A power system elasticity planning scheme multi-element benefit analysis method and system

Abstract

The application discloses a kind of power system elasticity planning scheme multi-element benefit analysis method and system, obtain new type power system planning scheme;The extreme event response capability of new type power system planning scheme is evaluated within the set year limit, and elasticity index is obtained;The obtained new type power system planning scheme is accounted and estimated using carbon emission flow method, and carbon emission benefit index is obtained;For the implementation cost of the obtained new type power system planning scheme, the construction cost of power facilities and the cost of station building, line reinforcement or modification are calculated, and economic index is obtained;Comprehensive elasticity index, carbon emission and economic index, under the new type power system planning scheme evaluation decision-making framework facing elasticity improvement, different planning schemes are evaluated and compared, decision-making closed loop is formed, planning scheme is fed back and corrected, new type power system construction and adaptability planning under climate change are realized.For improving investment decision, scientific decision basis is provided.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power system planning and technical economic analysis, and particularly relates to a multi-element benefit analysis method and system for power system elasticity planning scheme. BACKGROUND

[0002] At present, the research on the evaluation and decision of the new power system planning scheme is not deep enough, and the planning scheme decision considering both the conventional operation and the response to extreme events is still in blank. The decision of the traditional power system planning scheme is mainly based on the economic and technical analysis in the conventional operation scene. The new power system planning scheme facing the elasticity improvement needs to consider both the conventional operation and the response to extreme events, and how to make a reasonable planning scheme analysis and decision is the key problem to be solved in the new power system planning facing the elasticity improvement. Therefore, it is necessary to research a new cost-benefit analysis and evaluation decision method for the elasticity planning scheme of the new power system. SUMMARY

[0003] The technical problem to be solved by the application is to provide a multi-element benefit analysis method and system for power system elasticity planning scheme in view of the deficiencies in the prior art, to evaluate the new power system planning scheme from the aspects of elasticity, carbon emission reduction and economic efficiency, and to solve the technical problem that the robust / random planning of the traditional planning cannot consider multiple complex scenes such as elasticity and carbon benefit at the same time, and to provide a scientific decision basis for improving the investment decision.

[0004] The application adopts the following technical scheme:

[0005] A multi-element benefit analysis method for power system elasticity planning scheme comprises the following steps:

[0006] Obtain a new power system planning scheme;

[0007] Perform extreme event response capability evaluation on the obtained new power system planning scheme within a set year limit through extreme event simulation, component vulnerability analysis, system response behavior analysis and elasticity index calculation, to obtain an elasticity benefit index;

[0008] Use the carbon emission flow method to calculate and estimate the low-carbon cost of the power system construction, source measurement, load side and network side within the planning period for the obtained new power system planning scheme, to obtain a carbon emission index;

[0009] Calculate the power facility construction cost and the station building, line reinforcement or modification cost for the implementation cost of the obtained new power system planning scheme, to obtain an economic index;

[0010] The comprehensive elasticity index, carbon emission and economic index are used to evaluate and select different planning schemes in the decision-making framework of the new power system planning scheme facing elasticity improvement, to form a closed loop of decision-making, to feedback and correct the planning scheme, and to realize the construction of the new power system and the adaptive planning under climate change.

[0011] Preferably, the new power system planning scheme is specifically obtained by:

[0012] The planning period considered in the planning scheme;

[0013] The planning capacity, access location and construction year of each type of generator unit;

[0014] The planning capacity, access location and construction year of each type of energy storage device;

[0015] The planning location, line capacity and line construction year of the transmission corridor;

[0016] The planning location and station construction year of the substation;

[0017] The estimated typical load data in the planning year;

[0018] The typical daily operation mode of the power system in the planning year.

[0019] Preferably, the new power system planning scheme is evaluated to obtain the elasticity index, which is specifically:

[0020] For extreme event simulation, the influence of the extreme event is simulated through the frequency, location, duration and disaster intensity characteristics of the extreme event, a set of computer-simulated extreme event scenarios are generated, and the disaster intensity at each disaster site is analyzed and calculated for each simulated extreme event scenario; based on historical disaster data, key parameters representing the extreme event are analyzed and selected, a probability distribution model or an extreme regression model of the key parameters of the extreme event is established to depict the uncertainty of the extreme event, and hypothesis testing is performed on the model to verify the goodness of fit; for each simulated year in the planning period, the number of disasters is sampled based on the annual frequency distribution, and for each disaster scenario, the initial state of the simulated disaster is obtained by sampling other key parameters, and the parameters are converted into dynamic disaster scenarios with spatial and temporal characteristics through meteorological or geographical models;

[0021] For element vulnerability analysis, the failure rate of the elements in the power system is calculated based on the disaster scenarios generated in the extreme event simulation and the vulnerability curve of the power system elements, random numbers are used to sample the failure state of each element, and it is determined whether each element in the power system fails under the corresponding disaster scenario;

[0022] For system response behavior analysis, the response process of the power system to extreme disasters is described, and an emergency control and repair model for the power system to respond to extreme events is established to simulate the system restoration process.

[0023] For elasticity index calculation, the risk loss is defined as the weighted load loss and repair cost of the system during the entire disaster, the risk value of the selected loss and the tail value at risk are used as the specific elasticity index, the Monte Carlo method is used to simulate the economic loss caused each year, and the index convergence is realized by simulating year by year within the planning year.

[0024] Preferably, the elasticity quantitative index VaR α (X) and the tail value at risk TVaR α (X) are calculated as follows:

[0025] VaR α (X) = inf{x: P(X≤x)≥α}

[0026]

[0027] Where, inf{·} is the lower bound, P(·) is the probability of event occurrence, α is the set confidence level, X is the annual risk loss, and x is the risk loss auxiliary parameter under the given confidence level α.

[0028] Preferably, the annual risk loss X is:

[0029]

[0030] Where, Λ is the total number of passing typhoons, is the set of fault lines and fault nodes under the rth disaster, is the repair or reconstruction cost of the equipment corresponding to element k, is the load loss economic loss of node i, d i,r is the load loss time of node i during the rth typhoon.

[0031] Preferably, the carbon emission index is calculated and estimated for the new power system planning scheme, and the specific carbon emission index is:

[0032] For each planning year within the planning period, the construction and commissioning of units, energy storage, lines and stations in the year are determined, and the carbon emission levels of raw materials, production and installation during the construction of power facilities are converted;

[0033] For the direct carbon emission of the source side generation, the direct carbon emission of different power plants in the source side of the power system under the typical daily operation mode is used as the characterization, and the carbon emission generated by the unit power generation is converted by the power generation carbon emission factor;

[0034] For the indirect carbon emissions of the load side, the direct carbon emissions generated at the source side corresponding to the user's electricity consumption behavior under the typical day operation mode are used as the representation, and the unit indirect carbon emissions of the users belonging to each node are converted by the node carbon emission factor;

[0035] For the indirect carbon emissions of the network side network loss: the cumulative amount of coupled carbon emissions in the power flow corresponding to the network loss under the typical day operation mode is used for conversion through the carbon flow rate, including branch carbon flow rate and network loss carbon flow rate. The branch carbon flow rate is the indirect carbon emissions per unit time flowing through the branch with the power flow, and the network loss carbon flow rate represents the indirect carbon emissions per unit time attached to the network loss of the power flow;

[0036] Add up the carbon emissions of power facility construction, direct carbon emissions of source side power generation, indirect carbon emissions of load side electricity consumption, and indirect carbon emissions of network side network loss in each year of the planning period to obtain the carbon emission level of the new power system planning scheme in the planning period.

[0037] Quantify the low-carbon cost, including low-carbon investment cost and low-carbon loss cost. The low-carbon investment cost is estimated according to the initial investment of equipment, technology and related operation activity cost, and the low-carbon loss cost is the cost paid for emitting carbon dioxide.

[0038] Preferably, the low-carbon loss cost is:

[0039]

[0040] Where D G is the carbon emission quota, is the carbon trading price, E power is the carbon emissions generated by fuel consumption in the power system.

[0041] Preferably, the power facility construction cost and the station building, line reinforcement or reconstruction cost are calculated to obtain the economic indicators, which are specifically:

[0042] For power facility construction and configuration, the production, operation, maintenance and disposal costs in the planning period are calculated, and the power facilities include generator units, energy storage, lines and stations. For station building, line reinforcement, strengthening, reconstruction or construction standard improvement, the fixed investment cost and operation and maintenance cost are calculated.

[0043] Preferably, different planning schemes are evaluated and compared to form a decision-making closed loop, which is specifically:

[0044] On the basis of the evolution trend of extreme events, the planning scheme is developed through extreme event impact analysis;

[0045] The planning scheme to be taken is evaluated in terms of flexibility index, carbon emission index and economic index;

[0046] The planning schemes to be taken are compared and selected under a given economic budget, the Pareto optimal scheme is screened and implemented, and the implemented strategy is monitored and the effect is post-evaluated in the system operation, forming a decision-making closed loop.

[0047] In a second aspect, the embodiment of the present application provides a power system resilience planning scheme multi-element benefit analysis system, comprising:

[0048] The planning module acquires a new power system planning scheme;

[0049] The resilience module performs extreme event response capability evaluation on the new power system planning scheme within a set year limit through extreme event simulation, element vulnerability analysis, system response behavior analysis and resilience index calculation, and obtains a resilience benefit index;

[0050] The carbon emission module adopts a carbon emission flow method to account and estimate the low-carbon cost of the power system construction, source measurement, load side and network side within the planning period for the new power system planning scheme, and obtains a carbon emission index;

[0051] The economic module calculates the power facility construction cost and the station building, line reinforcement or modification cost for the implementation cost of the new power system planning scheme, and obtains an economic index;

[0052] The analysis module comprehensively analyzes the resilience index, the carbon emission and the economic index, evaluates and selects different planning schemes under the new power system planning scheme evaluation and decision-making framework facing resilience improvement, forms a decision-making closed loop, feeds back and corrects the planning scheme, and realizes the new power system construction and the adaptability planning under climate change.

[0053] In a third aspect, a computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the power system resilience planning scheme multi-element benefit analysis method when executing the computer program.

[0054] In a fourth aspect, the embodiment of the present application provides a computer readable storage medium comprising a computer program, and the computer program implements the steps of the power system resilience planning scheme multi-element benefit analysis method when executed by a processor.

[0055] Compared with the prior art, the present application has at least the following beneficial effects:

[0056] The method can quantitatively depict advantages and disadvantages between different planning schemes, balance economy and various benefit indexes, and provide scientific reference for practical problems such as new energy access, expansion planning arrangement, operation mode optimization, and investment decision improvement.

[0057] Further, a complete process of planning scheme elasticity benefit evaluation considering uncertainty of long-period extreme event occurrence and development is established, including extreme event simulation, element vulnerability analysis, system response behavior analysis, and elasticity index calculation. In the extreme event simulation link, the method depicts uncertainty of characteristic parameters such as extreme event occurrence frequency, position, duration, and disaster intensity in each simulation year through establishment of a probability distribution model or an extreme value regression model of key parameters of the extreme event, and converts the parameters into dynamic disaster scenarios with space-time characteristics through a meteorological or geographical model. Year-by-year simulation in the planning year realizes convergence of the implementation index, and realizes simulation of the system bearing the extreme event scenario in a long period. In the system response behavior analysis link, the method considers emergency control and emergency repair, and can accurately simulate the system response recovery process. In the index calculation link, the method uses the risk value of annual loss and the tail value at risk as quantitative indexes, realizes convergence of the indexes through year-by-year simulation in the planning year, and realizes probabilistic evaluation of the system disaster risk under the planning scheme.

[0058] Further, a process of planning scheme carbon emission benefit evaluation is established, and a carbon emission accounting method of different levels of source, network and load is given, considering low-carbon input cost and low-carbon loss cost, to realize accurate and comprehensive carbon emission benefit calculation.

[0059] Further, an evaluation process of planning scheme economy is established, considering construction cost of power facilities such as generating units, energy storage and lines, and station building, line reinforcement or modification cost, to quantitatively and comprehensively calculate economic cost of the new power system planning scheme.

[0060] It can be understood that the beneficial effects of the above-mentioned second aspect can be referred to the related description in the above-mentioned first aspect, which will not be repeated here.

[0061] In summary, the method of the present application establishes a scientific and complete evaluation method of planning scheme elasticity, carbon emission and economy, considers uncertainty of extreme event occurrence and development in a long period and realizes probabilistic evaluation of elasticity benefit, and quantitatively calculates carbon emission of source, network and load at all levels. The method can quantitatively depict advantages and disadvantages between different planning schemes, balance economy and various benefit indexes, and provide scientific reference for practical problems such as new energy access, expansion planning arrangement, operation mode optimization, and investment decision improvement.

[0062] The technical solutions of the present application are described in further detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 Flow chart for elasticity benefit analysis of new power system planning scheme;

[0064] Figure 2 Visual display for typhoon disaster process simulation;

[0065] Figure 3 Sampling schematic diagram of power system element failure under disaster scenario;

[0066] Figure 4 Schematic diagram of evaluation and decision framework for new power system planning scheme aiming at elasticity improvement;

[0067] Figure 5 Schematic diagram of computer device provided by an embodiment of the present application;

[0068] Figure 6 Block diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0069] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative work fall within the scope of protection of the present application.

[0070] In the description of the present application, it should be understood that the terms “include” and “contain” indicate the existence of described features, whole, steps, operations, elements and / or components, but do not exclude the existence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof.

[0071] It should also be understood that the terms used in the present application specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clearly indicated by the context, the singular forms “a”, “an” and “the” are intended to include the plural forms.

[0072] It should be further understood that the term "and / or" used in the description and claims of the application herein is used to mean any one and / or any combination of the associated listed items in the term in which it is used, and includes all possible combinations, whether explicitly stated or not. For example, A and / or B can mean, in the terms of this and similar items in the claims, A alone, B alone, A and B in combination, or any combination of the items A and B. In addition, the character " / " in the present application generally represents an "or" relationship between the front and rear associated objects.

[0073] It should be understood that, although the terms first, second, third, etc. can be employed in the embodiments of the application to describe various ranges, etc., these ranges should not be limited to these terms. These terms are only used to distinguish one range from another. For example, a first range can also be referred to as a second range, and similarly, a second range can also be referred to as a first range, without departing from the scope of the embodiments of the application.

[0074] Depending on the context, the word "if" as used herein can be interpreted to mean "when" or "while" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined" or "if (a stated condition or event) is detected" can be interpreted to mean "when it is determined" or "in response to determining" or "when (the stated condition or event) is detected" or "in response to detecting (the stated condition or event)".

[0075] Various structural diagrams according to the disclosed embodiments of the application are shown in the accompanying drawings. These drawings are not drawn to scale, in which certain details are exaggerated for the purpose of clarity and certain details can be omitted. The shapes of various regions, layers and their relative sizes and positional relationships shown in the drawings are only exemplary, and in actuality, they can deviate due to manufacturing tolerances or technical limitations, and regions / layers with different shapes, sizes and relative positions can be additionally designed by those skilled in the art according to actual needs.

[0076] The application provides a multi-element benefit analysis method for power system resilience planning scheme.

[0077] The application provides a multi-element benefit analysis method for power system resilience planning scheme.

[0078] S1, acquiring a new power system planning scheme, and determining a planning period, construction and production plans of units, energy storage, lines and stations in the planning scheme, typical load data estimated in a planning year, and typical daily operation modes in the planning year;

[0079] The new power system planning scheme is acquired, and the following data is sorted out:

[0080] S101, a planning period considered by the planning scheme;

[0081] S102, planning capacity, access location, construction year of each type of generator set such as new energy and flexible thermal power;

[0082] S103, planning capacity, access location, construction year of each type of energy storage device such as pumped storage and battery;

[0083] S104, planning location of transmission corridor, line capacity, line construction year;

[0084] S105, planning location of substation, station construction year;

[0085] S106, estimated typical load data in the planning year;

[0086] S107, typical daily operation mode of the power system in the planning year.

[0087] S2, for the flexibility improvement benefit of the planning scheme, evaluate through four links of extreme event simulation, component vulnerability analysis, system response behavior analysis and flexibility index calculation;

[0088] S201, for extreme event simulation, simulate the influence of extreme events through the characteristics of extreme event occurrence frequency, location, duration and disaster intensity, generate a large set of computer simulated extreme event scenarios, and for each simulated extreme event scenario, analyze and calculate the disaster intensity at each disaster site. Based on historical disaster data, analyze and select key parameters (frequency, intensity, duration, etc.) that can represent extreme events, establish a probability distribution model or extreme value regression model of extreme event key parameters to depict the uncertainty of extreme events, and perform hypothesis testing on the model to verify the goodness of fit. For each simulation year in the planning period, based on the annual frequency distribution, sample the number of disasters, for each disaster scenario, sample other key parameters to obtain the initial state of the simulated disaster, and convert the parameters into dynamic disaster scenarios (typhoon moving path, heavy rainfall process, etc.) with spatio-temporal characteristics through meteorological or geographical models.

[0089] Taking typhoon disaster as an example, first, use the best path data set of tropical cyclones in the Northwest Pacific to perform moment estimation, maximum likelihood estimation and interval estimation on the parameters in the probability distribution of five key parameters of typhoon, including annual occurrence rate, shortest distance, central pressure difference, moving speed and moving direction, and perform hypothesis testing on the probability model through the goodness of fit test method;

[0090] Second, integrate the probability distribution model of key parameters and the typhoon wind field and filling model to construct a typhoon simulation generator, which can generate typhoon passing scenarios with a certain disaster intensity according to a certain probability distribution. Subsequent model instances are based on typhoon disaster scenarios, as shown in Figure 2 .

[0091] S202, for element vulnerability analysis, based on the disaster scenario generated in the extreme event simulation and the vulnerability curve of the power system element, the failure rate of the element in the power system is calculated, and the failure state of each element is sampled by generating random numbers to determine whether each element in the power system fails under the corresponding disaster scenario.

[0092] Taking the vulnerability analysis of power cables under typhoon disaster as an example, the reliability function R(t) of the line during the typhoon passage is an exponential function with the failure rate λ(t) integrated with respect to time. Since the typhoon simulator generates typhoon information data with hourly time resolution, the failure rate of the line within each hour is considered to be a constant, so the availability function of the line during the typhoon passage is a piecewise exponential function. Combining the continuity property of the reliability curve, the availability function of the line during the typhoon passage can be written as:

[0093]

[0094] where the integral constant is determined by C k =R(t k ). The forced outage rate function of the line during the typhoon passage is:

[0095]

[0096] where C k =1-F(t k ). Figure 3 The schematic diagram of the forced outage rate function curve during the typhoon passage is shown.

[0097] According to the inverse function method, the random outage time of the line in the typhoon passage scenario is determined. The specific method is as follows: a uniformly distributed random number u~U[0,1] in the interval [0,1] is randomly generated, and the time t down corresponding to u=F(t down ) is determined, which is the random outage time of the line. For each line, the random outage time during the typhoon passage can be determined according to the above method. If the outage time of the line is greater than the departure time of the typhoon, the line will not be affected by the typhoon and will not fail during this typhoon scenario.

[0098] S203, for system response behavior analysis, the response process of the power system to extreme disasters is described, the emergency control and repair model of the power system to extreme events is established, and the simulation of the system outage and restoration process is realized, which includes:

[0099] During the disaster, control measures such as fault identification, isolation and load recovery are taken to reduce the impact of the disaster; after the disaster, repair personnel are dispatched to find and remove faults and quickly restore power supply.

[0100] Taking the response process of the new power distribution system under typhoon disaster as an example, the specific process is as follows:

[0101] 1) During the disaster, manual on-site operation cannot be performed due to safety problems, and control is completed through the power distribution automation system, including FTU, DTU and other elements collecting fault information and operating the state of remote switches;

[0102] 2) After the disaster, the line patrol task or repair task is assigned to the standby operation and maintenance personnel, wherein the line patrol task content is to go to the fault area according to the fault indication, confirm the area state, and the repair task content is to repair the fault equipment and remove the fault;

[0103] 3) When a fault area is confirmed to have no fault, the operation and maintenance personnel restore the power supply of the area through manual switches or remote switches and narrow down the fault range;

[0104] 4) When the fault point in the fault section is removed, the remote switch and the manual switch are operated to restore the power supply of the fault area, and the process is repeated until the system returns to normal power supply.

[0105] S204, for the calculation of the elasticity index, define the risk loss as the weighted load loss and maintenance cost of the system in the whole disaster, and the risk value (Value at Risk, VaR) and the tail value at risk (Tail Value at Risk, TVaR) of the selected loss are used. The economic loss caused each year is simulated by using the Monte Carlo method, and the convergence of the index is realized by planning the simulation year by year.

[0106] The calculation formula of annual risk loss X is as follows:

[0107]

[0108] Wherein, Λ is the total number of passing typhoons, is the set of fault lines and fault nodes under the rth disaster, is the maintenance or reconstruction cost of the equipment corresponding to element k, is the load loss economic loss of node i, d i,r is the load loss time of node i during the rth typhoon.

[0109] The calculation formula of the annual risk loss, the elasticity quantitative index VaR and TVaR is as follows:

[0110] VaR α(X) = inf{x: P(X≤x)≥α} (4)

[0111]

[0112] Where, inf{·} represents the lower bound, P(·) represents the probability of event occurrence, and a represents the set confidence level.

[0113] S3, for the carbon emission reduction benefit of the planning scheme, the carbon emission flow method is used to calculate and estimate the low-carbon cost of the power system construction, source measurement, load side, and network side in the planning period;

[0114] S301, for each planning year in the planning period, determine the construction and commissioning of units, energy storage, lines, stations, etc. in the year, and convert the carbon emission level of raw materials, production, and installation in the process of power facility construction;

[0115] S302, for the direct carbon emission of the source side power generation, the direct carbon emission of different power plants in the source side of the power system under the typical day operation mode is used to characterize, and the carbon emission generated by the unit power generation is converted by the power generation carbon emission factor;

[0116] S303, for the indirect carbon emission of the load side power consumption, the direct carbon emission generated by the user power consumption behavior in the source side under the typical day operation mode is used to characterize, and the indirect carbon emission per unit of the user at each node is converted by the node carbon emission factor;

[0117] S304, for the indirect carbon emission of the network side network loss: the cumulative amount of coupled carbon emission in the power flow corresponding to the network loss under the typical day operation mode is used, and the carbon flow rate is converted, including branch carbon flow rate and network loss carbon flow rate. The branch carbon flow rate is the indirect carbon emission per unit time flowing through the branch with the power flow, and the network loss carbon flow rate represents the indirect carbon emission per unit time attached to the network loss of the power flow;

[0118] S305, add the carbon emission of power facility construction, the direct carbon emission of source side power generation, the indirect carbon emission of load side power consumption, and the indirect carbon emission of network side network loss in each year in the planning period, and the carbon emission level of the new type power system planning scheme in the planning period can be obtained;

[0119] S306, quantify the low-carbon cost, which consists of low-carbon investment cost and low-carbon loss cost. The low-carbon investment cost can be estimated according to the initial investment of equipment, technology and related operation activity cost, and the low-carbon loss cost is the cost paid for the emission of carbon dioxide.

[0120] The calculation method is as follows:

[0121]

[0122] Where, For low-carbon loss cost, D G For carbon emission quota, For carbon trading price.

[0123] S4, for the implementation cost of the planning scheme, the construction cost of the power facilities such as computer group, energy storage, line and station, and the cost of station building, line reinforcement or reconstruction;

[0124] S401, for the construction and configuration of power facilities such as generator group, energy storage, line and station, calculate the cost of production, operation, maintenance and disposal in the planning period;

[0125] S402, for the station building, line reinforcement, strengthening, reconstruction or construction standard improvement, calculate the fixed investment cost and operation and maintenance cost.

[0126] S5, comprehensive elasticity, carbon emission, economy three kinds of indexes, in the new type electric power system planning scheme evaluation decision-making framework facing the elasticity improvement, different planning schemes are evaluated and compared, and a decision-making closed loop is formed.

[0127] S501, on the basis of extreme event evolution trend judgment, the planning scheme is formulated through extreme event influence analysis;

[0128] S502, for the planning scheme to be taken, the elasticity, carbon emission, economy three kinds of indexes are evaluated according to steps S1-S4;

[0129] S503, under the given economic budget, the planning scheme to be taken is compared and selected, the Pareto optimal scheme is screened for implementation, and the implemented strategy is monitored and the effect is evaluated in the system operation, so as to form a decision-making closed loop.

[0130] Those skilled in the art can understand that various aspects of the present application can be implemented as a system, a method or a program product. Therefore, various aspects of the present application can be specifically implemented as follows, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which can be collectively referred to as "circuit", "module" or "platform" here.

[0131] In another embodiment of the present application, a power system elasticity planning scheme multi-element benefit analysis system is provided, which can be used to realize the power system elasticity planning scheme multi-element benefit analysis method described above. Specifically, the power system elasticity planning scheme multi-element benefit analysis system includes a planning module, an elasticity module, a carbon emission module, an economic module and an analysis module.

[0132] The planning module acquires a new type electric power system planning scheme;

[0133] The elasticity module is configured to evaluate the extreme event response capability of the new power system planning scheme within a set year limit through extreme event simulation, element vulnerability analysis, system response behavior analysis and elasticity index calculation, and to obtain an elasticity benefit index.

[0134] The carbon emission module is configured to calculate and estimate the low-carbon cost of the power system construction, source measurement, load side and network side within the planning period for the new power system planning scheme by using a carbon emission flow method, and to obtain a carbon emission index.

[0135] The economic module is configured to calculate the power facility construction cost and the station building, line reinforcement or modification cost for the implementation cost of the new power system planning scheme, and to obtain an economic index.

[0136] The analysis module is configured to evaluate and compare different planning schemes under the new power system planning scheme evaluation and decision-making framework for elasticity improvement, to form a decision-making closed loop, to feed back and correct the planning scheme, and to realize the adaptability planning of the new power system construction and climate change.

[0137] In another embodiment of the present application, a terminal device is provided, which comprises a processor and a memory, the memory is used to store a computer program, the computer program comprises program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to realize the corresponding method flow or corresponding function. The processor in the embodiment of the present application can be used for the operation of the power system elasticity planning scheme multi-element benefit analysis method, including:

[0138] The new power system planning scheme is obtained; the extreme event response capability of the new power system planning scheme in a setting year limit is evaluated through extreme event simulation, component vulnerability analysis, system response behavior analysis and elasticity index calculation, and elasticity benefit indexes are obtained; the low-carbon cost of power system construction, source measurement, load side and network side in a planning period is calculated and estimated by using a carbon emission flow method, and the obtained new power system planning scheme is accounted, and carbon emission indexes are obtained; the economic indexes are obtained by calculating the construction cost of power facilities and the cost of station building, line reinforcement or modification according to the implementation cost of the obtained new power system planning scheme; the elasticity indexes, carbon emission and economic indexes are comprehensively evaluated and compared in the new power system planning scheme evaluation decision-making framework facing elasticity improvement, different planning schemes are evaluated and compared, a decision-making closed loop is formed, the planning scheme is fed back and corrected, and the new power system construction and adaptive planning under climate change are realized.

[0139] In another embodiment of the present application, the present application also provides a storage medium, specifically a computer readable storage medium (Memory), which is a memory device in a terminal device, used for storing programs and data. It can be understood that the computer readable storage medium here can include the built-in storage medium in the terminal device, and of course can also include the expansion storage medium supported by the terminal device, and can be any tangible medium containing or storing programs, which can be used by or in combination with an instruction execution system, device or apparatus. The computer readable storage medium provides a storage space, which stores the operating system of the terminal. Moreover, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and the instructions can be one or more computer programs (including program codes). It should be noted that more specific examples (non-exhaustive list) of the computer readable storage medium include an electrical connection with one or more conductive wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0140] Computer readable storage media further includes data signals transported through a carrier wave and a propagation medium comprising or storing the program code. These data signals can be transferred using any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, and the like, or any suitable combination of the foregoing.

[0141] The program code can be implemented in any of a variety of programming languages, including object-oriented programming languages such as Java, C++, and the like, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computing device, partly on the user's computing device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device or entirely on the remote computing device or server. In the latter scenario, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computing device, such as through the Internet using an Internet Service Provider (ISP).

[0142] The one or more instructions stored in the computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the method for multi-element benefit analysis of power system resilience planning scheme in the above embodiments; the one or more instructions stored in the computer-readable storage medium are loaded and executed by the processor to implement the following steps:

[0143] A new power system planning scheme is obtained; the obtained new power system planning scheme is evaluated for extreme event response capability within a set period of time through extreme event simulation, element vulnerability analysis, system response behavior analysis, and resilience index calculation, to obtain a resilience benefit index; the obtained new power system planning scheme is calculated and estimated for low-carbon cost of power system construction, source measurement, load side, and network side within a planning period by using a carbon emission flow method, to obtain a carbon emission index; the implementation cost of the obtained new power system planning scheme is calculated for power facility construction cost and station building, line reinforcement or modification cost, to obtain an economic index; the resilience index, the carbon emission index, and the economic index are comprehensively evaluated, different planning schemes are compared and selected under a new power system planning scheme evaluation and decision-making framework facing resilience improvement, to form a decision-making closed loop, the planning scheme is fed back and corrected, and adaptive planning of new power system construction and climate change is realized.

[0144] Please refer to Figure 5 , the terminal device is a computer device, the computer device 60 of the embodiment includes a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61, and the computer program 63 implements the method for calculating the fluid composition in the reservoir stimulation wellbore in the embodiment when executed by the processor 61. To avoid repetition, details are not repeated here. Alternatively, the computer program 63 implements the functions of each model / unit in the system for calculating the fluid composition in the reservoir stimulation wellbore in the embodiment when executed by the processor 61. To avoid repetition, details are not repeated here.

[0145] The computer device 60 can be a desktop computer, a notebook computer, a palm computer, and a cloud server, etc. The computer device 60 can include, but is not limited to, the processor 61 and the memory 62. Those skilled in the art can understand that Figure 5 The computer device 60 is only an example and does not constitute a limitation on the computer device 60, and can include more or fewer components than shown, or combine certain components, or different components, for example, the computer device can also include an input / output device, a network access device, a bus, etc.

[0146] The processor 61 can be a central processing unit (CPU), and can also be other general-purpose processors, central processors, graphics processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, quantum computing-based data processing logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0147] The memory 62 can be an internal storage unit of the computer device 60, such as a hard disk or a memory of the computer device 60. The memory 62 can also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0148] Further, the memory 62 can include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0149] Any reference to memory, database, or other medium in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. The non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include Random Access Memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), etc.

[0150] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0151] Please refer to Figure 6 The terminal device 600 is an electronic device, which is in the form of a general computing device. The components of the electronic device can include but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components including the storage unit 620 and the processing unit 610, a display unit 640, etc.

[0152] The storage unit stores program codes which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present application described in the above method part of the present specification. For example, the processing unit 610 can perform the steps as shown in the above method part of the present specification. Figure 1

[0153] The storage unit 620 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 6201 and / or a cache memory 6202, and can further include a read-only memory (ROM) 6203.

[0154] The storage unit 620 can further include a program / utility 6204 having a set of programs / modules 6205, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or a combination thereof, which can include implementation of a network environment.

[0155] The bus 630 can represent one or more of several types of bus structures, including a storage unit bus or bus controller, a peripheral bus, a graphics acceleration port, a processing unit bus, or a local bus using any of a variety of bus architectures.

[0156] The electronic device 600 can also communicate with one or more external devices 700 such as a keyboard or pointing device, a Bluetooth device, etc.; user interfaces and / or peripheral devices such as a printer, scanner, or the like; and / or one or more devices in a communications system. Communication with one or more devices can occur via an input / output (I / O) interface 650. Still yet, the electronic device 600 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet) via a network adapter 660. As depicted, the network adapter 660 can communicate with the other components of the electronic device 600 via the bus 630. It should be appreciated that the network adapter 660 and / or the bus 630 can be implemented using one or more types of communication media, such as IO devices, I / O device adapters, wireless links, wires, cables, and the like, including bus communication to one or more other buses.

[0157] ​For the purposes, technical solutions and advantages of the embodiments of the present application to be clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0158] In order to simulate the proposed multi-element benefit analysis method for power system resilience planning, a simulation environment is designed to simulate the performance of different planning schemes in terms of extreme events, component vulnerability, system response, carbon emissions and economic efficiency using computer software and algorithms. The following is a simplified simulation process example:

[0159] 1. Initialization and data preparation

[0160] Define system parameters: including the basic structure of the power system (such as power grid topology, power plant type and distribution, load points, etc.), device parameters (such as generator capacity, transmission line capacity and impedance, etc.).

[0161] Planning scheme input: prepare multiple new power system planning schemes, including different power supply configurations, expansion planning, energy storage configuration schemes, etc.

[0162] 2. Extreme event simulation

[0163] Simulate the impact of extreme events: simulate the impact of extreme events by their frequency, location, duration, and intensity, generate a large set of computer-simulated extreme event scenarios, and for each simulated extreme event scenario, analyze and calculate the disaster intensity at each affected location.

[0164] 3. Component vulnerability analysis and system response

[0165] Vulnerability analysis: based on historical data and expert knowledge, assess the failure probability and severity of each component under extreme events.

[0166] System response simulation: simulate the remote control and on-site repair response measures of the system after the extreme event (such as remote topology reconstruction, manual switch operation, fault repair, etc.), and record the system recovery process.

[0167] 4. Resilience index calculation

[0168] Define resilience indicators: Define risk loss as the weighted loss of load and repair costs during the entire disaster. The specific resilience indicators are selected as the value at risk and the tail value at risk of the loss.

[0169] Calculate resilience indicators: Use the Monte Carlo method to simulate the economic losses caused each year, and achieve convergence of the indicators by simulating year by year within the planning year.

[0170] 5. Carbon emissions and low-carbon cost accounting

[0171] Carbon emission flow model: Establish a carbon emission model for the entire life cycle of the power system, including the construction phase, operation phase, and decommissioning phase of carbon emissions.

[0172] Low-carbon cost accounting: According to the carbon emission flow model, combined with the carbon emission right transaction price or carbon tax policy, calculate the low-carbon cost of each planning scheme.

[0173] 6. Economic evaluation

[0174] Cost calculation: Including the construction cost of power facilities, the cost of station building and line reinforcement or modification, operation and maintenance cost, etc.

[0175] Economic indicators: Calculate the total cost, investment recovery period, net present value, and other economic indicators of each planning scheme.

[0176] 7. Comprehensive evaluation and decision-making

[0177] Build evaluation framework: Combine resilience indicators, carbon emission indicators, and economic indicators to build a new power system planning scheme evaluation and decision-making framework for resilience improvement.

[0178] Scheme comparison: Use the Pareto multi-objective method to comprehensively evaluate and compare different planning schemes.

[0179] Feedback correction: According to the evaluation results, feedback correction is made to the planning scheme to optimize the scheme design.

[0180] 8. Result output and visualization

[0181] Generate evaluation report: Organize the simulation results to generate a detailed evaluation report, including comparison charts of resilience, carbon emissions, and economic indicators of each planning scheme, comprehensive evaluation ranking, etc.

[0182] Visual display: Use charts, maps, and other forms to visually display key information such as the performance of different planning schemes under extreme events, carbon emission distribution, and economic cost.

[0183] Through the above simulation process, the comprehensive benefits of different new power system planning schemes in terms of resilience, carbon emissions, and economic efficiency can be systematically evaluated, providing scientific basis for decision-makers.

[0184] In summary, the power system elasticity planning scheme multi-element benefit analysis method and system can comprehensively evaluate the planning scheme of the new power system from the three indexes of elasticity, carbon emission and economy, and provide scientific reference for the actual problems such as the access of new energy of the system, the arrangement of expansion planning, the optimization of operation mode, and the improvement of investment decision.

[0185] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit or module in the embodiment can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit or module are only for easy distinction, and do not limit the protection scope of the application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0186] In the above embodiments, the description of each embodiment has its own emphasis, and the parts not described or recorded in detail in a certain embodiment can be referred to the related description of other embodiments.

[0187] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in the present application can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0188] In the embodiments provided by the present application, it should be understood that the disclosed apparatus / terminal and method can be implemented by other ways. For example, the above-described apparatus / terminal embodiments are only schematic, and the division of the modules or units is only a logical function division, and there can be another division way in actual implementation, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection between each displayed or discussed unit can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or in other forms.

[0189] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0190] In addition, each functional unit in various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0191] The integrated module / unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer-readable storage medium. When the processor executes the computer program, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the contents included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0192] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system), and computer program product of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of the flows and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a machine that implements the flowchart and / or block diagram. Figure 1 Each flow or multiple flows and / or blocks Figure 1means for performing the function specified in the block or blocks.

[0193] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 flow or flows and / or blocks Figure 1 means for performing the function specified in the block or blocks.

[0194] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow Figure 1 flow or flows and / or blocks ​ steps of means for performing the function specified in the block or blocks.

[0195] The above merely illustrates the technical idea of the present application, and cannot be used to limit the protection scope of the present application. Any modification made according to the technical idea of the present application, on the basis of the technical scheme, falls within the protection scope of the claims of the present application.

Claims

1. A method for multi-element benefit analysis of power system resilience planning schemes, characterized in that, The method comprises the following steps: obtaining a new power system planning scheme; through extreme event simulation, component vulnerability analysis, system response behavior analysis, and system resilience index calculation, the obtained new power system planning scheme is evaluated for extreme event response capability within a set period of time, and a resilience benefit index is obtained; the new power system planning scheme is evaluated, and the resilience index is specifically: for extreme event simulation, the influence of the extreme event is simulated through the frequency, location, duration, and disaster intensity characteristics of the extreme event, a computer-simulated extreme event scenario set is generated, and for each simulated extreme event scenario, the disaster intensity at each disaster site is analyzed and calculated; based on historical disaster data, key parameters representing extreme events are analyzed and selected, a probability distribution model or an extreme value regression model of the key parameters of the extreme event is established to depict the uncertainty of the extreme event, and a hypothesis test is performed on the model to verify the goodness of fit; for each simulation year within the planning period, the number of disasters is sampled based on the annual frequency distribution, for each disaster scenario, the initial state of the simulated disaster is obtained by sampling other key parameters, and the parameters are converted into dynamic disaster scenarios with spatial and temporal characteristics through meteorological or geographical models; for component vulnerability analysis, based on the disaster scenarios generated in the extreme event analysis and the vulnerability curve of the power system components, the failure rate of the components in the power system is calculated, random numbers are used to sample the failure state of each component, and it is determined whether each component in the power system fails under the corresponding disaster scenario; for system response behavior analysis, the response process of the power system to extreme disasters is depicted, an emergency control and repair model of the power system to extreme events is established, and the simulation of the system outage and restoration process is realized; For the elasticity index calculation, the risk loss is defined as the weighted load loss and repair cost of the system in the whole disaster, the risk value of the specific elasticity index selection loss and the tail value at risk are adopted, the Monte Carlo method is used to simulate the economic loss caused every year, the convergence of the index is realized through the planning of the simulation year by year, the elasticity index and the tail value at risk is calculated as follows: wherein, is a lower bound, is a probability of event occurrence, is a set confidence level, is an annual risk loss, is a risk loss auxiliary parameter at a given confidence level ; Annual risk loss is: wherein, is the total number of transiting typhoons, , is the first set of failed lines and failed nodes under the field disaster, is the element repair or reconstruction cost of the corresponding equipment, is the load loss economic loss of the node , is the load loss time of the node during the first typhoon. the low-carbon cost of the power system construction, source measurement, load side, and network side within the planning period is calculated and estimated by using the carbon emission flow method, and a carbon emission index is obtained; the new power system planning scheme is calculated and estimated, and the carbon emission index is specifically: for each planning year within the planning period, the construction and commissioning of units, energy storage, lines, and stations within the year are determined, and the carbon emission levels of raw materials, production, and installation during the construction of power facilities are converted; for direct carbon emissions of the source side, the direct carbon emissions of different power plants in the source side under typical daily operation modes are used as a representation, and the carbon emissions per unit of power generation of the unit are converted by using the carbon emission factor; for indirect carbon emissions of the load side, the direct carbon emissions corresponding to the user's power consumption behavior in the source side under the typical daily operation mode are used as a representation, and the indirect carbon emissions per unit of power consumption of the users belonging to each node are converted by using the node carbon emission factor; for network loss indirect carbon emissions: the cumulative amount of coupled carbon emissions in the power flow corresponding to the network loss under the typical daily operation mode is used as a representation, and the carbon flow rate is used for conversion, including branch carbon flow rate and network loss carbon flow rate, the branch carbon flow rate is the indirect carbon emissions per unit of time flowing through the branch, and the network loss carbon flow rate represents the indirect carbon emissions per unit of time attached to the network loss; The carbon emission level of the new power system planning scheme in the planning period is obtained by adding the carbon emission of power facility construction, the direct carbon emission of source-side power generation, the indirect carbon emission of load-side power consumption, and the indirect carbon emission of network-side network loss in each year of the planning period; Quantifying low-carbon cost, including low-carbon input cost and low-carbon loss cost, low-carbon input cost is estimated according to equipment, technology initial investment and related operation activity cost, and low-carbon loss cost is cost paid due to emission of carbon dioxide, and low-carbon loss cost is: wherein, is a carbon emission quota, is a carbon trading price, is a carbon emission amount generated by fuel consumption in the power system; The economic indicators are obtained by calculating the power facility construction cost and the station house and line reinforcement or reconstruction cost according to the implementation cost of the obtained new power system planning scheme; The different planning schemes are evaluated and compared under the new power system planning scheme evaluation and decision-making framework facing the flexibility improvement, the comprehensive flexibility indicators, carbon emission and economic indicators are formed, the decision-making closed loop is formed, the planning scheme is feedback corrected, the adaptability planning of the new power system construction and climate change is realized, and the different planning schemes are evaluated and compared, the decision-making closed loop is formed, which is specifically: On the basis of extreme event evolution trend judgment, the planning scheme is formulated through extreme event influence analysis; The flexibility indicators, carbon emission indicators and economic indicators of the planning scheme to be taken are evaluated; The planning schemes to be taken are compared under the given economic budget, the Pareto optimal scheme is screened for implementation, and the implemented strategy is monitored and the effect is evaluated in the system operation, forming the decision-making closed loop.

2. The method of claim 1, wherein, The new power system planning scheme is obtained, which is specifically: The planning period considered in the planning scheme; The planning capacity, access location and construction year of each type of generator unit; The planning capacity, access location and construction year of each type of energy storage device; The planning location, line capacity and line construction year of the transmission corridor; The planning location and station construction year of the substation; The typical load data in the planning year; The typical daily operation mode of the power system in the planning year.

3. The method of claim 1, wherein, The economic indicators are obtained by calculating the power facility construction cost and the station house and line reinforcement or reconstruction cost, which are specifically: For power facility construction and configuration, the construction, operation, maintenance and disposal costs in the planning period are calculated, and the power facilities include generator units, energy storage, lines and stations; for station house, line reinforcement, strengthening, reconstruction or construction standard improvement, the fixed investment cost and operation and maintenance cost are calculated.

4. A power system resilience planning solution multi-faceted benefit analysis system, characterized by, It includes: The planning module obtains the new power system planning scheme; The flexibility module evaluates the extreme event response ability of the new power system planning scheme in the setting period through extreme event simulation, component vulnerability analysis, system response behavior analysis and flexibility index calculation, and obtains the flexibility benefit index; The flexibility indicators of the new power system planning scheme are obtained by evaluation, which are specifically: For extreme event simulation, the impact of extreme events is simulated by the frequency, location, duration, and intensity characteristics of extreme events, a set of computer-simulated extreme event scenarios is generated, and the disaster intensity at each disaster site is calculated for each simulated extreme event scenario. Based on historical disaster data, key parameters representing extreme events are analyzed and selected, a probability distribution model or extreme value regression model of the key parameters of extreme events is established to depict the uncertainty of extreme events, and the model is tested to verify the goodness of fit. For each simulated year in the planning period, the number of disasters is sampled based on the annual frequency distribution, and for each disaster scenario, the initial state of the simulated disaster is obtained by sampling other key parameters, and the parameters are converted into dynamic disaster scenarios with spatial and temporal characteristics through meteorological or geographical models; For component vulnerability analysis, the failure rate of components in the power system is calculated based on the disaster scenarios generated in the extreme event analysis and the vulnerability curves of the components, and a random number is used to sample the failure state of each component to determine whether the components in the power system fail under the corresponding disaster scenario; For system response behavior analysis, the response process of the power system to extreme disasters is depicted, an emergency control and repair model of the power system to extreme events is established, and the system outage and restoration process is simulated; For the elasticity index calculation, the risk loss is defined as the weighted load loss and repair cost of the system in the whole disaster, the risk value of the specific elasticity index selection loss and the tail value at risk are adopted, the Monte Carlo method is used to simulate the economic loss caused every year, the convergence of the index is realized through the planning of the simulation year by year, the elasticity index and the tail value at risk are calculated as follows: wherein, is a lower bound, is a probability of occurrence of an event, is a set confidence level, is an annual risk loss, is a risk loss auxiliary parameter for a given confidence level under a given confidence level; Annual risk loss is: in, This refers to the total number of typhoons that have passed through the area. , For the first Set of faulty lines and faulty nodes under field disasters For components The cost of repairing or rebuilding the corresponding equipment. For nodes The economic losses due to load failure It is a node In the The period of load loss during the typhoon; The carbon emission module uses the carbon emission flow method to calculate the low-carbon cost of power system construction, source measurement, load side, and network side in the planning period to estimate the new power system planning scheme, and obtains the carbon emission index; The carbon emission index of the new power system planning scheme is calculated as follows: For each planning year in the planning period, determine the construction and commissioning of units, energy storage, lines, and stations, and convert the carbon emission level of raw materials, production, and installation during the construction of power facilities; For direct carbon emissions from source-side power generation, use the direct carbon emissions from different power plants in the power system under typical daily operation mode to characterize, and convert the carbon emissions per unit of power generation by using the carbon emission factor; For indirect carbon emissions from load-side power consumption, use the direct carbon emissions from source-side power consumption under typical daily operation mode to characterize, and convert the indirect carbon emissions per unit of power consumption by using the node carbon emission factor; For network-side network loss indirect carbon emissions: use the cumulative amount of coupled carbon emissions in the power flow corresponding to network loss under typical daily operation mode, and convert it by using carbon flow rate, including branch carbon flow rate and network loss carbon flow rate, branch carbon flow rate is the indirect carbon emissions per unit time flowing through the branch, and network loss carbon flow rate represents the indirect carbon emissions per unit time attached to the network loss; Add the carbon emissions from power facility construction, direct carbon emissions from source-side power generation, indirect carbon emissions from load-side power consumption, and indirect carbon emissions from network-side network loss in each year of the planning period to obtain the carbon emission level of the new power system planning scheme in the planning period; Quantifying low-carbon cost, including low-carbon input cost and low-carbon loss cost, low-carbon input cost is estimated according to equipment, technology initial investment and related operation activity cost, and low-carbon loss cost is cost paid due to emission of carbon dioxide, and low-carbon loss cost is: wherein, is a carbon emission quota, is a carbon trading price, is a carbon emission amount generated by fuel consumption in the power system; The economic module calculates the construction cost of power facilities and the cost of station building, line reinforcement, or modification to obtain economic indicators. The analysis module synthesizes the elasticity index, carbon emission and economic index, evaluates and compares different planning schemes in the new power system planning scheme evaluation decision-making framework facing elasticity improvement, forms a decision-making closed loop, feeds back and corrects the planning scheme, realizes the construction of the new power system and the adaptive planning under climate change, and specifically evaluates and compares different planning schemes to form a decision-making closed loop, which is: On the basis of the evolution trend of extreme events, planning schemes are formulated through extreme event influence analysis; The elasticity index, carbon emission index and economic index of the planning schemes to be adopted are evaluated; The planning schemes to be adopted are compared under the given economic budget, the Pareto optimal scheme is screened for implementation, and the implemented strategy is monitored and the effect is evaluated in the system operation, forming a decision-making closed loop.

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