CN116488257A - Emergency control method for electric power system considering wind power and photovoltaic active supporting capability - Google Patents

Abstract

The invention belongs to the technical field of safety and stability control of power systems, and particularly relates to an emergency control method of a power system considering wind power and photovoltaic active supporting capacity, which comprises the following steps: acquiring state parameters of the power system, and calculating stability measure functions of all branches of the power system; judging whether the power system is stable or not by screening a critical cut set based on the obtained stability measure function of each branch; when the system is unstable, calculating the sensitivity coefficient of the cut-set branch, and screening a controllable unit, wherein the controllable unit comprises a thermal power unit, a wind power unit and a photovoltaic unit; sequencing the screened controllable units according to the absolute value of the sensitivity coefficient, and determining the priority of the controllable units; combining the determined priority of the controllable unit, and constructing a controllable unit optimization model by taking the minimum cutting cost as an objective function; and solving the constructed controllable unit optimization model to obtain the action quantity of each unit, and finishing the emergency control of the electric power system.

Description

Emergency control method for electric power system considering wind power and photovoltaic active supporting capability

Technical Field

The invention belongs to the technical field of safety and stability control of power systems, and particularly relates to an emergency control method of a power system considering wind power and photovoltaic active supporting capacity.

Background

The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.

Along with the continuous expansion of the wind-solar grid-connected scale, the wind-solar grid-connected scale brings about a considerable threat to the safe and stable operation of a power system; particularly, after the high-proportion wind power is connected, the inertia of the system is reduced, the transient stability characteristic is changed, and it is particularly important to ensure the transient stable operation of the system after the fault.

The aim of achieving transient stability of a high-proportion new energy system depends on knowing the output characteristics (to the unit level) of new energy power generation. In the current large-scale wind-solar grid-connected scene, if a traditional mode of cutting off a thermal power unit is adopted in emergency control of transient stability of a power system, the maximum cutting amount which can be provided by the thermal power unit is reduced due to the fact that the grid-connected capacity of the thermal power unit is reduced, so that the system is difficult to ensure that the system can be restored to a stable running state after cutting off, and the inertia of the system is further reduced after cutting off the thermal power unit, so that larger cutting cost can be brought.

The new energy unit realizes grid connection through a power electronic device, and the rapid control of active output is easy to realize under the control of the pulse width modulation converter. The inverter used for photovoltaic consists of a power electronic device and a microprocessor control loop, and has flexible active and reactive control and high reaction speed. Although the active output of the wind turbine generator system suddenly drops, the mechanical input cannot drop in time due to low pitch angle adjusting speed, a large amount of unbalanced power is accumulated, and the over-rotation speed of the rotor is easy to cause. But still has some short-term power support capability after the introduction of the energy storage or unloading device. Even if the new energy unit is disconnected from the network by directly adopting a method of hard cutting under the emergency time scale, the response economic benefit of the new energy unit is far better than that of the power regulation mode of the existing thermal power unit.

The power upper limit of the new energy unit is generally lower, and the large-scale wind-light resource development brings the unit dimension problem for the system transient stability optimization problem. The branch transient potential energy stabilizing control method combined with the action cost of the new energy unit becomes an effective solution way for solving the problem of high-proportion new energy power support of the system because the branch potential energy method has the advantages of clear physical meaning, simple problem modeling, no influence of the power supply type and the like.

Disclosure of Invention

In order to solve the problems, the invention provides the emergency control method of the electric power system considering the active supporting capacity of wind power and photovoltaic, which solves the problem of failure of an online matching strategy caused by power fluctuation in the traditional emergency control by excavating the power quick adjusting capacity of a new energy unit and has strong adaptability in the future scene of high-proportion new energy characteristics.

According to some embodiments, the invention provides an emergency control method of an electric power system considering wind power and photovoltaic active supporting capability, which adopts the following technical scheme:

an emergency control method of an electric power system considering wind power and photovoltaic active supporting capability, comprising:

acquiring state parameters of the power system, and calculating stability measure functions of all branches of the power system;

judging whether the power system is stable or not by screening a critical cut set based on the obtained stability measure function of each branch;

when the system is unstable, calculating the sensitivity coefficient of the cut-set branch, and screening a controllable unit, wherein the controllable unit comprises a thermal power unit, a wind power unit and a photovoltaic unit;

sequencing the screened controllable units according to the absolute value of the sensitivity coefficient, and determining the priority of the controllable units;

combining the determined priority of the controllable unit, and constructing a controllable unit optimization model by taking the minimum cutting cost as an objective function;

and solving the constructed controllable unit optimization model to obtain the action quantity of each unit, and finishing the emergency control of the electric power system.

As a further technical definition, the obtained state parameters of the power system include a branch phase angle difference, a branch active power flow, a phase angle difference in a balanced state after a branch fault and an active power flow in a balanced state after a branch fault.

As a further technical limitation, the potential energy of any branch is an integral value of the phase angle difference between the branch active power flow and the active power flow in the balanced state of the branch after the fault in the interval from the phase angle difference in the balanced state of the branch after the fault to the phase angle difference of the branch.

As a further technical limitation, each branch stability measure function of the power system reflects the stability condition of the dynamic monitoring branch when the potential energy of the branch does not reach the maximum value; when the system is unstable, the value of its branch steady state measurement function tends to zero.

As a further technical definition, determining the stability index of the cut set according to the obtained branch stability measure function, and determining the transient stability of the power system through the real-time stability index of the critical cut set.

As a further technical limitation, considering that the critical state is reached by leading critical unstable branches in the critical cutting set, judging the stability index of the power system through the leading critical branches in the critical cutting set; and removing the branch with the minimum stability index until the power system forms a non-communicated network, wherein the set of all the removed branches is a critical cut set.

Further, after the critical cut set is identified, calculating the sensitivity coefficient of each branch in the critical cut set, and judging the relation between the stability of the critical cut set and a large power grid through the obtained sign of the sensitivity coefficient; if the sensitivity coefficient is positive, the stability index is reduced after the large power grid is cut off; if the sensitivity coefficient is negative, improving the stability of the system after the output of the large power grid is reduced; and judging the unit needing to act by combining the sensitivity coefficient.

As a further technical limitation, aiming at the thermal power generation unit and the wind power generation unit, only the sensitivity coefficient of the thermal power generation unit and the wind power generation unit is judged to be negative; for the photovoltaic unit, if the photovoltaic unit works in the maximum power tracking mode, only the cutting operation is performed, and if the photovoltaic unit works in the power limiting mode, the stability of the power system is improved through rapid power increase even if the sensitivity coefficient is positive.

As a further technical definition, the larger the value of the sensitivity coefficient, the higher the level of controllable unit priority.

As a further technical definition, the built controllable unit optimization model is:

the built controllable unit optimization model is as follows:

wherein subscripts D and i represent the ith unit in the set of units D capable of applying actions, j represents the jth photovoltaic unit running at limited power, subscript max represents the maximum actionable quantity of the units, n represents the number of all units, and beta _Di Representing the action cost of different types of units in different modulation and control modes, wherein deltaP of different subscripts represents the action quantity of different units; ΔP _Dn-j Representing the action quantity of the rest units after removing j photovoltaic devices running at limited power; ΔP _Dj Representing the action quantity of a photovoltaic unit running at limited power; c represents the set of units which do not allow shutdown; p (P) _s ⁰ For the power of the unit after fault clearing,permissible power for minimum operation of the unit, +.>Then representing a stable measure of the selected kth leg at a predetermined applied action time; k (k) _Di And k _Ds And each represents the fit slope of the stability measure function of the unit and the selected branch.

Compared with the prior art, the invention has the beneficial effects that:

in a large-scale grid-connected system, the invention can accurately predict the branch of the system 'tearing' working condition before destabilization according to the stability measure index. The problem of failure of an online matching strategy caused by power fluctuation in the traditional emergency control can be solved by fully excavating the power quick adjustment capability of the new energy unit. The proposal has strong adaptability in the future scene of high-proportion new energy characteristics.

The invention carries out strategy construction on the problem of rapid regulation of new energy power under an emergency control time scale according to the thought of branch stability measure calculation, critical cut set screening, potential energy sensitivity calculation, control unit selection, cost factor determination, model establishment and simulation verification. And (3) screening a critical cut set from the whole system by calculating the stability measure, and converting the system instability monitoring into the state monitoring of part of branches. Potential energy sensitivity of all power supplies is calculated for branches in the critical cutting set, an adjusting object is further reduced to be a limited potential energy forward-related actionable power supply, and the complexity of solving a follow-up model is greatly reduced. And determining a cost factor according to the power regulation type, and constructing a system transient stability economic optimization model. The construction of the linear model greatly reduces the calculation workload and saves more time for the engineering operation required by the subsequent maintenance of the system stability.

Drawings

The accompanying drawings, which are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification, illustrate and explain the embodiments and together with the description serve to explain the embodiments.

Fig. 1 is a flowchart of an emergency control method of an electric power system considering wind power and photovoltaic active supporting capability in an embodiment of the present invention.

Detailed Description

The invention will be further described with reference to the drawings and examples.

It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.

Examples

The embodiment of the invention introduces an emergency control method of a power system considering wind power and photovoltaic active supporting capacity.

When the power system is in transient instability, surplus transient energy can cause the phase angle difference amplitude of the power transmission element in a certain branch to be continuously increased until the system is torn. In the embodiment, a branch stability measure function is established to judge critical stable or unstable branches in the system by analyzing the fluctuation rule of the potential energy of the branches, and the branches are screened according to a water diffusion method to form a critical cut set; uniformly considering different types of units, calculating potential energy sensitivity indexes for each branch in a cut set, judging the relation between the stability of the critical cut set and a power generation source according to the sign of the coefficient, and selecting a node applying emergency control according to the absolute value; and establishing a transient stability model taking the unit characteristics and the action cost into consideration under an emergency time scale, and solving to obtain a final transient stability control scheme.

An emergency control method of an electric power system considering wind power and photovoltaic active supporting capability, comprising:

acquiring state parameters of the power system, and calculating stability measure functions of all branches of the power system;

judging whether the power system is stable or not by screening a critical cut set based on the obtained stability measure function of each branch;

when the system is unstable, calculating the sensitivity coefficient of the cut-set branch, and screening a controllable unit, wherein the controllable unit comprises a thermal power unit, a wind power unit and a photovoltaic unit;

sequencing the screened controllable units according to the absolute value of the sensitivity coefficient, and determining the priority of the controllable units;

combining the determined priority of the controllable unit, and constructing a controllable unit optimization model by taking the minimum cutting cost as an objective function;

and solving the constructed controllable unit optimization model to obtain the action quantity of each unit, and finishing the emergency control of the electric power system.

As shown in fig. 1, the control strategy of the emergency control method of the electric power system considering the wind power and photovoltaic active supporting capability is as follows:

calculating the stability measure function SBI of each branch;

identifying a critical cut set according to the absolute value of the index;

judging whether the system is stable or not based on the real-time measurement data;

calculating sensitivity coefficients of each power supply to the cut-set branch, and screening the controllable unit: aiming at the thermal power generation unit and the wind power generation unit, only the sensitivity coefficient of the thermal power generation unit and the wind power generation unit is judged to be negative; for the photovoltaic unit, if the photovoltaic unit works in the MPPT mode, only the cutting operation is performed, and if the photovoltaic unit works in the power limiting mode, even if the coefficient is a positive value, the system stability can be improved through rapid power increase, and partial 'switching by modulation' is realized;

after the adjustable units are screened out, in order to reduce the calculation time of the control optimization model, the units which can be controlled preferentially can be selected by sequencing according to the absolute value of the sensitivity coefficient;

fitting a corresponding slope by using the related data, solving an optimization model, and determining the action quantity of each unit;

after the emergency control place is obtained, simulating, verifying and solving the obtained action quantity of each unit, and if the system is stable, applying the action to maintain the system stable; if the model is unstable, changing the preset cut set stability index value to solve the model again until the system is stable.

As one or more embodiments, in the structure-preserving model, the potential energy of any one branch is:wherein sigma _k The phase angle difference is the k branch; />The phase angle difference of the kth branch in the equilibrium state after the fault is set; p (P) _k (u) is the kth branch active power flow,>is the active power flow of the kth branch in the balanced state relative to the post-fault.

Since the calculation of potential energy depends on the integration of the path, the potential energy increment is irrelevant to the selection of the reference point, and the phase angle difference at the fault removal moment is taken as the reference point. If the phase angle difference of the branch at the fault removal time isThen->Potential energy at fault removal time; i.e. < ->The branch potential energy function along the post-fault trajectory is: />

Defining a first swing arm stability index as:wherein t is _ak And t _bk Respectively representing the moments of the maximum value and the minimum value of the first swing of the potential energy of the branch. P (P) _k (t _bk ) At t _bk And (5) the tide of the kth branch at the moment. V (V) _PEk (t _bk ,t _ak ) Represents t _bk Potential energy function V of time _PEk (t _bk ) And t _ak Potential energy function V of time _PEk (t _ak ) Is a difference in (c). Also V _PEk (σ _bk ,σ _ak ) Then the phase angle difference sigma corresponding to the two moments is adopted _bk Sum sigma _ak The difference in the potential energy functions represented. dV (dV) _PEk /dσ _k |t _bk Indicated at t _bk Time potential energy function V _PEk For phase angle difference sigma _k Is a spatial derivative of (a). S is S _SBIk The sign of the kth branch phase angle difference sigma _k Is a variable direction of (a).

Get [ t ] _ak ,t _bk ]The time period when the potential energy function is monotonically increased isThe establishment is that:wherein dσ _k /dt＝ω _N ω _k (t)，ω _N And omega _k (t) represents the nominal angular frequency and the per-unit value of the angular frequency of the branch k at time t, respectively. The product of the two is the phase angle difference sigma _k Is a time derivative of (a). P (P) _k And (t) is the power flow of the kth branch at the moment t.

During this period, if omega _k (t)>0, the phase angle difference between the branches gradually becomes larger, at the moment, the requirement is satisfiedS is then _SBIk >0; if omega _k (t)<0, the phase angle difference between the branches is gradually reduced, and the +.>Namely S _SBIk <0. Thus, the first pendulum t can be judged _bk Time->Whether the branch stability is established or not is judged.

Establishing a branch stability degree function S _SBIk (t) is:wherein P is _k And (t) is the power flow of the branch k at the moment t. V (V) _PEk (t,t _ak ) Potential energy function V representing time t _PEk (t) and t _ak Time transient potential energy function V _PEk (t _ak ) Is a difference in (c). />By symbol P _k Represented by the formula. The remaining parameters are as defined above.

Therefore, the magnitude of the measuring function can be used for branch potential energyAnd dynamically monitoring the stable state of the branch when the maximum value is not reached. When the system is unstable, the branch index S contained in the critical cut set _SBIk (t) tends to be 0.

As one or more embodiments, the stability index of the cutset is defined as:accordingly, the stability measure function of the critical cutset is defined as:wherein C and subscript C represent the set of critical cutsets. The remaining parameters are as defined above.

The transient stability of the system is reflected by the real-time stability index of the critical cut set. Considering that the critical cut set is first brought to the critical state by the dominant critical unstable branch, the system stability index is judged by the dominant critical branch in the critical cut set, namely: si=sbi _k (t _bk ) The method comprises the steps of carrying out a first treatment on the surface of the The branch with the smallest stability index is selected and removed until the network becomes a non-connected graph, at which time the collection of all branches removed constitutes the critical cutset in this mode.

Brought into dσ _k /dt＝ω _N ω _k (t) to the branch potential energy function and time derivative thereof is:the spatial derivative is calculated as: />The active power flow of the branch is obtained by:re-pair sigma _k The derivation can be obtained: />

In addition, the active output can be obtained by deriving the active input node PG in the systemForce transfer factor D _k,g ：Get->Wherein PG is the active output of all units (a thermal power unit, a wind power unit and a photovoltaic unit); a is that _k,g The power transfer distribution factor can represent the influence of the output of the unit on the branch k and the effect of the load power change on the branch k; />A node association vector for branch k; x is X _g Is the g-th column vector of the inverse matrix of the direct current power flow matrix. P (P) _G,p And P _G,q Active power of the generators p and q, respectively.

Branch measurement function pair sigma _k The derivation can be obtained:

in summary, the sensitivity derivative of SBIk (t) to the power active force PG of the power supply is (CSSI) as:

after the critical cut set of the system is identified, a sensitivity index (defined as CSSI) is calculated for each branch in the cut set, and the relationship between the stability of the critical cut set and the power supply can be determined by the sign of the coefficient. If CSSI >0, the stability index is reduced after the power supply is switched off, if CSSI <0, the stability of the system can be improved after the power supply is reduced; and judging the unit needing to act through CSSI. Therefore, the system stability index can be calculated in real time according to the information such as the branch power, the voltage phase angle and the like obtained by the wide area measurement system.

When the system fails, firstly, determining a critical cut set in a corresponding mode according to a potential energy function, and taking the cut set containing the stability index of the branch or the stability of the critical branch k as a target object of emergency control; after the fault, the sensitivity coefficient of each active output unit relative to the branch k stability index is calculated, and the node for applying emergency control is selected according to the absolute value of the sensitivity coefficient and the corresponding energy unit type.

The fuel cost consumed by the unit in the start-stop switching process is simply called start-stop cost. The unit characteristics and the off-time together determine the value of the start-up consumption. Wherein the starting consumption and the time of furnace shutdown are approximately in an exponential function relation; the starting and stopping cost of the thermal power generating unit is as follows:wherein k, sigma and tau are the starting consumption coefficients of the generator set, S ₂ For the unit to fire for one hour, the starting cost is T ^off The machine set turn-off time is set.

The wind power cutter in the emergency control process has extremely high requirements on time scale, and the wind power plant power control can be rapidly realized only by starting or cutting off the in-site unit due to the slower reaction speed of the mechanical part. When the fan is cut and stopped, the whole process generates great mechanical damage and vibration to the fan rotating shaft, the blades and the actuating mechanism, and the cost of the wind turbine generator is defined as follows: f=λq+ζ; wherein lambda is the loss generated by adjusting the action unit angle of the pitch angle; q is pitch angle adjustment; ζ represents the additional economic losses caused by other control measures.

The photovoltaic unit is connected with the power electronic device in a grid mode, and power adjustment and start-stop of the unit can be rapidly achieved. The inverter acts as a power electronic equipment response process, and the action time can be controlled within 100 ms. Thus, the overall photovoltaic emergency power control system action time may not exceed 300ms. Whether frequent start-stop or power adjustment is performed, the transient process impacts the internal electronic devices, so that the service life of the electronic devices is shortened. The economic cost of the rapid adjustment is necessarily reduced in view of the difference between the rapid adjustment and the direct excision response process. This part of the economic cost is relatively low, and can be represented temporarily by a small constant.

The lowest cost of the cutting machine is taken as an objective function, the preset cutting set stability index value xi and the action limit of each unit are taken as constraints, and an optimization model is constructedType (2). Obtaining SBI relation of the generator under different cutting amounts, wherein the approximate slope of the linear fitting and the SBI relation is k _Di . The built controllable unit optimization model is as follows:

where subscripts D and i represent the ith unit in the set of units D to which actions can be applied. j represents the j-th photovoltaic unit operated under limited power. The subscript max represents the maximum actionable amount of the unit. n represents the number of all units. To simplify model expression, beta _Di Representing the action cost of different types of units in different modulation modes. The Δp of the different subscripts represent the different amounts of unit motion (positive direction represents cut/decrease). The first equation represents the action constraint of the photovoltaic unit in wind power, thermal power and maximum power tracking modes (only the forward cutting machine participates in control); wherein DeltaP _Dn-j Representing the action quantity of the rest units after removing j photovoltaic devices running at limited power. The third equation represents the photovoltaic unit motion constraint (reversible up-regulation participation control) for the limited power mode. Wherein DeltaP _Dj Representing the motion quantity of the photovoltaic unit running at limited power. In the second equation, the first part represents the influence of the motion quantity of the rest units on the branch stability SBI except for the units which are required by the system to keep the minimum power of the units to be constant. c represents the set of units that are not allowed to shut down.For the power of the unit after fault clearing, +.>And allowing power for the minimum operation of the unit. />Then representsA stable measure of the selected kth leg at a predetermined applied action time. k (k) _Di And k _Ds And each represents the fit slope of the stability measure function of the unit and the selected branch. The second formula has the meaning that on the premise of meeting the condition that the unit is not stopped, different units are properly selected to participate in adjustment to reach the preset value of the stability of the branch.

For the solution of this linear optimization problem, genetic algorithm/particle swarm algorithm heuristic optimization algorithm or commercial solver may be employed.

According to the method, strategy construction is carried out on the problem of rapid regulation of new energy power under an emergency control time scale according to the thought of branch stability measure calculation, critical cut set screening, potential energy sensitivity calculation, control unit selection, cost factor determination, model establishment and simulation verification; screening a critical cut set from the whole system by calculating a stability measure, and converting system instability monitoring into state monitoring of partial branches; potential energy sensitivity of all power supplies is calculated aiming at branches in critical cutting, an adjusting object is reduced to be a limited potential energy forward-related actionable power supply, and the complexity of solving a follow-up model is greatly reduced; determining a cost factor according to the power regulation type, and constructing a system transient stability economic optimization model; the construction of the linear model greatly reduces the calculation workload and saves more time for the engineering operation required by the subsequent maintenance of the system stability.

The above description is only a preferred embodiment of the present embodiment, and is not intended to limit the present embodiment, and various modifications and variations can be made to the present embodiment by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.

Claims (10)

1. An emergency control method of an electric power system considering wind power and photovoltaic active supporting capability, comprising:

acquiring state parameters of the power system, and calculating stability measure functions of all branches of the power system;

judging whether the power system is stable or not by screening a critical cut set based on the obtained stability measure function of each branch;

when the system is unstable, calculating the sensitivity coefficient of the cut-set branch, and screening a controllable unit, wherein the controllable unit comprises a thermal power unit, a wind power unit and a photovoltaic unit;

sequencing the screened controllable units according to the absolute value of the sensitivity coefficient, and determining the priority of the controllable units;

combining the determined priority of the controllable unit, and constructing a controllable unit optimization model by taking the minimum cutting cost as an objective function;

and solving the constructed controllable unit optimization model to obtain the action quantity of each unit, and finishing the emergency control of the electric power system.

2. An emergency control method for an electrical power system taking into account wind power and photovoltaic active support capabilities according to claim 1, wherein the obtained state parameters of the electrical power system comprise branch phase angle difference, branch active power flow, phase angle difference in balanced state after branch fault and active power flow in balanced state after branch fault.

3. An emergency control method for an electric power system taking into account wind power and photovoltaic active supporting capacity as set forth in claim 1, wherein the potential energy of any one branch is an integrated value of a phase angle difference between a branch active power flow and an active power flow in a balanced state after a fault in a section from the phase angle difference in the balanced state after the fault to the phase angle difference of the branch.

4. An emergency control method for an electric power system taking into account wind power and photovoltaic active supporting capacity as claimed in claim 1, wherein each branch stability measure function of the electric power system reflects the stability condition of a dynamically monitored branch when the potential energy of the branch does not reach a maximum value; when the system is unstable, the value of its branch steady state measurement function tends to zero.

5. An emergency control method for an electric power system taking into account wind power and photovoltaic active supporting capacity as claimed in claim 1, characterized in that the stability index of the cut-set is determined according to the obtained branch stability measure function, and the transient stability of the electric power system is determined by the real-time stability index of the critical cut-set.

6. The method for emergency control of an electrical power system taking into account wind power and photovoltaic active support capabilities as set forth in claim 1, wherein the electrical power system stability indicator is determined by a dominant critical leg in the critical cut set, taking into account that the critical cut set is first brought to a critical state by the dominant critical unstable leg; and removing the branch with the minimum stability index until the power system forms a non-communicated network, wherein the set of all the removed branches is a critical cut set.

7. The emergency control method of the electric power system considering wind power and photovoltaic active supporting capacity as claimed in claim 6, wherein after the critical cut-off set is identified, the sensitivity coefficient of each branch in the critical cut-off set is calculated, and the relation between the stability of the critical cut-off set and the large power grid is judged through the obtained sign of the sensitivity coefficient; if the sensitivity coefficient is positive, the stability index is reduced after the large power grid is cut off; if the sensitivity coefficient is negative, improving the stability of the system after the output of the large power grid is reduced; and judging the unit needing to act by combining the sensitivity coefficient.

8. The emergency control method of the electric power system considering wind power and photovoltaic active supporting capacity as claimed in claim 1, wherein for the thermal power generation unit and the wind power generation unit, only the sensitivity coefficient is required to be judged to be negative; for the photovoltaic unit, if the photovoltaic unit works in the maximum power tracking mode, only the cutting operation is performed, and if the photovoltaic unit works in the power limiting mode, the stability of the power system is improved through rapid power increase even if the sensitivity coefficient is positive.

9. An emergency control method for an electrical power system taking into account wind power and photovoltaic active support capabilities according to claim 1, wherein the larger the value of the sensitivity coefficient is, the higher the level of controllable unit priority is.

10. An emergency control method for an electric power system taking into account wind power and photovoltaic active supporting capacity as set forth in claim 1, wherein the built controllable unit optimization model is:

wherein subscripts D and i represent the ith unit in the set of units D capable of applying actions, j represents the jth photovoltaic unit running at limited power, subscript max represents the maximum actionable quantity of the units, n represents the number of all units, and beta _Di Representing the action cost of different types of units in different modulation and control modes, wherein deltaP of different subscripts represents the action quantity of different units; ΔP _Dn-j Representing the action quantity of the rest units after removing j photovoltaic devices running at limited power; ΔP _Dj Representing the action quantity of a photovoltaic unit running at limited power; c represents the set of units which do not allow shutdown; p (P) _s ⁰ For the power of the unit after fault clearing,permissible power for minimum operation of the unit, +.>Then representing a stable measure of the selected kth leg at a predetermined applied action time; k (k) _Di And k _Ds And each represents the fit slope of the stability measure function of the unit and the selected branch.