WO2019144934A1

WO2019144934A1 - Power grid regulation method

Info

Publication number: WO2019144934A1
Application number: PCT/CN2019/073192
Authority: WO
Inventors: 葛维春; 李家珏; 朱钰; 邵宝珠; 王刚; 孙峰; 王顺江; 高凯; 葛延峰; 苏安龙
Original assignee: 国网辽宁省电力有限公司电力科学研究院; 国网辽宁省电力有限公司; 国家电网有限公司
Priority date: 2018-01-26
Filing date: 2019-01-25
Publication date: 2019-08-01
Also published as: CN108258684A

Abstract

Disclosed is a power grid regulation method. The method comprises: constructing a calculation model for a balance regulation amount, and solving a demand value of a balance adjustment amount of an electric system according to the calculation model; defining an adjustment amount division function of multiple control domains according to an adjustment amount of multiple sources and multiple loads, and acquiring an adjustment amount for each control domain according to the adjustment amount division function; according to the adjustment amount division function of the multiple control domains and a decision coefficient of each control domain, constructing a "source-load-domain" control plane equation; according to the adjustment amount of each control domain, the demand value of the balance adjustment amount and the control plane equation, determining whether a current electric system operating point is inside or outside the regulation plane; building a "source-load-domain" coordination, regulation and optimization model, and where the current electric system operating point is inside the regulation plane, optimizing the operating point inside the regulation plane according to the regulation and optimization model, so as to obtain a decision vector between different control domains; substituting the obtained decision vector into the control plane equation, and judging whether a substitution result satisfies the demand value of the balance adjustment amount.

Description

Power grid regulation method

The present disclosure claims priority to Chinese Patent Application No. 20,181, 007, 645, filed on Jan. 26, 2011, the entire disclosure of which is incorporated herein by reference.

Technical field

The present disclosure relates to the field of power system operation and control, for example, to a power grid regulation method.

Background technique

In the safe and stable operation of the power grid, the grid balance adjustment margin is one of the core factors. Multi-source, multi-load and multi-domain multi-sources include conventional power sources: hydropower and thermal power; clean energy: photovoltaic, wind power and nuclear power; energy storage: battery energy storage, centralized heat storage and distributed heat storage; multi-hitter refers to translatable load, Including: refrigeration, air conditioning, irrigation and heating load; multi-domain refers to the power grid in the normal regulation stage, called the normal regulation domain, the grid has no normal regulation capability, is in the abnormal regulation stage, called the abnormal regulation domain, the power grid loses control ability In the state of emergency control, it is called emergency control domain; the normal control domain is controlled by hydropower and thermal power, and the abnormal control domain is controlled by energy storage, emergency control domain, and the control objects are nuclear power, wind power and photovoltaic.

The power grid has multiple sources including: thermal power, hydropower, nuclear power, wind power, photovoltaic, electric heat storage, battery energy storage; multi-load includes: transferable load, translatable load, interruptible load, etc.; to ensure clean energy acceptance and grid security Stable operation requires coordinated control and control of multiple sources and multiple loads; related technologies mainly focus on coordinated control between individual and multiple sources, including source-charge interaction control of thermal power, wind power, load, etc., provided by the grid, but not involved in regulation The independent variables of the system do not consider the multi-source, multi-load and multi-domain coordination from the perspective of the power system. The coordinated control of this mode is not suitable for the scheduling operation of the system after the large-capacity electric storage heat load is put into operation.

Summary of the invention

The disclosure provides a power grid regulation method to realize multi-source multi-source multi-domain coordinated regulation of a new energy power system, and is suitable for multi-source coordinated regulation of large-capacity electric storage heat load.

The present disclosure provides a power grid regulation method for implementing multi-source multi-load multi-domain coordinated regulation of a new energy power system, the method comprising the following steps:

According to the power-on mode and load extreme value of the whole network, a calculation model of the balance adjustment amount is constructed, and the demand value of the balance adjustment amount of the power system is solved according to the calculation model.

Facing the multi-source power supply and multi-class load of the power grid, the adjustment amount division function of multiple control domains is defined according to the adjustment amount of multi-source and multi-load, and the boundary adjustment variable is provided for the next “source-load domain” control plane equation; The partition function obtains the amount of adjustment for each control domain.

According to the adjustment quantity partition function of multiple control domains and the decision coefficients of each control domain, the "source-charge domain" control plane equation of multi-source, multi-charge and multi-domain is constructed, and the control plane of the "source-charge domain" space is depicted to guide more intuitively. Coordinated control of multiple sources and multiple domains.

According to the adjustment amount of each control domain, the demand value of the balance adjustment amount and the control plane equation, the power system operating point is determined inside or outside the “source-load domain” control plane, and the initial operation condition is provided for the next control optimization model. .

Establish a “source-source domain” coordinated regulation optimization model, and optimize the internal operating points of the control plane according to the regulation optimization model when the power system operating point is inside the control plane, and obtain the target decision between different control domains. vector.

The obtained target decision vector is brought into the control plane equation to determine whether the substitution result satisfies the balance adjustment requirement, and the coordinated control of the multi-source, multi-load and multi-domain is realized.

In an embodiment, the power source "source-load domain" is constructed to coordinate the control space, and a multi-source, multi-load, multi-domain control plane is drawn to monitor the actual operation of the power grid.

In an embodiment, the expression of the calculation model of the system balance adjustment amount is as follows:

|ΔP _balance |=|P _G,lim -P _L,lim |

Where: ΔP _balance is the balance adjustment required by the system, P _G,lim is the regulation limit of the grid rotating unit, and P _L,lim is the grid load limit.

In an embodiment, the expression of the adjustment amount partitioning function of the multi-control domain is as follows:

Where: t is the time value of the grid operation, ΔP _u,t is the adjustment amount in the normal control domain, ΔP _T,max (t) is the maximum adjustment amount of the thermal power unit at time t, ΔP _H,max (t) is t The maximum adjustment amount of the hydropower unit at the moment, ΔP _un,t is the adjustment amount in the abnormal regulation domain, ΔP _S,max (t) is the maximum adjustment amount of energy storage at time t, and ΔP _ur,t is the adjustment amount in the emergency regulation domain. , ΔP _W,max (t) is the maximum adjustment of wind power at time t, ΔP _P,max (t) is the maximum adjustment of photovoltaic at time t, ΔP _N,max (t) is the maximum adjustment of nuclear power at time t, ΔP _L,max (t) is the maximum adjustment of the interactive load at time t.

In an embodiment, the expression of the "source domain" control plane equation is as follows:

|ΔP _balance |=ΔP _u +ΔP _un +ΔP _ur =k _u,t ΔP _u,t +k _un,t ΔP _un,t +k _ur,t ΔP _ur,t

Where: ΔP _u is the regulation of normal regulatory domain, ΔP _un is the regulation of abnormal regulatory domain, ΔP _ur is the regulation of emergency regulatory domain, k _u,t is the decision coefficient of normal regulatory domain, k _un,t is the abnormal regulatory domain The decision coefficient, k _{ur, t} is the decision coefficient of the emergency regulation domain.

In an embodiment, the discriminant expression for determining whether the power system operating point is inside or outside the "source-load domain" control plane is as follows:

In the formula: margin is the system adequacy.

In an embodiment, the expression of the "source-load domain" coordinated regulation optimization model is as follows:

minΔP _k,t =k _u,t ΔP _u,t +k _un,t ΔP _un,t +k _ur,t ΔP _ur,t

Where: ΔP _k,t is the total amount of “source-load domain” regulation, χ is the multi-domain conversion criterion, χ _{un is the} criterion for the transition from the normal regulatory domain to the abnormal regulatory domain, and χ _ur is converted from the abnormal regulatory domain to The criteria for emergency regulation domains.

In an embodiment, the X-axis of the source-charge domain coordinated regulatory space is a normal regulatory domain, the Y-axis is an abnormal regulatory domain, and the Z-axis is an emergency regulatory domain.

The present disclosure also provides an electronic device, including: at least one processor; a memory configured to store at least one program,

The at least one program is executed by the at least one processor such that the at least one processor implements any of the methods described above.

The present disclosure also provides a computer readable storage medium storing computer executable instructions for performing any of the methods described above.

The power grid regulation method provided by the present disclosure fully considers the multi-source margin adjustment characteristics, the interactive load regulation characteristics, the multi-source regulation cost characteristics, the clean energy consumption maximization and the like, defines a multi-control domain scheduling mode, and introduces The decision vectors of the normal regulatory domain, the abnormal regulatory domain and the emergency regulatory domain are used to establish the source-domain coordinated control optimization model through the control priorities of different control domains, and the system can meet the sufficient demand with minimum adjustment to achieve maximum clean energy consumption. . By introducing a new multi-domain control operation method, the multi-source and multi-charge control characteristics are fully considered, and the multi-source and multi-load decision strategies are fully optimized. The integrated system adjustment margin, clean energy consumption, and regulation cost are comprehensively optimized. And other factors, to achieve the overall optimal allocation of system resources.

DRAWINGS

FIG. 1 is a flowchart of a power grid regulation method according to an embodiment;

2 is a schematic plan view showing a coordinated control space plane of a source domain of a clean energy grid according to an embodiment;

FIG. 3 is a schematic diagram of a source-domain domain control plane analysis result provided by an embodiment; FIG.

FIG. 4 is a schematic structural diagram of an electronic device according to an embodiment.

Detailed ways

The specific embodiments of the present disclosure will be described below with reference to the accompanying drawings.

The power system source-domain coordinated regulation space provided by the present disclosure is shown in FIG. 2,

The X-axis is the normal regulation domain. The power grid regulation requirements are met by hydropower and thermal power. It is the normal regulation of the grid during the lumbar load and peak period. When the grid is in the lumbar load period, the hydropower belt has the minimum output, and the thermal power is the main peak frequency modulation or The tie line, in the case of the power grid in the upper load phase, is mainly based on the addition of thermal power, and the hydropower is fine-tuned. In the case of the power grid under the load phase, the fire power is mainly reduced, and the hydropower is fine-tuned.

The Y-axis is an abnormal regulation domain. In the case that the grid is under the waist load or underestimation period, since the clean energy generation power exceeds the normal regulation capability, it is necessary to input electric heat storage and battery energy storage to ensure the grid is in normal operation state. The power grid is in an abnormal operating state; the heat storage and battery regulation strategies are activated, and during the lumbar load period, the battery energy storage is first started, and then the power storage heat of the power plant and the distributed electric heat storage are started; when the valley load falls, the distributed first is started. The electric heat storage, and then start the electric storage heat of the power plant and the battery energy storage; in the rising period of the low valley load, the electric storage heat of the power plant is first exited, and the distributed electric heat storage is successively withdrawn according to the heat storage capacity.

The Z-axis is an emergency regulation domain. When the grid is in an abnormal operating state, after the electric heat storage and battery energy storage are fully invested, the grid clean energy power generation still exceeds the grid demand. At this time, the grid is in an emergency operation state, and the clean energy is started. The power generation and power curtailment strategy is regulated according to the order of nuclear power, wind power and photovoltaic, and transferable load. The emergency operation state recovery process of the power grid is regulated according to the order of transferable load, photovoltaic, wind power and nuclear power.

The present disclosure provides a source-load-domain coordinated control method for a new energy grid, and realizes a multi-source, multi-field, multi-domain coordinated control space construction of a new energy power system. Referring to Figure 1, the method provided by the present disclosure includes the following steps.

Step 110: According to the power-on mode of the whole network and the extreme value of the load, construct a calculation model of the balance adjustment amount, and solve the demand value of the balance adjustment amount of the power system according to the calculation model.

Step 120: Facing the multi-source power supply of the power grid and multiple types of loads, define an adjustment amount division function of the multi-control domain according to the adjustment quantity of the multi-source multi-load, and provide a boundary adjustment variable for the next “source-load domain” control plane equation; The adjustment amount of each control domain is obtained according to the adjustment amount division function.

Step 130: Construct a “source-load domain” control plane equation of the multi-source, multi-charge and multi-domain according to the adjustment quantity partition function of the multi-control domain and the decision coefficient of each control domain, and characterize the control plane of the “source-load domain” space, Intuitively guide coordinated control of multiple sources, multiple loads and multiple domains.

Step 140: Collect a real-time state of the source load operation, and determine, according to the adjustment amount of each control domain, the demand value of the balance adjustment amount, and the control plane equation, the power system operating point is inside or outside the “source-load domain” control plane, as A one-step regulation optimization model that provides initial operating conditions.

Step 150: Establish a “source-load domain” coordinated regulation optimization model, and optimize the operation point inside the control plane according to the regulation optimization model when the power system operation point is inside the regulation plane, and obtain different control domains. Target decision vector.

Step 160: Bring the obtained target decision vector into the control space, determine whether the substitution result satisfies the demand value of the balance adjustment amount, and realize the coordinated control of the multi-source, multi-load and multi-domain.

In an embodiment, the method further includes: constructing a “source-load domain” coordination control space of the power system, and drawing a control plane of the multi-source multi-charge control domain to monitor the actual operation of the power grid.

The present disclosure will be described below in conjunction with the embodiments.

(1) In order to eliminate new energy power, the balance is often insufficient during the low load period. First, according to the whole network startup mode and load situation, to ensure the safe and stable operation of the power grid, calculate the current power system balance adjustment demand value. :

(2) Collect multi-source power supply and multi-class load operation information of the power grid, define the adjustment amount division function of multiple control domains according to the adjustment amount of multi-source and multi-load, and solve the adjustable value of multi-source, multi-load and multi-domain under the current operating state.

In this embodiment, in the normal control domain, the adjustable margin of the thermal power unit is 800,000 kilowatts, and the adjustable margin of the hydropower unit is 50,000 kilowatts; in the abnormal regulation domain, the adjustable margin of the electric heat storage energy and the battery heat storage is 1.5 million kilowatts; within the emergency control domain, the regulation margin achieved by wind power through power cuts is 2 million kilowatts. There is no adjustment margin for photovoltaics during nighttime low load period, and nuclear power needs to operate with base load, which can provide a adjustment margin of 500,000 kilowatts. The transfer load provides a 3 million kilowatt adjustment margin.

The multi-source and multi-charge adjustable capability is shown in Table 1:

Table 1 Multi-source multi-charge control domain adjustment capability table

(3) Constructing the "source-load domain" control plane equation of multi-source, multi-charge and multi-domain, and solving the control plane of the "source-charge domain" space to intuitively guide the coordinated control of multi-source, multi-load and multi-domain.

|ΔP _balance |'=ΔP _u +ΔP _un +ΔP _ur =k _u,t ΔP _u,t +k _un,t ΔP _un,t +k _ur,t ΔP _ur,t

=k _u,t ×85 million kW+k _un,t ×1.5 million kW+k _ur,t ×5.5 million kW

In an embodiment _, the initial value of k _u,t is a first preset value, k _{un ,} the initial value of _t is a second preset value, and k _ur, the initial value of _t is a third preset value. In an embodiment _, the initial value of k _u,t can be set according to ΔP _u,t , _and the initial value of k _un,t can be preset according to ΔP _un,t , _and the initial value of k _ur,t can be based on ΔP _{ur , t} setting.

(4) Collect the real-time status of the source-load operation, and determine whether the current power system operating point is inside or outside the “source-load domain” control plane. By optimizing the regulation, the system operation point is outside the control plane to ensure the system is running abundance.

(5) Establish a “source-source domain” coordinated regulation optimization model, and optimize the internal operating points of the control plane according to the regulation optimization model when the power system operating point is inside the control plane, and obtain different control domains. Optimal decision vector.

minΔP _k,t =k _u,t ×85 million kW+k _un,t ×1.5 million kW+k _ur,t ×5.5 million kW

(6) According to step (5), the decision vector is solved, and the decision vector is substituted into the control plane equation to determine whether the substitution result satisfies the demand value of the balance adjustment amount, and the coordinated control of multi-source, multi-load and multi-domain is realized.

[k _u,t ,k _un,t ,k _ur,t ]=[1,0.8,0]

(7) Set up the “source-load domain” coordination control space of the power system, and draw the multi-source multi-load multi-domain control plane of this embodiment, as shown in Figure 3, monitor the actual operation of the grid.

Through the coordinated regulation of multi-source, multi-load and multi-domain, the system keeps ample operation while absorbing new energy. In this embodiment, in the source-charge domain control space, thermal power deep regulation, hydropower fine-tuning, and heat storage input are adopted, which operate in the normal regulation domain and the abnormal regulation domain, and do not enter the emergency regulation domain, satisfying the new energy grid. Adjusting the abundance ensures safe and stable operation of the grid. Through the example demonstration, the source-domain coordination control method proposed in the present disclosure obtains the highest comprehensive weighting index in the process of grid balance adjustment, which is the global optimal solution. The comparison argument table is shown in Table 2:

Table 2 Comparison of the results of the example scheme

FIG. 4 is a schematic diagram of a hardware structure of an electronic device according to an embodiment. As shown in FIG. 4, the electronic device includes: one or more processors 210 and a memory 220. One processor 410 is taken as an example in FIG.

The electronic device may further include: an input device 230 and an output device 240.

The processor 210, the memory 220, the input device 230, and the output device 240 in the electronic device may be connected by a bus or other means, and the bus connection is taken as an example in FIG.

The input device 230 can receive input numeric or character information, and the output device 240 can include a display device such as a display screen.

The memory 220 is a computer readable storage medium that can be configured to store software programs, computer executable programs, and modules. The processor 210 executes a plurality of functional applications and data processing by executing software programs, instructions, and modules stored in the memory 220 to implement any of the above embodiments.

The memory 220 may include a storage program area and an storage data area, wherein the storage program area may store an operating system, an application required for at least one function; the storage data area may store data created according to use of the electronic device, and the like. In addition, the memory may include volatile memory such as random access memory (RAM), and may also include non-volatile memory such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device.

Memory 220 can be a non-transitory computer storage medium or a transitory computer storage medium. The non-transitory computer storage medium, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 220 can optionally include memory remotely located relative to processor 210, which can be connected to the electronic device over a network. Examples of the above networks may include the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

Input device 230 can be configured to receive input digital or character information and to generate key signal inputs related to user settings and function control of the electronic device. The output device 240 can include a display device such as a display screen.

The embodiment further provides a computer readable storage medium storing computer executable instructions for performing the above method.

All or part of the processes in the foregoing embodiment may be performed by a computer program executing related hardware, and the program may be stored in a non-transitory computer readable storage medium, and the program may include the above method when executed. The flow of the embodiment, wherein the non-transitory computer readable storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a RAM, or the like.

Claims

A power grid regulation method includes:

Constructing a calculation model of the balance adjustment amount, and solving the demand value of the balance adjustment amount of the power system according to the calculation model;

Defining an adjustment amount division function of the multi-control domain according to the adjustment amount of the multi-source multi-charge; and obtaining an adjustment amount of each control domain according to the adjustment amount division function;

Constructing a "source-load domain" control plane equation according to the adjustment amount partitioning function of the multi-control domain and the decision coefficient of each control domain, and characterizing the control plane of the "source-load domain" space;

Determining, according to the adjustment amount of each control domain, the demand value of the balance adjustment amount, and the control plane equation, that the power system operating point is inside or outside the control plane;

Establishing a “source-load domain” coordinated regulation optimization model, and optimizing the operating point inside the control plane according to the regulation optimization model in the case that the power system operating point is inside the control plane, and obtaining a target a decision vector; wherein the target decision vector includes decision coefficients for each control domain;

Substituting the obtained target decision vector into the control plane equation, and determining whether the substitution result satisfies the demand value of the balance adjustment amount.
The method according to claim 1, wherein, after the obtained decision vector is substituted into the control plane equation to determine whether the substitution result satisfies the demand value of the balance adjustment amount, the method further includes:

Set up the power source "source domain" to coordinate the control space, and draw the control plane of the multi-source, multi-charge and multi-control domain to monitor the actual operation of the grid.
The method according to claim 1 or 2, wherein the expression of the calculation model of the balance adjustment amount is as follows:

|ΔP balance |=|P G,lim -P L,lim |

Where: ΔP balance is the balance adjustment required for the power system, P G,lim is the regulation limit of the grid rotating unit, and P L,lim is the grid load limit.
The method of claim 1, 2 or 3, wherein the expression of the adjustment amount division function of the multi-control domain is as follows:

Where: t is the time value of the grid operation, ΔP u,t is the adjustment amount in the normal control domain, ΔP T,max (t) is the maximum adjustment amount of the thermal power unit at time t, ΔP H,max (t) is t The maximum adjustment amount of the hydropower unit at the moment, ΔP un,t is the adjustment amount in the abnormal regulation domain, ΔP S,max (t) is the maximum adjustment amount of energy storage at time t, and ΔP ur,t is the adjustment amount in the emergency regulation domain. , ΔP W,max (t) is the maximum adjustment of wind power at time t, ΔP P,max (t) is the maximum adjustment of photovoltaic at time t, ΔP N,max (t) is the maximum adjustment of nuclear power at time t, ΔP L,max (t) is the maximum adjustment of the interactive load at time t.
The method of any of claims 1-4, wherein the expression of the "source-load domain" control plane equation is as follows:

|ΔP balance |'=ΔP u +ΔP un +ΔP ur =k u,t ΔP u,t +k un,t ΔP un,t +k ur,t ΔP ur,t

Where: ΔP u is the regulation of normal regulatory domain, ΔP un is the regulation of abnormal regulatory domain, ΔP ur is the regulation of emergency regulatory domain, k u,t is the decision coefficient of normal regulatory domain, ΔP u,t is within the normal regulatory domain The adjustment quantity, k un,t is the decision coefficient of the abnormal regulation domain, ΔP un,t is the regulation quantity in the abnormal regulation domain, k ur,t is the decision coefficient of the emergency regulation domain, ΔP ur,t is the emergency regulation domain The amount of adjustment available.
The method according to any one of claims 1 to 5, wherein the discriminant expression for discriminating the power system operating point inside or outside the control plane is as follows:

In the case of margin=Yes, the power system operating point is outside the control plane; in the case of margin=No, the power system operating point is inside the control plane;

Where: margin is the system adequacy, k u,t is the decision coefficient of the normal regulatory domain, ΔP u,t is the adjustment amount in the normal regulatory domain, k un,t is the decision coefficient of the abnormal regulatory domain, ΔP un,t For the regulation quantity in the abnormal regulation domain, k ur,t is the decision coefficient of the emergency regulation domain, ΔP ur,t is the adjustment amount in the emergency regulation domain, and |ΔP balance | is the demand value of the balance adjustment amount.
The method of any of claims 1-6, wherein the expression of the "source-load domain" coordinated regulation optimization model is as follows:

minΔP k,t =k u,t ΔP u,t +k un,t ΔP un,t +k ur,t ΔP ur,t

Where: ΔP k,t is the total amount of “source-load domain” regulation, χ is the multi-domain conversion criterion, χ un is the criterion for the transition from the normal regulatory domain to the abnormal regulatory domain, and χ ur is converted from the abnormal regulatory domain to The criterion of the emergency regulation domain, k u,t is the decision coefficient of the normal regulatory domain, ΔP u,t is the regulation quantity in the normal regulatory domain, k un,t is the decision coefficient of the abnormal regulation domain, ΔP un,t is abnormal The regulation quantity in the regulatory domain, k ur,t is the decision coefficient of the emergency regulation domain, and ΔP ur,t is the adjustment amount in the emergency regulation domain.
The method according to any one of claims 2 to 7, wherein the X-axis of the "source-load domain" coordinated control space is a normal regulatory domain, the Y-axis is an abnormal regulatory domain, and the Z-axis is an emergency regulatory domain.
The method according to claim 8, wherein the normal regulation domain is regulated by hydropower and thermal power, and the grid is in the normal regulation of the waist load and the peak period, the waist load period, the minimum output of the water and power band, and the thermal power is the main peak frequency modulation or contact. Line, the upper load stage, mainly based on the addition of thermal power, fine-tuning of hydropower, under the load phase, mainly to reduce thermal power, fine-tuning of hydropower.
The method according to claim 8 or 9, wherein in the case that the power grid is in an abnormal operating state, the heat storage and battery regulation strategy is activated: when the power grid is in the lumbar load period, the battery energy storage is started first, and then the power generation is started. Plant-side electric heat storage and distributed electric heat storage; in the case that the grid is in a period of low valley load drop, first start distributed electric heat storage, then start power storage heat storage at the power plant and battery energy storage; In the case, the power storage heat of the power plant is first withdrawn, and the distributed electric heat storage is successively withdrawn according to the heat storage capacity.
The method according to claim 8, 9 or 10, wherein in the case that the power grid is in an emergency running state, the clean energy power generation and power limiting strategy is activated, and the power is regulated according to the order of nuclear power, wind power, photovoltaic, and transferable load, and the power grid is urgently operated. The state recovery process is regulated in the order of transferable load, photovoltaic, wind power and nuclear power.
An electronic device comprising:

At least one processor;

a memory, set to store at least one program,

The at least one program is executed by the at least one processor such that the at least one processor implements the method of any of claims 1-11.
A computer readable storage medium storing computer executable instructions for performing the method of any of claims 1-11.