950 results about "Clean energy" patented technology

The invention discloses a source network load storage oriented regional collaborative scheduling method and system, and relates to the technical field related to power resource scheduling, and the method comprises the steps: traversing target region source network load storage to carry out real-time data collection, and constructing a source network load storage multi-dimensional data set to carry out multi-scale layered optimization; operation constraint conditions are set, limitation is carried out in combination with a power grid topological structure, a cooperative scheduling instruction set is determined, cooperative control feedback is carried out, and regional power scheduling feedback parameters are generated; and multi-channel dynamic correction is carried out, and a cooperative scheduling optimization strategy is generated to carry out energy balance cooperative scheduling on the source network load storage in the target area. The technical problems that in the prior art, intermittent fluctuation of new energy is difficult to consume, the collaboration of all links of source network load storage is poor, the dispatching flexibility of a power system is insufficient, and the resource configuration efficiency is low are solved. The technical effects of optimizing regional energy resource allocation and improving the clean energy consumption level, the power grid operation stability and the source grid load storage cooperative response capability are achieved.

Provided are a method and apparatus for optimizing an energy storage system, and a device and a storage medium. The method comprises: on the basis of an energy storage configuration to be solved, unit energy storage configuration cost, demand response cost to be acquired, net load fluctuation value to be acquired, cost discount rate and energy storage service life of an energy storage system to be optimized, constructing an energy storage configuration objective function; on the basis of a total demand response duration, demand response load, system output value, electricity price to be solved and unit clean energy curtailment cost of the energy storage system to be optimized, constructing a demand response objective function; on the basis of the energy storage configuration objective function, energy storage configuration constraints, the demand response objective function and demand response constraints, jointly solving the energy storage configuration to be solved and the electricity price to be solved to obtain a target energy storage configuration and a target electricity price, so as to realize the optimization of the energy storage system to be optimized. Thus, the operating costs are reduced and clean energy integration is also maximized.

The invention relates to the field of clean energy, and provides a distributed secondary control method for an island micro-grid system based on event triggering, which comprises the following steps: S1, connecting adjacent distributed units in an island micro-grid through a local communication link, and constructing a distributed control architecture to eliminate dependence on a central controller; s2, triggering communication of the local communication link based on a preset threshold value, and transmitting a secondary control signal when the system state deviation exceeds the threshold value; s3, performing cooperative calculation on the secondary control signal by using the distributed control architecture, adjusting frequency and voltage deviation, and shielding original power data; and S4, connecting a newly added distributed unit to the distributed control architecture through the local communication link, thereby reducing high communication burden and single-point fault of centralized control of the island microgrid.

The invention provides a hydropower station fusion computing power intelligent server system, and relates to the technical field of carbon emission. The method comprises the following steps: an acquisition correction module acquires hydropower station generation power data and server cluster instantaneous energy consumption data in real time, establishes a time sequence corresponding relation between a power generation side and a power utilization side, and obtains clean energy supply quantity data; the prediction scheduling module generates a non-tampering carbon footprint tracking chain number, and predicts a clean energy supply fluctuation trend sequence by adopting a long short-term memory network algorithm; training a random forest model to predict a computing power demand trend sequence; optimizing task scheduling according to a carbon emission minimization target, and generating dynamic balance configuration data of a computing power task and clean energy supply; and the monitoring evaluation module outputs computing power task level carbon emission and a clean energy use ratio in real time through an application programming interface according to the dynamic balance configuration data, and generates quantitative evaluation data of a computing power service carbon neutralization target by adopting a data visualization technology monitoring technology.

The invention relates to the technical field of energy meteorology and intelligent power grids, in particular to a multi-extreme meteorological high-risk scene set generation method, system and equipment based on a joint training generative adversarial network. The method comprises the following steps: constructing a physical information generative adversarial network framework comprising a generator, a discriminator, a predictor and a physical constraint module; designing a multi-objective loss function fusing adversarial loss, prediction loss, physical consistency loss and task performance loss; adopting a training strategy combining meta-learning initialization and incremental learning to jointly optimize parameters of the generator and the discriminator in stages; extreme risk scene data of specified disaster types, seasons and intensity grades are generated through condition vector control, and the extreme risk scene data are stored in a high-risk scene library after physical consistency verification. Through the method, a multi-extreme-weather high-risk scene set with statistical authenticity, physical rationality and task correlation can be directly generated, and the risk identification, scheduling optimization and toughness evaluation capabilities of the clean energy base under extreme weather conditions are remarkably improved; the problems of sample scarcity, model overfitting and lack of physical constraints in scene generation in the prior art are solved, efficient and automatic generation of a high-risk scene is realized, and reliable data support is provided for power grid toughness evaluation and scheduling decision of a clean energy base.

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 relates to a real-time scheduling method and system for a port gathering, distributing and transporting energy system based on double-consolidation continuous reinforcement learning. The method comprises the following steps: constructing a port micro-grid; acquiring related data in real time based on the port micro-grid, and performing preprocessing; constructing the port gathering, distributing and transporting energy system into an intelligent agent, and defining a state space, a dynamically limited action space and a reward function based on the pre-processed related data; and on the basis of a double-consolidation continuous reinforcement learning framework fusing a deep learning algorithm and a double-consolidation mechanism, performing optimization scheduling on the intelligent agent, generating an energy storage scheduling strategy, outputting optimal charging and discharging power, and completing a real-time scheduling process. Compared with the prior art, the method has the advantages of realizing dynamic collaborative optimization of clean energy supply and traffic load and the like.

An example operation may include one or more of detecting a first amount of energy that is received by an energy data storage system during a predetermined period of time, detecting at least one source of the first amount of energy, detecting a second amount of energy that is consumed from the energy data storage system during the predetermined period of time, generating a digital token that includes a value based on the first amount of energy, the second amount of energy, and the at least one source of the first amount of energy, and storing the digital token in a digital wallet.

The invention relates to the technical field of clean energy, and discloses a photovoltaic power prediction method based on foundation cloud picture prediction and computer equipment, and the method comprises the steps: obtaining historical cloud picture data of a target photovoltaic field station; interpolating the historical cloud picture data to obtain interpolated cloud picture data with a preset time resolution; constructing a multi-dimensional space-time condition vector based on the motion trail feature and the shape feature of the interpolation cloud picture data; performing conditional diffusion based on the interpolation cloud picture data by taking the multi-dimensional space-time condition vector as a reference to obtain predicted cloud picture data; acquiring historical power data and historical meteorological data corresponding to the time sequence resolution of the interpolation cloud picture data; and performing power prediction based on the cloud cluster characteristics of the prediction cloud picture data, the power change characteristics of the historical power data and the meteorological change characteristics of the historical meteorological data to obtain a power prediction result.

The invention relates to a membrane electrode and application thereof in deuterium-enriched water, and belongs to the field of clean energy development and utilization. The membrane electrode comprises a proton exchange membrane, an anode catalyst and a cathode catalyst, the anode catalyst is an iridium / iridium oxide catalyst with a three-dimensional porous network structure, and the cathode catalyst is a platinum-ruthenium alloy catalyst. The preparation method comprises the following steps: coating one side of the N117 proton exchange membrane with the anode catalyst, coating the other side of the N117 proton exchange membrane with the cathode catalyst, and then performing hot pressing to prepare the membrane electrode. The method comprises the following steps: assembling a membrane electrode into an electrolytic cell, and electrolyzing water by using the electrolytic cell to realize deuterium enrichment. The membrane electrode and the electrolytic cell are reasonable in design, the preparation process is simple and controllable, and the obtained product is high in efficiency and long in service life when used for enriching deuterium and facilitates industrial application.

The invention discloses a blade state monitoring device for a wind driven generator and the wind driven generator, and relates to the field of data monitoring, and the blade state monitoring device comprises a device integration multi-mode sensor module, a self-cleaning deicing module, a lightning stroke monitoring module, an edge calculation module, an anti-typhoon monitoring module, an energy supply module and a communication gateway module. Strain, vibration and temperature sensors are arranged at the root, the tip and the surface of the blade, and an icing detector is arranged at the front edge. And deicing is realized through hot air injection and the nano coating. And a lightning sensor and ultraviolet imaging are used for positioning lightning stroke. And an AI chip is arranged in the edge computing node to diagnose damage. The fiber grating sensor monitors typhoon strain. The solar film and the miniature wind driven generator supply power. And the communication module supports LoRaWAN and Beidou short messages. And the far-end intelligent diagnosis module predicts the service life through machine learning and provides maintenance suggestions. The system has the advantages that the blade state is accurately monitored in real time through the integrated multi-mode sensor and module technology, operation safety is guaranteed, the service life of equipment is prolonged, and efficient utilization of clean energy is facilitated.

The invention discloses a renewable energy penetration power distribution system scheduling method and system based on a block chain, and relates to the technical field of power distribution system scheduling, and the method comprises the following steps: constructing a cross-hierarchy time sequence integrity observation layer, introducing a multi-source high-precision reference signal into a synchronous time service link, and carrying out the multi-source high-precision reference signal; the fingerprint acquisition module is used for acquiring external environment electromagnetic disturbance and atmospheric propagation delay data in real time and generating a phase offset fingerprint corresponding to a time service state; and performing causal decomposition operation based on the phase offset fingerprint, performing noise stripping processing on the acquired electromagnetic disturbance signal, and extracting a real time service error trajectory. Through combination of multi-source time service correction, phase fingerprints and virtual impedance time marks, time self-calibration and cross-node synchronization of the block chain power distribution system are realized, account book wrong sequence caused by time service drift is eliminated, power flow reversal is suppressed through time reversal traction and dynamic constraint, scheduling stability and energy flow consistency are ensured, and the power distribution efficiency is improved. The system safety and the clean energy utilization efficiency are improved.

The invention provides a solar energy-ground source heat pump coupled intelligent phase change energy storage heat supply method and system which comprises a solar heat collection unit, a ground source heat pump unit, a phase change energy storage unit, a user side heat exchange unit and an AI intelligent control unit. Wherein the solar heat collection unit and the ground source heat pump unit are connected into the input end of the phase change energy storage unit in parallel through a closed-loop pipeline, and the output end of the solar heat collection unit and the output end of the phase change energy storage unit are both connected with the user side heat exchange unit. The AI intelligent control unit is electrically connected with the solar heat collection unit, the ground source heat pump unit, the phase change energy storage unit and the user side heat exchange unit. According to the system, on the premise that the heat supply quality is guaranteed, solar energy which is clean energy is utilized to the maximum extent, dependence on the ground source heat pump and traditional electric power is reduced, operation cost and carbon emission are reduced, and remarkable energy-saving benefits, economical efficiency and environment-friendly value are achieved.

The invention discloses a protective device for offshore power generation, which relates to the field of offshore energy equipment protection and comprises a multi-stage buffer anchor cable system, an annular cabin type floating body structure, a dynamic gravity center adjusting unit and an anti-resonance component. The multi-stage buffering anchor cable system is arranged in the circumferential direction of the floating body and comprises a main cable, an elastic buffering section, a damping adjusting section and a universal hinge joint. The annular cabin type floating body structure is provided with an inner cabin body, an outer annular cabin and a wave impact guide plate; the outer annular cabin is divided into an independent sealed cabin; the dynamic gravity center adjusting unit is arranged at the bottom of the inner cabin body, and the anti-resonance assembly is horizontally arranged in the outer annular cabin; according to the device, storm impact is attenuated through multi-stage buffering anchor cables, and buoyancy is optimized to resist waves through an annular cabin structure and a flow guide plate; the dynamic gravity center adjusting unit adjusts the balance weight in real time to counteract inclination of the floating body; the anti-resonance partition plate inhibits resonance, reduces structural abrasion, can adapt to complex sea conditions, guarantees stable operation of power generation equipment, prolongs the service life, and provides safety protection for offshore clean energy development.

A hydro power generation system may include a powerhouse and an entrance region structure. The powerhouse may include an intake port, a draft port, and a power generator disposed therebetween, the power generator configured to generate electrical power. The entrance region structure may be coupled to the powerhouse and define a portion of a boundary of an entrance region and the natural run-of-the-river portion of a waterway. The entrance region may be distinct from the natural run-of-the-river portion of the waterway and fluidically adjacent to the intake port.

The invention relates to the field of agricultural equipment, and provides an optical weeding system and method. The optical weeding system comprises a base and a solar weeding device, the solar weeding device is arranged on the base and comprises a lighting assembly, a collimating lens, a light guide assembly and a cylindrical lens, the lighting assembly comprises a supporting frame and a Fresnel lens, and the Fresnel lens is arranged on the upper portion of the supporting frame. Sunlight is focused to a focus through the Fresnel lens to form a high-energy light spot, light output by the Fresnel lens is collimated through the collimating lens, and the focused light is output through the cylindrical lens to form a linear high-temperature light spot on the ground; solar energy of renewable clean energy is directly utilized to form a light knife for physical thermal cutting weeding, consumption of non-renewable energy sources is reduced, and the use cost is reduced; due to the fact that optical weeding is adopted, chemical reagents are not needed, and pollution to soil and water sources is avoided.

The invention discloses a production and manufacturing enterprise cluster chain type interaction carbon emission reduction method based on dynamic electrical carbon factors, and relates to the technical field of industrial carbon emission reduction and energy management systems. According to the method, a four-layer decision-making framework of a global coordination layer, a cluster coordination layer, an enterprise execution layer and an equipment control layer is constructed, and dynamically updated electric carbon factors are introduced, so that accurate identification, carbon emission accounting and collaborative optimization of enterprise clusters on a product chain are realized. The core of the method is that carbon quota allocation, production scheduling and resource allocation are carried out among hierarchies by utilizing a multi-objective and double-layer optimization model, so that the total carbon emission of a cluster is minimized while the economic benefit is ensured. A dynamic monitoring and feedback mechanism is also established, the power carbon factor weight can be adjusted and a resource allocation plan can be triggered according to real-time data such as the proportion of clean energy of the power grid, closed-loop regulation from a macroscopic strategy to microscopic operation is formed, the overall carbon footprint of an industrial chain is effectively reduced finally, and the participation barrier of small and medium-sized enterprises is broken.

The invention provides a micro-grid system supply and demand balance and green energy scheduling optimization method and system, which can accurately match the user side power demand and green energy production, and can call an energy storage system to release stored electric energy or buy electricity through a main power grid to complement power vacancy when there is a supply and demand electric quantity difference in a power generation trough and a power consumption peak period; in the peak period of solar power generation, photovoltaic electric energy is preferentially used for meeting the load requirement, when the total power generation amount is larger than the total power consumption amount, redundant power can be used for charging an energy storage device, efficient consumption of renewable energy sources is achieved, meanwhile, the stable and continuous characteristics of wind power generation are utilized, basic power is provided for loads in the whole time period day and night, and energy is saved. And in the solar valley stage and the load valley stage, the energy storage system is matched to carry out charging and discharging scheduling and stabilize power fluctuation, challenges caused by load peak-valley difference and renewable energy intermittency can be effectively handled through multi-energy cooperative control logic, and the reliability, economical efficiency and clean energy permeability of micro-grid operation are improved.

The application discloses a base station intelligent energy coordination method and system, and belongs to the technical field of energy management, and the technical solution points comprise the following steps: collecting a data set of each base station in a regional base station cluster; calculating energy constraint data based on energy data and environment data to obtain an energy scheduling sequence of each base station; obtaining a load prediction curve of each base station through a preset LSTM network model based on load data to determine a first base station; and obtaining a corresponding second base station and a third base station according to the load prediction curve of the first base station. The application obtains the load prediction curve of each base station through the preset LSTM network model and determines the first base station, obtains the second base station through the analytic hierarchy process, and obtains the third base station through multi-target reinforcement learning, so that the energy scheduling of the regional base station cluster is realized, the clean energy utilization efficiency and the energy scheduling precision are improved, and the stability of base station operation is improved.

The invention discloses an industrial park enterprise carbon performance evaluation method, system, equipment and medium based on a multi-dimensional carbon index, and belongs to the technical field of industrial carbon management, and the method comprises the steps: collecting real-time power consumption data of an enterprise in a period and power carbon data of a corresponding time period, clearly defining an evaluation range, determining an evaluation object, and carrying out the evaluation of the enterprise carbon performance. The method comprises the following steps: calculating a core index to obtain a core index original value, carrying out standardization processing on the core index original value, endowing the standardized core index with a corresponding weight according to a preset standard, carrying out calculation through a primary algorithm to obtain an enterprise carbon performance comprehensive score, and dividing enterprise rating according to a comprehensive score interval. According to the method, three core indexes are constructed, and the problems of limitation of a single efficiency index, evaluation time lag and lack of power grid collaboration are solved; through standardization processing and weight distribution, quantitative evaluation of enterprise carbon emission efficiency, load regulation capability and clean energy consumption level is realized, and the defect that a traditional method only pays attention to total amount and static efficiency is overcome.

The invention discloses a distributed plasma and electrocatalytic synthesis ammonia device which comprises a plasma nitrogen fixation unit, an electrocatalytic synthesis ammonia unit and a power supply module, and the plasma nitrogen fixation unit comprises an air pump, a plasma discharge reactor, a plasma power supply and an aeration head. The electro-catalytic ammonia synthesis unit comprises a cathode side liquid storage tank, a cathode side liquid pump, an ammonia production electrolytic bath, an anode side liquid pump, a direct-current power supply and an anode side liquid storage tank, and the power supply module is a clean energy module. The aeration head is immersed in the cathode side liquid storage tank, and electrolyte is stored in the cathode side liquid storage tank and the anode side liquid storage tank; the device takes air and water as raw materials and carries out a synthesis ammonia process at normal temperature and normal pressure. The method has the beneficial effects that the method adapts to clean energy, can realize on-site absorption and adapts to the volatility of the clean energy; raw materials are cheap and easy to obtain, hydrogen storage and transportation risks and extra cost pollution are avoided, and zero carbon is generated in the whole process; the device is small in scale and modularized, does not depend on large-scale facilities, and assists ammonia and chemical fertilizer production in regions deficient in resources.

The invention discloses a photovoltaic cleaning robot operation method and a photovoltaic cleaning robot, and the method comprises the steps: collecting the surface pollution image data and environment perception data of a photovoltaic module in real time, and constructing a time-space correlation pollution state sequence; inputting the pollution state sequence into the edge AI prediction model, and outputting a pollution trend prediction value; constructing a dynamic pollution state transition matrix based on the pollution trend predicted value, and constructing a Markov decision process model based on the dynamic pollution state transition matrix; solving the Markov decision process model, and generating a dynamic path planning sequence considering clean energy consumption and power generation income balance; the cleaning robot is controlled to execute the dynamic path planning sequence, and pollution removal effect feedback data is obtained in real time in the operation process; and updating the parameters of the edge AI prediction model and the probability distribution of the state transition matrix on line according to the feedback data. According to the invention, the cleaning efficiency maximization, the energy consumption minimization and the long-term power generation benefit optimization can be realized.

The invention belongs to the technical field of biological fermentation hydrogen production. The invention provides a method for producing hydrogen by dark fermentation of pericarp biomass, which comprises the following steps: drying pericarp, crushing, and sieving to obtain powdery pericarp particles; performing acid heat pretreatment on the powdery fruit peel particles to obtain fruit peel pretreatment liquid; and inoculating the clostridium butyricum solution into the pericarp pretreatment liquid, and carrying out dark fermentation under an anaerobic condition to obtain a fermentation gas containing hydrogen. According to the method, the pericarp byproducts are used for dark fermentation for hydrogen production, so that high-value recycling utilization of agricultural wastes is realized; lignin in the pericarp is effectively removed through acid heat pretreatment, the availability of cellulose and hemicellulose is remarkably improved, conditions such as acid concentration, temperature and time are optimized, the inhibition effect of by-products is avoided, and the hydrogen production efficiency is remarkably improved; moreover, the method has the advantages of good stability and high repeatability, and provides a new technical approach for efficient production of clean energy.

The invention discloses a hospital energy resource intelligent management method and related equipment. The method comprises the following steps: predicting the output of renewable energy and the energy demand of each department in a future time period by using an LSTM-Attention model; on the basis of a dynamic mixed AHP analytic hierarchy process, the department energy consumption priority is evaluated by comprehensively considering the emergency state, the number of patients, the equipment operation state, historical energy consumption data and multi-dimensional factors of special medical tasks; and formulating an energy scheduling strategy through a multi-objective optimization model by combining the real-time energy consumption demand and the renewable energy source yield of the hospital according to the department energy consumption priority evaluated by the dynamic hybrid AHP method. The problems that due to insufficient application of clean energy and energy storage technology in hospitals, hospital operation cost is high, carbon emission is increased, a traditional system is difficult to dynamically adapt to complex energy consumption requirements, and stable energy supply of key areas cannot be guaranteed can be solved.

The invention relates to the technical field of clean energy, and discloses a photovoltaic generating capacity prediction method and device and computer equipment. According to the method, the theoretical generating capacity of the monthly clear sky under the theoretical condition is calculated based on the geographic position of the target photovoltaic station, and meanwhile, the average coefficient of the monthly generating capacity of the target photovoltaic station in each month in the future is calculated according to the difference between the theoretical data of the corrected irradiance of the earth surface clear sky and the actually measured data of the historical irradiance data; and finally obtaining a photovoltaic generating capacity prediction result. According to the method, the generating capacity of the target photovoltaic station is based on the theoretical generating capacity of the monthly clear sky determined by combining the geographic position of the photovoltaic station with the pre-constructed physical model; and correcting the theoretical generating capacity of the monthly clear sky by taking the difference between the calculated corrected irradiance of the earth surface clear sky and the historical irradiance data actually recorded by the target photovoltaic field station as a correction basis, and finally calculating to obtain a more accurate photovoltaic generating capacity prediction result with the monthly time scale.

The invention discloses a multi-source heat pump system and a control method thereof, and relates to the technical field of road roadbed maintenance equipment. Comprising ground heat source equipment, underground heat source equipment, a first heat exchange part, a second heat exchange part and heat dissipation equipment, the ground heat source equipment and the underground heat source equipment are connected, the first heat exchange part is arranged in the ground heat source equipment, the second heat exchange part is arranged in the underground heat source equipment, the first heat exchange part and the second heat exchange part are both connected with the heat dissipation equipment, and the heat dissipation equipment is used for being buried in a road roadbed. In the first state, an inner cavity of the first heat exchange piece and an inner cavity of the second heat exchange piece both communicate with an inner cavity of the heat dissipation equipment, and the first heat exchange piece and the second heat exchange piece are both in a heat absorption state; and in the second state, the inner cavity of the first heat exchange piece and the inner cavity of the second heat exchange piece are both disconnected from the inner cavity of the heat dissipation equipment, the inner cavity of the first heat exchange piece communicates with the inner cavity of the second heat exchange piece, the first heat exchange piece is in a heat absorption state, and the second heat exchange piece is in a heat dissipation state. The problem that an existing clean energy heat pump system is large in integration difficulty can be solved.

The invention relates to the technical field of power system dispatching, and discloses a power grid multi-target coordinated dispatching optimization method, device and equipment and a medium, and the method comprises the steps: constructing a dispatching target function which at least comprises a power abandoning penalty term and a safety out-of-limit risk penalty term; establishing a security constraint set of power grid operation; scheduling scheme solving is carried out based on the security constraint set, and when it is detected that power abandoning is caused by relaxation constraints, self-adaptive relaxation is carried out on the corresponding relaxation constraints according to a preset relaxation priority sequence; in the relaxed and updated feasible region, carrying out optimization solution by adopting a hierarchical reinforcement learning framework, and outputting an optimal scheduling instruction; wherein the upper layer of the hierarchical reinforcement learning framework is used for generating a scheduling feasible region meeting safety requirements, and the lower layer of the hierarchical reinforcement learning framework is used for performing rolling optimization of unit output based on the scheduling feasible region. According to the invention, on the premise of guaranteeing the safety of the power grid, the clean energy power abandonment rate is reduced and the optimization solution speed is improved.

The invention discloses an ammonia hydrogen fuel engine combustion system and method, and belongs to the technical field of clean energy, the system comprises a shell, the shell is provided with a combustion chamber, a pre-combustion chamber, an air inlet channel and an exhaust channel, and the pre-combustion chamber, the air inlet channel and the exhaust channel communicate with the combustion chamber; the injection valve set comprises an air inlet channel hydrogen injection valve, a pre-combustion chamber hydrogen injection valve, a direct injection hydrogen injection valve and an air inlet channel ammonia injection valve. The supply assembly comprises a hydrogen supply unit and an ammonia gas supply unit, the ammonia gas supply unit supplies ammonia gas to the combustion chamber through a gas inlet channel ammonia gas injection valve, and the hydrogen supply unit supplies hydrogen gas to the combustion chamber through a gas inlet channel hydrogen injection valve, a pre-combustion chamber hydrogen injection valve and a direct injection hydrogen injection valve; switching of the pure hydrogen premixed combustion mode, the pure hydrogen stratified combustion mode and the ammonia-hydrogen mixed combustion mode is achieved by adjusting the injection valve set and the supply assembly, the problems of abnormal combustion, power reduction and NOX and N2O emission existing on the engine are solved, and the operation stability of the engine is improved.

The invention discloses a high-low temperature heat storage single-tank device with a composite partition plate. The problems that an existing single-tank heat storage system is thick in thermocline, single in partition plate performance, poor in disturbance rejection and the like are solved. The device comprises a cylindrical tank body, a composite partition plate system, a driving mechanism, a matched pipeline and a heat exchange system, the composite partition plate is composed of a high-temperature phase-change material, a middle heat insulation layer and a low-temperature phase-change material, heat transfer between high-temperature media and low-temperature media is restrained through a thermal delay mechanism, and the dynamic disturbance resistance is enhanced through the movable partition plate. The device can reduce the thickness of the thermocline, improve the heat storage efficiency and stability, reduce the driving energy consumption and cost, is suitable for the scenes of solar thermal power generation, industrial waste heat recovery, ship heat storage and cold storage and the like, and can provide continuous and stable clean energy.

The utility model discloses a blue-green algae mud dehydration treatment device based on a solar photothermal conversion technology, which belongs to the technical field of blue-green algae dehydration and comprises a dehydration chamber, an evaporation chamber, a collection chamber, a water storage chamber and a photovoltaic power supply system which are communicated in sequence, the dehydration chamber is located below the treatment device, the outer side of the dehydration chamber is connected with an algae mud branch pipe, and an evaporation system is arranged in the dehydration chamber and comprises an underwater heat conduction shell and a floating type composite fabric material; the evaporation chamber is positioned above the whole device; a water collecting top plate is arranged in the evaporation chamber; the floating type composite fabric material is a carbon fiber fabric modified by a nitrogen-doped carbon nano tube; the collecting chamber is positioned on one side of the evaporation chamber; and the water storage chamber is positioned below the collecting chamber. Solar energy is used as clean energy, moisture in blue-green algae is evaporated through the photothermal effect, and therefore efficient treatment of the blue-green algae is achieved, environmental pollution caused by chemical treatment can be reduced, and economic cost of blue-green algae treatment can be effectively reduced.