111results about How to "Realize rationality" patented technology

The invention provides a machine room overall electrical scheme configuration method and system for cabinet layout, and relates to the technical field of electrical design, and the method comprises the steps: building a machine room three-dimensional digital model, and carrying out the function partitioning; optimizing the cabinet layout and determining the maximum capacity; constructing an electricity load prediction model; uPS load balancing is carried out by adopting deep reinforcement learning; designing an intelligent bus duct wiring and circuit breaker access scheme; constructing an equipment topological graph and collecting operation parameters; extracting equipment association features based on the graph attention network; and identifying an abnormal power consumption mode and optimizing a regulation and control scheme.

According to the coastal saline-alkali land underground water level adjusting system based on real-time monitoring and intelligent regulation and control, the system integrates the soil salinity sensor, the underground water level sensor and the central processing unit, future trend prediction is carried out by monitoring key parameters such as soil salinity and underground water level in real time in combination with a deep learning model, and the real-time monitoring and intelligent regulation and control are achieved. And precise intelligent regulation and control are realized. The system can effectively reduce soil salinization, prevent seawater from flowing backwards, improve the utilization efficiency of water resources and reduce the labor management cost at the same time. The method is characterized in that the application of multi-parameter comprehensive monitoring, a deep learning prediction model and a self-adaptive intelligent regulation and control algorithm provides a new technical solution for coastal saline-alkali land treatment.

The invention relates to the technical field of data processing, provides a strategy selection method for node backup in a multi-domain network, and solves the problem that an existing backup management method cannot effectively deal with complex resource distribution in the multi-domain network. A weighted undirected graph is used for representing a network structure, a multi-domain network model is trained, a random forest algorithm is used for evaluating storage network element node attributes, node priority ranking is determined, reasonable allocation of backup tasks is achieved, and in the task allocation process, node resource use conditions are monitored in real time, and a backup strategy is dynamically adjusted. According to the method, the backup efficiency and the data reliability are improved, the storage and calculation cost is reduced, and the method is suitable for large-scale enterprise cloud environments, financial institution cross-domain data backup and other scenes.

The invention discloses a CFD-based liquefied natural gas after-condenser structure optimization method and device. The method comprises the steps that an initial model is established based on an assembly drawing, and geometric pretreatment is completed; extracting a fluid channel, segmenting and selecting a computational domain, and carrying out local encryption on a key region; generating a polyhedral grid by using a grid division tool, and completing grid independence verification; importing the polyhedral mesh into a solver, and carrying out model setting; boundary and wall surface conditions are set, and solver parameters are configured; setting an initial flow field through a hybrid initialization method, and establishing a flow monitoring window and a temperature monitoring window to adjust simulation until convergence; analyzing the temperature cloud picture and the flow vector diagram, and adjusting the structure of the baffle plate; the tower diameter and the height of the filler layer are adjusted according to a physical quantity field change curve of the filler layer, and the performance of the recondenser is continuously improved. The problem of how to deeply study the flow heat transfer rule in the after-condenser and obtain the flow field distribution characteristics is solved, so that the working performance of the after-condenser is improved.

The invention relates to an index weight dynamic correction method and device for comprehensive evaluation and a medium. The method comprises the steps that all indexes needed by the comprehensive evaluation at the initial moment and index values and weight values of all the indexes are obtained; according to the change of the index required at the current moment relative to the index required at the previous moment, constructing a column connection table for representing the change degree of each index; calculating a posterior probability matrix representing the posterior probability of each index through the Bayesian probability based on the concatenation table; correcting the posterior probability matrix through a correction matrix obtained based on a Probit function to obtain a correction probability matrix; performing standard normal correction on the correction probability matrix; and obtaining a weight value of each index at the current moment based on a result after standard normal correction. According to the invention, dynamic correction of the index weight is realized.

The invention relates to an edge service cache optimization method and device, computer equipment and a storage medium. The method comprises the following steps: modeling an edge service cache optimization problem into an MDP model, and collecting state information of a current environment through an intelligent agent at each time step; based on the state information of the current environment, the intelligent agent adopts a depth deterministic strategy gradient algorithm to optimize a cache strategy, and generates a cache strategy through a strategy network; executing the caching strategy, calculating a service access delay after executing the caching strategy through a value network, and calculating a reward function according to the service access delay; and evaluating the execution effect of the cache strategy according to the reward function, and optimizing the strategy network to generate an optimal target network. According to the embodiment of the invention, through intelligent agent learning and cache strategy optimization, the storage resources of the edge server can be utilized more effectively, so that the cache hit rate, the resource utilization efficiency and the service quality are improved.

The invention relates to the technical field of environmental science and information, in particular to a rural land space carbon emission assessment method, which collects real-time data through a distributed sensor network and an unmanned aerial vehicle remote sensing technology, analyzes and extracts key features by using an adaptive variational auto-encoder and topological data, and effectively identifies a land utilization mode. The graph neural network and the Bayesian optimization generative adversarial network are combined to dynamically evaluate and predict carbon emission, and uncertainty quantitative data are generated; a multi-objective genetic algorithm and a game theory model are used for optimizing land utilization layout, an optimization scheme is executed on a block chain through an intelligent contract and a multi-agent system, and automatic management and dynamic adjustment are achieved; according to the method, the accuracy and the real-time performance of rural land carbon emission evaluation are remarkably improved, and a scientific basis is provided for low-carbon sustainable development.

The invention relates to a lung image data processing method and device, computer equipment, a medium and a product. The method comprises the following steps: acquiring a lung scanning image of a to-be-detected object; performing tissue segmentation processing on the lung scanning image to obtain a tissue segmentation result corresponding to the lung scanning image; performing three-dimensional reconstruction on the tissue segmentation result to obtain a three-dimensional tissue image corresponding to the lung scanning image; performing region segmentation processing on a lung region of the to-be-detected object according to the three-dimensional tissue image to obtain a region segmentation result corresponding to the lung region; and positioning a focus area in the lung area based on an area segmentation result. The method comprises the following steps: firstly, segmenting and reconstructing tissues in a lung scanning image to obtain a three-dimensional multi-tissue image, and then carrying out multi-region division on a lung region based on the three-dimensional multi-tissue image to obtain a three-dimensional lung region segmentation result, so that the three-dimensional lung region segmentation result can stereoscopically present a plurality of regions of the lung, and therefore, the lung region segmentation efficiency is improved. Fine division of lung focuses can be realized.

The invention provides a container resource management method and device, electronic equipment and a medium, and relates to the technical field of cloud computing. The method comprises the following steps: scanning stock resources of each node device of a service node, and constructing a resource topology model; on the basis of the resource topology model, according to the access performance parameters among the resources in the service node, determining a cost factor of the Pod for performing cross-domain access on the resources on the service node; the optimal resource combination of the Pod in the resource topology model is determined by minimizing a target function according to the Qos type of resource allocation of the Pod on the service node, and the target function is obtained based on cost factor construction. Through the technical scheme provided by the invention, the problems of high access cost, limited performance and low refinement degree of resource allocation when Pod uses hardware resources of a service node in related technologies are solved, resource optimization allocation is performed according to different service types of Pod, the access cost of Pod node-level resource allocation is reduced, and the resource allocation efficiency is improved. And the access performance and the refinement degree are improved.

The invention relates to the technical field of ship task scheduling, and discloses a pure electric unmanned ship battery safety management control method, which comprises the following steps: step S101, collecting historical task data, constructing and training a random forest model, and obtaining required electric quantity of M tasks; s102, collecting second task feature data of the M tasks and ship feature data of the U ships; s103, constructing a fleet task atlas, constructing an adaptation degree prediction model according to the fleet task atlas, and outputting the adaptation degree between the ship and the task; and step S104, generating a distribution scheme according to the adaptation degree prediction model in combination with an improved geyser optimization algorithm, wherein the distribution scheme represents that the task is distributed to the ship. According to the method, the optimal allocation scheme is automatically generated by constructing the adaptation degree prediction model and combining the improved geyser optimization algorithm, maximum coverage and reasonable allocation of task execution are achieved, and the energy utilization efficiency is improved.

A residual oil conversion process method and a reaction system belong to the field of oil refining processing, and the process method comprises the following steps: mixing a heavy inferior residual oil raw material with a dispersed molybdenum-containing catalyst and a partially circulated heavy fraction cracking product; after heat exchange and temperature rise, pretreatment is conducted through a 10-30 KHz ultrasonic device; after preheating, entering a slurry bed hydrogenation reactor, and carrying out a hydro-conversion reaction in a hydrogen atmosphere under the conditions of 380-500 DEG C and 5-18 MPa; after subsequent processes and equipment separation, the heavy liquid hydrocarbon part enters a catalytic cracking device and is subjected to a contact reaction with a residual oil cracking catalyst containing aluminum extraction and silicon supplement Y zeolite under the conditions that the temperature is 500-540 DEG C and the catalyst-oil ratio is 5-15; fractionating the product in a fractionating tower; the reaction system comprises an ultrasonic pretreatment device, a slurry bed reactor, a catalytic cracking device, a product fractionating tower and heat exchange, separation and circulation equipment. According to the method, the conversion efficiency and process stability of the heavy inferior residual oil raw material are improved, the yield of light fraction gasoline is increased, the energy consumption is reduced, and the method has good economical efficiency and practicability.

The invention discloses an airport roof rainwater treatment monitoring system and method based on cloud computing, relates to the technical field of rainwater monitoring, and solves the technical problems that under extreme weather conditions such as rainstorm, a traditional drainage system is difficult to drain roof accumulated water quickly, accumulated water flooding may be caused, and normal operation of an airport is affected. The rainfall of the target area is predicted; determining a drainage pipeline combination according to the rainfall of the target area; obtaining the content of each element in the rainwater, and analyzing the water quality index of the rainwater; evaluating the pollution level of the rainwater based on the water quality index; based on the pollution level of the rainwater, different water qualities are conveyed to the corresponding reservoirs; based on the pollution level of the rainwater, different water quality is conveyed to the corresponding filter tanks; the device can quickly and effectively disperse and drain accumulated water on the roof, so that the pressure of the accumulated water on an airport building structure is reduced, and the service life of a building is prolonged.

The invention discloses a configuration optimization method based on low-demand and non-low-demand ship spare parts, and belongs to the technical field of water surface JT equipment guarantee, and the method comprises the steps: solving a low-demand ship spare part configuration optimization model through employing improved gray Markov prediction; a TOPSIS-fused multi-target particle swarm optimization algorithm is adopted to solve the non-low-demand ship spare part configuration optimization model; and performing analogue simulation on an optimal spare part configuration list obtained by solving the multi-target particle swarm optimization model by adopting Monte Carlo, performing a simulation experiment by utilizing the configuration model, and verifying the multi-target particle swarm optimization model. According to the method, the low-demand spare part configuration optimization model and the non-low-demand spare part configuration optimization model are fused, and a better ship spare part configuration optimization method is realized by virtue of respective advantages, so that continuous, safe and reliable operation of a ship is ensured. And the configuration optimization efficiency and accuracy are improved.

The invention discloses an energy-saving and carbon-reducing optimization method and system for a low-carbon park, and relates to the technical field of low-carbon building and park design, and the method comprises the steps: formulating a carbon emission function, and quantifying each influence factor; performing virtualization operation on the spatial layout of the park, and performing multi-objective optimization; and establishing a low-carbon and thermal comfort evaluation feedback mechanism by optimizing a constraint program. According to the method, the goal of promoting carbon emission reduction is achieved, and refined measurement and evaluation are also beneficial to scientific supervision of policy formulators, promote transformation of a park to low-carbon development, improve the efficiency of resource allocation, promote implementation of a green building concept, ensure harmonious coexistence of a building and a natural environment, and improve the economic benefit. Iteration and optimization of the park design become more efficient, it is guaranteed that various services and facilities can be adjusted and improved in time in the actual operation process, and the park continuously develops towards the lower-carbon and more environment-friendly target.

The invention discloses a layout optimization method and device for a mining area and a medium, and relates to the technical field of mineral engineering, and the method comprises the steps: detecting ore body thickness data of a target mining area, and carrying out layout division in a combined layout mode defined by adjacent layered chambers; establishing an ore body geological space through the mining area ore body prediction map of the target mining area; performing primary layout optimization, and determining a first single-layer layout position distribution structure; secondary layout optimization is carried out, and a second single-layer layout position distribution structure of the cross connection roadway is determined; and corresponding mining equipment is connected, mining efficiency optimization is carried out, and an optimal layout scheme of the target mining area is determined. The technical problems that in the prior art, the mining layout lacks rationality and safety, and the mining efficiency is low are solved, and the technical effects that the rationality and safety of the mining layout are achieved, and the mining efficiency is improved are achieved.

The invention is suitable for the technical field of equipment management, and provides a laboratory equipment management method and system for chemical detection, and the method comprises the following steps: receiving an experimental equipment use demand inputted by a user, the experimental equipment use demand comprising an experimental item, user information, demand equipment and a demand time period; judging whether the demanded equipment needs to be queued for use, if so, calling the priority, the credit and the integrity of the corresponding user information, and calculating to obtain an equipment use cardinal number of the user information; determining the deadline of the demand time period, and determining user information allocated to the equipment at the deadline; and calling historical equipment use data of the distributed user information, analyzing the historical equipment use data, and sending equipment training information to the user account. According to the invention, based on a multi-dimensional equipment allocation strategy, the equipment use cardinal number is determined by calling the priority, the credit and the integrity of the user information, so that the fairness and the reasonability of equipment allocation are realized.

The utility model discloses a modularized combined high-low voltage switch cabinet, which comprises a switch cabinet main body, a wire outlet is arranged on the bottom surface of the switch cabinet main body, at least two wire inlets are arranged on the back surface of the switch cabinet main body, and the bottom of the switch cabinet main body is fixedly connected with a support plate. The surface of the supporting plate and the surface of the switch cabinet body are provided with a set of switch cabinet fixing through holes, the switch cabinet fixing through holes are connected through bolts and fixing plates, and the back face of the switch cabinet body is connected with a cable passing plate through cable passing plate fixing holes and bolts. According to the utility model, the switch cabinet fixing through holes among different cabinets are connected through the bolts and the fixing plates, so that the connection among the cabinets is more stable, the heat dissipation effect of the switch cabinet body is improved, the extrusion of cables is avoided, and the overall stability and use effect of the cabinets are improved.

The utility model relates to a dry stream type water flow channel suitable for a rainwater regulation and storage wetland purification system, which is characterized in that an upstream water body is communicated with a downstream water body by adopting a dry stream, and a first water distribution gabion wall used as a water inlet overflow weir is transversely arranged at the communicated part of the dry stream and the upstream water body; a second water distribution gabion wall used as a water making overflow weir is transversely arranged at the position where the first water distribution gabion wall is communicated with the downstream water body, and the first water distribution gabion wall and the second water distribution gabion wall are each provided with a low-position water passing channel. The water distribution gabion wall has a good rainwater retention effect in the process of transferring incoming water of an upstream water body to a downstream water body, pollutants in the water can be effectively filtered and diluted, the water quality is purified, the incoming water and outgoing water can be filtered and purified through the water permeation function of the water distribution gabion wall, and the water distribution gabion wall can be used for filtering and purifying water. And incoming water and outgoing water can quickly pass through when the incoming water quantity is too large, so that overflow caused by retention in upstream water and stream is avoided.

The invention relates to the technical field of data processing, in particular to an intelligent processing method for operation data of automatic textile equipment, which comprises the following steps of: in the operation process of the textile equipment, acquiring a multi-dimensional data set output by a sensor, selecting a Gaussian kernel function, extracting features of the multi-dimensional data set, generating a feature projection value by utilizing matrix operation, and calculating the feature projection value; dimensionality reduction is carried out to obtain low-dimensional space mapping, and density distribution of data points is calculated by drawing a point cloud distribution diagram. According to the method, through feature extraction of a multi-dimensional data set, a feature projection value is generated by using a Gaussian kernel function and matrix operation, key features are accurately extracted, and sufficient information is still kept after data dimension reduction, so that more efficient data processing is realized. The density calculation of the data points and the identification of the local extreme points are performed based on the point cloud distribution map, so that the positioning accuracy of the key data points in the low-dimensional space is improved, and the noise interference in the processing process is reduced.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle target classification matching strike control method and system based on deep learning, and the method comprises the following steps: S1, collecting the original environment data of an unmanned aerial vehicle flight region, carrying out the preprocessing of the original environment data, and generating multi-mode perception data; and S2, inputting the multi-modal sensing data into a pre-constructed deep learning classification network, extracting multi-level depth features of the target through the deep learning classification network, carrying out classification identification on the target based on the multi-level depth features, and outputting target category information and target position information of the target. The multi-modal sensing data is input into the deep learning classification network for target recognition, the multi-modal fusion sensing mode can give full play to the complementary advantages of different sensors, high target recognition accuracy can still be kept in complex environments such as night, low illumination and severe weather, and the adaptive capacity of the system to environment changes is remarkably improved.

The utility model belongs to the technical field of RTO furnaces, and discloses an RTO furnace energy-saving blowback device which comprises a bottom plate, a furnace body is fixedly arranged on the upper surface of the bottom plate, a blowing pipeline is fixedly arranged on one side of the furnace body, an air mixing box is fixedly arranged at one end of the blowing pipeline, an RTO fan is fixedly arranged on one side of the air mixing box, and a blowing fan is fixedly arranged on the other side of the blowing pipeline. The lower surface of the RTO fan is fixedly connected with the bottom plate, a high-temperature bypass is fixedly arranged on one side of the furnace body, a high-temperature air mixing box is fixedly arranged on one side of the furnace body, and the high-temperature air mixing box is fixedly connected with the lower end of the high-temperature bypass. The blowback operation can be carried out on equipment, the use of an RTO system fan is reduced, reasonable distribution, regulation and control of gas entering the furnace body can be realized through the combustion chamber and the air distribution chamber located below the combustion chamber, sufficient combustion of the gas in the combustion chamber is ensured, and the combustion efficiency is improved.

The embodiment of the present invention discloses a method, device, terminal device and storage medium for determining a logistics distribution network. The method includes: taking an initial network as a candidate network, determining its lower bound value and upper bound value; cyclically taking the network with the smallest lower bound value in the candidate network as a parent node, and determining whether to stop the loop according to the difference value between the lower bound value and the upper bound value of the parent node; if the loop is not stopped, generating a child node by setting the subsequent connectivity relationship between a site and a sorting center based on the parent node; updating the row candidate network according to the lower bound value of the child node; if the loop is stopped, taking the network corresponding to the upper bound value of the parent node when the loop is stopped as the logistics distribution network; the lower bound value is determined based on the previous connectivity relationship between the warehouse and the sorting center in the corresponding network; the upper bound value is determined based on the previous connectivity relationship and the subsequent connectivity relationship between the site and the sorting center in the corresponding network. For large-scale networks, the solution can be quickly obtained, and the rationality of the current solution can be evaluated.

This utility model relates to the field of civil engineering technology, specifically a pile foundation shaking table test device. It includes a shaking table body, a container on top of which holds soil and a pile foundation model. The container includes a coaxially arranged rigid inner frame and a rigid outer frame. A flexible sidewall structure is provided between the rigid inner frame and the rigid outer frame. The flexible sidewall structure consists of circumferentially spliced ​​flexible plates and multiple sets of micro-springs connecting the inner surface of the flexible plates to the outer surface of the rigid inner frame. The top and bottom of the flexible plates are connected to the rigid inner and outer frames via sliding guide components to allow radial displacement of the flexible plates in the horizontal plane. This pile foundation shaking table test device, by improving the boundary structure, effectively reduces the soil boundary effect, more realistically simulates the interaction between the pile and soil system under seismic loading, and improves the accuracy of the test.

The present invention belongs to the technical field of heat exchangers, and particularly relates to a modular HVAC heat exchanger, including a low-temperature liquid inlet, a low-temperature liquid outlet, a high-temperature liquid inlet, and a high-temperature liquid outlet; it also includes a general bearing system and a plurality of heat exchange units; the above four liquid inlets and outlets are all opened in the general bearing system, and the general bearing system includes a plurality of connecting components; a single heat exchange unit includes secondary flow channels for mutual heat exchange, and the secondary flow channels are respectively provided with liquid inlets and outlets; the general bearing system is connected to the liquid inlets and outlets of the secondary flow channels of the plurality of heat exchange units in sequence through a plurality of connecting components. This modular HVAC heat exchanger can adaptively adjust the number of heat exchange units connected to the general bearing system according to changes in heating conditions; at the same time, when a heat exchange unit fails and cannot work normally, it can be removed, replaced or repaired without affecting the normal operation of other heat exchange units, thereby ensuring the normal use of this modular HVAC heat exchanger.

The invention discloses a private charging pile real-time load prediction method based on edge calculation, and relates to the technical field of load prediction, and the method comprises the following steps: obtaining historical charging efficiency trajectory data and environmental influence data of a private charging pile; constructing a private charging pile real-time load prediction model based on a bp neural network according to the charging efficiency trajectory data and the environmental influence data; acquiring real-time data of the private charging pile, inputting the real-time data into the private charging pile real-time load prediction model, and performing real-time load prediction on the edge computing equipment to obtain a load prediction value of the private charging pile in the future t time; and the prediction result is sent to the user terminal equipment through the communication module, and a charging plan is reasonably arranged according to the prediction result. According to the invention, the powerful processing capability of the edge computing device is fully utilized, and rapid acquisition, preprocessing and load prediction of the real-time data of the private charging pile are realized.

The invention relates to a toughness evaluation method, device and equipment based on a multi-energy coupling active power distribution network. The method comprises the steps of determining energy network types of the multi-energy coupling active power distribution network, constructing multi-stage evaluation indexes according to network characteristics corresponding to the energy network types, and constructing an energy network multi-stage evaluation index system according to the multi-stage evaluation indexes. Determining index levels of the energy network multi-level evaluation index system, determining a paired comparison matrix corresponding to each index level, and if it is determined that an index consistency characteristic value determined according to the paired comparison matrix meets an index consistency requirement, determining an index weight corresponding to each evaluation index according to the paired comparison matrix, and determining the weight of each screened target toughness index, determining a fuzzy measure according to each target toughness index and the respective index weight, and performing weighted fusion according to the fuzzy measure and the index value of each target toughness index to obtain a toughness evaluation result. The method can improve the accuracy of a power grid toughness evaluation result.

The invention relates to an automobile service process supply chain management method, system and device, and a storage medium, and the method comprises the steps: obtaining vehicle reservation information from an automobile service platform, and carrying out the project analysis, and obtaining vehicle information and maintenance reservation information; designing a vehicle inspection process based on the vehicle information and the maintenance reservation information to obtain a corresponding initial inspection scheme; performing maintenance characteristic matching on the maintenance reservation information according to a preset comprehensive automobile database to obtain a corresponding maintenance standard group; performing maintenance scheduling on the vehicle reservation information according to the maintenance standard group to obtain an initial maintenance scheme; and carrying out integration processing on the initial inspection scheme and the initial maintenance scheme to obtain an automobile service scheme. According to the invention, seamless connection from reservation to maintenance can be provided, and the overall quality and efficiency of automobile service are greatly improved.

The invention discloses wastewater treatment and recovery equipment for environment-friendly water treatment engineering, and belongs to the technical field of wastewater treatment. The device comprises a backflow guide frame, the top of the backflow guide frame is concavely provided with a water flowing channel, a first lifting frame is erected in the center of the top of the water flowing channel, a rotating belt is arranged at the top of the first lifting frame, a primary filtering belt strip is arranged between the first lifting frame and the water flowing channel in a sleeved mode, and a second lifting frame is erected at the bottom of the water flowing channel; the inner wall of the bottom outlet area of the water flowing channel is sleeved with an impeller; through the design of the backflow guide frame and the water flowing channel, wastewater flowing is accelerated, and the treatment efficiency is improved; the flexibility and adaptability of the device are enhanced through the double-power-source design, the sewage visible impurity filtering supervision system monitors impurity data in real time, discovers and treats abnormities in time, ensures the treatment stability, accurately controls the cleaning speed and the wastewater pumping amount through an automatic adjusting mechanism, reduces manual intervention, and achieves reasonable utilization of resources, energy conservation and emission reduction. And sustainable development is promoted.

The utility model relates to the technical field of mold accessories, in particular to a self-lubricating mold guide device which comprises a guide sleeve installed on a fixed mold of a mold and a guide column installed on a movable mold of the mold. The guide column is located in the guide lubricating cavity and is in sliding connection with the guide lubricating cavity, an upper flow channel arranged in the vertical direction is formed in a shell of the guide sleeve, a flaring cavity is formed in the bottom of the upper flow channel, and a side edge inlet hole communicated with the guide lubricating cavity is formed in the inner side cavity wall of the flaring cavity. A lower runner is arranged on the bottom wall of the flaring cavity, a bottom runner is arranged at the bottom of the lower runner and located in a bottom shell of the guide sleeve, and a plurality of bottom overflow holes communicated with the guide lubricating cavity are formed in the top wall of the bottom runner. The utility model is convenient for self-lubricating operation, is not easy to wear, and is favorable for prolonging the service life.

The invention relates to the technical field of micro-grids, and discloses a multi-virtual power plant carbon sharing optimization method. The method comprises the following steps: establishing a single virtual power plant optimization model, and considering carbon sharing between virtual power plants (VPP); establishing a multi-virtual power plant asymmetric Nash bargaining model based on the carbon sharing contribution degree: quantifying bargaining capability of each virtual power plant based on the carbon sharing contribution degree, and establishing a multi-virtual power plant (MVPP) asymmetric Nash bargaining model based on the carbon sharing contribution degree; and solving the MVPP asymmetric Nash bargaining model, and decomposing into two steps of solving: solving the cooperative alliance cost minimization model to obtain the carbon quota shared by the VPP, and solving the MVPP asymmetric Nash bargaining model to obtain the shared carbon price of the VPP. Compared with the prior art, the MVPP carbon sharing optimization method is established, and the carbon sharing strategy of the VPP is solved by adopting the asymmetric Nash bargaining game based on the carbon sharing contribution degree, so that the carbon cost of each VPP is reduced, the economic benefit of each VPP is improved, the benefit distributed by the VPP with the high carbon sharing contribution degree is larger, and the fairness of benefit distribution is ensured.