83 results about "Power planning" patented technology

The invention discloses a multi-scene coupled extreme weather adaptive power system planning method and system, belongs to the technical field of power system planning, and aims to solve the problem that traditional planning does not fully consider extreme weather influence and does not integrate multi-energy complementarity. Comprising the steps of collecting installed capacity, historical weather and power load data of a power grid unit; a conventional weather scene set is generated through clustering by adopting a kmeans algorithm, and an extreme weather scene set is generated in combination with types of extreme high temperature, cold waves and the like; constructing operation models and policy constraints of the thermal power unit, the new energy unit and the electrochemical energy storage unit; based on the planning-operation coupling framework, establishing a two-stage stochastic programming model with the goal of minimizing the total investment and operation cost; and integrating the multi-scene solving model, and outputting an adjustment power supply planning scheme. Through multi-scene coupling and two-stage optimization, planning and operation collaboration is realized, the economy, safety and adaptability of the power system in extreme weather are improved, and technical support is provided for low-carbon transformation.

The invention relates to an energy management method and system for a green electricity hydrogen production and hydrogenation all-in-one machine, and relates to the technical field of hydrogen energy application, the system comprises an upper layer control system and a communication interface module, collaborative optimization scheduling is executed in the day-ahead stage, the rolling stage and the real-time stage; the communication interface module supports IEC104, private UDP and other industrial protocols, and realizes real-time data interaction with a green electricity prediction system and a hydrogen production DCS system. The method comprises the following steps: making an electrolytic cell start-stop and power plan in a day-ahead stage; periodically correcting prediction and demand errors in a rolling stage; the power of the electrolytic cell is dynamically adjusted to fluctuate along with green electricity in the real-time stage. According to the invention, cross-section and multi-time scale coordination control is realized, and the green power consumption rate, the system operation economy and the hydrogen energy supply reliability are improved.

The invention discloses a chip design method, chip design equipment and a medium, and relates to the technical field of chips, during chip design, a target module in a chip is firstly determined, power supply planning of the target module is independently adjusted to avoid the influence of voltage drop on crosstalk when the wiring density is too large, crosstalk prevention is started in advance in the power supply planning stage, and the crosstalk is prevented from being damaged. After the layout and wiring design of the chip is carried out according to the power supply plan and the module layout, the crosstalk condition existing in the chip is directly analyzed, and if the crosstalk occurs in a target module, a mode of enlarging the layout space of the target module is adopted to cope with the crosstalk; if crosstalk occurs in other modules, a mode of adjusting electrical parameters of a signal line is adopted to cope with the crosstalk. Crosstalk prevention is carried out in the chip design stage, and different response modes are adopted according to different areas where crosstalk is located, so that the influence of crosstalk on normal working of the chip is avoided, and the accuracy and stability of the chip during working are improved.

The invention relates to the technical field of power planning, provides an AI-based virtual power plant energy supply and demand accurate matching method and system, and solves the problems of low accuracy of virtual power plant energy supply and demand matching and low overall operation efficiency. The method comprises the following steps: acquiring an output data sequence of power supply equipment in a virtual power plant and an electricity price data sequence of an electricity market; dynamically adjusting the initial charging and discharging power of the energy storage equipment in the virtual power plant to obtain target charging and discharging power; carrying out fusion optimization on the load prediction model of each energy participation node in the virtual power plant by using a federated learning mode, and generating a global demand adjustment plan; generating a power dispatching plan based on the output data sequence and the electricity price data sequence; and the power dispatching plan and the global demand adjustment plan cooperatively act on energy supply and demand matching of the virtual power plant, and AI-based accurate energy supply and demand matching of the virtual power plant is realized. According to the invention, the accuracy of energy supply and demand matching of the virtual power plant and the overall operation efficiency are improved.

The invention belongs to the crossing field of power system dispatching automation and artificial intelligence, and particularly relates to a parameter dynamic generation technology based on cooperation of a large model and a mechanism model. Comprising the following steps: S1, receiving natural language instruction input of a dispatcher; s2, intention recognition and instruction analysis are carried out through the power planning model, and key scheduling parameters are extracted; s3, the analysis result is converted into mathematical parameters which can be executed by the mechanism model; S4, the mechanism model carries out multi-objective optimization calculation based on the input parameters, and a preliminary scheduling scheme is generated; s5, performing semantic verification on the preliminary scheme through the large model; and S6, dynamically adjusting the parameter weight according to the verification result, and iteratively optimizing the scheduling scheme. Through deep fusion of natural language processing and a power system physical mechanism, full-process intelligent conversion and closed-loop optimization from a dispatcher instruction to a mathematical model parameter are realized, and limitation of a traditional static rule is broken through.

The invention discloses an EMIR verification method and system, a computer and a storage medium. The method comprises the following steps: appointing a time sequence library file directory, an RC file path and a constraint file path when an automatic script runs; traversing a time sequence library directory through an automatic script, analyzing time sequence library files, and extracting a PVT condition and an RC model corresponding to each file; automatically classifying and mapping the extracted PVT condition and RC model according to a preset classification rule to generate a multi-process corner combination; automatically generating a multi-mode multi-corner-point MMMC configuration file according to the multi-process corner point combination, and outputting a traceable mapping list and an association table; in a chip physical implementation process, dual-stage EMIR verification is executed in a power supply planning stage and a verification stage. According to the method, the MMMC configuration file matched with the angular point is automatically analyzed based on the time sequence library, and staged EMIR verification is combined in the physical implementation process, so that the overall design efficiency and reliability are improved.

The application discloses a kind of grid-connected detection method, equipment, medium and product of AC-DC distribution system, the method includes: establishing the power flow model of AC-DC distribution system before distributed power grid connection, and according to power flow model obtains time series power flow result, the reliability calculation of AC-DC distribution system is carried out, obtains reliability calculation index, according to time series power flow result and reliability calculation index, the comprehensive performance index of AC-DC distribution system is constructed, according to comprehensive performance index, the operation state information of AC-DC distribution system is generated for distributed power grid connection.According to operation state information, the weak link that AC-DC distribution system needs to be reformed can be determined, and technical support and guidance can be provided for distributed power grid connection strategy, which is conducive to promoting the safe and reliable operation of AC-DC distribution system.Through optimization scheduling and power supply planning, the operation efficiency of AC-DC distribution system can be improved, the operation cost is reduced, and the accuracy of grid-connected detection of AC-DC distribution system is improved.

This invention discloses a method, apparatus, equipment, medium, and product for power configuration in clean energy bases, belonging to the field of power configuration technology. The method for power configuration in clean energy bases includes the following steps: obtaining demand data for various power configurations; constructing a power configuration model for the clean energy base based on the demand data; and generating a power configuration scheme for the clean energy base using the power configuration model. This invention constructs a power configuration model applicable to integrated wind, solar, coal gas, and hydrogen storage systems. It eliminates repetitive manual work, significantly shortens the design workflow, improves power planning and design efficiency, and eliminates reliance on manual experience, enhancing the scientific rigor and standardization of various power configuration schemes, improving the quality of power planning and design, and reducing power planning and design costs, thereby promoting the development of clean energy bases.

The invention discloses a conventional unit installed capacity estimation method and system based on a load characteristic index, and belongs to the technical field of power system planning. The method comprises the following steps: acquiring historical load information, and calculating daily load and annual load characteristic indexes; deriving and planning annual total power consumption based on indexes, and calculating the minimum installed capacity of a conventional unit through annual and typical daily power balance; and energy storage peak regulation parameters are further calculated, and climbing verification and power receiving correction are carried out. The system comprises a data module, an index module, a capacity module and a correction module. The time sequence characteristics are quantified through the key load indexes, the complex power source planning process is simplified, rapid and accurate estimation of the installed capacity is achieved, the method is suitable for a new energy high-permeability system, and the planning efficiency and economical efficiency are improved.

The invention discloses a transformer area three-phase balance and regional load balance method, device, equipment and medium, and belongs to the field of power distribution network power planning, and the method comprises the steps: screening a first sub-region with unbalanced load from each sub-region according to the total energy consumption of each sub-region in a to-be-planned region and the total number of users; obtaining and preprocessing three-phase current time sequence data of each first device in the first sub-region; the energy consumption of the first equipment is greater than preset energy consumption; according to the preprocessed three-phase current time sequence data, screening out a second device with unbalanced three phases from the first devices; constructing a multi-objective optimization mathematical model by taking the three-phase current balance of each second device and the load balance of the to-be-planned area as optimization objectives; and according to a solving result of the multi-objective optimization mathematical model, redistributing a connection phase of each second device and a sub-region to which the second device belongs. According to the invention, the problem that the three-phase balance and regional load balance of the low-voltage transformer area of the power distribution network cannot be optimized in time in a dynamic environment can be solved.

The present invention relates to the technical field of power grid investment optimization, and specifically discloses a power grid investment optimization method based on big data analysis, the method comprising: monitoring meteorological data of a power planning area, processing to obtain a time series function of power generation of new energy sites in the power planning area, predicting the demand load based on historical load data of the power planning area, and comprehensively analyzing to obtain the demand construction scale data of the energy storage system in the power planning area; obtaining new energy vehicle usage data in the power planning area, and comprehensively analyzing to obtain virtual energy storage compensation parameters in the power planning area; and optimizing the demand construction scale data of the energy storage system in the power planning area based on the virtual energy storage compensation parameters in the power planning area. The present invention comprehensively considers the charging demand and discharge capacity of electric vehicles, determines the optimal construction scale of the energy storage system, and provides a more scientific basis for power grid investment optimization.

The invention belongs to the technical field of AC / DC hybrid power grid reactive power planning, and particularly relates to a target scene-oriented AC / DC hybrid power grid reactive power planning parameter optimization method, which comprises the steps of S1, establishing a reactive power planning model considering reactive power equipment distribution, capacity and internal parameters, and introducing a reduced-order mapping matrix to pre-reduce variable dimensions; s2, performing simplified linearization processing on the transient stability constraint optimal power flow problem of the power system, and performing analysis and processing to obtain the linearization stability constraint of the reactive power planning model; s3, removing the corresponding minimum probability distance scene from the set until the representative scene is equal to a preset value; s4, integrating the linearization stability constraint of the reactive power planning model and the representative scene set into the reactive power planning model to obtain an optimal power system reactive power planning model; and S5, performing dynamic reactive power planning by using the optimal power system reactive power planning model. According to the method, the planning efficiency can be effectively improved on the premise of ensuring the voltage qualification rate.

The invention discloses a power distribution network reactive power planning method based on an improved point estimation method and chance constraint, and the method comprises the steps: S1, carrying out the mixing moment calculation and sample point selection of an uncertainty parameter through employing the improved point estimation method, and obtaining an estimation value of the uncertainty parameter; the uncertainty parameters comprise distributed power supply output and load; s2, constructing a power distribution network reactive power planning model based on opportunity constraint, taking the minimum comprehensive operation cost of the power distribution network as a target function, and determining various constraint conditions; the constraint conditions comprise a power flow equation equality constraint of the power distribution network, an inequality constraint of a node voltage amplitude, branch current and reactive compensation equipment capacity, and a chance constraint of the node voltage amplitude and branch power; and S3, substituting the estimated values of the uncertainty parameters into the reactive power planning model, and solving the reactive power planning model by adopting a genetic algorithm combined with quantum behaviors. According to the method, the defects of a traditional point estimation method and deterministic constraints are overcome, and a better reactive power planning scheme is obtained.

The application provides a multi-objective power supply planning method based on Pareto front shape optimization and a related device, including obtaining a multi-objective power supply planning model of a project to be planned, and extracting investment decision variables and operation variables from the multi-objective power supply planning model; continuously optimizing solutions composed of the investment decision variables and the operation variables by using a genetic algorithm until the optimization is stopped after a stop condition is met, and a solution set is obtained; selecting a compromise solution meeting a requirement based on a Pareto front shape of the solution set, so as to determine a final multi-objective power supply planning scheme. The application optimizes the investment decision variables and the operation variables by using the genetic algorithm, minimizes conflict relationships between different objectives, selects a balanced compromise solution, and finally determines the multi-objective power supply planning scheme. The method not only considers uniformity and convergence of the Pareto front, but also particularly focuses on influences of the power supply planning on conflict relationships of operation objectives, and improves accuracy and reliability of decision-making.

The invention provides an electric power planning method for renewable green new energy development, and belongs to the technical field of energy planning, and the method comprises the steps: calibrating a plurality of supply points in a region according to the position of each electric device in the current region and the type of an energy demand in combination with a change plan; performing preliminary modeling on each building in the area, and inferring an energy transformation scheme by combining the energy demand quantity and the energy demand type designed by each supply point; transmitting energy generated by the new energy system to a plurality of corresponding electric devices for consumption; and the new energy system is integrated into the current actual construction scheme and the building construction scheme to be carried out in the future, and finally energy supply transformation of the buildings in the area is completed. According to the electric power planning method for renewable green new energy development, the proportion of new energy supply of the whole area can be increased, efficient nearby consumption of energy is achieved, dependence on traditional energy is reduced, and a limited new energy system structure is optimized.

The application provides a multi-time scale power supply guarantee analysis method and system, which comprises the following steps: collecting load parameters in a system to be studied; performing load characteristic analysis and new energy characteristic analysis based on the load parameters to obtain preliminary typical day simulation analysis results; performing typical day simulation calculation based on the preliminary typical day simulation analysis results to obtain an intraday power supply guarantee result, and ending the power supply guarantee analysis if the system has no power shortage; if there is a power shortage, performing the next step of analysis; if there is a power shortage, performing monthly power balance calculation to measure seasonal power shortage, and formulating a seasonal power supply guarantee scheme; after the seasonal power supply guarantee scheme is adopted to ensure seasonal power balance, performing continuous multi-day power balance calculation to measure continuous multi-day peak shaving demand, formulating a continuous multi-day power supply guarantee scheme according to the size of the extreme weather power shortage, and performing typical day simulation analysis again if there is no power shortage. The method can quantitatively analyze the peak demand of different time scales in the system during the power supply guarantee period, and provide support for power source planning.

This invention belongs to the field of power planning and new energy power generation. It discloses a method, system, equipment, and medium for configuring the capacity of an amphibious power plant based on monthly balance. Based on the load forecast of the amphibious power plant and the predicted new energy power generation during the hydropower peak and off-peak seasons, a monthly power balance analysis of the amphibious power plant is performed to obtain the power deficit for each power-deficient month and the power balance for each power-excessive month. Based on the power deficit for each power-deficient month, the required coal-fired power generation capacity to ensure power supply during each power-deficient month is determined, and the maximum value is selected to obtain the coal-fired power generation capacity of the amphibious power plant. Based on the power balance for each power-excessive month, the required energy storage capacity to ensure the complete consumption of abandoned new energy power during each power-excessive month is determined, and the maximum value is selected to obtain the energy storage capacity of the amphibious power plant. This achieves a reasonable determination of the coal-fired power generation capacity and the energy storage capacity of the amphibious power plant.

This invention belongs to the field of power planning and design technology, and discloses a method and system for simulating wind farm output. The method first calculates the theoretical output, stochastic reduction factor, low temperature reduction factor, and maintenance reduction factor based on the target basic data of the project location, and calculates the hourly comprehensive reduction factor. Then, the actual output is calculated based on the theoretical output and the hourly comprehensive reduction factor. In this way, the impact of uncertainties such as temperature and maintenance on the output during the actual operation of the wind farm is taken into account. Based on mesoscale reanalysis data or measured wind speed data, it can quickly and accurately simulate the actual output data of the wind farm without the need for a complex modeling process, which can meet the needs of wind power project output prediction.

The present application relates to the technical field of data processing, and especially relates to a power planning optimization method based on artificial intelligence, which comprises the following steps: collecting data; determining abnormal events; predicting parameters; determining candidate shutdown equipment; determining high-risk equipment; determining target shutdown equipment; generating a power planning scheme; and adjusting thresholds. The present application collects multi-dimensional data in real time, determines abnormal events according to total power consumption, predicts load loss and residual time in combination with a preset model, determines high-risk equipment according to residual time, heat consumption rate, vibration frequency and rotor speed, determines target shutdown equipment according to active power, climbing rate and load loss of high-risk equipment, and adjusts thresholds dynamically according to total power consumption and rotor speed based on the power planning scheme, thereby effectively solving the problems of low precision of shutdown decision and response lag caused by the complexity of the operation background of the power system and excessive dependence on models.

The application discloses a novel power system multi-dimensional supporting demand index evaluation method and system, belongs to the field of power system demand estimation, and comprises the following steps: based on system load data and new energy output data, analyzing power system net load data conditions; based on the power system net load data conditions, screening extreme weather new energy continuous low output data according to the new energy output data, determining an extreme weather time segment, and acquiring extreme weather period net load data; and based on the extreme weather period net load data and total time sequence net load data, determining a supporting demand index in the time sequence, and supporting new power system power sources for planning. The application more comprehensively constructs a multi-dimensional supporting index system of supporting power sources, and provides a reference basis for new power system supporting power source planning.

The invention relates to the field of power distribution network reactive power optimization, and discloses a reactive power planning optimization method and system for a high-voltage power distribution network, and the method comprises the steps: obtaining real-time power data collected by a sensor, calculating a reactive power demand, and obtaining reactive power demand distribution; when the variance of the reactive power demand distribution exceeds a preset threshold value, the compensation capacity is adjusted, and a preliminary planning scheme is obtained; simulating an operation state according to the preliminary planning scheme, and obtaining a voltage deviation; when the voltage deviation value is larger than a preset threshold value, parameters are dynamically adjusted, and refining scheme output is obtained; reactive power compensation capacity is adjusted according to the refining scheme output, a first reactive power compensation scheme is obtained, reactive power distribution is optimized according to the first reactive power compensation scheme, a final reactive power optimization scheme is obtained, reactive power compensation parameters are adjusted according to the final reactive power optimization scheme, and final reactive power optimization configuration is obtained. According to the method, a reactive power planning scheme adapting to dynamic characteristics and prediction deviation can be constructed in the face of load random change.

The invention relates to a reverse deduction power system planning method, which comprises the following steps of: obtaining a long-term annual total installed capacity target in a long-term planning layer; in the middle-term coordination layer, an adjusted long-term annual total installed capacity target is obtained; in the short-term verification layer, outputting a final long-term annual total installed capacity target; the long-term planning layer, the middle-term coordination layer and the short-term verification layer jointly form a long-term-middle-term-short-term three-layer coupling deduction framework, and iterative optimization circulation of verification is operated from bottom to top. According to the method, a long-term-middle-term-short-term three-layer coupling deduction framework is constructed, reverse solution is carried out with the carbon peak reaching target year as rigid constraint, the problem that long-term strategy and short-term operation are disjointed frequently occurring in traditional electric power planning is effectively solved, the planning result has perspectiveness, and the method is suitable for large-scale popularization and application. The scientificity and the performability of the planning scheme are obviously improved; the total economic cost of low-carbon transformation of the whole power industry is effectively reduced, and collaborative improvement of economy and reliability is achieved.

The application discloses an abnormal power meteorological data correction method and device for power planning, relates to the power technology field, and mainly aims to improve the accuracy of power system operation and planning. The main technical scheme of the application is as follows: obtaining initial power meteorological data sequences corresponding to each meteorological parameter in each transformer substation; constructing a power grid topology graph according to the initial power meteorological data sequences, the topology structure of a power transmission network, the geographical relationship between each transformer substation and the admittance matrix relationship; determining the space-time correlation characteristics between each node in the power grid topology graph based on a preset construction method; identifying abnormal data in the initial power meteorological data sequences corresponding to each meteorological parameter in each transformer substation based on the power grid topology graph and the space-time correlation characteristics between each node; and correcting the abnormal data according to the space-time correlation characteristics between each node and a preset data correction rule to obtain optimized power meteorological data, so that power planning is performed according to the optimized power meteorological data.

The application discloses a kind of combination clustering scene reduction method and system based on potential decision result, the uncertainty factor of each node in power system is expressed as multidimensional curve input domain in the form of time sequence curve;Based on multidimensional curve input domain, the power supply planning problem solving model under different time scale scene is constructed, considering operation checking, multidimensional curve input domain is converted into potential decision result domain for clustering analysis;SOM neural network clustering is carried out to potential decision result, and preliminary clustering result is obtained;SOM and k-medoids combination clustering method is used to finally classify preliminary clustering result, and finally the typical scene used in operation checking is obtained.The application is used to cluster the most representative scene set in power supply planning typical scene operation checking, to reduce the complexity of solving model to the greatest extent under the condition of guaranteeing the reliability of checking result, improve calculation efficiency.

The application provides a distributed power supply planning method and device, electronic equipment and storage medium, and belongs to the field of distribution network planning. The method comprises the following steps: screening the optional nodes of the distributed power supply to be planned based on the small world theory to obtain the candidate nodes, and determining the solution space according to the candidate nodes; constructing an optimization objective function and a constraint condition, initializing the to-be-planned variable of the distributed power supply to be planned to obtain an initial Onomarchus population, improving the Onomarchus algorithm of the initial Onomarchus population through an adaptive weight and a Levy flight strategy to obtain a child population, determining the population fitness of the child population according to the optimization objective function and screening to obtain a new round of Onomarchus population, and iteratively optimizing to obtain optimal planning variables. The important node screening through the small world theory can effectively reduce the solution dimension, the adaptive weight and the Levy flight strategy can improve the convergence speed and the global search ability of the algorithm, and the fast and accurate solution of the distributed power supply planning problem is realized.

The invention relates to an electric power planning report three-level title structured analysis generation method and device and a medium, and the method calls a large language model to execute the following steps: obtaining a to-be-processed electric power planning report and carrying out report paragraph text extraction to obtain an original text; segmenting the original text into overlapped text blocks, wherein the overlapped part comprises a three-level title context; constructing a power planning professional cue word, for each text block, identifying a three-level title in a specific format, classifying sub-section contents into a corresponding three-level title text, and outputting an analysis result; and detecting repeated contents in analysis results of adjacent text blocks, eliminating repetition based on text tail fix matching, integrating the analysis results of all the text blocks, generating a structured result containing three-level titles, corresponding texts, analysis time and text statistical information, and performing structural optimization. Compared with the prior art, the method has the advantages of high three-level title recognition accuracy, high structured data format compliance rate and the like.

The invention discloses an offshore wind power AC / DC power transmission planning method and device, electronic equipment and a storage medium, and belongs to the technical field of power planning, and the method comprises the steps: constructing a multi-stage probability planning model corresponding to a power system according to the multi-source data of the power system, and then according to the multi-stage probability planning model, constructing a multi-stage probability planning model corresponding to the power system; constructing a corresponding objective function and a constraint condition by taking the minimum total air transportation cost of the power system as an objective; under the constraint of the constraint condition, solving the target function to obtain the total wind transportation cost, the number of newly added lines, the wind power installed capacity and the power transmission power of a generator set corresponding to the power system when the total wind transportation cost of the power system is minimum; according to the method, the planning scheme of the offshore wind power AC / DC power transmission is obtained, and then the offshore wind power AC / DC power transmission planning is carried out according to the planning scheme, so that the problem that no related technical means exists in the prior art to realize scientific offshore wind power transmission planning can be solved.

The invention discloses a power distribution network power supply recovery method considering flexible resources. The method comprises the following steps: collecting power distribution network data; obtaining typical daily load data based on the historical load data; evaluating the fitting effect of the distribution curve; based on the output characteristics of the distributed power supply and the energy storage system, reasonably selecting the composition of an elastic power supply in the power distribution network, and establishing a corresponding emergency output model; carrying out constant-volume scheduling on a subsequent power supply based on the typical daily load data; based on the optimal power supply planning configuration scheme, when a fault occurs, rapid power supply recovery is realized; according to the invention, power supply constant-volume scheduling is carried out based on the typical load fitting value, so that flexible resources have enough standby capacity to support important loads to carry out emergency power supply recovery, and the power supply recovery speed and the power supply reliability of the power distribution network are improved.

The application discloses a kind of intelligent network connection plug-in hybrid electric bus electric quantity planning methods, comprising: the speed curve of the intelligent network connection plug-in hybrid electric bus of fixed route operation is collected as typical working condition, the optimal variation curve of battery state of charge (SOC) of typical working condition is obtained using global planning algorithm, the interval power consumption of each working condition segment is extracted and the interval power consumption identification model based on the characteristics of working condition segment is constructed, on the basis, the best electric quantity planning value of next working condition segment is determined by introducing improved interactive multi-model algorithm, and the limitation of single electric quantity distribution mode is eliminated.The application realizes the optimal planning of the electric quantity of intelligent network connection plug-in hybrid electric bus, and focuses on solving the problem of vehicle energy consumption deterioration caused by unreasonable electric quantity distribution, which has great theoretical and practical value for deeply tapping the energy-saving and emission-reducing potential of plug-in hybrid power system and promoting the green and sustainable development of urban public transportation.

The invention discloses a power expansion planning method based on flexible resources and a related device. The method comprises the following steps: acquiring historical data of a target area, and power planning data and prediction data in a planning year; optimizing the target flexibility model through the preprocessed historical data and prediction data; carrying out flexibility planning solution according to power planning data through the optimized target flexibility model, and outputting planning information by taking the minimum sum of investment cost, operation and maintenance cost, unsatisfied load, excessive power generation and renewable energy source abandoning cost and flexibility default cost as a target function under the condition of satisfying model planning constraints; and performing extension path analysis according to the planning information, and generating a power extension planning strategy considering both economy and flexibility.