110 results about "Extreme climate" patented technology

The invention relates to a groundwater safety assessment method under an extreme climate event, which comprises the following steps: collecting multi-source heterogeneous data such as meteorological data, geological data, hydrological data and remote sensing data, and constructing a unified groundwater safety knowledge graph through standardized cleaning, semantic alignment and deletion completion; monitoring an extreme climate event in real time, and updating a node relation weight and sparsifying a transmission path based on knowledge graph dynamic evolution and a time sequence attention mechanism; performing risk propagation path reasoning on the dynamic knowledge graph in combination with an improved graph neural network, identifying key pollution nodes, and outputting a structured risk level and a coping suggestion; the system continuously optimizes atlas and model parameters based on evolution feedback, and high adaptability and reasoning precision of emergency response are achieved. According to the method, the intelligence, the real-time performance and the accuracy of underground water risk assessment are improved. The problems that the underground water pollution propagation path is difficult to dynamically identify and the decision adaptability is insufficient under extreme climate events are solved.

The invention discloses a regional wind speed meteorological reference station representativeness evaluation method based on a correlation function field, a medium and a program product. The regional wind speed meteorological reference station representativeness evaluation method comprises the following steps: collecting multi-year day-by-day wind speed data of a high-density meteorological observation station in a target region and environment information of the observation point; selecting an independent sample of day-by-day wind speed data in each same time period in the region; establishing a correlation function field between every two stations, and fitting a relation model of correlation functions and distances; estimating a standardized observation random mean square error; calculating the relative standard deviation generated by replacing the target point wind speed truth value data with the reference station wind speed observation data; and evaluating the excellent grade of the spatial distance range represented by the wind speed of the reference station. The method can achieve the good representative evaluation of the reference station in the distance range, and has important practical values for the selection of a reliable meteorological reference station in the climate feasibility demonstration of wind power development site selection, urban and rural construction planning and the like, the evaluation of extreme climate risks and the calculation of the accuracy of engineering meteorological parameters.

The invention discloses an air-ground cooperative photovoltaic panel intelligent snow removal system, and relates to the technical field of intelligent control. A central intelligent scheduling management subsystem is used for receiving operation and maintenance requirements of a photovoltaic power station, planning a routing inspection path, receiving a routing inspection result, analyzing the routing inspection result, and generating an optimal snow removal scheme; the parking station unmanned aerial vehicle subsystem is used for collecting surface data of the photovoltaic panel according to the inspection path and analyzing the surface data of the photovoltaic panel by adopting an accumulated snow automatic identification model to obtain an inspection result; and the ground operation vehicle subsystem is used for cleaning the snow accumulation area according to the optimal snow removal scheme and uploading a cleaning result to the central intelligent scheduling management subsystem. The problems that an existing photovoltaic panel snow removal technology is low in efficiency, poor in adaptability and lack of air-ground cooperative linkage are solved, whole-process intelligentization of routing inspection, diagnosis, sweeping and dispatching is achieved, and the operation and maintenance efficiency and power generation stability of a photovoltaic power station under extreme climate and complex terrain are improved.

The invention provides a high-resolution forest ecological safety evaluation method, which comprises the following steps: S1, acquiring and preprocessing multi-source high-resolution spatial data; three criterion layers are systematically calculated: 1) sensitivity, including preparation of a climate sensitivity index for quantifying the response intensity of vegetation to climate fluctuation and preparation of a human footprint response index for quantifying the response intensity of vegetation to a plurality of human footprint subclass indexes; 2) exposure degree, wherein a standardized extreme climate exposure index and a human footprint index are integrated; and 3) toughness: evaluating the recovery capability of the forest ecosystem by adopting a first-order time sequence autocorrelation coefficient based on a critical deceleration theory. According to the method, the weight of each index is determined by adopting a subjective and objective weighting method, and a refined forest ecological safety index spatial distribution diagram is generated through a comprehensive evaluation model, so that refined, dynamic and objective evaluation of forest ecological safety is realized, and scientific decision and support are provided for accurate forest management and risk early warning.

The invention discloses multi-parameter test analysis equipment for a complex environment, which belongs to the technical field of chemical or physical test analysis and comprises a test cabin, a comprehensive measurement and control system, a vacuum pumping system, a field environment simulation system and a climate temperature and humidity simulation system. The vacuum pumping system, the field environment simulation system and the climate temperature and humidity simulation system are sequentially arranged on the outer side of the test cabin body and are communicated with the test cabin body. By changing and adjusting the air pressure, the temperature, the humidity, the wind, the ultraviolet radiation, the space range and the air density in the specified range in the test cabin body, the extreme climate environment of any single parameter can be simulated, the special environment of combination, alternation and intersection of multiple parameters can also be simulated, and different types of test pieces can be made to have different functions. Test detection operation under a traditional atmospheric state, atrocious weather and an extreme environment of an outdoor environment is completed in the same space, so that multi-parameter data of different types of test pieces can be obtained.

The invention provides a power transmission and transformation project concrete mix proportion optimization method considering drought and cold region constraints, and relates to the technical field of design optimization. Key parameters are randomly allocated, and a time partition concept is adopted, so that the flowability and the hardening performance are respectively optimized in a concrete generation stage and a concrete hardening stage; through double screening of a fluidity index vector and a hardening index vector, the method ensures that the concrete has excellent resistance in a freeze-thaw cycle, and the service life of the structure is prolonged; the time position of the minimum freezing and thawing cycle number is selected through a simulation experiment, the defect that freezing and thawing influences are neglected in a traditional method is effectively overcome, the durability and reliability of concrete under the extreme weather condition are remarkably improved, and the optimization method can effectively reduce material waste and construction cost and is suitable for popularization and application. An economical and efficient solution is provided for concrete construction in the drought and cold areas, and the method has wide application prospects.

The utility model relates to the technical field of conveying pipeline protection, and discloses a pipeline external protection mechanism in an extreme environment, which comprises a pipeline, two groups of mounting flanges and a protection component. According to the pipeline external protection mechanism in the extreme environment, the outer side of the pipeline is sleeved with a set of sleeves, the two ends of the sleeves achieve sealing of the contact portions of the pipeline and the sleeves through sealing assemblies, temperature loss caused by air convection is reduced, meanwhile, through the multiple sets of annular pipes in the pipeline and argon filled in the annular pipes and the heat preservation cavity, the temperature loss caused by air convection is reduced; meanwhile, through supporting and shaping of the annular pipe, it is guaranteed that the whole sleeve is not prone to deformation, the annular groove formed in the outer side of the sleeve can guide rain and snow accumulated at the top end of the sleeve to flow downwards, the rain and snow are prevented from being accumulated at the top of the pipeline, and the service life of the sleeve is prolonged. And therefore, the safe use performance of the whole pipeline under extreme climate conditions is improved.

The invention discloses a multi-lake system low-carbon-ecology collaborative scheduling method and system adapting to extreme climate. The method comprises the following steps: constructing a future extreme climate scene set; constructing an urban-natural drainage basin coupling hydrological model, and obtaining multiple groups of lake inflow runoff sequences driven by various future extreme climate scenes according to the urban-natural drainage basin coupling hydrological model; taking minimization of annual total diversion carbon emission as a single target, and constructing a low-carbon-ecological collaborative optimization model according to a future extreme climate scene set and an urban-natural drainage basin coupling hydrological model; inputting each group of into-lake runoff sequences into a low-carbon-ecological collaborative optimization model for solving to obtain a plurality of groups of candidate scheduling schemes; and screening the candidate scheduling schemes to obtain an optimal scheduling scheme. The method can fully consider the uncertainty of future climate, improves the reliability of a scheduling scheme, solves the problem of difficulty in decision making of a multi-target model, and can be widely applied to the technical field of water resource scheduling.

The invention relates to the technical field of wind power generation equipment maintenance, in particular to a dynamic deicing system for a fan blade, which comprises an impact device for generating impact waves to an icing area of the fan blade, a monitoring device and a control device. Wherein the control device is used for calculating target impact energy required for deicing according to the ice layer thickness, the ice layer environment temperature and the crack value monitored by the monitoring device, and controlling the impact device to generate impact waves to an icing area for deicing based on the target impact energy; and calculating new impact energy of the impact device when the icing area meets a preset secondary impact condition, and controlling the impact device to perform secondary impact according to the new impact energy. Therefore, the problems that a traditional physical deicing technology is low in energy transmission efficiency, thick ice is difficult to remove, and the icing position positioning precision is insufficient are solved, the ice layer is subjected to chain fracture by accurately controlling the impact position, energy and the time sequence, and the method is suitable for efficient deicing of the large wind generating set under the extreme weather conditions of freezing rain, wet snow and the like.

This invention discloses an adaptive flight control system for unmanned aerial vehicles (UAVs) in complex terrain and extreme weather conditions, belonging to the field of UAV adaptive flight control technology. This adaptive flight control system for UAVs in complex terrain and extreme weather conditions includes a flight data acquisition and preprocessing module, a climate prediction and risk assessment module, an optimal path and task sequence adjustment module, a real-time flight control and path optimization module, and a safety emergency response and recording module. Specifically, the flight data acquisition and preprocessing module acquires weather data; the climate prediction and risk assessment module constructs a neural network model to predict the climate; the optimal path and task sequence adjustment module performs path and task safety assessments; the real-time flight control and path optimization module converts the path and task sequence into aircraft commands; and the safety emergency response and recording module executes emergency strategies and records the data. This system solves the problem in existing technologies where constantly changing weather conditions make it difficult for UAVs to adjust their flight in real time.

This invention discloses a comprehensive energy operation simulation method and system based on multi-objective optimization, belonging to the field of energy technology, aiming to solve the problems of equipment overload and discontinuous power supply caused by supply and demand imbalance under extreme climate conditions. The method establishes a multi-objective collaborative optimization model based on the renewable energy types and seawater desalination load characteristics of the island microgrid. An improved NSGA-III algorithm is used to simulate the model and generate a scheduling scheme, including the start-up and shutdown sequence of the hydrogen production equipment. When a typhoon warning signal is received, the seawater electrolysis hydrogen production equipment is forcibly locked, and the output power of the diesel generator is fixed within a preset range. During the operation of the hydrogen production equipment, the output fluctuation data of the wave energy generator is collected in real time, and the operating power of the reverse osmosis seawater desalination unit is adjusted through a dynamic correction algorithm. When the hydrogen storage capacity of the hydrogen production equipment reaches a threshold, the power lock of the diesel generator is released, switching to a multi-energy coupling control mode, and the charging and discharging strategy of the energy storage equipment is updated synchronously.

This invention discloses an intelligent inverter control method based on an adaptive algorithm, belonging to the field of intelligent inverter control technology. It employs a five-step approach: multi-source temperature acquisition and environmental identification, machine learning-based electro-thermal coupling prediction, adaptive inverter parameter optimization, collaborative thermal management, and fault diagnosis and self-repair. Addressing the risk of high or low temperature failures in motors and inverters under extreme climates, it acquires real-time temperature distribution and load information, predicts temperature rise trends in advance, and proactively adjusts inverter current, voltage, and modulation strategies to achieve safe derating or torque compensation. Furthermore, it performs multi-sensor cross-validation and observer fusion when sensors drift or components age, maintaining stable system operation and efficient energy utilization, significantly improving driving performance and vehicle reliability in extreme environments. During this process, online model updates further refine fault diagnosis and self-repair, enhancing the durability and economy of the electric drive system.

1. Name of the product in this design: Plateau Extreme Climate Environment Test Bench. 2. Purpose of this design: To provide simulated environmental conditions such as temperature, rain, ice accumulation, and high altitude during testing. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1. 5. The bottom surface of this product is a part that is not easily seen or cannot be seen during use, so the bottom view is omitted.

This invention discloses a method for quantifying the concurrent impact and legacy effects of extreme climate events on terrestrial carbon flux, relating to the fields of data analysis and artificial intelligence. Compared with traditional regression methods, this invention employs machine learning, which offers advantages such as automated decision-making, adaptive learning, real-time computation, and reduced human error. It can better handle complex and nonlinear relationships. Machine learning algorithms can automatically extract patterns from data and make decisions accordingly, thereby reducing the need for manual intervention and significantly improving work efficiency. With the rapid growth of data, machine learning systems can continuously learn from new data, update decision-making or prediction models, and quickly process and analyze massive datasets. Through big data analysis and pattern recognition, machine learning can reveal deep correlations and trends hidden in the data.

The invention discloses a nasal cavity biological protection preparation, a preparation method and application thereof and a nasal cavity intelligent protection system. The formulation comprises a mucin inspired polymer having a specific "brush-like bottleneck" molecular configuration, and an interpenetrating network formed from oppositely charged polysaccharides, which construct a three-dimensional hydrated gel by dynamic non-covalent cross-linking. The gel has the characteristics of shear thinning, strong mucous membrane adhesion and efficient particle interception. Temperature-sensitive, pH-sensitive or oxidation-reduction-sensitive intelligent microspheres can also be integrated in the preparation, so that responsiveness protection to the external environment is realized. The invention further provides an intelligent protection scheme comprising the preparation, a quantitative spraying device and a simple monitoring system. The preparation is safe and free of medicine, is suitable for preventing nasal cavity discomfort caused by air pollution, allergens, viruses and environment dryness, and is especially suitable for daily health protection under high-risk environment or extreme weather conditions.

The invention belongs to the technical field of forest fire monitoring and early warning, and particularly relates to an extreme climate prediction method based on a large warm period weighted FWI index and application. According to the specific technical scheme, the method comprises the following steps: acquiring climate data of a great warm period, and calculating FWI index components in each time period according to the climate data of the great warm period; the method comprises the following steps: acquiring forest vegetation data and topographic data by utilizing satellite remote sensing, performing space matching on the forest vegetation data and the topographic data, and calculating a vegetation-topographic collaborative weight factor; calculating a weighted FWI index based on the vegetation-terrain collaborative weight factor; and analyzing the relationship between the weighted FWI index and the occurrence frequency, intensity and duration of the extreme climate event by adopting a time sequence analysis method and a space analysis method, and visualizing the analysis result. The application blank of vegetation and topographic factors in large warm period FWI calculation is filled, so that the scientificity and accuracy of extreme climate prediction are improved.

The invention discloses an extreme climate city dynamic function toughness measurement method based on mobile phone signaling data, and the method comprises the following steps: S1, determining a research region, dividing research units, and extracting an OD sample; s2, constructing a high-precision three-dimensional static city function data set based on the multi-source city space data, and obtaining a grid static function vector; s3, measuring the dynamic function toughness index of the urban space under the extreme climate; and S4, explaining the toughness mechanism under the extreme climate. Compared with the prior art, the method for measuring the dynamic function toughness of the city in the extreme climate based on the mobile phone signaling data has the advantages of being convenient to measure and use, ensuring high-precision use and providing effective data support.

The invention discloses an indoor micro-beam tube type optical cable, which comprises a micro-beam tube, aramid yarn, a tearing rope and an outer sheath, and is characterized in that the outer sheath is arranged outside the micro-beam tube and the tearing rope, and the outer sheath is made of a low-smoke halogen-free material with an oxygen index greater than or equal to 40%; the micro beam tube comprises an optical fiber, a filling layer and an inner sheath, the inner sheath is arranged on the outer side of the optical fiber, and the filling layer is filled between the optical fiber and the inner sheath. The invention provides a dynamic adaptation strategy of a filling layer material and an inner layer sheath material, the provided indoor micro beam tube type optical cable can guarantee the structural integrity of the sheath, gives consideration to protection performance and construction operability, solves the contradiction that the inner layer sheath of a traditional optical cable is insufficient in protection or too hard to operate, can block moisture intrusion in a humid environment, and also can prevent the inner layer sheath from being damaged. And external force impact can be buffered through the filling layer, so that stable operation of the optical cable under extreme weather conditions such as high temperature and cold and complex scenes such as industrial oil contamination and high humidity can be ensured.

The application discloses a dew point temperature control system of a light composite environment simulation test box, and belongs to the technical field of extreme climate light composite environment simulation test. In view of the problem that the existing light environment simulation test box cannot be compatible with low-temperature and high-temperature and high-humidity extreme climate environment simulation test due to condensation of light glass, the dew point temperature control system of the light composite environment simulation test box is automatically controlled by using light-transmitting double-layer glass devices and software, the temperature of the interlayer glass is automatically adjusted by the control system according to a test program, the temperature of the interlayer glass is always higher than the dew point temperature corresponding to the temperature and humidity in the test chamber, the condensation phenomenon of the light glass is fundamentally avoided, the composite light environment simulation test of the test box under the extreme climate of low temperature-50 DEG C, high temperature 125 DEG C and humidity 20%-95% is realized, the accuracy of test results is ensured, and the test standard requirements are met.

This invention relates to a connector for a graphene electric heating unit for wind turbine blades, its preparation method, and its application. The connector comprises a metal core, a graphene composite conductive layer, and a weather-resistant sealing sleeve sequentially arranged from the surface of the metal core outwards. The wind turbine blade graphene electric heating unit connector provided by this invention adopts a three-layer synergistic structure consisting of a metal core, a graphene composite conductive layer, and a weather-resistant sealing sleeve. This structure reduces contact resistance, improves sealing performance, and broadens the weather resistance temperature range. It is suitable for extreme climate scenarios such as high-altitude cold regions, coastal salt spray, and hot and humid environments, which helps ensure the long-term reliable operation of the wind turbine blade de-icing system in extreme environments, while reducing installation costs and subsequent maintenance frequency.

The application discloses a climate-driven hybrid energy storage comprehensive energy optimization method, system, device and storage medium, which is applied to the technical field of comprehensive energy system planning and optimization, and comprises a Wasserstein generative adversarial network based on gradient fusion penalty and small batch discriminant term, which generates annual wind and light hourly scenes covering seasonal characteristics; the annual wind and light hourly scenes are taken as random inputs to construct a hybrid energy storage comprehensive energy system capacity-scheduling joint optimization model, and a Monte Carlo decomposition strategy is adopted to solve the model, so that optimal capacity configuration and hourly scheduling strategies of each scene under the optimal capacity configuration are obtained; and the hourly scheduling strategies are subjected to energy storage time length integral evaluation, so that the utilization distribution of battery energy storage and hydrogen energy storage in the hybrid energy storage comprehensive energy system under different time scales is obtained. The application significantly improves the robustness and economy of the comprehensive energy system under extreme climate conditions.

The invention provides a digital twinning-based water conservancy scheduling processing method and system, and the method comprises the steps: obtaining multi-source sensing data corresponding to historical extreme climate events, constructing a historical event resource library, obtaining real-time water conservancy monitoring data, carrying out the matching with the historical event resource library, and obtaining the current water conservancy project operation data for mapping adaption. The method comprises the steps of generating a scheduling instruction candidate set, inputting a digital twinning basin model, simulating a full-process operation process of a water conservancy project under the guidance of the scheduling instruction candidate set, obtaining a simulation operation result, identifying abnormal change nodes with parameter change rates exceeding a preset range, positioning scheduling operation items causing the abnormal change nodes, and correcting parameter values of the scheduling operation items. And inputting the corrected scheduling instruction candidate set into the digital twinborn basin model again to carry out simulation operation calculation, and outputting a water conservancy scheduling scheme. The scheduling scheme can be gradually optimized, and the stability and effectiveness of the scheme in practical application are improved.

This utility model relates to the field of greenhouse technology, specifically a three-layer air-conditioning and stable insulation structure for dragon fruit greenhouses, designed to address the problem of reduced dragon fruit yields caused by temperature fluctuations in extreme climates. The structure comprises an arc-shaped frame consisting of a support frame, a middle support layer, and a top support layer, sequentially covered with a PE bottom layer, an EVA middle layer, and a PEP top layer. A 20-30 cm gap between the bottom and middle layers forms a first air gap, and a 20-30 cm gap between the middle and top layers forms a second air gap, creating a low-thermal-conductivity buffer zone. Fixing holes with metal rings are provided on both sides of the coverings, and the top layer includes drainage pipes and seepage holes. Through the synergistic effect of the three layers of covering materials and the air gaps, this structure ensures that the temperature inside the greenhouse is 8-10°C higher than the outside temperature in winter and 3-5°C lower in summer, reducing frost damage by over 90% and achieving stable temperature control.

This invention relates to the field of ecological afforestation technology, specifically to a rapid secondary forest construction system and method based on vegetation restoration. The system includes: a geomorphic fractal quantification module, a soil physical property inversion module, a site suitability screening module, an ecological fatigue calculation module, and a succession regulation decision module. In this invention, by analyzing the fractal characteristics of surface micro-geomorphology, a mapping relationship between surface roughness and underground soil physical properties is established. A depth attenuation model is used to invert soil physical state indicators at specific depths. Under the premise of non-destructive surface detection, suitable underground growth spaces that meet root penetration resistance requirements are accurately located. A non-Markov memory effect algorithm is combined to process historical environmental monitoring time-series data, quantifying the cumulative ecological fatigue caused by extreme climate events to the site environment. The fatigue index is then integrated into the nonlinear adjustment process of the forest growth succession probability matrix.

The invention discloses a corn yield high-temperature loss prediction method based on machine learning, particularly relates to the technical field of high-temperature loss prediction, and realizes refined, dynamic and spatialized prediction of corn yield high-temperature loss by constructing a machine learning prediction system based on high-temperature-drought composite coupling characteristics. The method effectively captures the interaction of high temperature and drought stress under an unsteady climate condition, quantifies the composite stress characteristics through the joint analysis of a high temperature stress function and a drought response matrix, reduces the misjudgment caused by characteristic aliasing through nonlinear orthogonal decomposition and mutual information analysis, and improves the reliability of the system. According to the method, a deep learning model is trained, network parameters are optimized and prediction deviation is dynamically corrected by using a composite stress confusion distortion index constraint deep learning model, stable and robust prediction of the yield loss under an extreme climate condition is realized, and meanwhile, through feature contribution degree analysis and spatial grid mapping, the spatial and temporal distribution of the yield loss under a composite stress condition can be visually displayed.

The utility model discloses a cold storage door not prone to freezing, and relates to the technical field of cold storage equipment, the cold storage door comprises a door frame, a first cold storage door body and a second cold storage door body, sliding grooves are formed in the upper portion and the lower portion of the inner side of the door frame, and the first cold storage door body is fixedly arranged on the inner side of an inner frame; the second cold storage door body is arranged on the inner side of the door frame in a sliding mode through a sliding groove, heat insulation door bridges are fixedly connected to the inner sides of the two sides of the door frame, anti-collision strips are arranged on the heat insulation door bridges, sealing strips are arranged on the two sides of the second cold storage door body, and heating elements are embedded into the inner edges of the periphery of the second cold storage door body. The heating element, the heat insulation door bridge and the anti-freezing layer effectively prevent frosting, and the reliability and durability in extreme climate are improved. The insulation board enhances heat insulation, the low-temperature-resistant sealing strip ensures good sealing, cold air leakage is prevented, and the internal environment is guaranteed. An easy-to-operate handle and an observation window are additionally arranged, the opening and closing process is simplified, the interior is conveniently monitored, and the working efficiency is improved.

The invention relates to the technical field of heat pumps, in particular to a solar ground source heat pump coupling heat supply control method and system. Comprising the following steps that S1, working modes of the solar ground source heat pump in high-altitude and high-latitude areas are obtained, and the working modes comprise a normal mode, a transition mode and an extreme night mode; determining a reference heat supply control value of the solar ground source heat pump based on the working mode; and S2, based on the reference heat supply control value, the working mode limit value of the solar ground source heat pump is calculated, and the working mode limit value refers to the bearing limit value of the working mode of the solar ground source heat pump. According to the system, the extreme climate is matched through dynamic mode division, efficient cooperative heat supply of the solar energy and the ground source heat pump is achieved, heat unbalance is avoided based on real-time monitoring optimization control, the service life of the system is prolonged through a stepped adjusting mechanism, energy consumption is optimized, the operation cost is reduced, and an environment-friendly and economical sustainable heat supply scheme is provided for high-altitude and high-latitude areas.

The application discloses a solar power station photovoltaic support and relates to the technical field of photovoltaic supports.The support leg is provided with a motor fixedly installed on the right side, the output end of the motor is rotationally penetrated through the support leg, the side, away from the motor, of the support leg is fixedly provided with a support frame, the inner wall of the support frame is slidably provided with a rotating shaft, the fixing frame is fixedly installed on the circumferential surface of the rotating shaft, the side, away from the support leg, of the fixing frame is fixedly provided with a fixing plate, the surface of the support frame is further provided with a fixing device, the contact between the convex block and the groove is lost when the convex block moves, the limiting of the stop rod is released, the stop rod is driven by the first spring to slide towards the direction of the photovoltaic panel, the fixing of the installed photovoltaic panel is strengthened, the fixing between the photovoltaic panel and the fixing frame is strengthened, the photovoltaic panel can be more firm under various weather conditions, and the loosening or falling of the photovoltaic panel under strong wind, heavy rain or other extreme weather conditions is avoided.

The invention relates to the technical field of hydro meteorology, in particular to a method and a system for predicting and tracing extreme hydrological events in a reservoir area. The method comprises the following steps of S1, collecting meteorological and hydrological data, a global climate mode data set, geographic space data and stable isotope data of a reservoir area, and unifying a multi-source data scale through a time sequence fusion algorithm; according to the method, isotope data is adopted as an independent evidence constraint model, and compared with a traditional single model method, the method can more comprehensively capture a complex mechanism of occurrence of an extreme event, so that a simulation result is closer to an actual situation, and countermeasures can be taken in the face of an extreme climate event; the climate prediction and the isotope traceability technology are coupled for the first time, how causes of the extreme events change under different future climate scenes can be pre-judged in advance, and the research method and the model framework are not only suitable for specific areas, but also can be widely applied to research of the extreme events of large reservoirs and drainage basins.

The invention discloses a multi-element power resource planning method and system for improving the toughness of a power system, equipment and a medium, and the method comprises the following steps: obtaining historical climate data of a place where a power grid is located and a multi-source data set of a corresponding time period, carrying out the statistics of a correction coefficient under an extreme climate condition, and generating joint probability distribution; generating an extreme climate scene according to the joint probability distribution, and evaluating a toughness index of the power system to obtain an initial toughness index; determining a disaster prevention key node, evaluating the toughness improvement effect of the disaster prevention key node, and determining a multi-element power resource scale according to the initial toughness index and the improved toughness index; the cost of different toughness improvement schemes is compared, and the scheme with low cost is used as a means for improving the toughness of the power system. By establishing the joint probability distribution of the meteorological factors, the new energy output and the power load, the extreme climate scene close to the reality is generated, and the problem of insufficient prediction precision of the extreme climate scene in the prior art is solved.