184 results about "Power planning" patented technology

The invention discloses a regional power grid layout planning system, a storage medium and computer equipment wherein the regional power grid layout planning system is realized based on a three-dimensional geographic information model and a territorial space information model. Comprising a transformer substation site selection planning plate used for selecting a site meeting given conditions, technical rules and policies and regulations in a given area, and a power transmission line path planning plate used for planning a reasonable path scheme according to a line rule on the basis of a given line starting point and a given line ending point in a planning area. And the regional power grid layout planning system platform plate is used for solving the problems that planning data models and attributes formed in each specialty and each technical process in the spatial layout service of the electric power facilities in the regional power grid are not uniform, data is distorted and results are difficult to share. Through regional power grid layout optimization technology research, effective landing of power planning can be guaranteed, uncertain factors of engineering construction are reduced, construction coordination difficulty is reduced, and source-grid-load-storage coordination development is promoted.

The invention relates to the technical field of power system control, in particular to a novel power system control method with participation of new energy. The method comprises the following steps: acquiring historical and predicted environmental data, power consumption data and power supply quantity data; determining a stability coefficient according to the numerical fluctuation of the power supply quantity data and the correlation of the environmental data; determining a predicted power supply accuracy index in combination with the numerical fluctuation of the predicted power supply quantity data; determining a historical power consumption influence coefficient according to the numerical value change of the historical power consumption data; determining a power storage reliability index at the current moment by combining the numerical fluctuation of the predicted power consumption data in the prediction time period; and performing new energy access control at the current moment according to the power storage reliability index and the predicted power supply accuracy index. The stability of power consumption and power supply can be effectively combined, so that stable control of the whole power system is ensured, and the stability of power planning of the power system is improved.

The invention discloses a new energy medium and long term stochastic programming method and system coupled with an electro-hydrogen water regulation power supply, and the method comprises the steps: building a power supply planning model with the minimum planning operation cost as an optimization target; bringing the new energy power supply and energy storage adjusting equipment operation model and the new energy consumption rate upper and lower limit constraint expression into a power supply planning model; in consideration of the randomness of fluctuation at two sides of a source and a load in power supply planning, based on the obtained power system operation scene set S and the power supply planning model, dividing into an investment decision-making layer and an operation simulation layer according to a time period influenced by a decision, and constructing a power supply planning two-stage stochastic optimization model based on a typical scene; and solving the power supply planning two-stage stochastic optimization model under a medium and long term planning framework, and determining the investment planning installed capacity of the adjusting power supply and the new energy in the planning level year. According to the invention, economy of medium and long term planning and power supply capacity configuration of new energy can be improved, and reasonable consumption and flexible adjustment of new energy electric power are promoted.

The invention provides a charging pile power distribution method and system based on dynamic load balancing, and the method comprises the following steps: obtaining the local state information of each charging pile, the state information at least comprises the charging queuing length, the current vehicle charge state, the current load power, the battery health state, the predicted residence time, the electricity price information and the power grid load state; based on the historical charging behavior, the electricity price fluctuation and the traffic flow data, the vehicle access frequency, the electricity price trend and the power demand of each charging pile in the future time period are predicted through a time sequence neural network; a prediction model is constructed; according to the method, forward-looking power planning is realized by entering a multi-dimensional prediction mechanism; the power distribution efficiency is improved by adopting a local collaborative game; the self-adaption and generalization ability is realized through reinforcement learning, and the robustness of a scheduling strategy in multiple scenes is enhanced; through a multi-target scheduling index, the electricity price, the battery life, the waiting time and the power grid load are optimized at the same time.

The invention discloses a new energy capacity confidence evaluation method based on a conditional denoising diffusion model, and belongs to the field of reliability analysis and power supply planning of a power system. According to the technical scheme, wind power data and photovoltaic power data serve as input samples, firstly, a noise prediction network is trained, a conditional denoising diffusion model is constructed based on the noise prediction network, then the samples are preprocessed and modeled, and effective information in the samples is reserved; then, according to a label vector of a given scene and pure noise data, a scene set of a new energy power curve with specific characteristics is generated through a condition denoising diffusion model which is trained through reasoning; and finally, based on the scene set of the power supply installed capacity, the fault rate parameter, the historical load curve and the new energy power curve of the power grid system, evaluating the capacity confidence after the new energy accesses the power grid system through a power generation side COPT convolution method. The power supply guarantee capability of the new energy system is accurately quantified, so that guarantee is provided for safe operation of a power system.

The invention particularly relates to a high-voltage distribution network reactive power planning method and system based on an improved particle swarm optimization algorithm, and the method comprises the steps: determining a target function of a high-voltage distribution network reactive power planning model; setting constraint conditions and related variables; a particle swarm algorithm is used as a reference algorithm, an improved particle swarm algorithm is adopted to optimize the reactive power planning model of the high-voltage distribution network, and the improved particle swarm algorithm comprises the step of introducing a self-adaptive adjustment strategy on an inertia weight and an acceleration factor; initializing related parameters in the particle swarm optimization; performing iterative calculation, updating the adaptive value, the individual optimal value and the global optimal value of each particle and the speed and the position of the particle to judge whether the maximum number of iterations is reached or not, and if the maximum number of iterations is reached, stopping iteration and outputting an optimal solution; and if the maximum number of iterations is not reached, continuing the iterative operation. According to the method, reactive power distribution can be optimized, network loss and operation cost are remarkably reduced, and reactive power optimization of the high-voltage power distribution network is more efficient and reliable.

The invention discloses a grid-connected detection method, device, medium and product for an AC / DC power distribution system, and the method comprises the steps: building a power flow model of the AC / DC power distribution system before grid connection of a distributed power supply, obtaining a time sequence power flow result according to the power flow model, carrying out the reliability calculation of the AC / DC power distribution system, and obtaining a reliability calculation index, and according to the time sequence power flow result and the reliability calculation index, constructing a comprehensive performance index of the AC / DC power distribution system, and according to the comprehensive performance index, generating operation state information of the AC / DC power distribution system for distributed power supply grid connection. According to the operation state information, weak links needing to be transformed of the AC / DC power distribution system can be determined, technical support and guidance can be provided for a distributed power supply grid connection strategy, and safe and reliable operation of the AC / DC power distribution system can be promoted. By optimizing scheduling and power supply planning, the operation efficiency of the AC / DC power distribution system can be improved, the operation cost can be reduced, and the accuracy of grid-connected detection of the AC / DC power distribution system can be improved.

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 a control method and system of a car home light storage and charging system and electronic equipment, and is applied to the technical field of vehicles, and the method comprises the steps that comprehensive energy data of the car home light storage and charging system are acquired, the car home light storage and charging system comprises multiple pieces of power equipment, and the power equipment comprises an inverter and a vehicle; according to the comprehensive energy data, determining an energy management strategy of the vehicle home light storage and charging system, wherein the energy management strategy is used for indicating the adjustment condition of the charging and discharging power of each device in the vehicle home light storage and charging system; obtaining an electric power planning strategy sent by the vehicle, wherein the electric power planning strategy is used for indicating the power utilization planning condition of each device in the vehicle home light storage and charging system; and based on the energy management strategy and the power planning strategy, controlling each power device in the car home light storage and charging system.

The invention relates to the technical field of new energy station transformation and multi-type power supply collaborative optimization, and discloses a new energy station transformation and multi-type power supply collaborative optimization method, system and device and a medium, and the method comprises the steps: obtaining a power system target parameter, and building and solving a first power supply planning model; preset disturbance is applied to the model, and frequency safety is checked. If not, adding system parameters and obtaining sensitivity cut constraints, and rebuilding and solving the model according to the system parameters and the sensitivity cut constraints. And after the conditions are met, outputting an optimization scheme. According to the method, the efficiency of a new energy station is improved, multi-power-supply collaborative optimization is realized, and the stability and reliability of a power system are enhanced. A power system is optimized in a targeted manner by accurately acquiring target parameters and establishing a first power supply planning model. And the model is solved and preset disturbance is configured, so that the frequency safety problem can be found and solved in time. In addition, by adding system parameters and obtaining sensitivity cut constraints, the scheme can be further refined and optimized, and accuracy and efficiency are improved.

The invention discloses an energy storage system benefit evaluation method considering new energy output uncertainty, and the method comprises the steps: describing a low-carbon performance index through employing CO2 emission, SO2 emission and a system coal consumption index, and describing an economic performance index through employing system global operation cost; and the reliability index is described by adopting the expected insufficient power supply quantity, the expected power failure duration and the system power reserve rate. The method comprises the following steps: under the condition of constructing low-carbon-economic-reliability operation indexes of an energy storage system, determining an operation objective function of the energy storage system by adopting the minimum global operation cost of the system, formulating constraint conditions including operation of multiple types of units and systems, and determining an influence mechanism of the energy storage system; and on the basis of the established model, configuring an energy storage system on a power grid side by adopting a power planning decision and evaluation system, and establishing and solving a low-carbon-economy-reliability benefit evaluation model of the energy storage system by taking the capacity of the energy storage system as an analysis variable. And reference is provided for consumption of renewable energy sources and construction of a novel power system.

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 provides a multi-region asynchronous interconnected power grid planning method and system considering frequency security constraints. The method comprises the steps of obtaining frequency response characteristic related parameters and frequency deviations of alternating current power grids in all regions of a power system; according to the frequency response characteristic related parameters and the frequency deviation of the AC power grid in each region of the power system, determining the frequency safety constraint of the AC power grid in each region under the DC fault; and constructing a multi-region asynchronous interconnected power grid direct current and power supply planning model considering the frequency safety constraint by taking the frequency safety constraint of the alternating current power grid of each region under the direct current fault as a constraint condition, and carrying out optimization solution on the planning model by utilizing a GUROBI optimizer to obtain a direct current and power supply planning scheme of the asynchronous interconnected power grid of each region of the power system. According to the technical scheme, it can be effectively guaranteed that the direct current and power source planning scheme of the multi-region asynchronous power grid interconnected power grid meets the frequency safety requirement under high-proportion new energy access, and decision support is provided for power system planning.

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 discloses a port distributed power supply planning method and system based on an improved Pedal optimization algorithm, and the method comprises the steps: constructing a photovoltaic power generation model and a wind power generation model, and converting the wind speed and illumination intensity of a typical wind and light time sequence scene in each season into the time sequence output power of a distributed power supply; constructing a distributed power supply planning model based on the annual comprehensive cost objective function, the annual total voltage deviation objective function and constraint conditions of the distributed power supply multi-objective planning model; performing performance improvement on the Pedal optimization algorithm to obtain an improved Pedal optimization algorithm; and solving the distributed power supply planning model based on an improved Pedal optimization algorithm to obtain an optimal planning result of the port distributed power supply. According to the method, the overall economic benefit of the power system is remarkably improved, the operation cost is reduced by optimizing resource allocation, effective utilization of green energy is promoted, and the active loss of the system is successfully reduced by optimizing the layout and operation strategy of the distributed power supply.

The invention discloses a novel electric power system multi-dimensional support demand index evaluation method and system, and belongs to the field of electric power system demand estimation, and the method comprises the steps: analyzing the net load data condition of an electric power system based on system load data and new energy output data; screening extreme weather new energy continuous low output data according to the new energy output data based on the power system net load data condition, determining the time slice of the extreme weather, and obtaining the net load data of the extreme weather period; and determining a support demand index in the time sequence based on the extreme weather period net load data and the total time sequence net load data, and carrying out support planning on the novel power system power supply. According to the method, a multi-dimensional supporting index system of the supporting power supply is more comprehensively constructed, and a reference basis is provided for novel power system supporting power supply planning.

The present invention provides a method and system for optimizing the configuration of distribution network resources based on artificial intelligence. It relates to data processing technology, and the method includes: establishing a virtual network corresponding to the distribution network based on digital twin technology, obtaining the power planning starting point and the power planning ending point selected by the resource configuration end; determining the initial planning route composed of the power planning starting point and the ending point, and performing corridor interception on the virtual corridor based on the relative position relationship between the initial planning route and the virtual corridor to obtain the corridor planning section; segmenting the corridor planning section, and updating the route of the initial planning route based on each divided sub-segment of the corresponding idle attribute to obtain the current planning route; configuring route temperature control, and sending circuit resource optimization data to the resource configuration end; in response to receiving the configuration completion signal sent by the resource configuration end, obtaining temperature monitoring data, and updating the operation status of the current planning route in the virtual network. The present invention at least improves the planning efficiency.

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 relates to the technical field of data classification, and discloses an industrial power consumption data classification method considering energy consumption characteristics, which comprises the steps of data acquisition, preprocessing, feature extraction, data classification and data integration, data acquisition covers multiple parameters, the data source is wide, and the applicability is high. In the preprocessing link, through data marking, missing value filling and abnormal value replacement, the data accuracy and integrity are guaranteed, and a foundation is built for subsequent analysis; in feature extraction, multiple feature values are determined from the dimensions of power, electricity consumption, electricity consumption time and the like, and electricity consumption features are described in multiple directions; according to data classification, the characteristic value is compared with a preset threshold value, and multi-dimensional judgment is combined, so that classification is more accurate, and the actual power utilization condition of the industry is met; the data is integrated to form a comprehensive classification result, which is convenient for direct application in the aspects of power planning, industrial layout and the like. On the whole, the method is helpful to accurately grasp the industrial electricity utilization rule, and provides a scientific and effective basis for reasonable allocation of electric power resources, electricity utilization management and the like.

The invention discloses a scene generation method and system for new energy extreme meteorological disturbance modeling, and relates to the technical field of power systems, and the method comprises the steps: recognizing a strong disturbance event under meteorological drive according to a constructed new energy effective output sample set, and constructing a generative adversarial neural network model embedded in a wind power photovoltaic physical boundary condition, acquiring a virtual disturbance section; and based on the virtual disturbance section, constructing a new energy annual extreme disturbance scene set by integrating a plurality of typical days embedded with disturbance, and applying the new energy annual extreme disturbance scene set to new energy extreme meteorological disturbance modeling and sample enhancement. The method has strong representation capability, good training stability and scene expansion capability, and can provide more representative and diversified input scenes for dispatching optimization and supporting power supply planning of the power system, so that the robustness and risk perception capability of the system for coping with extreme events are improved.

The invention belongs to the technical field of power planning, and particularly relates to an urban power utilization evaluation method based on power big data and a related device. The urban power utilization evaluation method comprises the following steps: collecting real-time power utilization behaviors of intelligent electric meter data, SCADA data and power grid GIS data to form multi-dimensional power utilization big data; constructing a knowledge graph based on the multi-dimensional power utilization big data and the topological structure association information; performing urban power consumption behavior analysis based on the knowledge graph to obtain power consumption behavior characteristic data; embedding the power consumption behavior characteristic data into a geographic space model by combining a geographic space technology, and mining regional power consumption distribution characteristics; based on regional power distribution characteristics, a spatial calculation algorithm is used, the power consumption population density is considered, and the urban power consumption layout is optimized. The problem that a traditional power system evaluation method cannot accurately evaluate the urban power demand is solved.

The invention relates to the technical field of power grids, in particular to a smart power grid environment adaptive data processing method and system. According to the method, through cooperative work of an environment sensing sensor, a high-definition camera and an unmanned aerial vehicle inspection system, omnibearing environment information including meteorological data, landform data, vegetation coverage data and human activity data is obtained; a distributed storage architecture and a parallel processing technology are adopted to efficiently pre-process the environmental data; constructing a smart grid environment adaptive analysis model covering power planning decision support, power operation and maintenance decision support and power dispatching decision support; an analysis result is visually displayed through a multi-level visual interface based on the GIS technology, and environmental adaptability optimization of active defense, automatic recovery and optimal adaptation is achieved. The problems of uneven data quality, low processing efficiency, insufficient analysis capability and the like of a traditional power grid are solved.

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 relates to a trans-provincial green electricity optimal scheduling method considering AC / DC tie line constraint, and belongs to the technical field of power planning. The method comprises the following steps: constructing an inter-provincial first-level optimization scheduling cost model based on output of each conventional unit and each new energy unit in a scheduling range, and conventional energy power and new energy power transmitted by each trans-provincial tie line; constructing an intra-province secondary optimization scheduling cost model based on the output of each conventional unit and the output of each new energy unit in each province; with the minimum first-level scheduling cost as the target, the transmission power of the inter-provincial tie line is solved based on set constraints and serves as an inter-provincial scheduling scheme; and solving based on the transmission power of the inter-province tie line and the set constraint by taking the minimum in-province secondary optimization scheduling cost as a target to obtain an in-province unit output scheduling scheme of each province region. According to the method, the alternating current and direct current tie line constraint of trans-provincial dispatching is considered, and the secondary optimization model is constructed, so that the system power generation cost can be reduced, and the inter-provincial and intra-provincial new energy consumption can be improved.

The invention relates to the technical field of weeding robots, and discloses a photovoltaic field weeding robot path planning method and device and related equipment.The photovoltaic field weeding robot path planning method comprises the steps that a grid map of a photovoltaic field is obtained, region division is conducted on the grid map, and the grid map is obtained; obtaining an impassable area including the obstacle and a passable area not including the obstacle; dividing the passable area into one or more sub-areas based on the impassable area; extracting inscribed rectangles of the sub-regions to obtain inscribed rectangular regions; path planning is carried out in each inscribed rectangular area based on a cattle farming coverage method to obtain a target sub-path; and connecting each target sub-path based on the region sequence of each sub-region to obtain a target path of the weeding robot. The navigation complexity can be reduced, and the path planning efficiency can be improved.

The invention discloses a new energy grid-connected system voltage sensitivity index evaluation method based on an entropy weight method. According to the method, firstly, construction of a new energy grid-connected system voltage sensitivity evaluation index system is researched; and constructing a new energy grid-connected system voltage sensitivity evaluation index system by integrating a reactive power response coefficient reflecting reactive power disturbance and a voltage control factor reflecting voltage supporting capability. Secondly, a new energy base simulation model is constructed, power flow simulation is carried out, and index values of reactive response coefficients and voltage control factors of new energy station nodes are obtained through calculation; furthermore, how to apply the entropy weight method to new energy grid-connected system voltage sensitivity index evaluation is researched, a scientific evaluation result is obtained, a voltage weak point is determined, and a theoretical basis is provided for reactive power planning.

A reactive power planning method considering transient voltage stability for large-scale wind and solar access includes the following steps: Step 1: Based on the scenario probability theory, typical scenarios of uncertainty characterizing large-scale wind power and large-scale photovoltaic power are constructed in sequence; Step 2: A transient voltage safety margin index based on a voltage binary table is proposed to guide reactive power planning, and a benchmark scenario for reactive power planning is constructed; Step 3: First, the configuration scheme of the dynamic reactive power compensation device is screened by the improved entropy weighted superior and inferior solution distance method TOPSIS method, and then the final configuration scheme of the dynamic reactive power compensation device is determined by the perturbation method. The method of the present invention takes into account the uncertainty of large-scale wind power and large-scale photovoltaic output, and the resulting planning scheme is applicable to all working conditions, and while ensuring the compensation effect, it saves economic costs to a great extent.

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 present application proposes a method and system for automatic start and shutdown of a power station based on an active power plan curve, the method comprising: obtaining the active power plan curve of the power station for the whole plant today; performing automatic start and shutdown operations of the power station according to the active power plan curve of the whole plant today; wherein the active power plan curve of the whole plant includes a V-shaped curve. The technical solution proposed in the present application eliminates the need for manual start and shutdown operations for the centralized control and power plant, and eliminates the need for manual load adjustment in the vibration zone of the unit, saving a lot of operation time for the on-duty personnel, and making the start and stop of the unit more reasonable, and the load adjustment more accurate and stable, thereby increasing the life of the unit and ensuring the safe and stable operation of the power grid; there is no need to exit AGC control during the start and stop process of the unit, which improves the availability of AGC, can provide frequency regulation services stably and continuously, improves the automation level of the power station, and avoids the deduction of frequency regulation mileage compensation and AGC regulation capacity compensation for the corresponding transaction cycle due to the cumulative time of exiting AGC exceeding 5 minutes, thereby improving the company's economic benefits.

The invention provides a large model application system for energy power planning and intelligent optimization. The system comprises a data acquisition end and a model application end, the data acquisition end is used for acquiring, integrating and storing multi-dimensional electric power information of an electric power system; the model application end is used for intelligently planning and optimizing the power transmission of the power system based on the data acquired by the data acquisition end, so as to ensure the efficient utilization of power resources and the stability of the system; through multi-dimensional data integration and intelligent optimization, efficient distribution and stability guarantee of electric power resources are realized, and the flexibility and response capability of an electric power system are improved.