1391 results about "Supply energy" patented technology

The invention discloses an urban energy network intelligent allocation method and system, and the method comprises the steps: obtaining building energy consumption data and energy supply network topology information, building a supply and demand matching reference, recognizing a load peak value dense time period and a peak clipping and valley filling potential region, and exporting transferable load data to form a regional supply and demand distribution diagram; generating a peak shifting adjustment space in combination with the user response delay duration and the equipment start-stop period; performing gap matching analysis on the regional supply and demand distribution map and the peak shifting adjustment space, creating a hierarchical regulation instruction set, and differentially generating an instant response instruction and a delay response instruction; a regulation and control coordination parameter is formed through coordination configuration of the peak shifting revenue coefficient and the instant response instruction; finally, a regulation and control execution range is determined, cost benefit evaluation is implemented, an urban-level energy scheduling execution scheme is formed, accurate matching and efficient scheduling of urban energy supply and demand are achieved, and comprehensive and efficient scheduling decision support can be provided for application scenes such as an intelligent power grid, regional heat supply and comprehensive energy service.

The invention discloses a water energy accumulator and ground source heat pump combined control method, relates to the technical field of building environment and equipment engineering, accurately captures a time sequence change rule of a building cold load based on the load prediction capability of a time convolution network, overcomes the defect that a traditional method is insufficient in response to sudden fluctuation, and improves the control efficiency. The system can plan an energy storage strategy in advance; an electricity price-load change rate sensitivity index is introduced, and through an adaptive weight adjustment mechanism, economic operation and load tracking requirements are dynamically balanced, so that strategy stiffness caused by fixed priorities is avoided, and the utilization efficiency of time-of-use electricity price signals is remarkably improved; according to the joint optimization design of the mixed integer linear programming model, the equipment operation constraint and the cost target are comprehensively considered, the collaborative decision of the energy accumulator charging and discharging strategy and the heat pump frequency setting is realized, and the direct energy supply dependence in the midday high electricity price period is effectively reduced.

The invention relates to an integrated energy system optimization method considering a carbon emission reward and punishment mechanism and shared electrochemical energy storage, and the method comprises the following steps: carrying out the modeling of an integrated energy system which comprises energy supply, energy conversion, load and shared electrochemical energy storage; constructing a peak-flat-valley period stepped carbon emission mechanism considering the carbon emission difference of different energies and a dynamic carbon price factor, and determining a corresponding carbon transaction cost / reward according to the total carbon emission of the integrated energy system in a scheduling period; based on a capacity leasing and power service mechanism, modeling is carried out on the cost of the shared electrochemical energy storage mode; an optimization scheduling problem is constructed by taking system operation cost minimization and clean energy utilization rate improvement as targets; and solving the optimization scheduling problem to obtain an optimal output scheme and an energy storage charging and discharging strategy of each energy device in the integrated energy system, thereby realizing optimization of the integrated energy system.

The invention provides an energy efficiency prediction and energy-saving scheduling optimization system and method for a food cold chain system, and relates to the technical field of cold chain system energy-saving scheduling, and the system comprises a data recognition module which is used for recognizing cold chain loading state data, and analyzing the space influence characteristics of the loading state data of a cold chain loading space; the strategy obtaining module is used for carrying out energy efficiency optimization on cold chain energy supply according to the space energy efficiency relation between the cold chain space and the link energy supply parameters and the space influence characteristics; the state chain establishment module is used for carrying out loading state dynamic analysis based on the cold chain vehicle path and predicting a path switching node; and the optimization strategy obtaining module is used for carrying out path state node scheduling optimization according to the cold chain path state chain by taking a space energy efficiency strategy as an initial parameter based on the vehicle energy supply coupling relationship and the space energy efficiency relationship of the cold chain system. The technical problem of energy consumption waste in cold chain transportation in the prior art can be solved, and the technical effect of reducing cold chain energy consumption is achieved.

A road construction machine in the form of a road paver or a feeder vehicle for conveying paving material to a road paver, the road construction machine being self-propelled and having a primary drive source, a hopper, at least one working unit and at least one electric consumer for heating the working unit, the road construction machine having an energy supply system with at least one electrical energy storage which can be charged by means of electric current generated outside the road construction machine and is present on the road construction machine as an internal power source for direct current supply to the electric consumer. Furthermore, the disclosure relates to the use of such an energy storage for direct current supply to an electric consumer of a road construction machine.

The invention belongs to the technical field of aircraft control, particularly relates to a range extender control system for an unmanned aerial vehicle and a controller, and aims to solve the problems of limited endurance, poor flight stability and the like caused by discontinuous energy supply and power response lag. The system comprises a range extender power source module, an electric energy conversion and distribution module, a flight state sensing module, a load power prediction module, a multi-target optimization scheduling module and a closed-loop feedback execution module. Through flight state real-time perception and load power prediction based on a recurrent neural network, an optimal power generation instruction is generated in combination with multi-target optimization scheduling, and precise rotating speed tracking is realized through adaptive PID control. A fuel consumption, power supply smooth switching and battery health combined cost function is introduced, dynamic weighting is carried out according to task types, and the cruising ability and the system robustness are improved; the system has the functions of fault emergency response, power battery hot plug and model online updating, and safety and maintainability are enhanced.

The invention relates to the technical field of ground source heat pump control, in particular to an intelligent cooperative control system for a ground source heat pump system and building energy management. The method comprises the steps that a data collecting and preprocessing unit collects multiple types of data in real time and preprocesses the data to form system state vectors; the load and power generation prediction unit predicts future cooling and heating load and photovoltaic power generation power of the building through a machine learning regression model and a time sequence prediction model; the operation optimization unit generates an optimal operation strategy of the ground source heat pump based on a depth deterministic strategy gradient algorithm; and the multi-source energy coordinated control unit realizes multi-device coordinated control through multi-target mixed integer linear programming. Through combination of prediction data and an optimization algorithm, a dynamic matching relation between load fluctuation and energy supply is fully considered, and the problems of soil heat imbalance and unstable comprehensive energy efficiency ratio of the ground source heat pump system in a traditional fixed parameter operation mode are solved.

The invention provides a distributed scheduling method for railway traction stations and peripheral micro-energy grids, and belongs to the technical field of energy supply of micro-energy grid groups containing the railway traction stations, and the method comprises the steps: building a micro-energy grid sharing mutual aid grid structure containing the railway traction stations, obtaining a power model of each railway traction station, and optimally configuring energy storage equipment, obtaining operation constraints of the energy storage equipment; constructing an energy sharing benefit function by taking each micro-energy network agent as a game main body and taking individual benefit maximization as a target, setting constraint conditions, and establishing an energy sharing non-cooperative game model; and solving the energy sharing non-cooperative game model by adopting an alternating direction multiplier algorithm to obtain a distributed energy transaction behavior result and a price result. According to the method, distributed solution is carried out on the micro-energy network energy sharing non-cooperative game model based on the alternating direction multiplier method, original centralized optimization is converted into coupling optimization among a plurality of micro-energy network agents through interactive variables, the efficiency of the whole iteration process is guaranteed, and the privacy of each energy network is protected.

The invention belongs to the technical field of energy consumption management, and particularly relates to an energy consumption optimization control method and system for heating and ventilation equipment, and the method comprises the steps: constructing a distributed pump set architecture, and converting a transmission and distribution system from a centralized regulation and control mode into a distributed regulation and control mode; developing adaptation technology and equipment; establishing a dynamic hydraulic balance regulation and control model by combining a digital twinning technology and an intelligent algorithm; the dynamic regulation and control model is used for optimizing the pump set operation state and the valve opening degree in real time; by constructing a distributed pump set framework, the system can independently adjust the rotating speed of the pump units according to the actual requirements of different sub-areas, the adaptability of the system to different working conditions and load changes is greatly improved, and the heating and ventilation requirements of all the areas can be more accurately met; the problem of excessive energy supply or insufficient energy supply of partial areas caused by overall adjustment in a centralized regulation and control mode is avoided, so that the overall operation efficiency and comfort of the system are effectively improved.

The invention discloses an electrical integrated energy system toughness index evaluation method, which comprises the following steps: firstly, considering disaster-causing uncertainty of extreme disasters, and establishing a typical fault scene set of an electrical integrated energy system; secondly, considering dynamic and static characteristics and coupling constraints of an electric and gas heterogeneous energy flow system, constructing a numerical simulation model of the electrical integrated energy system under a fault condition, and simulating a cascade fault and energy supply recovery process of the system under a typical fault scene set; and finally, based on a simulation result, drawing a multi-stage toughness curve of the system, and constructing a multi-dimensional comprehensive evaluation index system of the electricity-gas dependency under a toughness perspective. The invention further discloses an electrical integrated energy system toughness index evaluation system, full-dimension quantitative analysis of the multi-energy dependency relationship under the fault working condition can be achieved, and weak links caused by multi-energy flow strong coupling can be effectively screened out.

The invention discloses a comprehensive design method for an anti-freezing pavement of a highway in a high-altitude severe cold area, relates to the technical field of road engineering, and solves the problems of high energy consumption, short service life, unfriendly environment or poor system reliability and the like generally existing in the prior art. And the design of combining structures, materials, energy and intelligent control is lacked. A comprehensive design method for an anti-freezing pavement of a highway in a high-altitude severe cold area comprises the following steps that S1, a multi-layer composite pavement structure is constructed, and the multi-layer composite pavement structure is composed of an anti-sliding and ice-inhibiting functional layer, an energy active layer and a heat preservation structure layer from top to bottom; and S2, a distributed state sensing network is arranged in the multi-layer composite pavement structure and on the roadside of the multi-layer composite pavement structure. Passive ice suppression, active ice melting, intelligent sensing and green energy are organically integrated to form a complete'sensing-decision-execution-energy supply 'closed-loop system, and the limitation of a single technology is broken through.

The invention relates to the technical field of unmanned aerial vehicles, and particularly discloses an unmanned aerial vehicle take-off and landing cabin which is characterized in that cabin doors are symmetrically arranged above a cabin body and connected with the two sides of the cabin body, and the two cabin doors are closed at the top of the cabin body to cover the cabin body; a stop two-dimensional code is arranged on the top and / or the side surface of the cabin door The parking platform is arranged in the cabin body, and a lifting mechanism is arranged at the bottom of the cabin body; a guiding two-dimensional code is arranged in the cabin body, and the express cabinet and the storage room are connected to the lower portion of the cabin body. The management system carries out real-time monitoring and data statistics on the use state, energy supply and unmanned aerial vehicle access records of the take-off and landing cabin. The cabin body is made of a high-strength waterproof material and a sealing structure and is matched with a cabin door closing design, so that severe environments such as wind, rain and dust can be effectively resisted, and the unmanned aerial vehicle is prevented from being interfered by the environment in the taking-off, landing and parking processes; smoke, temperature and vibration sensors are integrated, fire hazards, temperature abnormity and illegal invasion are detected in real time, alarm and emergency measures are automatically triggered when abnormity occurs, and the safety of equipment and the unmanned aerial vehicle is guaranteed.

The invention relates to the technical field of aircraft energy management, in particular to an aircraft power supply system and a management method. The aircraft power supply system comprises a power generation subsystem, an energy storage subsystem, an electricity load, a power distribution bus and a first controller, the power generation subsystem and the energy storage subsystem are connected to the power distribution bus in parallel and electrically connected with the power distribution bus, the electricity load is electrically connected with the power distribution bus, and the first controller is electrically connected with the electricity load. The first controller is in communication connection with the power generation subsystem, the energy storage subsystem, the power utilization load and the power distribution bus. The first controller is used for determining the current working mode of the aircraft power supply system based on the generated power of the power generation subsystem and the electric power of the electric load, controlling the power generation subsystem and / or the energy storage subsystem to supply energy to the power distribution bus based on the current working mode of the aircraft power supply system, and controlling the power storage subsystem to supply energy to the power distribution bus based on the current working mode of the aircraft. And controlling the power distribution bus to transmit the electric energy to the electric load and / or the energy storage subsystem. According to the invention, stability of airborne energy supply, dynamic energy balance and bus voltage stabilization can be realized.

The invention provides a large-scale heat energy incremental storage and flexible regulation and control energy supply system and an operation method thereof.The large-scale heat energy incremental storage and flexible regulation and control energy supply system comprises a low-temperature-stage heat pump, a medium-temperature phase change heat storage unit and a high-temperature-stage heat pump, and the low-temperature-stage heat pump exchanges heat with an environment heat source or industrial waste heat and is used for absorbing heat released by the low-grade heat source; the medium-temperature phase change heat storage unit is used for storing heat released by the low-temperature-stage heat pump, and the high-temperature-stage heat pump is connected with the user side in a heat exchange mode and used for outputting hot water or steam to the user side. Incremental heat storage and energy quality regulation and control functions are achieved through the technical path that temperature rise is shared through two-stage compression, and in the heat storage mode, the low-temperature-stage heat pump absorbs heat from environment or industrial waste heat and stores the heat in the phase change heat storage unit in an upgrading mode; in the heat release mode, the high-temperature-stage heat pump further improves the quality of heat storage energy and then outputs high-grade heat energy, the theoretical limitation of traditional electric heating equivalent conversion is broken through, the capacity of peak load shifting and on-demand flexible heat supply is achieved, and the system can be widely applied to the fields of building heating, industrial process heat consumption and the like.

The invention discloses a hydrogen-electricity hybrid energy management method for a low-altitude operation composite wing unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle energy management, and the method comprises the steps: S1, constructing an energy management system which comprises a working condition recognition module, an energy state monitoring module, a decision module and an execution module; s2, real-time operation parameters of the composite-wing unmanned aerial vehicle are collected through a working condition recognition module, and the current operation working condition of the composite-wing unmanned aerial vehicle is judged; s3, collecting real-time energy parameters of the hydrogen fuel cell and the power cell through an energy state monitoring module; s4, the decision module outputs a target energy supply strategy based on the current operation condition and the real-time energy parameters; and S5, the execution module controls the energy supply states of the hydrogen fuel cell and the power cell according to the target energy supply strategy. The three typical working conditions of the low-altitude operation composite wing unmanned aerial vehicle are accurately judged through the working condition recognition module, a decision matrix is constructed in combination with multi-dimensional energy parameters, dynamic matching of energy supply strategies is achieved, and the working condition adaptability is enhanced.

The invention belongs to the technical field of electricity-hydrogen coupling system control, and provides a voltage-air pressure stability control method and system for an electricity-hydrogen coupling system. The voltage-air pressure stability control method for the electricity-hydrogen coupling system comprises the steps that a battery energy storage system serves as an execution unit, and a voltage regulation model is constructed based on the dynamic relation between voltage and current; a solid hydrogen storage system is used as an object, and an air pressure adjusting model is constructed based on the relation between flow and pressure; constructing a hydrogen production / hydrogen consumption model based on hydrogen production / hydrogen consumption behaviors of the electrolytic cell and the fuel cell; on the basis of real-time sharing of state variables of an electricity-hydrogen coupling system, charging and discharging of a battery energy storage system in a millisecond period are adjusted according to a voltage adjusting model, so that rapid and stable control over the voltage of a direct-current bus is achieved. And regulating and controlling the hydrogen charging and discharging flow of the solid hydrogen storage system in a second-level time scale according to the air pressure regulation model to ensure the stable pressure of the buffer tank and continuous hydrogen supply, regulating the electrolysis and fuel cell power according to the hydrogen production / consumption model to ensure the balance of energy supply and demand, and finally realizing the voltage-air pressure stability coordinated regulation and control between the electric domain and the hydrogen domain.

The invention relates to the technical field of engineering equipment, and discloses a guardrail breakdown van. Comprising a device body and a drilling rig mechanism, the top of the device body is provided with the drilling rig mechanism, one side of the drilling rig mechanism is provided with a crane, the top of the device body is fixedly connected with an oil-gas separator, and one side of the oil-gas separator is provided with a radiator. An original engine of an automobile is utilized, additional installation is not needed, normal walking of the automobile is guaranteed, energy is directly supplied to the drilling frame mechanism, the working efficiency is greatly improved, in the aspect of heat dissipation, the drilling frame mechanism adopts a double-rotation and double-transverse-movement mode, a base is flexible, and large-range transverse movement and 360-degree rotation can be achieved; the drilling mechanism and the piling mechanism are installed in an interchange mode, the turning step is reduced, the truck-mounted crane is telescopic and can hoist goods of 3 tons, the truck is stabilized during working, space is saved when the truck-mounted crane does not work, and convenience and high efficiency of first-aid repair operation are improved in an all-around mode.

The invention relates to the field of electrochemical energy storage systems, in particular to a multi-energy complementary electrochemical energy storage system adaptive to load power abrupt change, which comprises a multi-source energy supply component, a power conversion module, an instantaneous power compensation unit (supercapacitor), a direct current bus, an energy storage converter and a central controller. The multi-source energy supply assembly is connected to the direct-current bus through the corresponding power conversion module, the super capacitor is directly connected with the direct-current bus, the energy storage converter is connected with the direct-current bus and the load, and the central controller is connected with all the assemblies. And when the load instantaneous power abrupt change exceeds a threshold value and the bus voltage deviates from an allowable range, the supercapacitor automatically triggers charging and discharging response, releases or absorbs peak current, and fills a power gap. According to the system, instantaneous load compensation is undertaken through the supercapacitor, a low-rate lithium battery and multi-energy priority power supply and dynamic power distribution are matched, an impact load is quickly responded, meanwhile, the system cost is reduced, the power supply stability and safety are improved, and the energy utilization efficiency is optimized.

The present invention relates to the technical field of energy network regulation and control. Disclosed is a user-side integrated energy network coordination control method and system. The method comprises: acquiring energy supply and consumption data of each loop, calculating an actually measured value of a carbon emission responsibility factor of each node, and calculating an actual value of the total carbon emission amount of a user; comparing the actual value of the total carbon emission amount of the user with a limit value of the total carbon emission amount of the user, and when the total carbon emission amount of the user reaches an alarm state, sending warning information to the user; on the basis of predicted data of energy supply and consumption at time t, calculating a predicted value of the carbon emission responsibility factor of each node at time t, and obtaining a carbon emission high-crossing limit value of each node; and comparing the actually measured value of the carbon emission responsibility factor, the predicted value of the carbon emission responsibility factor and the carbon emission high-crossing limit value, and on the basis of the comparison result, configuring an operation mode of each node or issuing an execution instruction to an instruction execution device of each node loop. The present invention ensures that the total carbon emission amount of a user-side integrated energy network meets the limit requirements.

The invention relates to a joint beam and track design method for multi-unmanned aerial vehicle auxiliary sensing energy supply, which is expected to obtain better performance while considering multi-equipment position uncertainty and unmanned aerial vehicle energy consumption. According to the scheme, firstly, a system model and a two-stage sensing auxiliary energy transfer scheme are constructed, then the optimization problem of beam forming and associated scheduling in the sensing stage and the optimization problem of beam forming and trajectory planning in the WPT stage are established respectively, and the two optimization problems are solved by using an optimization algorithm, so that the sensing performance and the WPT efficiency of the system are maximized respectively. By establishing a simulation model for simulation and comparison, the advantages of the proposed algorithm are verified. The multi-unmanned-aerial-vehicle auxiliary sensing, communication and energy transmission network can well serve multiple communication users and multiple energy receiving devices, sensing auxiliary wireless power transmission is achieved, meanwhile, the communication performance requirement is met, and the multi-unmanned-aerial-vehicle auxiliary sensing, communication and energy transmission network has the great advantages in the aspects of sensing precision and wireless power transmission efficiency.

The invention discloses an optimal scheduling method for a comprehensive energy system, relates to the field of energy management, and is used for solving the problems that a traditional scheduling method is difficult to realize overall optimization, the traditional scheduling method is limited, the traditional scheduling method generally simplifies an energy system into a deterministic model, the uncertainty of energy supply and demand is ignored, and the energy consumption is low. And the scheduling scheme is poor in adaptability in actual operation. The method comprises the following steps of S101, data comprehensive acquisition and fine preprocessing, S102, precise system model construction, S103, uncertainty scene scientific generation, S104, optimal scheduling model elaborate construction, S105, model efficient solving and verification, and S106, scheduling scheme robust implementation and dynamic adjustment. The invention provides an optimal scheduling method for a comprehensive energy system, which can fully consider the energy supply and demand uncertainty and various energy coupling characteristic factors, realizes the economic and efficient operation of the comprehensive energy system, and reduces the energy cost and environmental pollution.

The invention relates to a zero-carbon / negative-carbon energy supply system based on carbon flow and energy flow coordinated regulation and a design method, and belongs to the technical field of carbon comprehensive energy power generation. An upper capacity design layer of the system adopts a genetic algorithm to obtain an equipment capacity design scheme of each unit, and outputs the equipment capacity design scheme to a lower operation strategy optimization module; the lower-layer operation design optimization layer obtains an optimal operation strategy of the equipment capacity design scheme by adopting a sequential solution algorithm guided by knowledge rules, takes the leveled kilowatt-hour cost under the optimal operation strategy as the operation cost and feeds back the leveled kilowatt-hour cost to the upper-layer capacity design layer, and the upper-layer capacity design layer evaluates the leveled kilowatt-hour cost based on the fed-back operation cost. According to the system, combined optimization of capacity configuration and an operation strategy is realized, the solving efficiency is greatly improved, and feasibility is provided for solving of a large-scale complex system.

The invention provides a ship waste heat recovery and reutilization system. The ship waste heat recovery and reutilization system comprises a waste heat collection unit and a solar energy collection unit, wherein the solar energy collection unit and the waste heat collection unit form a photo-thermal-waste heat complementary energy supply network; the thermal energy conversion unit adopts an ORC system; the energy storage unit, the heat energy utilization unit and the optimization control module are configured to monitor system operation data in real time, identify a low-efficiency operation state in which the waste heat recovery rate and the electric energy conversion efficiency do not reach a preset threshold value, and dynamically adjust key parameters of each unit based on a low-efficiency alternative solution corresponding to the operation state in an algorithm; the wide-range load fluctuation of the marine main engine is adapted, and the comprehensive benefit maximization of the system is realized; the adjustment mode comprises the following steps of: randomly disturbing the low-efficiency alternative solution by taking the median of the current population as a benchmark, and separating from local optimum; and determining the search direction based on the preference weight of the optimal alternative solution in the population, and finely adjusting the parameters through the local search of which the search range shrinks along with iteration.

The invention relates to an air suction type cusped field electric propulsion system with multiple working medium supply modes and a supply method. The invention relates to the technical field of air suction type electric propulsion systems. The system comprises an electric thruster and collection device module, a microwave cathode module, a xenon storage and supply module and a control and energy supply module. According to the air-breathing cusped field electric propulsion system with the multiple working medium supply modes, the adaptive capacity of the electric thruster under the complex working condition is improved through the xenon working medium carried by the air-breathing cusped field electric propulsion system while the ultra-low orbit rarefied atmospheric environment is fully utilized. In addition to an ultra-low rail air-breathing type electric propulsion task, the xenon working medium carried by the ultra-low rail air-breathing type electric propulsion device can enable the ultra-low rail air-breathing type electric propulsion device to give consideration to a higher rail range, and a traditional xenon electric propulsion rail interval and an ultra-low rail space of 150 km or above are covered.

The invention relates to a fault diagnosis identification and early warning decision-making method for an integrated energy system, and belongs to the technical field of intelligent management of energy systems. Comprising the following steps: multi-source heterogeneous data acquisition: acquiring operation data of power, gas, heat and cold multi-energy flow subsystems in real time; performing space-time alignment and normalization processing on the collected data, and extracting a multi-modal feature vector reflecting a system coupling relationship; fault diagnosis and identification: based on a pre-trained artificial intelligence analysis engine, performing anomaly detection on the feature vector, positioning fault equipment and types, and outputting fault confidence; multi-level early warning decision making: generating an early warning level according to the fault confidence and the influence range, and generating a control strategy set in combination with an energy supply and demand balance model; dynamic feedback optimization: updating a fault diagnosis model and an early warning threshold based on system response data after strategy execution; the limitation of traditional single-dimensional monitoring is broken through, an accurate positioning result is fused and output, and the early warning response time is shortened through establishment of an elastic early warning decision model.

The invention discloses an electricity-hydrogen-gas comprehensive energy system self-adaptive optimization method oriented to multi-dimensional carbon asset collaborative transaction, and the method comprises the following steps: 1, introducing a dynamic emission factor and a multi-dimensional carbon asset collaborative transaction mechanism, and constructing a carbon emission optimization model of an electricity-hydrogen-gas three-energy coupling system; 2, performing dynamic allocation of carbon emission responsibility by adopting a game equilibrium-deep learning hybrid model; step 3, taking minimization of energy supply cost, carbon emission cost and green certificate-carbon transaction cost as targets, and constructing an electricity-hydrogen-gas coupled comprehensive energy system scheduling model; 4, simulation is carried out, and the effectiveness of the optimization model and method is verified; according to the invention, the cooperative efficiency of the power system, the natural gas network and the hydrogen energy system is effectively improved, so that the energy utilization is optimized, and the carbon emission of the system is reduced.

The invention relates to the technical field of energy supply control, in particular to a multi-mode energy supply control system and an optimization method thereof, and the system comprises an energy supply module, a main transmission channel, a main regulator, a plurality of parallel energy distribution branches, and a control regulation module. The energy distribution branch comprises a branch control node and an energy utilization outlet; the control regulation module periodically acquires energy demand data, calculates a global demand fluctuation index, and compares a threshold interval to generate an energy supply mode switching instruction; in the priority mode, the branch with the highest demand at present is dynamically appointed as a virtual main channel, and energy priority distribution is realized by adjusting equivalent impedance of the branch. According to the method, the global demand fluctuation index is used as a quantitative perceptron, a'balance-priority-emergency 'multi-stage mode is constructed, a dynamic virtual main channel and closed-loop feedback calibration are combined, conversion from static energy distribution to dynamic routing is achieved, and the system operation efficiency, the energy supply reliability, the power distribution network friend performance and the economical efficiency are improved.

The invention relates to a battery charging and replacing collaborative optimization method and system for multiple unmanned mine cars, and belongs to the technical field of battery charging and replacing collaborative optimization. Comprising the steps that mine car states, infrastructure states and task plan data are collected, and a personalized energy supply recommendation list is generated for each mine car based on an improved collaborative filtering algorithm; determining an overall service execution sequence based on the personalized energy supply recommendation list in combination with the task plan, executing the service execution sequence, and evaluating the service capability and expected income of each charging facility; in combination with the vehicle state data, the infrastructure state data, the expected service capability and the income evaluation report, generating a mine car dispatching instruction set by using a deep reinforcement learning algorithm, and optimizing the mine car dispatching instruction set into a cross-regional cooperative scheduling instruction set through a multi-aggregator cooperation mechanism; calculating a comprehensive service performance index when the cross-regional collaborative scheduling instruction set is executed, and if the comprehensive service performance index is superior to a preset service performance index, executing the scheduling scheme; otherwise, triggering the degradation strategy, and readjusting the scheduling scheme.

The invention discloses a natural gas-diesel oil injection switching control system of a dual-fuel diesel engine, which relates to the technical field of automatic control and comprises a data acquisition monitoring module, a fuel analysis module, a prediction control module, a control optimization module and a switching protection module. Engine operation parameter data are collected in real time through an engine sensor interface and preprocessed, and fuel dynamic proportion analysis is carried out according to different rotating speeds and load intervals of an engine by taking a preset proportion as an initial reference datum and applying an intelligent algorithm; the engine can obtain the most appropriate natural gas and diesel oil mixing proportion under various working conditions, according to an ideal gas state equation, based on pressure and temperature data, monitored in real time, in a gas supply pipeline, dynamic compensation is conducted on the gas volume flow, real-time gas supply energy is calculated, the gas supply amount can be accurately controlled in the mode, and the gas supply efficiency is improved. It is guaranteed that the engine obtains stable and accurate energy supply, and therefore stable operation of the engine is maintained.

The embodiment of the invention discloses an efficient compressed air energy supply control method and system based on an AI agent. The method comprises the steps that a first working condition parameter collected and reported by a second AI module locally deployed by each terminal device is received, and the first AI model adopts a graph neural network GCN to generate a feature vector based on the first working condition parameter and the topology of the compressed air system; constructing a reward and punishment function related to energy consumption, pressure stability and equipment loss on the basis of taking the feature vectors as state input; determining a current optimal scheduling strategy; generating a scheduling instruction based on the optimal scheduling strategy; receiving a second working condition parameter after the scheduling instruction is processed by a second AI model of each terminal device, optimizing the scheduling instruction according to the second working condition parameter, and correspondingly collecting a first training set; the first training set is used for optimizing the first AI model and / or the second AI model.