CN110735764A - electric automobile wind power generation system - Google Patents
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D7/00—Controlling wind motors
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D9/00—Adaptations of wind motors for special use; Combinations of wind motors with apparatus driven thereby; Wind motors specially adapted for installation in particular locations
- F03D9/10—Combinations of wind motors with apparatus storing energy
- F03D9/11—Combinations of wind motors with apparatus storing energy storing electrical energy
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
- F03D—WIND MOTORS
- F03D9/00—Adaptations of wind motors for special use; Combinations of wind motors with apparatus driven thereby; Wind motors specially adapted for installation in particular locations
- F03D9/30—Wind motors specially adapted for installation in particular locations
- F03D9/32—Wind motors specially adapted for installation in particular locations on moving objects, e.g. vehicles
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/72—Wind turbines with rotation axis in wind direction
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/728—Onshore wind turbines
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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Abstract
The invention discloses electric automobile wind power generation systems, which comprise a physical layer and a network technology layer, and provides a scheme of electric automobile wind power generation systems, wherein the design and the system development of a wind power framework are carried out from two aspects of the physical layer and the network layer technology according to the operation requirements of the automobile wind power generation systems, the scheme is based on a cloud computing technology and the large data analysis of a 5G network and the operation of a wind power generator and the power consumption requirements of users, the wind power resources in the running process of an automobile are utilized to the maximum extent, the intelligent processing of wind power generation data is realized, the deep fusion of wind power generation services and the network is realized, the decision is carried out according to different wind power scenes and the power consumption of the users by improving the cloud computing capacity under a complex heterogeneous wind field, the refined and personalized wind power design deployment with the power generation and control efficiency taking the power consumption requirement characteristics of the users into consideration is realized, the power generation technology is more intelligent, and more flexible, efficient and higher-quality.
Description
Technical Field
The invention relates to the technical field of automobile power generation, in particular to wind power generation systems of electric automobiles.
Background
The core concept of the wind power generation application of the electric automobile is a brand-new energy (wind resource) development, utilization and design and operation and maintenance management mode, and extreme user experience of approximate infinite endurance mileage is provided for electric automobile users. The wind power generation by utilizing the wind energy in the high-speed running of the automobile is the most important power generation mode with large-scale development and commercial utilization value, and the outstanding effects of reducing pollution, reducing greenhouse gas emission and promoting sustainable development are increasingly emphasized by people, and the wind power generation device with reliable development and design work, high efficiency and low cost has great economic value.
The generator is designed according to input stable torque and rotating speed, and cannot adapt to the change torque and rotating speed of wind energy output, the automobile wind power generation utilizes wind resistance in the high-speed running process of an automobile, the obtained wind energy is converted into rotary mechanical energy through a wind turbine or a wind wheel to be driven, and then the wind energy is converted into electric energy through a special generator, because the uncertainty of the wind energy and the instability of the wind speed form a heterogeneous wind field of the wind energy under most conditions, the traditional grid-connected wind power generation technology is directly solving the problems of power generation and operation under complex wind conditions, and the specific technical means comprises a blade speed regulation device, a gear speed regulation device, a yaw protection technology, stall control, a braking system, a generator stator coil temperature measurement device, a generator speed measurement rotor device and the like, the problems of light load, large wind speed overload and the like of the generator under low wind speed are relieved to the certain extent in , however, the traditional wind power generator is designed according to input stable torque and rotating speed, has strict requirements on the rotating speed of power generation, and cannot adapt to the transient change of the output under severe torque and instantaneous change of the automobile, so that the automobile cannot effectively solve all the problems of the wind energy during running under the wind energy
The automobile wind power generator device must ensure that the automobile wind power generator device can safely operate for a long time under various running wind conditions and climate conditions, turbulence and other extreme wind conditions must be considered, abnormal changes of a wind pressure coefficient, stall effect of separation of airflow and blades and the like must be responded, and in cold regions, the automobile wind power generator device must be provided with anti-freezing measures.
In the field of wind power generation, large-scale weakening characterized by wind energy is an important factor of wind power generation attenuation, damage to a generator caused by overload of the rotating speed of the generator due to excessive wind speed is fatal, change of the wind speed is which is the most complex challenge of automobile wind power generation, a large amount of unstable wind energy can greatly deteriorate the rotating speed of the generator and stable current output during driving, and particularly dynamic change of the wind energy caused by changes of climate, road conditions and vehicle speed makes a wind power generation operation mechanism more complex.
The wind power resource is a key factor directly influencing the overall performance of the automobile wind power system and also directly influencing the power supply capability of the wind power equipment and the power consumption experience of the terminal user, and the wind power resource is used as a core resource and an important carrier for continuous innovation and development of the automobile wind power generation technology and even the wind power supply industry, and needs to deal with a plurality of challenges facing the operation of a wind driven generator while meeting the requirement of wind power generation.
Disclosure of Invention
In order to solve the technical problems, the invention provides the technical scheme that the electric automobile wind power generation systems are characterized by comprising a physical layer and a network technical layer;
wherein the physical layer comprises:
the power generation terminal module is used for receiving wind energy and realizing terminal wind power generation;
the intelligent sensing module is used for acquiring a wind energy signal; acquiring the rotating speed information of a generator and the power utilization information of a user;
the network technology layer comprises:
the cloud computing control center module is connected with the plurality of power generation terminal modules and the intelligent sensing module, and controls each power generation terminal module by utilizing wind power resources in the running process of the automobile so as to enable the rotating speed of a generator of each power generation terminal module to be matched with the wind speed; data transmission is carried out between the power generation terminal and other functional modules, so that centralized management and control of the power generation terminal are realized; establishing a central database, and storing relevant power generation information; analyzing data in the central database and establishing a power generation control strategy taking the power consumption demand of a user as the center according to the data analysis result;
other functional modules include:
the centralized control module is in data transmission with the cloud computing control center module, processes and feeds back the power generation terminal by utilizing 5G network clustering centralized control and data of the cloud computing control center, and realizes dynamic closing or opening of the automobile power generator and reasonable power utilization selection of the terminal; the power generation efficiency and the wind power utilization rate are improved;
the power generation perception prediction module is used for predicting and identifying the power consumption demand of a user and sending the power consumption demand information to the cloud computing control center module and the centralized control module;
the wind energy discovery and selection module is in data transmission with the cloud computing control center module, can respond to a request for selecting wind power generation of the terminal, assists the terminal in discovering available wind energy, and controls and processes the power generation terminal to select a power generation state to be accessed among different wind power systems according to the upper limit wind power information of the power generation terminal and the user power demand information;
the generator trigger switching module is used for carrying out data transmission with the cloud computing control center module, rapidly entering a power generation mode according to the wind power information acquired by the cloud computing control center module and adjusting the power generation state of the power generation terminal;
the wind power generation boundary determining module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, determining the working operation interval range of the power generation terminal according to the optimal operation relation between wind energy and the power generation terminal of the wind turbine, and determining the starting and stopping boundaries of the generator;
the power generation self-configuration and self-optimization module of the 5G network performs data transmission with the centralized control module, dynamically coordinates the power generation terminal with the 5G network signaling transmission, configures power generation load balancing and optimization parameters, and controls the power generation terminal to optimize power generation capacity;
the wind energy inter-system access module is used for carrying out data transmission with the cloud computing control center module and is connected with the power generation terminal module, and the wind energy inter-system access module outputs power generation strategy information according to current wind information and power generation operation rotating speed information of the power generation terminal module and transmits the power generation strategy information to the cloud computing control center module;
the available wind energy discovery and distribution module is used for carrying out data transmission with the cloud computing control center module and the centralized control module and controlling the power generation terminal to realize the switching between the available wind energy discovery and distribution and different wind power scenes;
the wind power resource management module is in data transmission with the cloud computing control center module, is used for managing and controlling the wind wheel rotating speed and the generator operation data stored in the cloud computing control center module, and conducts resource multiplexing and sharing on the wind power resource acquisition and power generation output operation data through the cloud computing control center;
the wind power distribution module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, acquiring wind power resource information, distributing wind power resources to coordinate and control the power generation terminal and controlling the power generation access of the power generation terminal;
the wind power generation shutdown dormancy module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, judging the optimal power generation shutdown and dormancy strategy and realizing the shutdown and dormancy control of the power generation terminal according to the control strategy;
the generating capacity statistics and electricity consumption charging planning module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, carrying out real-time monitoring and management on the generating capacity of the power generation terminal and providing a scheme for carrying out statistics and electricity consumption charging according to the generating capacity.
As an improvement, the power generation terminal module adopts a plurality of double salient pole direct current generators which can expand the wind speed data rate and the rotating speed and can support the multi-level wind speed operation.
As an improvement, the power generation information in the central database of the cloud computing control center module includes wind energy environment information, wind power index information, generator rotation speed information, generator no-load information, generator short-circuit information, generator external characteristic information, generator excitation current intelligent distribution information, load balancing information, network information, and user power consumption information.
As an improvement, the centralized control module comprises a power generation selection unit transparent to users and used for matching the rotating speed of the terminal generator with the wind energy; the power generation control unit supports cloud centralized control and is used for automatic access control, intelligent turn-off control, stall control and overload protection control of the power generation terminal; and the multi-electric fusion control unit is used for controlling a plurality of power generation terminals simultaneously.
As an improvement, the implementation method of the power generation perception prediction module comprises the steps of researching the power consumption demand of a user and a power generation service model, and determining a high-probability service demand; through the autonomous learning of the machine, all the power generation business requirements are identified by utilizing the automatic identification technology of the equipment; according to the power generation service requirements, carrying out virtual partitioning on wind power generation implementation, and simultaneously, forecasting new wind power generation requirements by matching with historical data and big data statistical analysis technology; and carrying out secondary division on the virtual partitions, thereby providing basic conditions for self-organization and self-optimization of the power generation technology.
As an improvement, the generator trigger switching module adjusts the power generation state of the power generation terminal, including self-starting configuration adjustment, self-optimizing intelligent turn-off adjustment, monitors the rotation speed of the generator, and transmits the rotation speed information and the power utilization information of the generator back to the cloud computing control center module.
As an improvement, the implementation method of the wind power generation starting and stopping boundary determination module comprises the steps of researching an optimal operation mathematical model of wind power and a generator, determining the maximum and minimum operation modes of the operation of the high-probability power generation terminal, meanwhile, matching with the big data analysis of historical data of the cloud computing control center module, correcting the mathematical model, predicting to obtain the working operation interval range of the power generation terminal, further determining the working operation boundary of the wind power generator of the power generation terminal, virtually dividing the control on the basis of determining the boundary, and dynamically generating the virtual control of the wind power operation boundary.
As an improvement, the data management of the wind resource management module comprises the establishment, modification and deletion of wind energy input of a power generation terminal for power generation input operation. And wind energy isolation is supported, and a power generation terminal is protected.
As an improvement, the wind power distribution module adopts a centralized distribution mode and a distributed distribution mode.
As an improvement, the implementation method of the intelligent shutdown and dormancy module for wind power generation comprises the steps of calculating an optimal power generation shutdown and dormancy strategy by using a generator shutdown and dormancy optimization model according to the automobile storage capacity statistical result obtained by the intelligent sensing module.
As an improvement, the system further comprises a power generation system safety module, and the implementation method of the power generation system safety module comprises the steps of acquiring fault information when a specific function or hardware equipment is unavailable, stripping a fault from the power generation equipment, and enabling the power generation terminal to be in quick physical communication with a 5G core network through the coordination of a 5G network by a centralized control module.
As an improvement, the cloud computing control center module includes a control plane and a user plane that operate independently, the control plane can add wind power service logic to form user plane programmability, the processing function of the user plane can be decomposed, and the decomposed functions can be adjusted and combined according to the wind power processing logic issued by the control plane. And the electricity generation service customized by the user is realized.
As an improvement, the cloud computing control center module is a programmable and extensible network open module.
The invention has the advantages that the invention provides schemes of wind power generation systems of electric automobiles, the design and the system development of a wind power framework are carried out from two aspects of physical layer and network layer technologies according to the operation requirements of the wind power generation systems of the automobiles, and the scheme is based on the cloud computing technology and the 5G network, the large data analysis of the operation of a wind power generator and the power consumption requirements of users, the wind power resources in the driving process of the automobiles are utilized to the maximum extent, the intelligent processing of the wind power generation data is realized, the deep fusion of the wind power generation service and the network is realized, the decision is carried out aiming at different wind power scenes and the power consumption of the users by improving the cloud computing capacity under the complex heterogeneous wind field, the refined and personalized wind power design deployment of the power generation and control efficiency taking the power consumption characteristics of the users into consideration is realized, the service perceptibility of the power consumption of the users is achieved, the power generation technology is more intelligent, and more flexible.
Drawings
FIG. 1 is a schematic structural diagram of a wind power generation system of electric vehicles according to the invention.
FIG. 2 is a schematic structural diagram of a centralized control module of electric automobile wind power generation systems.
Detailed Description
With reference to the attached drawings
wind power generation system for electric automobile comprises a physical layer and a network technology layer;
wherein the physical layer comprises:
the power generation terminal module is used for receiving wind power and realizing terminal wind power generation; the power generation terminal module adopts a multi-phase electro-magnetic doubly salient direct-current generator supporting a plurality of extensible wind speed data rates and rotating speeds; because the output of the electric excitation doubly salient motor is a diode rectifying circuit, the output direct current power supply is kept not to change due to the rotating speed and the load size through excitation regulation, meanwhile, the electric excitation doubly salient motor rotor is simple in structure and only formed by laminating silicon steel sheets, and the rotor is not provided with a permanent magnet and an excitation winding, so that the electric excitation doubly salient motor is particularly suitable for working under high-temperature, high-speed and severe environments, and is suitable for being used as an automobile wind power generation terminal due to the advantages of simple system structure and no need of a complex converter.
The intelligent sensing module is used for acquiring a wind energy signal; the double closed-loop control of the rotating speed and the current of the generator is realized through a cloud computing system and a 5G technology.
The network technology layer comprises:
the cloud computing control center module is connected with the plurality of power generation terminal modules and the intelligent sensing module and controls each power generation terminal module to enable the rotation speed of a generator of each power generation terminal module to be intelligently matched with the wind speed; data transmission is carried out between the power generation terminal and other functional modules, so that centralized management and control of the power generation terminal are realized; establishing a central database, and storing relevant power generation information; analyzing data in the central database and establishing a power generation control strategy taking a user as a center according to a data analysis result; the cloud computing control center module provides multiple wind energy configurations, so that the power generation terminal module can support multi-energy-level wind speed operation, different wind conditions are distributed in a centralized mode by using a wind energy signal processing algorithm, the rotating speed of the generator is matched, more control and resource reuse of the wind generator are realized, the hardware working capacity of the generator is improved, and the harsh requirements under different wind power scenes are further met; the power generation information in the central database of the cloud computing control center module comprises wind energy environment information, wind power index information, generator rotating speed information, generator no-load and short-circuit information, generator exciting current intelligent distribution information, generator external characteristic information, generator regulation characteristic information, load balance information, network information and user power utilization information. By deploying cloud computing control in a complex heterogeneous wind farm, the power generation service is changed from a wind response mode to a predictive and active operation mode.
The cloud computing control center is used for differentiating and accurately adapting wind energy, optimizing a power generation power control mechanism, so that the rotating speed of the automobile wind driven generator is based on the actual power generation service requirement, obtaining better power generation comprehensive performance, avoiding the problems of unbalanced wind load of the generator, frequent switching in a system and between systems and the like under complex wind conditions, realizing optimization of wind power generation, and simultaneously ensuring the maximum utilization of wind power resources;
the cloud computing control center module is a programmable and extensible network open module and comprises a control surface and a user surface which operate independently, the control surface can increase wind power business logic, the user surface can realize programming, the processing function of the user surface can be decomposed, and the functions after decomposition are adjusted and combined according to the wind power processing logic issued by the control surface. And constructing a logic combination control framework for power generation function deployment, and realizing efficient integration and cooperation of functional modules, the running rotating speed of a generator, elastic expansion along with wind power, fault isolation and self-healing according to power utilization services and power generation requirements.
Other functional modules include:
the centralized control module is in data transmission with the cloud computing control center module, processes and feeds back the power generation terminal by utilizing 5G network clustering centralized control and data of the cloud computing control center, and realizes dynamic closing or opening of the automobile power generator and reasonable power utilization selection of the terminal; the centralized control module migrates a complex power generation program or other processing tasks from the terminal to the cloud computing data processing center, and the processing and feedback of the wind power operation of the terminal are realized by utilizing the strong data processing capacity and high-speed network transmission of the cloud computing or data processing center, so that the processing tasks of the terminal are reduced, and the energy efficiency of the wind power generation terminal is improved.
The centralized control module also comprises a power generation selection unit which is transparent to users and is used for matching the rotating speed of the terminal generator with wind energy; the power generation control unit supports cloud centralized control and is used for automatic access control, intelligent turn-off control, stall control and overload protection control of the power generation terminal; and the control units are fused and used for simultaneously controlling the plurality of power generation terminals.
The power generation perception prediction module is used for predicting and identifying the power consumption demand of a user and sending the power consumption demand information to the cloud computing control center module and the centralized control module; the power generation perception prediction module determines a high-probability service demand by researching the power demand of a user and a power generation service model; through the autonomous learning of the machine, all the power generation business requirements are identified by utilizing the automatic identification technology of the equipment; according to the power generation service requirements, carrying out virtual partitioning on wind power generation implementation, and simultaneously, forecasting new wind power generation requirements by matching with historical data and big data statistical analysis technology; and carrying out secondary division on the virtual partitions, thereby providing basic conditions for self-organization and self-optimization of the power generation technology.
The wind energy discovery and selection module is in data transmission with the cloud computing control center module, can respond to a request for selecting wind power generation of the terminal, assists the terminal in discovering available wind energy, and controls and processes the power generation terminal to select and access a power generation state among different wind power systems according to the upper limit wind power information of the power generation terminal and the user power demand information.
The generator trigger switching module is used for carrying out data transmission with the cloud computing control center module, rapidly entering a power generation mode according to the wind power information acquired by the cloud computing control center module and adjusting the power generation state of the power generation terminal; the generator triggering switching module adjusts the power generation state of the power generation terminal, including self-starting configuration adjustment, self-optimizing intelligent turn-off adjustment, monitors the rotation speed of the generator, and transmits rotation speed information and power utilization information of the generator back to the cloud computing control center module.
The wind power generation boundary determining module is used for carrying out data transmission with the cloud computing control center module and the centralized control module and determining the working operation boundary of the power generation terminal according to the optimal operation relation between wind energy and the power generation terminal of the wind turbine; the implementation method of the wind power generation starting and stopping boundary determination module comprises the steps of researching an optimal operation mathematical model of wind power and a generator, determining the maximum and minimum operation modes of the operation of the high-probability power generation terminal, simultaneously, matching historical data and large data analysis of the cloud computing control center module, correcting the mathematical model, predicting the range of the working operation interval of the power generation terminal, further determining the working operation boundary of the wind power generator of the power generation terminal, virtually dividing the control on the basis of the determined boundary, and dynamically generating the virtual control of the wind power operation boundary.
The power generation self-configuration and optimization module of the 5G network performs data transmission with the centralized control module, dynamically cooperates the operation of the power generation terminal with the signaling transmission of the 5G network to complete optimal allocation of wind power resources and optimal scheduling of power generation services, and the power generation terminal dynamically configures power generation load balancing and optimization parameters according to current wind pressure and wind energy load data to control the power generation terminal to optimize power generation capacity.
The wind energy system indirect access module is used for carrying out data transmission with the cloud computing control center module and is connected with the power generation terminal module, and the wind energy system indirect access module outputs power generation strategy information according to current wind information and power generation operation rotating speed information of the power generation terminal module and transmits the power generation strategy information to the cloud computing control center module; the method comprises the steps of generating rule priority, priority access generating information, effective wind power information, wind power overload information, stall information and the like.
The available wind energy discovery and distribution module is used for carrying out data transmission with the cloud computing control center module and the centralized control module and controlling the power generation terminal to realize seamless switching between available wind energy discovery and distribution and different wind power scenes; providing shorter wind energy discovery time and more efficient wind resource utilization, efficiently managing and allocating available wind power generation discovery resources.
The wind power resource management module is in data transmission with the cloud computing control center module and is used for managing and controlling the wind wheel rotating speed and the generator operation data stored in the cloud computing control center module, the data are shared and isolated through the cloud computing control center, generator rotating speed control resource pools are formed, wind power resources can be shared by common wind energy of generators with different rotating speeds, the challenge of complex and heterogeneous wind pressure in driving can be effectively met, the rotating speed of the generator is rapidly matched with the wind speed, wind power resources are reasonably distributed, the data management of the wind power resource management module comprises the establishment, modification and deletion of wind energy input of a power generation terminal, and the wind energy isolation is supported to protect the generators.
The wind power distribution module is in a centralized distribution mode and a distributed distribution mode, the centralized algorithm controls the wind power distribution and power generation access processes through a centralized unit, each -level wind power index in the distributed algorithm participates in a wind power distribution decision, the sensitivity and reliability of the wind power detection control process are improved, wind power resource information is obtained, a wind power resource is distributed to coordinate and control a power generation terminal, and the power generation access of the power generation terminal is controlled;
and the wind power generation intelligent shutdown dormancy module is used for obtaining the automobile storage capacity statistical result according to the intelligent sensing module and calculating the optimal power generation shutdown and dormancy strategy by using a generator shutdown and dormancy optimization model. The shutdown and dormancy of the power generation terminal are controlled according to the control strategy;
and the generating capacity counting and electricity consumption charging planning module is used for carrying out data transmission with the cloud computing control center module and the centralized control module and carrying out real-time monitoring and management on the generating capacity of the generating terminal. And providing a scheme for counting according to the generated energy and charging for electricity utilization.
The power generation device system safety module is realized by the method that safe deployment is realized at a place needing time, wherein the place needing time comprises a failure event, fault information is obtained when a power generation terminal is unavailable, the position of data information is easily changed and is stored again, and a fault is stripped from power generation equipment. When the cloud computing platform fails unexpectedly, the centralized control module enables the power generation terminal to be communicated with the 5G core network through the coordination of the 5G network. Supporting fail-soft rather than full interruption.
The multi-electric fusion and multi-electric power control module performs data transmission with the cloud computing control center module and the centralized control module, automobiles can keep a multi-electric-generation terminal device to generate electricity simultaneously to form a multi-channel power supply power generation structure through the centralized control module, the 5G technology and the deep fusion of the cloud computing control network, the power generation capacity and high-power supply can be improved, the reliability of power supply can be enhanced through multi-electric-room load balance, when a plurality of generators work in parallel, the power control system has the function of parallel current sharing among the generators, the power generation performance is improved, the matching of electricity consumption of the plurality of generators and the terminals is realized, the power generation terminal integrates the plurality of wind driven generators, more power generation devices and power supply capacity are provided, and the redundant.
In the description herein, reference to the terms " embodiments," " embodiments," "examples," "specific examples," or " examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least embodiments or examples of the invention.
In summary, if a person skilled in the art receives the teaching of the present invention, the technical scheme and the embodiments similar to the technical scheme are not creatively designed without departing from the spirit of the present invention, and the present invention shall fall into the protection scope of the present invention.
Claims (13)
- The electric automobile wind power generation system is characterized by comprising a physical layer and a network technology layer;wherein the physical layer comprises:the power generation terminal module is used for receiving wind energy and realizing terminal wind power generation;the intelligent sensing module is used for acquiring a wind energy signal; acquiring the rotating speed information of a generator and the power utilization information of a user;the network technology layer comprises:the cloud computing control center module is connected with the plurality of power generation terminal modules and the intelligent sensing module, and controls each power generation terminal module by utilizing wind power resources in the running process of the automobile so as to enable the rotating speed of a generator of each power generation terminal module to be matched with the wind speed; data transmission is carried out between the power generation terminal and other functional modules, so that centralized management and control of the power generation terminal are realized; establishing a central database, and storing relevant power generation information; analyzing data in the central database and establishing a power generation control strategy taking the power consumption demand of a user as the center according to the data analysis result;other functional modules include:the centralized control module is in data transmission with the cloud computing control center module, processes and feeds back the power generation terminal by utilizing 5G network clustering centralized control and data of the cloud computing control center, and realizes dynamic closing or opening of the automobile power generator and reasonable power utilization selection of the terminal; the power generation efficiency and the wind power utilization rate are improved;the power generation perception prediction module is used for predicting and identifying the power consumption demand of a user and sending the power consumption demand information to the cloud computing control center module and the centralized control module;the wind energy discovery and selection module is in data transmission with the cloud computing control center module, can respond to a request for selecting wind power generation of the terminal, assists the terminal in discovering available wind energy, and controls and processes the power generation terminal to select a power generation state to be accessed among different wind power systems according to the upper limit wind power information of the power generation terminal and the user power demand information;the generator trigger switching module is used for carrying out data transmission with the cloud computing control center module, rapidly entering a power generation mode according to the wind power information acquired by the cloud computing control center module and adjusting the power generation state of the power generation terminal;the wind power generation boundary determining module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, determining the working operation interval range of the power generation terminal according to the optimal operation relation between wind energy and the power generation terminal of the wind turbine, and determining the starting and stopping boundaries of the generator;the power generation self-configuration and self-optimization module of the 5G network performs data transmission with the centralized control module, dynamically coordinates the power generation terminal with the 5G network signaling transmission, configures power generation load balancing and optimization parameters, and controls the power generation terminal to optimize power generation capacity;the wind energy inter-system access module is used for carrying out data transmission with the cloud computing control center module and is connected with the power generation terminal module, and the wind energy inter-system access module outputs power generation strategy information according to current wind information and power generation operation rotating speed information of the power generation terminal module and transmits the power generation strategy information to the cloud computing control center module;the available wind energy discovery and distribution module is used for carrying out data transmission with the cloud computing control center module and the centralized control module and controlling the power generation terminal to realize the switching between the available wind energy discovery and distribution and different wind power scenes;the wind power resource management module is in data transmission with the cloud computing control center module, is used for managing and controlling the wind wheel rotating speed and the generator operation data stored in the cloud computing control center module, and conducts resource multiplexing and sharing on the wind power resource acquisition and power generation output operation data through the cloud computing control center;the wind power distribution module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, acquiring wind power resource information, distributing wind power resources to coordinate and control the power generation terminal and controlling the power generation access of the power generation terminal;the wind power generation shutdown dormancy module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, judging the optimal power generation shutdown and dormancy strategy and realizing the shutdown and dormancy control of the power generation terminal according to the control strategy;the generating capacity statistics and electricity consumption charging planning module is used for carrying out data transmission with the cloud computing control center module and the centralized control module, carrying out real-time monitoring and management on the generating capacity of the power generation terminal and providing a scheme for carrying out statistics and electricity consumption charging according to the generating capacity.
- 2. The electric vehicle wind power generation system of claim 1, wherein the power generation terminal module employs a plurality of double salient dc generators capable of supporting multi-level wind speed operation with scalable wind speed data rate and speed.
- 3. The electric vehicle wind power generation system of claim 1, wherein the power generation information in the central database of the cloud computing control center module includes wind energy environment information, wind power index information, generator speed information, generator external characteristic information, generator excitation current intelligent distribution information, load balancing information, network information, and user power consumption information.
- 4. The electric automobile wind power generation system of claim 1, wherein the centralized control module comprises a user transparent generation selection unit for matching the terminal generator speed with the wind energy, a generation control unit supporting cloud centralized control for automatic access control, intelligent turn-off control, stall control and overload protection control of the generation terminals, and a fusion control unit for controlling multiple generation terminals simultaneously.
- 5. The electric automobile wind power generation system of claim 1, wherein the implementation method of the power generation perception prediction module comprises researching user power demand and power generation business models to determine high probability business demand, identifying all power generation business demands by automatic learning of machines and using automatic identification technology of devices, virtually partitioning wind power generation according to power generation business demand, predicting new wind power generation demand by matching historical data and high data statistical analysis technology, and secondarily partitioning virtual partitions to provide basic conditions for self organization and self optimization of power generation technology.
- 6. The electric vehicle wind power generation system of claim 1, wherein the generator trigger switching module adjusts the power generation state of the power generation terminal including self-starting configuration adjustment, self-optimizing intelligent turn-off adjustment, monitors the generator speed, and transmits the generator speed information, generator no-load information, short circuit information, and power consumption information back to the cloud computing control center module.
- 7. The electric automobile wind power generation system of claim 1, wherein the implementation method of the wind power generation start and stop boundary determination module includes studying a wind power and generator optimal operation mathematical model, determining maximum and minimum operation modes of a high probability power generation terminal operation, and meanwhile, in cooperation with a big data analysis of historical data of a cloud computing control center module, correcting the mathematical model, predicting to obtain a power generation terminal operation interval range, further determining a wind power generator operation boundary of the power generation terminal, virtually dividing control on the basis of determining the boundary, and dynamically generating wind power operation boundary virtual control.
- 8. The electric vehicle wind power generation system of claim 1, wherein the data management of the wind resource management module for power generation input operations includes creation, modification, deletion of wind energy input for the power generation terminal.
- 9. The electric automobile wind power generation system of claim 1, wherein the wind power distribution modules are centralized distribution and distributed distribution.
- 10. The electric vehicle wind power generation system according to claim 1, wherein the implementation method of the intelligent shutdown and dormancy module for wind power generation comprises calculating an optimal power generation shutdown and dormancy strategy by using a generator shutdown and dormancy optimization model according to the statistics result of the vehicle charge capacity obtained by the intelligent sensing module.
- 11. The electric automobile wind power generation system of claim 1, further comprising a power generation system safety module, wherein the implementation method of the power generation system safety module includes acquiring fault information when a specific function or hardware device is unavailable, stripping the fault from the power generation device, and the centralized control module coordinates through a 5G network to enable the power generation terminal to be in fast physical communication with a 5G core network.
- 12. The electric automobile wind power generation system of claim 1, wherein the cloud computing control center module includes a control plane and a user plane running independently, the control plane can add wind power service logic, the user plane can implement programming, the processing function of the user plane can be decomposed, the decomposed function can adjust and combine the user plane function according to the wind power processing logic issued by the control plane to form the user-customized wind power service.
- 13. The electric vehicle wind power generation system of claim 1, wherein the cloud computing control center module is a programmable and extensible network open module.
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