14 results about "Energy factor" patented technology

The invention discloses a carbon market price prediction method considering multi-dimensional influence factors, and relates to the technical field of carbon market price prediction, comprising the following steps: obtaining carbon market price influence data including energy factor influence data and index influence data; obtaining text data of carbon market internal cause information, processing the text data of the carbon market internal cause information based on a natural language to obtain a plurality of keyword vectors, and obtaining a comprehensive feature vector of the carbon market internal cause information based on cross fusion of the plurality of keyword vectors; obtaining a carbon market price prediction model based on the comprehensive feature vectors of the carbon market price influence data and the carbon market internal cause information on the basis of SVR (Support Vector Regression); and generating short-term and long-term carbon market price curve graphs according to the carbon market price prediction model, and judging the carbon market price prediction trend according to the short-term and long-term carbon market price curve graphs. Through the SVR technology, the problem that the accuracy of a prediction model is reduced due to the fact that data collection and considered factors are often not perfect enough is solved. And some models may have limitations when processing a nonlinear relationship and multivariable interaction, resulting in insufficient predictive ability.

The invention discloses a range hood energy efficiency test method and system, and the method comprises the steps: selecting a typical oil smoke region set, constructing an oil stain anomaly detection model, marking abnormal points in the typical oil smoke region set based on the oil stain difference before and after oil suction, and carrying out the oil smoke test at the abnormal points. The method comprises the steps of obtaining a deviation distribution function based on a variable change condition, obtaining a time energy efficiency factor set and a space energy efficiency factor set, constructing an objective function, determining weights of factors in the time energy efficiency factor set and the space energy efficiency factor set, and constructing an energy efficiency test model based on the objective function and the weights of the factors. And obtaining test results of the range hood under different gears by using the energy efficiency test model. The method improves test comprehensiveness, improves scientificity and accuracy of product energy efficiency evaluation, has good interpretability, and can be directly applied to an energy efficiency test system of the range hood.

The invention relates to the technical field of pipelines, in particular to a complex FLNG cabin three-dimensional pipeline layout method which comprises the following steps that S1, basic parameters are initialized; s2, calculating initial solutions by adopting an intelligent initial strategy based on obstacle density, and taking an optimal solution in the initial solutions as a current global optimal solution; s3, entering an iteration process, calculating an energy factor, if the energy factor is greater than 1, performing long-distance migration with the probability of 30%, and performing hole digging with the probability of 70%; otherwise, randomly foraging or avoiding the predator at equal probability; s4, periodically performing an elitism and neighborhood search strategy; s5, executing an adaptive orthogonal constraint relaxation strategy and boundary limitation operation; and S6, calculating and determining a final global optimal solution, and outputting a final layout result. According to the method, the calculation efficiency and the convergence speed are improved, the actual engineering situation is fit, and the engineering cost is reduced on the basis of preferentially meeting orthogonalization feasibility.

The invention provides a reactive voltage optimization method and device, computer equipment and a storage medium, and belongs to the field of power grid optimizing.The method comprises the steps that a reactive voltage mathematical model of a regional power grid in each time period is established, and parameters are initialized; the improved Golden litsea rotundifolia algorithm comprises the step of introducing a self-adaptive decline factor for regulating and controlling escape energy and a mutation strategy based on a Cauchy distribution function for updating the positions of male Golden litsea rotundifolia individuals; obtaining an initial active power loss value, a node voltage deviation and investment cost data of each time period; and constructing an objective function, carrying out iterative optimization on the mathematical model through an improved Golden Litsea Algorithm to obtain an optimal solution of the objective function in each time period, and optimizing the operation of the power grid based on the optimal solution of the objective function in each time period. Therefore, through the synergistic effect of the adaptive energy factor and the Cauchy variation and the greedy strategy screening, the method has remarkable advantages in the aspects of reducing the active power loss, improving the voltage stability, controlling the investment cost and the like.

The invention discloses an energy consumption and endurance determination method, device and equipment of a hybrid electric vehicle and a storage medium, and relates to the technical field of electric vehicles, and the method comprises the steps of obtaining instantaneous fuel consumption per hundred kilometers and average fuel consumption per hundred kilometers based on the vehicle speed, the preset driving mileage, the driving time and the fuel injection volume flow; on the basis of the instantaneous output power of the battery pack, the vehicle speed and the fuel energy factor, instantaneous power consumption per hundred kilometers, average power consumption per hundred kilometers and average equivalent oil consumption per hundred kilometers are obtained; and on the basis of the preset working condition, the vehicle electric quantity state and the fuel tank residual fuel volume, the pure electric mode endurance mileage and the hybrid mode endurance mileage are obtained. According to the method, real-time and average parameters of oil consumption and power consumption are subjected to cooperative processing, fuel energy factors are introduced to realize unified quantification of oil and power consumption, and the endurance calculation model is dynamically selected based on preset working conditions, so that the problem of insufficient energy consumption and endurance estimation precision caused by independent calculation of multiple systems and inconsistent data benchmarks in the prior art is solved.

This invention provides a method for predicting sweet spots in overpressured, low-permeability gas reservoirs based on a grain size reconstruction seepage evaluation model. This method uses core grain size analysis data and conventional logging curves, employing a neural network algorithm to train a core grain size prediction model. Using the Kozeny-Carman equation and the fitting coefficients of core mercury injection data, a conversion model between core grain size and pore throat radius is obtained. By defining a natural seepage capacity index, an energy factor, and a comprehensive natural sweet spot index, the conversion model is reconstructed into a novel evaluation model coupling seepage capacity and formation energy attributes. Based on this evaluation model, and combined with highly sensitive 3D seismic attributes related to porosity, permeability, and gas content, a 3D evaluation model of the comprehensive natural sweet spot index is output. The beneficial effects of this invention are: it can intuitively, accurately, and cost-effectively predict the "natural sweet spot" of low-permeability gas reservoirs, and quantitatively evaluate the natural production potential of the reservoir.

The invention discloses a shale gas well effusion prediction method and device and a storage medium, and the prediction method comprises the steps: collecting historical production characteristic data, critical effusion state data, well bore structure characteristic data, fluid characteristic data and oil casing size data of a typical well, and calculating wellhead energy and P < output > according to gas production rate Qg and liquid production rate Ql during actual production; calculating the bottom hole flowing pressure pwf according to the gas production rate Qg and the liquid production rate (1 + 5%) Ql during actual production, calculating the inlet energy P < in >, and calculating the energy factor beta according to the formula that beta = P < in > / P < out >-1; each typical well obtains a corresponding energy factor beta, and an expression of a standard energy factor beta * is solved; p < in > and P < out > of the predicted well are calculated, and if P < in > > (1 + beta *) P < out >, no liquid is accumulated; if P is in lt; if (1 + beta *) P < output >, effusion exists; if P < in > = (1 + beta *) P < out >, determining the critical state. The method is wide in application range and particularly suitable for predicting the wellbore liquid accumulation of the shale gas well with the high liquid-gas ratio.

The invention discloses a transportation process management method and system based on the Internet of Things, and relates to the technical field of logistics transportation, and the method comprises the steps: carrying out the analysis of the transportation historical data of goods through deep learning; predicting possible delay or problems, and collecting feedback information to optimize a prediction result; constructing a multi-objective optimization model, and solving an optimal solution through a Pareto optimization algorithm; and re-planning a path and optimizing a transportation strategy based on an optimized prediction result. According to the method, the overall efficiency of logistics transportation is greatly improved, the cargo transportation time is shortened, the transportation cost is reduced, and the logistics industry is promoted to develop in the greener and sustainable direction by considering environment and energy factors. According to the invention, the flexibility and adaptability of logistics transportation are enhanced, various emergencies can be responded quickly and accurately, and safe and on-time arrival of goods is ensured. By using the Internet of Things technology, real-time monitoring and management of the logistics transportation process are realized, and the accuracy and timeliness of decision making are improved.

A method and system for electrical energy transfer and allocation that includes a blockchain systems for identifying and tracking energy demands and requests by geographical and coordinates and other characteristics through a usage and / or consumption chain that includes consumers and producers (prosumers). A microgrid identifier can be used to tag a consumer and relate the consumer to a producer by geography or demand. Based on demand and location data an energy factor can be calculated and thereby serve to match consumers and producers. A federated learning model can be used to accommodate an energy sharing stage on the blockchain and thereby facilitate, by a server computer, the transport of excess available energy from one energy producer in a first microgrid to either an energy consumer in the first microgrid or an energy storage unit of a second microgrid.

The invention discloses a battery pack abnormity determination method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the sampling of the charging voltage of each battery cell in a battery pack under the condition that the battery pack is in a charging state, obtaining the voltage value of each battery cell at each sampling moment, and calculating the abnormity of each battery cell according to the voltage value corresponding to each battery cell at each sampling moment; determining a reference voltage value at a sampling moment; calculating a first voltage difference between the voltage value corresponding to each cell and a reference voltage value; for each battery cell, determining an energy factor of the battery cell in a charging state according to a first voltage difference between a voltage value corresponding to the battery cell at each sampling moment and a reference voltage value; the energy factor is used for representing the accumulated voltage deviation of the battery cell; determining an energy threshold value according to the energy factors corresponding to the plurality of battery cells in the battery pack; determining whether the battery pack is abnormal or not according to the energy factor and the energy threshold value corresponding to each battery cell in the battery pack; the accuracy of determining the abnormality of the battery pack can be improved.

The permanent magnet is combined with a mechanical device to convert into practical mechanical kinetic energy. The invention is a brand new magnetic energy conversion technology and is a revolution in the fields of energy and power. The invention belongs to the field of energy and power. As for the existing mechanical power technology, normal work can be achieved only by using energy sources such as oil, electricity and natural gas, energy sources are consumed, and the environment is polluted. The problem is solved by a brand new magnetic energy conversion technology, a stator, a rotor, a magnetic field interference unit, an anti-reversal magnet block and other devices are ingeniously utilized for circulation, and when a rotor magnetic field stop point A is close to a stator magnetic field stop point 1, a magnetic field interference sheet driven by the rotor interferes a magnetic field between the rotor magnetic field stop point A and the stator magnetic field stop point 1; the rotor magnetic field A point can smoothly pass through the stop point of the stator magnetic field 1, the magnetic field interference sheet automatically resets after being stopped by the stopping screw rod, and the operation is repeated. The device is characterized in that magnetic energy is combined with a mechanical device to be converted into kinetic energy under the condition of not using other energy factors, and the device can be used in the fields of mechanical power, transportation, aerospace and the like.

The invention discloses a pile foundation damage identification method and device and a storage medium, and belongs to the technical field of engineering detection.The method comprises the following steps that structural dynamic response signals under wave excitation in the intact state and the current state of an ocean structural pile are obtained; the penalty factor of each frequency component in variational mode decomposition is adaptively adjusted through the penalty weight coefficient to decompose the dynamic response signal, and a decomposition result corresponding to each mode number is obtained; performing evaluation based on the signal integrity, and determining an impact signal in a decomposition result corresponding to the modal number of the maximum signal integrity as a damage characteristic sub-signal; calculating an energy factor of an effective component of the dynamic response signal according to the damage characteristic sub-signal; and judging whether a certain point of the structure is damaged or not according to the difference between the energy factors. According to the method, the penalty factor of each frequency component is adaptively adjusted through the penalty weight coefficient, and the optimal modal number is determined through the signal integrity of the decomposition result, so that the effective signal is extracted, and the purpose of accurately identifying the local damage of the pile foundation is achieved.

The application provides a coal mine mechanical equipment bearing online fault diagnosis method and device, and belongs to the technical field of bearing fault online diagnosis; the application solves the problem of complex algorithm of existing bearing online diagnosis or detection, which is not conducive to the online arrangement of diagnosis capacity; and comprises the following steps: bearing vibration related signal collection: collecting the vibration signal and rotation speed of the bearing, and dividing according to frames; bearing vibration dimension feature extraction: according to the vibration signal, rotation speed and sampling frequency of the bearing, the bearing vibration features-energy level and energy factor are sequentially calculated; bearing vibration time feature extraction: according to the energy factor, the time information of the energy factor in a certain time interval is sequentially calculated; bearing fault diagnosis of fused dimension-time features: according to the dimension information-energy level and the time information of the energy factor in a certain time interval, whether the bearing is faulty at a certain moment, and the damage type and severity of the bearing are given; the application is applied to bearing fault diagnosis.

The application relates to the technical field of pipelines, in particular to a complex FLNG cabin three-dimensional pipeline layout method, which comprises the following steps: S1, initializing basic parameters; S2, calculating an initial solution by adopting an intelligent initial strategy based on obstacle density, and taking the optimal solution in the initial solution as a current global optimal solution; S3, entering an iteration process, calculating an energy factor, if the energy factor is greater than 1, performing long-distance migration with a probability of 30%, and performing hole digging with a probability of 70%; otherwise, randomly performing foraging or avoiding predators with equal probability; S4, periodically performing an elite reservation and neighborhood search strategy; S5, performing an adaptive orthogonal constraint relaxation strategy and boundary limiting operation; S6, calculating and determining a final global optimal solution, and outputting a final layout result. The application improves the calculation efficiency and convergence speed, and is in line with the actual engineering situation; on the basis of preferentially meeting the orthogonalization feasibility, the engineering cost is reduced.