energy, energy storage, generators, etc.), and it is difficult to reveal the operating risks of various types of automatic control system AGC faults and the superimposed risks induced by their interaction with the operating risks of power grid equipment. In particular, there are relatively few studies on the risk modeling of automatic control system AGC and the reliability assessment of the combined failures of automatic control system AGC operating risks and power grid equipment operating risks. Summary of the invention

[0005] In order to address the deficiencies in the prior art, the present invention provides a reliability assessment method and system for a high-proportion new energy power grid taking into account the operating risks of an AGC system, proposes a modeling method for operating risks of various faults in the AGC system, takes into account the superimposed risks induced by the interactive impact of the operating risks of the AGC system and the operating risks of power grid equipment, and quantitatively assesses the degree of reliability degradation of a high-proportion new energy power grid caused by the superimposed risks induced by the interactive impact of the operating risks of the AGC system and the operating risks of power grid equipment, thereby providing a technical basis for assessing the reliability of a high-proportion new energy power grid.

[0006] The present invention adopts the following technical solution.

[0007] The present invention proposes a reliability assessment method for a high-proportion new energy power grid taking into account the operational risk of an AGC system, comprising:

[0008] Obtain the failure rate and repair rate of the AGC function in the AGC control unit, establish an AGC function risk model for the AGC control unit to determine the failure probability of the AGC function; obtain the deviation between the power regulation command issued by the AGC system to the AGC control unit and the power regulation amount, and establish a dispatch instruction risk model for the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction; obtain the failure rate and repair rate of the line, establish a line operation risk model to determine the failure probability of the line; obtain the failure rate and repair rate of the new energy unit, establish a new energy unit operation risk model to determine the failure probability of the new energy unit; obtain the failure rate and repair rate of the conventional unit, establish a conventional unit operation risk model to determine the failure probability of the conventional unit; establish a power grid failure probability model using the failure probability of the AGC function, the failure probability of the dispatch instruction, the failure probability of the line, the failure probability of the new energy unit, and the failure probability of the conventional unit;

[0009] A sampling method is used to generate different fault scenarios of a high-proportion new energy power grid; based on the power grid fault probability model, the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the AGC control unit; based on the state auxiliary variables of the AGC control unit, the operation risk constraints of the AGC control unit under different fault scenarios are established; the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the equipment; based on the state auxiliary variables of the equipment, the power flow model and power flow constraint conditions of a high-proportion new energy power grid considering the operation risk of the AGC system are constructed;

[0010] The power flow model, power flow constraints and operation risk constraints of the AGC-controlled units under different fault scenarios are iteratively solved to obtain the minimum load reduction of the power grid under each fault scenario. The expected variance coefficient of the reliability index of the high-proportion new energy power grid is calculated based on the minimum load reduction of the power grid under all random faults. When the variance coefficient β≤0.01, the expected value of power shortage is used as the reliability assessment result of the high-proportion new energy power grid considering the operation risk of the AGC system.

[0011] Preferably, the AGC function risk model of the AGC control unit includes the failure probability and normal probability of the AGC function, which respectively satisfy the following relations:

[0012]

[0013]

[0014] In the formula, and They represent the failure probability and normal probability of the AGC function of AGC control unit k, and They represent the failure rate and repair rate of the AGC function of AGC control unit k, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in operation state, k∈n AGC , n AGC represents the set of AGC control units, → represents the mapping relationship between probability and state;

[0015] Based on the AGC function risk model of the AGC control unit, the failure probability of the AGC function is determined as follows:

[0016]

[0017] Preferably, the power adjustment command value sent by the AGC system to the AGC control unit and the power adjustment amount of the AGC control unit are obtained, and the deviation between the power adjustment command value and the power adjustment amount is determined based on the power adjustment state of the AGC control unit, satisfying the following relationship:

[0018]

[0019] In the formula, represents the power adjustment command value sent by the AGC system to the AGC control unit k from time τ = 1 to time τ = t, It represents the power regulation of AGC control unit k, It indicates the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation value. represents the power linear regulation rate of AGC control unit k at time τ, It represents the power regulation state identification variable of the AGC controlled unit k at time τ. A value of 1 indicates that the unit increases its output, a value of 0 indicates that the unit operates smoothly, and a value of -1 indicates that the unit reduces its output.

[0020] Preferably, a deviation is established obey The probability distribution of satisfies the following relationship:

[0021]

[0022] In the formula, is the standard deviation of the normal distribution;

[0023] Using the probability distribution of deviation and the power adjustment amount, a scheduling instruction risk model is established, including the failure probability and normal probability of the scheduling instruction, which respectively satisfy the following relationships:

[0024]

[0025]

[0026] In the formula, and The failure probability and normal probability of the dispatching instruction of AGC control unit k respectively;

[0027] Based on the dispatch instruction risk model of the AGC control unit, the failure probability of the dispatch instruction is determined as

[0028] Preferably, the line operation risk model includes the failure probability and normal probability of the line, which respectively satisfy the following relationship:

[0029]

[0030]

[0031] In the formula, and They represent the failure probability and normal probability of line ll′ respectively, and They represent the failure rate and repair rate of line ll′ respectively, Indicates that line ll′ belongs to line set l B , Auxiliary variable representing the state of line ll′, 0 represents a fault state, 1 represents a running state, → represents the mapping relationship between probability and state;

[0032] Based on the line operation risk model, the failure probability of the line is determined as

[0033] Preferably, the new energy unit operation risk model includes the failure probability and normal probability of the new energy unit, which respectively satisfy the following relationship:

[0034]

[0035]

[0036] In the formula, and They represent the failure probability and normal probability of the new energy unit i respectively, and They represent the failure rate and repair rate of new energy unit i respectively, Indicates that new energy unit i belongs to new energy unit set n RE , The auxiliary variable representing the state of the new energy unit i, 0 represents a fault state, 1 represents an operating state, → represents the mapping relationship between probability and state;

[0037] Based on the operation risk model of new energy units, the failure probability of new energy units is determined as follows:

[0038] Preferably, the conventional unit operation risk model includes the failure probability and normal probability of the conventional unit, which respectively satisfy the following relationship:

[0039]

[0040]

[0041] In the formula, and represent the failure probability and normal probability of conventional unit j respectively, and represent the failure rate and repair rate of conventional unit j respectively, Indicates that conventional unit j belongs to conventional unit set n G , represents the state auxiliary variable of conventional unit j, 0 represents the fault state, 1 represents the running state, → represents the mapping relationship between probability and state;

[0042] Based on the conventional unit operation risk model, the failure probability of the conventional unit is determined as

[0043] Preferably, the power grid failure probability model satisfies the following relationship:

[0044]

[0045] In the formula, δsys represents the probability of power grid failure, represents the failure probability of the AGC function of AGC control unit k, represents the failure probability of the dispatch instruction of AGC control unit k, represents the failure probability of transmission line ll′, represents the failure probability of new energy unit i, represents the failure probability of conventional unit j, → represents the mapping relationship between probability and state, x sys For power grid failure events, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in running state, It indicates the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation value. Auxiliary variable representing the state of transmission line ll′, 0 means it is in fault state, 1 means it is in operation state, Auxiliary variable representing the state of new energy unit i, 0 means it is in fault state, 1 means it is in operation state, Auxiliary variable representing the state of conventional unit j, 0 indicates a fault state, and 1 indicates an operating state;

[0046] Among them, k∈n AGC , n AGC represents the set of AGC control units, i∈n RE , n RE Represents the set of new energy units, j∈n G , n G represents a set of conventional units, satisfying n AGC =n RE ∪n G .

[0047] Preferably, the operating risk constraint of the AGC control unit in a single fault scenario satisfies the following relationship:

[0048]

[0049]

[0050] In the formula, and They represent the lower and upper limits of the adjustable capacity of AGC control unit k, and They represent the minimum and maximum output limits of AGC control unit k, respectively. represents the power linear regulation rate of AGC control unit k at time τ, It represents the power regulation state identification variable of the AGC control unit k at time τ. 1 means the unit increases its output, 0 means the unit runs smoothly, and -1 means the unit reduces its output. It represents the power adjustment command value sent by the AGC system to the AGC control unit k from the time τ=1 to the time τ=t.

[0051] Preferably, the power flow model of the high-proportion new energy grid includes:

[0052] 1) System power balance model satisfies the following relationship:

[0053]

[0054] In the formula, is the power of conventional unit j at time τ, is the power of new energy unit i at time τ, is the power of AGC controlled unit k at time τ, is the power of load node m at time τ, is the load reduction amount of load node m at time τ;

[0055] 2) Node power balance constraint, satisfying the following relationship:

[0056]

[0057] In the formula, and They represent the power flowing from node l′ to node l and from node l to node l′ at time τ, l′∈B l Indicates that node l′ belongs to the set of nodes directly connected to node l.

[0058] Preferably, the power flow constraints of a high-proportion new energy grid include:

[0059] 1) Line flow constraints satisfy the following relationship:

[0060]

[0061] In the formula, B ll′ represents the mutual admittance of line ll′, δ l,τ and δ l′,τ They represent the voltage phase angles of node l and node l′ at time τ, Auxiliary variable representing the state of line ll′, 0 represents a fault state, 1 represents a running state, and M represents an arbitrarily large (not infinite) positive number;

[0062] 2) Line transmission capacity constraints satisfy the following relationship:

[0063]

[0064] In the formula, represents the maximum transmission capacity of line ll′;

[0065] 3) Output constraints of conventional units satisfy the following relationship:

[0066]

[0067] In the formula, and Respectively represent the maximum output and minimum output of conventional unit j;

[0068] 4) Load reduction constraints satisfy the following relationship:

[0069]

[0070] 5) The output constraint of new energy units satisfies the following relationship:

[0071]

[0072] In the formula, represents the maximum output of new energy unit i at time τ;

[0073] 6) Node angle constraint, satisfying the following relationship:

[0074] -θ max ≤θ τ ≤θ max

[0075]

[0076] In the formula, θ max and θ τ They represent the maximum voltage phase angle of the grid node and the voltage phase angle at time τ, respectively. Represents the voltage phase angle reference value at time τ.

[0077] Preferably, the minimum load reduction of a high-proportion new energy grid in a single fault scenario satisfies the following relationship:

[0078]

[0079] In the formula, is the power grid fault event corresponding to fault scenario e The minimum load reduction caused by is the load reduction amount of load node m at time τ, is the load reduction of all load nodes from time τ = 1 to time τ = t under fault scenario e, ML is the total number of load nodes.

[0080] Preferably, the expected variance coefficient of the reliability indicator satisfies the following relationship:

[0081]

[0082] Where β is the variance coefficient of the expected value of power shortage, E is the total number of fault scenarios, is the expected value of power shortage,

[0083] The present invention also proposes a high-proportion new energy power grid reliability assessment system taking into account the AGC system operation risk, comprising:

[0084] A power grid fault probability model establishment module is used to obtain the failure rate and repair rate of the AGC function in the AGC control unit, establish the AGC function risk model of the AGC control unit to determine the failure probability of the AGC function; obtain the deviation between the power regulation command issued by the AGC system to the AGC control unit and the power regulation amount, and establish the dispatch instruction risk model of the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction; obtain the failure rate and repair rate of the line, establish the line operation risk model to determine the failure probability of the line; obtain the failure rate and repair rate of the new energy unit, establish the new energy unit operation risk model to determine the failure probability of the new energy unit; obtain the failure rate and repair rate of the conventional unit, establish the conventional unit operation risk model to determine the failure probability of the conventional unit; establish a power grid failure probability model using the failure probability of the AGC function, the failure probability of the dispatch instruction, the failure probability of the line, the failure probability of the new energy unit and the failure probability of the conventional unit;

[0085] The power grid model and constraint generation module is used to generate different fault scenarios of a high-proportion new energy power grid by using a sampling method; based on the power grid fault probability model, the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the AGC control unit; based on the state auxiliary variables of the AGC control unit, the operation risk constraints of the AGC control unit under different fault scenarios are established; the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the equipment; based on the state auxiliary variables of the equipment, the power flow model and power flow constraint conditions of the high-proportion new energy power grid considering the operation risk of the AGC system are constructed;

[0086] The power grid reliability assessment module is used to iteratively solve the power flow model, power flow constraints and operation risk constraints of the AGC control unit of the high-proportion renewable energy power grid under different fault scenarios, and obtain the minimum load reduction of the power grid under each fault scenario; based on the minimum load reduction of the power grid under all random faults, the expected variance coefficient of the reliability index of the high-proportion renewable energy power grid is calculated; when the variance coefficient β≤0.01, the expected value of power shortage is used as the reliability assessment result of the high-proportion renewable energy power grid considering the operation risk of the AGC system.

[0087] A terminal comprises a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0088] A computer-readable storage medium stores a computer program, which implements the steps of the method when executed by a processor.

[0089] The beneficial effects of the present invention are that, compared with the prior art, at least the method proposed in the present invention improves the traditional reliability assessment method for a high-proportion new energy power grid, proposes a modeling method for the operation risks of various types of faults in the AGC system, takes into account the superimposed risks induced by the interactive impact of the operation risks of various types of faults in the AGC system and the operation risks of the power grid equipment, quantitatively assesses the degree of reliability reduction of the high-proportion new energy power grid caused by the operation risks after the superposition of the operation risks of the AGC system and the operation risks of the power grid equipment, and provides a technical basis for assessing the reliability of a high-proportion new energy power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] Figure 1 It is a specific flow chart of the reliability assessment method of a high-proportion new energy power grid considering the operation risk of the AGC system established by the present invention;

[0091] Figure 2 It is a schematic diagram of the grid structure of an actual example system in an embodiment of the present invention. DETAILED DESCRIPTION

[0092] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0093] In the prior art, the reliability assessment of a high-proportion new energy power grid is only modeled from the physical level of the grid equipment or the operating risk of the generator set, and only focuses on the physical level of the operating risk; however, the prior art does not consider the AGC system operating risk that often occurs in practice and causes consequences that are far more serious than the physical equipment operating risk. Therefore, the present invention proposes a reliability assessment method for a high-proportion new energy power grid that takes into account the operating risk of the AGC system. The equipment of the high-proportion new energy power grid includes: conventional generator sets, new energy generator sets, AGC control units and transmission lines; the AGC system is deployed on the control platform of the power grid dispatching center, which is responsible for managing the decentralized AGC control units, and the AGC control units include conventional generator sets controlled by AGC and new energy generator sets controlled by AGC.

[0094] The present invention proposes a reliability assessment method for a high-proportion renewable energy power grid that takes into account the operational risk of the AGC system. Figure 1 As shown, including:

[0095] Step 1: Obtain the failure rate and repair rate of the AGC function in the AGC control unit, and establish an AGC function risk model of the AGC control unit to determine the failure probability of the AGC function.

[0096] Since the AGC controlled units include conventional generator sets controlled by AGC and new energy generator sets controlled by AGC, when conducting reliability assessment of a high-proportion new energy power grid considering the operating risks of the AGC system, an operating risk model that characterizes the AGC control function in the AGC controlled units is separately established, thereby achieving decoupling of the unit operating risk and the AGC control function operating risk. When considering a single random failure, the corresponding load reduction amount is determined based on the unit failure probability and the AGC function failure probability, respectively, thereby improving the accuracy of the load reduction amount under a single random failure and being able to more accurately assess the reliability of the power grid.

[0097] Specifically, the AGC function risk model of the AGC control unit includes the failure probability and normal probability of the AGC function, which respectively satisfy the following relations:

[0098]

[0099]

[0100] In the formula, and They represent the failure probability and normal probability of the AGC function of the AGC control unit k, respectively, and constitute the AGC function risk model. and They represent the failure rate and repair rate of the AGC function of AGC control unit k, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in operation state, k∈n AGC , n AGC Represents the AGC control unit set;

[0101] Based on the AGC function risk model of the AGC control unit, the failure probability of the AGC function is determined as follows:

[0102]

[0103] Step 2: Obtain the deviation between the power regulation command value sent by the AGC system to the AGC control unit and the power regulation amount, and establish a dispatch instruction risk model for the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction.

[0104] Specifically, during the control period (from time τ=1 to time τ=t), the AGC system sends a power adjustment command to the AGC control unit. Due to the existence of various unknown operating risks of the AGC system, there is an error between the power adjustment command issued and the power adjustment command calculated by the controller. The deviation between the power adjustment command issued and the actual power adjustment amount of the AGC control unit caused by the error will have an impact on the reliability of the power grid. By determining the failure probability of the AGC system dispatching instruction through this deviation, the load reduction caused by the dispatching instruction can be accurately evaluated, which is more suitable for reliability assessment scenarios of power grids with a high proportion of AGC systems.

[0105] Specifically, step 2 includes:

[0106] Step 2.1, obtain the power adjustment command value issued by the AGC system to the AGC control unit and the power adjustment amount of the AGC control unit, and determine the deviation between the power adjustment command value issued and the power adjustment amount based on the power adjustment state of the AGC control unit, satisfying the following relationship:

[0107]

[0108] In the formula, represents the power adjustment command value sent by the AGC system to the AGC control unit k from time τ = 1 to time τ = t, It represents the power regulation of AGC control unit k, It indicates the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation value. represents the power linear regulation rate of AGC control unit k at time τ, The power regulation state identification variable of the AGC controlled unit k at time τ, 1 indicates that the unit increases its output, 0 indicates that the unit operates smoothly, and -1 indicates that the unit decreases its output;

[0109] Step 2.2, Establish bias obey The probability distribution of satisfies the following relationship:

[0110]

[0111] In the formula, is the standard deviation of the normal distribution;

[0112] Step 2.3, using the probability distribution of deviation and the power adjustment amount, establish a scheduling instruction risk model, including the failure probability and normal probability of the scheduling instruction, which respectively satisfy the following relationship:

[0113]

[0114]

[0115] In the formula, and The failure probability and normal probability of the dispatching instruction of AGC control unit k respectively;

[0116] Based on the dispatch instruction risk model of the AGC control unit, the failure probability of the dispatch instruction is determined as

[0117] Step 3: Obtain the failure rate and repair rate of the line, and establish a line operation risk model to determine the failure probability of the line.

[0118] Specifically, the line operation risk model includes the failure probability and normal probability of the line, which respectively satisfy the following relationships:

[0119]

[0120]

[0121] In the formula, and They represent the failure probability and normal probability of line ll′ respectively, and They represent the failure rate and repair rate of line ll′ respectively, Indicates that line ll′ belongs to line set l B , Auxiliary variable representing the state of transmission line ll′, 0 indicates a fault state, and 1 indicates an operating state;

[0122] Based on the line operation risk model, the failure probability of the line is determined as

[0123] Step 4, obtain the failure rate and repair rate of the new energy unit, and establish a new energy unit operation risk model to determine the failure probability of the new energy unit.

[0124] Specifically, the operation risk model of new energy units includes the failure probability and normal probability of new energy units, which respectively satisfy the following relationships:

[0125]

[0126]

[0127] In the formula, and They represent the failure probability and normal probability of the new energy unit i respectively, and They represent the failure rate and repair rate of new energy unit i respectively, Indicates that new energy unit i belongs to new energy unit set n RE , Auxiliary variable representing the state of new energy unit i, 0 means it is in a fault state, and 1 means it is in a running state;

[0128] Based on the operation risk model of new energy units, the failure probability of new energy units is determined as follows:

[0129] Step 5, obtain the failure rate and repair rate of conventional units, and establish a conventional unit operation risk model to determine the failure probability of conventional units.

[0130] Specifically, the conventional unit operation risk model includes the failure probability and normal probability of the conventional unit, which respectively satisfy the following relationships:

[0131]

[0132]

[0133] In the formula, and represent the failure probability and normal probability of conventional unit j respectively, and represent the failure rate and repair rate of conventional unit j respectively, Indicates that conventional unit j belongs to conventional unit set n G , Auxiliary variable representing the state of conventional unit j, 0 indicates a fault state, and 1 indicates an operating state;

[0134] Based on the conventional unit operation risk model, the failure probability of the conventional unit is determined as

[0135] In the present invention, for the new energy units and conventional units controlled by AGC, the failure probability of the AGC function related to the AGC system and the failure probability of the dispatching instruction are separated, so that the failure probability of the new energy units and the conventional units can highlight the impact of the AGC system operation risk on the reliability of the power grid on the basis of using the relevant data of the non-AGC units.

[0136] Step 6, using the failure probability of the AGC function, the failure probability of the dispatching instruction, the failure probability of the line, the failure probability of the new energy unit and the failure probability of the conventional unit, a power grid failure probability model is established;

[0137] The power grid failure probability model satisfies the following relationship:

[0138]

[0139] In the formula, δ sys represents the probability of power grid failure, → represents the mapping relationship between probability and state, x sys For power grid failure events, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in running state, It represents the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation amount.

[0140] Among them, k∈n AGC , n AGC represents the set of AGC control units, i∈n RE , n RE Represents the set of new energy units, j∈n G , n G represents a set of conventional units, satisfying n AGC =n RE ∪n G ;

[0141] At present, all new energy units and conventional thermal power units are included in the management and control scope of the provincial AGC control system. Through the provincial AGC control system, dispatching can achieve precise AGC control of all new energy units and thermal power units. At the same time, with the increase of energy storage devices, energy storage devices are also gradually included in the provincial AGC control system.

[0142] The present invention further constructs a random failure probability model of the operation risk of the AGC control system on the basis of the random failure probability model of the operation risk of the power grid equipment or the generator set at the traditional physical level, introduces the operation risk of the AGC control system into the problem of reliability assessment of the physical equipment of the traditional power grid, and takes the influence of the AGC control system on the output and start-up and shutdown of the generator set of the traditional power grid as the interaction point at the physical-information level. The influence of the operation risk of the AGC control system on the reliability of the original power grid system at the physical level is analyzed, so as to promote the power grid to continuously improve the reliability of the information system and control system.

[0143] Step 7, using a sampling method to generate different fault scenarios of a high-proportion new energy power grid; based on a power grid fault probability model, mapping the generated different fault scenarios into power grid fault events to obtain state auxiliary variables of the AGC control unit; based on the state auxiliary variables of the AGC control unit, establishing the operation risk constraints of the AGC control unit under different fault scenarios;

[0144] The operating risk constraint of the AGC control unit under a single fault scenario satisfies the following relationship:

[0145]

[0146]

[0147] In the formula, and They represent the lower and upper limits of the adjustable capacity of AGC control unit k, and They represent the minimum and maximum output limits of AGC control unit k, respectively. Auxiliary variable representing the state of AGC control unit k. If it is 0, it means it is in a fault state, and if it is 1, it means it is in an operating state.

[0148] represents the power linear regulation rate of AGC control unit k at time τ, The power regulation state identification variable of the AGC controlled unit k at time τ, 1 indicates that the unit increases its output, 0 indicates that the unit operates smoothly, and -1 indicates that the unit decreases its output;

[0149] In the embodiment, after a single fault scenario of a high-proportion new energy power grid is generated by sampling based on a power grid failure probability model, the operating risk constraint of the AGC control unit in the single fault scenario is an operating constraint condition that considers the superposition of the operating risk of the AGC system and the risk of the power grid equipment after a single random fault; through the operating risk constraint of the AGC control unit in the single fault scenario, the operating risk of the AGC system (failure probability of the AGC function, failure probability of the dispatching instruction) is introduced into the subsequent power flow calculation.

[0150] Step 8: Based on the power grid fault probability model, the generated different fault scenarios are mapped into power grid fault events to obtain the state auxiliary variables of the equipment; based on the state auxiliary variables of the equipment, a power flow model and power flow constraint conditions of a high-proportion new energy power grid considering the operation risk of the AGC system are constructed;

[0151] The power flow model of high-proportion renewable energy grid includes:

[0152] 1) System power balance model satisfies the following relationship:

[0153]

[0154] In the formula, is the power of conventional unit j at time τ, is the power of new energy unit i at time τ, is the power of AGC controlled unit k at time τ, is the power of load node m at time τ, is the load reduction amount of load node m at time τ;

[0155] 2) Node power balance constraint, satisfying the following relationship:

[0156]

[0157] In the formula, and They represent the power flowing from node l′ to node l and from node l to node l′ at time τ, l′∈B l Indicates that node l′ belongs to the set of nodes directly connected to node l;

[0158] The power flow constraints of a high-proportion renewable energy grid include:

[0159] 1) Line flow constraints satisfy the following relationship:

[0160]

[0161] In the formula, B ll′ represents the mutual admittance of line ll′, δ l,τ and δ l′,τ They represent the voltage phase angles of node l and node l′ at time τ, Auxiliary variable representing the state of line ll′, 0 represents a fault state, 1 represents a running state, and M represents an arbitrarily large (not infinite) positive number;

[0162] 2) Line transmission capacity constraints satisfy the following relationship:

[0163]

[0164] In the formula, represents the maximum transmission capacity of line ll′;

[0165] When iteratively optimizing the objective function, the state auxiliary variable of line ll′ is used The mapping of line power flow constraints, line transmission capacity constraints and line operation risk models is realized;

[0166] 3) Output constraints of conventional units satisfy the following relationship:

[0167]

[0168] In the formula, and Respectively represent the maximum output and minimum output of conventional unit j;

[0169] When iteratively optimizing the objective function, the state auxiliary variable of conventional unit j is used. The mapping between the output constraints of conventional units and the operating risk model of conventional units is realized;

[0170] 4) Load reduction constraints satisfy the following relationship:

[0171]

[0172] 5) The output constraint of new energy units satisfies the following relationship:

[0173]

[0174] In the formula, represents the maximum output of new energy unit i at time τ;

[0175] When iteratively optimizing the objective function, the state auxiliary variable of the new energy unit i is used The mapping between the output constraints of new energy units and the operating risk model of new energy units has been realized;

[0176] 6) Node angle constraint, satisfying the following relationship:

[0177] -θ max ≤θ τ ≤θ max

[0178]

[0179] In the formula, θ max and θ τ They represent the maximum voltage phase angle of the grid node and the voltage phase angle at time τ, respectively. Represents the voltage phase angle reference value at time τ.

[0180] Step 9, iteratively solving the power flow model, power flow constraint conditions and operation risk constraint of the AGC control unit of the high-proportion new energy power grid under different fault scenarios, and obtaining the minimum load reduction amount of the power grid under each fault scenario;

[0181] The minimum load reduction of a high-proportion new energy grid under a single fault scenario satisfies the following relationship:

[0182]

[0183] In the formula, is the power grid fault event corresponding to fault scenario e The minimum load reduction caused by is the load reduction amount of load node m at time τ, is the load reduction of all load nodes from time τ = 1 to time τ = t under fault scenario e, M L is the total number of load nodes.

[0184] Step 10, based on the minimum load reduction of the power grid under all random faults, calculate the expected variance coefficient of the reliability index of the high-proportion new energy power grid, satisfying the following relationship:

[0185]

[0186] Where β is the variance coefficient of the expected value of power shortage, E is the total number of fault scenarios, is the expected value of power shortage,

[0187] When the variance coefficient β≤0.01, the expected value of power shortage As a reliability assessment result of a high proportion of renewable energy power grid considering the operating risks of the AGC system.

[0188] by Figure 2 Taking the actual simulation system shown in the figure as an example, the implementation process of the high-proportion new energy power grid reliability assessment method considering the operation risk of the AGC system is as follows:

[0189] 1. Random fault sampling generation of high proportion of new energy power grid

[0190] For a certain actual high-proportion new energy power grid, its structure diagram is as follows Figure 2As shown, the load at Bus17 in the IEEE-RTS24 node system is converted into a tie line node with the external network, and the conventional generators at Bus1 and Bus2 in the IEEE-RTS24 node system are converted into new energy nodes. Based on the failure rate of each component in the system, the Monte Carlo module of Matlab software is used to generate 10,000 random fault samples of a high-proportion new energy power grid, and the components and corresponding failure rates of each random fault in the high-proportion new energy power grid are determined. Here, the operational risk model of the failure of the AGC system control link, the operational risk model of the AGC system command value being issued incorrectly due to human error, the risk of single first-order to third-order fault forms such as line faults and unit faults, and the risk of second-order to third-order fault superposition forms of various types of faults are considered.

[0191] 2. Construct and solve the optimal power flow model for reliability assessment of high-proportion renewable energy power grid under single random fault

[0192] For an actual high-proportion renewable energy power grid, based on the single fault form obtained by sampling, the Matlab software YALMIP toolkit is used to build the optimal power flow model program for reliability assessment of high-proportion renewable energy power grid under a single random fault. The IPOPT solver is called to solve the optimal power flow model of the high-proportion renewable energy power grid considering the operation risk of the AGC system after the e-th random fault, and the minimum load reduction under the e-th random fault is obtained.

[0193] 3. Obtain reliability assessment results of a high-proportion new energy grid taking into account the operating risks of the AGC system

[0194] Based on the minimum load reduction under all random faults, the expected estimated value of the reliability index of the high-proportion renewable energy power grid is calculated, and the above steps are repeated until the expected estimated value of the comprehensive cost of the reliability of the high-proportion renewable energy power grid meets the convergence condition, and the reliability evaluation result of the high-proportion renewable energy power grid considering the operation risk of the AGC system is obtained.

[0195] For the convenience of comparison, the reliability assessment situation of a new energy power grid with a high proportion of random failures after the superposition of multiple risks such as the operation risk model of the failure of the AGC system control link, the operation risk model of the AGC system command value issued incorrectly due to human error, and the AGC system and its operation risks with the power grid equipment is regarded as scenario 1, and the reliability result is obtained based on the method proposed in the embodiment of the present invention; the reliability assessment situation of a new energy power grid with a high proportion of random failures after the superposition of multiple risks such as the operation risk model of the failure of the AGC system control link and the operation risk of the power grid equipment is regarded as scenario 2. The reliability assessment situation of a new energy power grid with a high proportion of random failures after the superposition of multiple risks such as the operation risk model of the AGC system command value issued incorrectly due to human error and its operation risk with the power grid equipment is regarded as scenario 3, and the reliability assessment result is obtained by using the traditional reliability assessment method. The reliability assessment situation of a new energy power grid with a high proportion of random failures after only considering the operation risk of the power grid equipment is regarded as scenario 4, and the reliability assessment result is obtained by using the traditional reliability assessment method. The results of the four are shown in Table 1:

[0196] Table 1 Calculation results under various scenarios

[0197] Scenario EENS (MWh / 24h) 1 <![CDATA[7.3146×10 3 ]]> 2 <![CDATA[6.6546×10 3 ]]> 3 <![CDATA[6.4534×10 3 ]]> 4 <![CDATA[3.3423×10 3 ]]>

[0198] It can be seen from Table 1 that the more risk types are considered, the higher the reliability index EENS is, which verifies the effectiveness of the method; at the same time, it also provides some references and information for subsequent power grid operation.

[0199] The present invention aims at the problem of reliability assessment method for high-proportion new energy power grid considering operation risk of AGC system, proposes operation risk modeling method for various faults of AGC system, considers superimposed risk induced by interaction of operation risk of AGC system and operation risk of power grid equipment, quantitatively assesses the degree of reliability decline of high-proportion new energy power grid caused by superimposed risk induced by interaction of operation risk of AGC system and operation risk of power grid equipment, provides technical basis for assessing reliability of high-proportion new energy power grid, and thus accurately guides reliable operation of future high-proportion new energy power grid of the system.

[0200] The present invention also proposes a high-proportion new energy power grid reliability assessment system taking into account the AGC system operation risk, comprising:

[0201] A power grid fault probability model establishment module is used to obtain the failure rate and repair rate of the AGC function in the AGC control unit, establish the AGC function risk model of the AGC control unit to determine the failure probability of the AGC function; obtain the deviation between the power regulation command issued by the AGC system to the AGC control unit and the power regulation amount, and establish the dispatch instruction risk model of the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction; obtain the failure rate and repair rate of the line, establish the line operation risk model to determine the failure probability of the line; obtain the failure rate and repair rate of the new energy unit, establish the new energy unit operation risk model to determine the failure probability of the new energy unit; obtain the failure rate and repair rate of the conventional unit, establish the conventional unit operation risk model to determine the failure probability of the conventional unit; establish a power grid failure probability model using the failure probability of the AGC function, the failure probability of the dispatch instruction, the failure probability of the line, the failure probability of the new energy unit and the failure probability of the conventional unit;

[0202] The power grid model and constraint generation module is used to generate different fault scenarios of a high-proportion new energy power grid by using a sampling method; based on the power grid fault probability model, the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the AGC control unit; based on the state auxiliary variables of the AGC control unit, the operation risk constraints of the AGC control unit under different fault scenarios are established; the generated different fault scenarios are mapped to power grid fault events to obtain the state auxiliary variables of the equipment; based on the state auxiliary variables of the equipment, the power flow model and power flow constraint conditions of the high-proportion new energy power grid considering the operation risk of the AGC system are constructed;

[0203] The power grid reliability assessment module is used to iteratively solve the power flow model, power flow constraints and operation risk constraints of the AGC control unit of the high-proportion renewable energy power grid under different fault scenarios, and obtain the minimum load reduction of the power grid under each fault scenario; based on the minimum load reduction of the power grid under all random faults, the expected variance coefficient of the reliability index of the high-proportion renewable energy power grid is calculated; when the variance coefficient β≤0.01, the expected value of power shortage is used as the reliability assessment result of the high-proportion renewable energy power grid considering the operation risk of the AGC system.

[0204] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0205] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0206] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0207] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A reliability assessment method for a high-proportion renewable energy power grid considering the operational risk of an AGC system, characterized in that: include: Obtain the failure rate and repair rate of the AGC function in the AGC control unit, and establish an AGC function risk model for the AGC control unit to determine the failure probability of the AGC function; Obtain the deviation between the power regulation command issued by the AGC system to the AGC control unit and the power regulation amount, and establish a dispatch instruction risk model for the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction; obtain the failure rate and repair rate of the line, and establish a line operation risk model to determine the failure probability of the line; obtain the failure rate and repair rate of the new energy unit, and establish a new energy unit operation risk model to determine the failure probability of the new energy unit; obtain the failure rate and repair rate of the conventional unit, and establish a conventional unit operation risk model to determine the failure probability of the conventional unit; establish a power grid failure probability model using the failure probability of the AGC function, the failure probability of the dispatch instruction, the failure probability of the line, the failure probability of the new energy unit, and the failure probability of the conventional unit; The sampling method is used to generate different fault scenarios of the high-proportion renewable energy power grid; based on the power grid fault probability model, the generated different fault scenarios are mapped into power grid fault events to obtain the state auxiliary variables of the AGC control unit; Based on the state auxiliary variables of the AGC control unit, the operation risk constraints of the AGC control unit under different fault scenarios are established; the generated different fault scenarios are mapped into power grid fault events to obtain the state auxiliary variables of the equipment; Based on the state auxiliary variables of the equipment, the power flow model and power flow constraint conditions of the high-proportion new energy power grid considering the operation risk of the AGC system are constructed; Iteratively solve the power flow model, power flow constraints and operation risk constraints of the AGC control unit under different fault scenarios of the high-proportion renewable energy power grid to obtain the minimum load reduction of the power grid under each fault scenario; based on the minimum load reduction of the power grid under all random faults, calculate the expected variance coefficient of the reliability index of the high-proportion renewable energy power grid; When the variance coefficient is not greater than 0.01, the expected value of power shortage is used as the reliability assessment result of the high-proportion renewable energy power grid considering the operation risk of the AGC system.

2. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 1 is characterized in that: The AGC function risk model of the AGC control unit includes the failure probability and normal probability of the AGC function, which respectively satisfy the following relationships: In the formula, and They represent the failure probability and normal probability of the AGC function of AGC control unit k, and They represent the failure rate and repair rate of the AGC function of AGC control unit k, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in operation state, k∈n AGC , n AGC represents the set of AGC control units, → represents the mapping relationship between probability and state; Based on the AGC function risk model of the AGC control unit, the failure probability of the AGC function is determined as follows:

3. The reliability assessment method for a high-proportion new energy power grid considering the operation risk of an AGC system according to claim 2 is characterized in that: The power adjustment command value sent by the AGC system to the AGC control unit and the power adjustment amount of the AGC control unit are obtained, and the deviation between the power adjustment command value and the power adjustment amount is determined based on the power adjustment state of the AGC control unit, satisfying the following relationship: In the formula, represents the power adjustment command value sent by the AGC system to the AGC control unit k from time τ = 1 to time τ = t, represents the power regulation of AGC control unit k, It indicates the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation value. represents the power linear regulation rate of AGC control unit k at time τ, It represents the power regulation state identification variable of the AGC controlled unit k at time τ. A value of 1 indicates that the unit increases its output, a value of 0 indicates that the unit operates smoothly, and a value of -1 indicates that the unit reduces its output.

4. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 3 is characterized in that: Establishing Bias obey The probability distribution of satisfies the following relationship: In the formula, is the standard deviation of the normal distribution; Using the probability distribution of deviation and the power adjustment amount, a scheduling instruction risk model is established, including the failure probability and normal probability of the scheduling instruction, which respectively satisfy the following relationships: In the formula, and The failure probability and normal probability of the dispatching instruction of AGC control unit k respectively; Based on the dispatch instruction risk model of the AGC control unit, the failure probability of the dispatch instruction is determined as 5. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 4 is characterized in that: The line operation risk model includes the failure probability and normal probability of the line, which respectively satisfy the following relationships: In the formula, and They represent the failure probability and normal probability of line ll′ respectively, and They represent the failure rate and repair rate of line ll′ respectively, Indicates that line ll′ belongs to line set l B , Auxiliary variable representing the state of line ll′, 0 represents a fault state, 1 represents a running state, → represents the mapping relationship between probability and state; Based on the line operation risk model, the failure probability of the line is determined as 6. The reliability assessment method for a high-proportion new energy power grid considering the AGC system operation risk according to claim 5 is characterized in that: The operation risk model of new energy units includes the failure probability and normal probability of new energy units, which respectively satisfy the following relationships: In the formula, and They represent the failure probability and normal probability of the new energy unit i respectively, and Respectively represent the failure rate and repair rate of new energy unit i, Indicates that new energy unit i belongs to new energy unit set n RE , The auxiliary variable representing the state of the new energy unit i, 0 represents a fault state, 1 represents an operating state, → represents the mapping relationship between probability and state; Based on the operation risk model of new energy units, the failure probability of new energy units is determined as follows:

7. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 6 is characterized in that: The conventional unit operation risk model includes the failure probability and normal probability of the conventional unit, which respectively satisfy the following relationships: In the formula, and represent the failure probability and normal probability of conventional unit j respectively, and represent the failure rate and repair rate of conventional unit j respectively, Indicates that conventional unit j belongs to conventional unit set n G , represents the state auxiliary variable of conventional unit j, 0 represents the fault state, 1 represents the running state, → represents the mapping relationship between probability and state; Based on the conventional unit operation risk model, the failure probability of the conventional unit is determined as 8. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 7 is characterized in that: The power grid failure probability model satisfies the following relationship: In the formula, δ sys represents the probability of power grid failure, represents the failure probability of the AGC function of AGC control unit k, represents the failure probability of the dispatch instruction of AGC control unit k, represents the failure probability of transmission line ll′, represents the failure probability of new energy unit i, represents the failure probability of conventional unit j, → represents the mapping relationship between probability and state, x sys For power grid failure events, Auxiliary variable representing the state of AGC control unit k, 0 means it is in fault state, 1 means it is in running state, It indicates the deviation between the power regulation command value sent by the AGC system to the AGC control unit k and the power regulation value. Auxiliary variable representing the state of transmission line ll′, 0 means it is in fault state, 1 means it is in operation state, Auxiliary variable representing the state of new energy unit i, 0 means it is in fault state, 1 means it is in operation state, Auxiliary variable representing the state of conventional unit j, 0 indicates a fault state, and 1 indicates an operating state; Among them, k∈n AGC , n AGC represents the set of AGC control units, i∈n RE , n RE Represents the set of new energy units, j∈n G , n G represents a set of conventional units, satisfying n AGC =n RE ∪n G .

9. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 8 is characterized in that: The operating risk constraint of the AGC control unit under a single fault scenario satisfies the following relationship: In the formula, and They represent the lower and upper limits of the adjustable capacity of AGC control unit k, and They represent the minimum and maximum output limits of AGC control unit k, respectively. represents the power linear regulation rate of AGC control unit k at time τ, It represents the power regulation state identification variable of the AGC control unit k at time τ. 1 means the unit increases its output, 0 means the unit runs smoothly, and -1 means the unit reduces its output. It represents the power adjustment command value sent by the AGC system to the AGC control unit k from the time τ=1 to the time τ=t.

10. The reliability assessment method for a high-proportion new energy power grid considering the AGC system operation risk according to claim 8, characterized in that: The power flow model of high-proportion renewable energy grid includes: 1) System power balance model satisfies the following relationship: In the formula, is the power of conventional unit j at time τ, is the power of new energy unit i at time τ, is the power of AGC controlled unit k at time τ, is the power of load node m at time τ, is the load reduction amount of load node m at time τ; 2) Node power balance constraint, satisfying the following relationship: In the formula, and They represent the power flowing from node l′ to node l and from node l to node l′ at time τ, l′∈B l Indicates that node l′ belongs to the set of nodes directly connected to node l.

11. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 10 is characterized in that: The power flow constraints of a high-proportion renewable energy grid include: 1) Line flow constraints satisfy the following relationship: In the formula, B ll′ represents the mutual admittance of line ll′, δ l,τ and δ l′,τ They represent the voltage phase angles of node l and node l′ at time τ, Auxiliary variable representing the state of line ll′, 0 represents a fault state, 1 represents a running state, and M represents an arbitrarily large (not infinite) positive number; 2) Line transmission capacity constraints satisfy the following relationship: In the formula, represents the maximum transmission capacity of line ll′; 3) Output constraints of conventional units satisfy the following relationship: In the formula, and Respectively represent the maximum output and minimum output of conventional unit j; 4) Load reduction constraints satisfy the following relationship: 5) The output constraint of new energy units satisfies the following relationship: In the formula, represents the maximum output of new energy unit i at time τ; 6) Node angle constraint, satisfying the following relationship: -θ max ≤θ τ ≤θ max In the formula, θ max and θ τ They represent the maximum voltage phase angle of the grid node and the voltage phase angle at time τ, respectively. Represents the voltage phase angle reference value at time τ.

12. The reliability assessment method for a high-proportion new energy power grid considering the AGC system operation risk according to claim 10, characterized in that: The minimum load reduction of a high-proportion new energy grid under a single fault scenario satisfies the following relationship: In the formula, is the power grid fault event corresponding to fault scenario e The minimum load reduction caused by is the load reduction amount of load node m at time τ, is the load reduction of all load nodes from time τ = 1 to time τ = t under fault scenario e, M L is the total number of load nodes.

13. The reliability assessment method for a high-proportion new energy power grid considering the operating risk of an AGC system according to claim 12 is characterized in that: The expected variance coefficient of the reliability index satisfies the following relationship: Where β is the variance coefficient of the expected value of power shortage, E is the total number of fault scenarios, is the expected value of power shortage, 14. A high-proportion new energy power grid reliability assessment system considering the AGC system operation risk, characterized in that: include: A power grid fault probability model establishment module is used to obtain the failure rate and repair rate of the AGC function in the AGC control unit, establish the AGC function risk model of the AGC control unit to determine the failure probability of the AGC function; obtain the deviation between the power regulation command issued by the AGC system to the AGC control unit and the power regulation amount, and establish the dispatch instruction risk model of the AGC control unit based on the probability distribution of the deviation and the power regulation amount to determine the failure probability of the dispatch instruction; obtain the failure rate and repair rate of the line, establish the line operation risk model to determine the failure probability of the line; obtain the failure rate and repair rate of the new energy unit, establish the new energy unit operation risk model to determine the failure probability of the new energy unit; obtain the failure rate and repair rate of the conventional unit, establish the conventional unit operation risk model to determine the failure probability of the conventional unit; establish a power grid failure probability model using the failure probability of the AGC function, the failure probability of the dispatch instruction, the failure probability of the line, the failure probability of the new energy unit and the failure probability of the conventional unit; The power grid model and constraint generation module is used to generate different fault scenarios of a high-proportion renewable energy power grid using a sampling method; based on the power grid fault probability model, the generated different fault scenarios are mapped into power grid fault events to obtain the state auxiliary variables of the AGC control unit; Based on the state auxiliary variables of the AGC control unit, the operation risk constraints of the AGC control unit under different fault scenarios are established; the generated different fault scenarios are mapped into power grid fault events to obtain the state auxiliary variables of the equipment; Based on the state auxiliary variables of the equipment, the power flow model and power flow constraint conditions of the high-proportion new energy power grid considering the operation risk of the AGC system are constructed; The power grid reliability assessment module is used to iteratively solve the power flow model, power flow constraints and operation risk constraints of the AGC control unit of the high-proportion renewable energy power grid under different fault scenarios, and obtain the minimum load reduction of the power grid under each fault scenario; based on the minimum load reduction of the power grid under all random faults, the expected variance coefficient of the reliability index of the high-proportion renewable energy power grid is calculated; when the variance coefficient β≤0.01, the expected value of power shortage is used as the reliability assessment result of the high-proportion renewable energy power grid considering the operation risk of the AGC system.

15. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 13.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 13 are implemented.

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