14747 results about "Power capacity" patented technology

The invention discloses a storage battery abnormity early warning system based on an intelligent battery gateway, and relates to the technical field of battery monitoring. The system comprises a sensor module used for collecting voltage, internal resistance, temperature, thermal runaway state and floating charge voltage parameters of a single battery in real time; the intelligent battery gateway comprises a data processing module and an early warning module, and the data processing module carries out fusion analysis on sensor data through an intelligent algorithm, calculates the battery remaining capacity SOC and the state of health SOH and executes an intelligent equalization strategy; and the early warning module generates a multi-stage early warning signal according to the parameter threshold and the anomaly detection model. According to the invention, through a multi-dimensional fusion sensing technology and a dual-drive intelligent algorithm, the aging sign of the internal microstructure of the battery is accurately captured, and high-precision estimation of the residual electric quantity and the health state of the storage battery is realized; and in the aspect of early warning performance, a multi-dimensional linkage detection model and an intelligent early warning mechanism are established, so that the accuracy and timeliness of fault early warning are effectively improved, and the early warning time is greatly advanced.

The invention discloses a light storage and charging energy allocation system based on data driving and a control method, and relates to the technical field of light storage and charging energy allocation, and the method comprises the following steps: carrying out the real-time collection of the real-time power generation amount of a photovoltaic power generation system, the current power state of an energy storage battery, and the power consumption data of a load; and cleaning, normalization processing and time serialization are carried out on the collected data, so that the accuracy and continuity of the input data are ensured. According to the invention, by monitoring the power consumption data of the load in real time, combining with the long-term energy prediction model and dynamically adjusting the energy storage and discharge strategy, excessive discharge in a non-peak period is avoided, sufficient energy storage in a peak period is ensured, the power grid dependence is reduced, and the power consumption cost is reduced. Through load sudden increase detection and an adaptive scheduling algorithm, the system can quickly cope with sudden load changes, preferentially guarantee power supply of key loads, flexibly adjust a discharge mode, improve endurance time and system stability, and maximize green energy utilization efficiency.

The invention discloses an electric power and electric quantity balancing method and system, and relates to the technical field of electric power management. S2, demand prediction; s3, evaluating the power supply capability; s4, carrying out resource optimization configuration; s5, integrating renewable energy sources; s6, demand side management; s7, performing real-time monitoring and adjustment; and S8, performing performance evaluation and feedback, and constructing an electric power and electric quantity balance system based on the method. According to the electric power and electric quantity balancing method and system, the accuracy and efficiency of electric power and electric quantity balancing can be remarkably improved, various electric power demand changes can be effectively handled, and stable operation of a power grid is ensured. Meanwhile, by dynamically adjusting access and demand side management of renewable energy sources, the purposes of maximum utilization of energy sources, energy conservation and emission reduction are achieved. Finally, through regular performance evaluation and feedback, the system performance is continuously optimized, a closed-loop optimization process is formed, and powerful support is provided for sustainable development of a power system.

The invention discloses an AGV scheduling system optimization method based on dynamic priority adjustment and real-time load balance, and the method comprises the steps: dynamically monitoring the emergency degree and arrival time of cargos, enabling a system to adjust the task priority in real time, guaranteeing the priority processing of emergency cargos, and giving consideration to the scheduling efficiency of common cargos; information such as current positions, loads and electric quantity of the AGVs is collected, weighted load values are calculated, weight factors are dynamically adjusted according to task types, load balance is achieved, and the situation that part of the AGVs are overloaded and part of the AGVs are insufficient in load is avoided; and finally, scheduling optimization is carried out by comprehensively considering factors such as the adaptation degree between the task and the AGV, the path distance, the predicted completion time and the load balance, and the overall performance of the AGV system is fully exerted. The flexibility, efficiency and resource utilization rate of the AGV scheduling system are effectively improved, and the AGV scheduling system is suitable for various scenes such as logistics storage and production and manufacturing.

The invention relates to the field of new energy charging, in particular to a new energy charging management method for a smart city. The method comprises the steps that a municipal vehicle operation feature data set is acquired, on the basis, municipal vehicles are subjected to type division through a vehicle type classification strategy, and a municipal vehicle driving type set is determined; acquiring a municipal vehicle task set, and on the basis, tracking a dynamic task variable set of a task execution vehicle in a municipal vehicle driving type set in a task execution process; according to the dynamic task variable set, analyzing an association relationship between the dynamic task variable set and the real-time power consumption data through a multi-modal fusion strategy, and determining dynamic power change information; and acquiring a charging station information set, dynamically optimizing a charging decision in combination with the municipal vehicle task set and the dynamic electric quantity change information, and determining and outputting an optimal charging strategy. In the municipal vehicle charging decision-making process, the utilization rate of charging resources is improved, and the continuity of municipal task execution is ensured.

The present application discloses a calculation method for multi-scale electric-carbon energy efficiency optimization for a power system, which includes designing a carbon flow calculation improvement model of the power system that takes into account a photovoltaic cluster auxiliary service, converting a power lossy transmission network of the power system equivalent to a lossless power consumption network, and calculating a carbon flow of the power system that takes into account a photovoltaic reactive power cluster auxiliary service; designing a decision-making system for low-carbon operation of the power system based on a coupling of electric-carbon energy efficiency, and calculating a correlation between electric quantity and the carbon flow of the power system that takes into account the photovoltaic cluster auxiliary service; the output varies in the range of 0-1, larger values represent a stronger correlation between electric-carbon energy efficiency.

The present application relates to a multi-terminal linkage energy scheduling method and apparatus. The method comprises: acquiring multi-terminal data, wherein the multi-terminal data comprises power supply side data, power grid side data, load side data, and energy storage side data; on the basis of the acquired multi-terminal data, predicting multi-terminal electricity amount related information within a future preset time period by means of a prediction algorithm, wherein the multi-terminal electricity amount related information comprises photovoltaic power generation related information, power grid power generation related information, power consumption information of a load side device, and electricity charging and discharging related information of an energy storage device; on the basis of an energy efficiency target, acquiring energy regulation information by means of the multi-terminal electricity amount related information; and controlling the energy storage device and / or the load side device on the basis of the energy regulation information. According to the solution of the present application, by means of a multi-party linkage mechanism, a scheduling plan formed on the basis of a preset scheduling target is more suitable for actual requirements and more accurate, and the energy storage device and the load side device can be automatically controlled on the basis of the scheduling plan.

The invention discloses a battery health state prediction method and device, a detection assembly and a vehicle, and belongs to the technical field of new energy. The method comprises the following steps: acquiring a plurality of time-varying expansive force values and residual electric quantity of a to-be-detected battery in a single charging process; and under the condition that the difference between the second residual electric quantity at the end of charging and the first residual electric quantity at the start of charging is greater than the preset charging depth, determining at least two expansive force extreme values and the residual electric quantity corresponding to the sampling time of each expansive force extreme value. The expansion force extreme value corresponds to a key feature point in a single charging process, and the health degree of the battery can be reflected by combining the synchronous residual electric quantity. According to the method, the at least two expansive force extreme values and the corresponding residual electric quantities are input into the preset prediction model, the correlation between the independent variable (expansive force extreme value) and the dependent variable (health state information) is subjected to regression analysis through the preset prediction model, the health state information is predicted, and the accuracy of the health state of the battery is improved.

The invention provides a watershed cascade water, wind, light and storage integrated scheduling operation simulation method considering long-short term nesting correction, and the method comprises the steps: constructing a watershed cascade water, wind, light and storage integrated medium-long term optimization scheduling model, and solving the model, thereby obtaining a water, wind, light and medium-long term scale electric quantity complementation scheduling scheme; and constructing a long-short-term nested correction model, and performing refined correction on each power supply output process of the watershed cascade water, wind, light and storage integrated multi-energy complementary base to obtain a water, wind, light and short-term scale electric power complementary scheduling scheme. On the basis of medium and long term optimization scheduling, a long-short term nested correction model is further constructed, and the random volatility of short-term wind and light output and the adjusting capacity of a short-term hydropower station and a pumped storage power station are fully considered. Effective undertaking of long-term absorption and short-term grid connection of the water, wind, light and storage integrated multi-energy complementary base under high-proportion new energy permeation is achieved, and the refined requirement of a multi-energy complementary dispatching system for evaluating indexes such as the new energy absorption rate is met.

The invention provides a distributed BMS battery active equalization type safety management method and system, and the method comprises the steps: obtaining the state information and performance change trend corresponding to each single battery through real-time monitoring, constructing a target battery pack topological structure model, combining a reinforcement learning algorithm, generating an intelligent agent model, and employing the intelligent agent model and a fuzzy logic controller to achieve the active equalization type safety management of a battery pack. Determining an energy flow management scheme; based on the feedback data and historical data of the energy flow management scheme, using a deep belief network to construct an anomaly detection model, based on the anomaly detection model, generating a risk assessment report, and constructing a security record platform based on the block chain technology to obtain security record information; optimizing each model parameter based on the risk assessment report and the security record information, and generating a security management system in combination with a transfer learning algorithm and a quantum computing method; and high-precision monitoring, intelligent electric quantity balance regulation and control, anomaly detection, risk management and continuous optimization of the distributed BMS battery system are realized.

The invention relates to the technical field of SOC estimation, in particular to an SOC estimation method and system for a lithium battery pack. The method comprises the following steps: collecting basic parameters and voltage data of a lithium battery pack, generating steady-state voltage data by using singular value decomposition and time domain reconstruction, further performing multi-level feature mapping and performance reconstruction to obtain basic discharge data, calculating battery energy efficiency and deducing normal power consumption based on the data, and calculating the energy efficiency of the lithium battery pack. Discharging simulation is carried out to evaluate the temperature rise condition, discharging capacity attenuation is predicted in combination with working environment parameters, relative errors are calculated, finally, the charge state is corrected, electric quantity self-calibration is carried out, and intelligent state estimation of the lithium battery pack is achieved. According to the invention, a more efficient SOC estimation method is realized.

The invention provides a distributed energy access-oriented intelligent electric meter multi-device collaborative optimization method and device, equipment and a medium, and the method comprises the steps: carrying out the interpolation of a unified electric meter, an inverter and energy storage data granularity, building a joint time error model, obtaining calibration reference data, and completing the multi-device time synchronization calibration; based on the reference data, acquiring operation data of three devices, and using a joint energy consumption model to distinguish electric meter hardware faults and multi-device collaborative anomalies to complete fault diagnosis; calculating local line loss by combining an inverter-to-ammeter line and electric quantity data, verifying residual electricity metering deviation, and tracing and correcting settlement data to complete line loss-bidirectional metering linkage verification; associating the fault result with the corresponding relation between the long-term statistical fault type of the metering data and the deviation rate and the line loss to establish a model to predict deviation trend early warning; and determining a multi-device cooperative abnormal source and transformer area load interference relation, calculating an interference coefficient, feeding back a scheduling system, and marking a line reconstruction priority. By adopting the method, the distributed energy consumption efficiency and the operation reliability of the power distribution network are improved.

The invention discloses a gas generator and energy storage battery hybrid energy supply scheduling strategy, belongs to the technical field of storage and charging, and mainly solves the problems that in an energy supply mode of a gas generator in existing oil and gas drilling operation, the power generation efficiency of the gas generator is low, and the gas generator is prone to flameout when coping with an impact load. Measuring and acquiring data of voltage and current of oil and gas drilling operation energy consumption equipment, the starting number of gas generators and the residual electric quantity of an energy storage battery; 2, calculating the real-time total power, the power abrupt change rate and the load rate of the gas generator according to the measured data; 3, the number of gas generators needing to be started and the charging and discharging state of energy storage electricity are determined according to the calculation and analysis result; and 4, repeating the steps 1-3 until the drilling operation is finished. The scheduling strategy depends on an existing energy management system, the starting number of the gas generators and the charging and discharging states of the energy storage batteries are reasonably controlled by combining the total power fluctuation characteristics of oil and gas drilling operation, comprehensive management of hybrid energy supply of the gas generators and the energy storage batteries in the oil and gas drilling operation is achieved, the power generation efficiency of the gas generators is improved, and the energy consumption is reduced. Meanwhile, flameout of the gas generator is avoided, and operation safety is guaranteed.

The invention discloses a power distribution network voltage control method based on distributed photovoltaic active-reactive cooperation, and the method comprises the steps: analyzing the influence of reactive / active injection on voltage stability through building a sensitivity matrix, deducing a critical control gain constraint condition, and guaranteeing the static stability of the voltage of a power distribution network; a photovoltaic inverter active / reactive cooperative control general model suitable for different scenes is constructed based on an intra-day scheduling and real-time control two-stage framework, and control curve parameters of each node photovoltaic inverter are optimized by taking minimization of network loss cost, active reduction cost, inverter voltage regulation cost and voltage deviation as targets in the intra-day scheduling stage; in the real-time control stage, active power reduction and reactive power regulation are dynamically coordinated based on an optimal control curve, reactive power margin is preferentially utilized to suppress voltage rise, and power flow distribution is directly regulated through active power reduction when reactive power capacity is saturated. According to the method, the safety and economy of the power grid are considered, and theoretical support and a practical solution are provided for voltage control of the high-permeability photovoltaic power distribution network.

The invention relates to the technical field of inverter control, and discloses an inverter output power control method and device, equipment and a storage medium. The method comprises the following steps: performing power frequency fundamental wave extraction and multi-band band-pass filtering on acquired voltage and current sampling data; performing phase compensation, first coordinate transformation and positive and negative sequence decoupling operation on the filtered fundamental wave principal component data; on the basis of a synchronous phase angle and a power grid fundamental wave frequency obtained by positive and negative sequence decoupling operation, carrying out second coordinate transformation, moving average and harmonic power delay difference operation on three-phase current and voltage data of an alpha-beta coordinate system; performing multi-level power calculation, power capacity distribution, error characteristic evaluation and decoupling operation on the inversion fundamental component and the inversion harmonic component subjected to the difference operation; and performing output signal modulation on the inversion power control quantity of the decoupling operation based on the fundamental wave synchronization phase angle, and generating a power control result. According to the invention, the control performance of the inverter on the output power in actual operation is improved.

A charging system comprises a local energy storage disposed at a charging site; an electric coupling configured to provide an electrical interconnect between the charging site and an electric vehicle (EV); and one or more controllers configured to: (i) detect a condition related to availability of electrical energy at the charging station, (ii) in response to the detecting of the condition: (a) estimate a number of EVs to which a charge remaining at the local energy storage is to be distributed within a certain time interval, (b) initiate a charging session for transferring electric energy from the local energy storage to the EV, via the electric coupling, and (c) limit an amount of electrical energy in the charging session in view of at least the estimated number of EVs.

The invention discloses a vehicle network interaction regulation and control method and system based on charging pile data. The method comprises the steps that electric quantity data of each adjustable vehicle at the current collection moment, power supply load data of each node in a power distribution network, position data of each charging pile and charging power data, charging load data and environment data at each collection moment are collected, and the charging load of each charging pile is predicted; obtaining load prediction data of each charging pile, calculating to obtain a vehicle-network interaction suitability index of each charging pile, and determining the power supply load prediction data of each node based on the vehicle-network interaction suitability indexes of all the charging piles, the electric quantity data of all the adjustable and controllable vehicles and the determined matching degree among the power supply load prediction data of each node. And executing a vehicle network interaction regulation and control strategy corresponding to the matching result. According to the charging pile data-based vehicle network interaction regulation and control method and system provided by the embodiment of the invention, the efficiency of vehicle network interaction regulation and control is improved.

Disclosed in the present invention a green power tracing method for a high-proportion renewable energy supply park, comprising: building a park network architecture model, and, on the basis of power flow data at any moment t throughout the year, splitting the park network architecture model into a plurality of active radiation-type power distribution lines; calculating the green power component of each renewable energy in each power distribution line in a single power user; accumulating the green power components to obtain green power consumed by the single power user at any time t and green power generation capacity output by a single renewable energy at any moment t; and forming a green power consumption matrix of the single power user throughout the year and a green power generation capacity matrix of the single renewable energy throughout the year. According to the present invention, the green power consumption of power users can be accurately evaluated, thereby providing accurate data support for green power tracing for users within parks.

The invention discloses an electric power capacity market clearing method and device considering flexibility. The method comprises the following steps: constructing an electric power capacity market clearing model considering flexible adjustment requirements of a system; performing dual change and linearization processing on the clearing model, and solving the model; carrying out capacity market pricing and settlement based on a solving result; wherein the step of constructing the power capacity market clearing model considering the flexible adjustment demand of the system comprises the following steps: determining a capacity demand curve which can adopt a variable resource demand curve; constructing a target function with maximization of social welfare as a target; determining capacity market clearing constraint conditions considering flexibility; according to the invention, the capacity value of the new energy can be priced and metered, and the new energy operation cost is reduced.

The invention discloses an intelligent wireless charging power distribution method and system, and aims to improve the efficiency and safety of simultaneous charging of multiple devices, and the system design comprises a plurality of key modules: a device detection and recognition module automatically recognizes the charging devices and collects the power demands of the charging devices; the power demand analysis module calculates the power demand of each device according to the device electric quantity and the charging mode, and the power distribution control module dynamically adjusts the power output according to the priority, the distance and other factors; the real-time monitoring and feedback module ensures the stability and safety of the charging process, and the data recording and learning optimization module optimizes the charging strategy by analyzing historical data. Through cooperative work of the modules, the system can adjust the charging power in real time, optimize the charging efficiency, improve the user experience, and ensure the safety of the charging process. The system shows good adaptability in a multi-device environment, and important reference and application prospects are provided for development of a wireless charging technology.

A power transmission network carbon emission accounting method based on a full life cycle theory. The method comprises: acquiring a bill of materials required in a production stage of a power transmission network device and carbon emission factors of materials corresponding to the bill of materials, constructing a carbon emission accounting model and calculating carbon emissions; acquiring transportation modes and carbon emission coefficients of related materials in the transportation and construction stages, constructing a model and calculating carbon emissions; establishing a model, which takes into consideration indirect carbon emissions generated due to line losses and carbon emissions generated during a replacement process related to conventional consumables and device failure, and calculating carbon emissions; constructing a carbon emission accounting model in the decommissioning and recycling stages, and calculating carbon emissions and carbon emission reductions generated in the stages; and performing accounting on carbon emissions throughout the full life cycle of a power transmission network, and calculating the carbon emission intensity. A carbon emission reduction effect of device recycling in a decommissioning stage is taken into consideration, the carbon emission intensity throughout the full life cycle of the power transmission network is calculated by means of a net power transmission capacity, and practical significance is given to a carbon emission target.

The invention relates to the technical field of battery electric quantity estimation, in particular to a lithium ion battery electric quantity accurate estimation method and system based on a BMS. The method comprises the following steps: collecting BMS original data, carrying out voltage current interval slicing, constructing a charging and discharging period node map, detecting node interruption joints, comparing slope differences to identify charging and discharging turning points, dividing independent charging and discharging periods according to the turning points, and determining current change time sequence data of each period. The actual charging and discharging electric quantity is calculated through the time sequence data, the charging and discharging difference is compared, the historical input and discharging electric quantity is further inquired, the fuzzy electric quantity range of the battery is deduced, and finally the real-time remaining available electric quantity is accurately calculated according to the fuzzy electric quantity range and the actual charging and discharging electric quantity difference and is uploaded to the BMS system. According to the invention, real-time monitoring and management of the electric quantity estimation result are realized, and the intelligent level of the battery management system is improved.

The invention relates to the technical field of battery control, in particular to a new energy automobile battery device and a control method thereof. The method comprises the following steps that dynamic parameter monitoring is conducted on an automobile battery, a battery state parameter set is obtained, and the battery state parameter set comprises a residual electric quantity continuous parameter, a voltage continuous parameter, a current continuous parameter and a temperature continuous parameter; according to the battery state parameter set, working condition identification is carried out on the automobile battery, a battery working condition type is obtained, and the battery working condition type is any one of a discharging working condition, a charging working condition and a standing working condition; if the battery working condition type is a discharge working condition, performing driving behavior data acquisition on the target automobile to obtain a driving behavior data set; and performing driving behavior pattern recognition on the target automobile based on the driving behavior data set to obtain a driving pattern type. The use efficiency and the safety of the battery are improved.

The invention relates to an energy self-adaptive communication method and system based on a sensing acquisition system, which are applied to the technical field of sensor networks, and the method comprises the following steps: arranging sensors at preset node positions, and carrying out network initialization; detecting the energy state of the sensor at the node position in real time, wherein the energy state at least comprises the residual electric quantity and the voltage level; dynamically adjusting communication parameters according to the energy state, and selecting an optimal communication protocol; sharing the information of the energy state among the nodes in a low-power-consumption broadcast mode; and performing node data relay and energy transfer based on the shared energy state. Through energy detection and communication parameter adjustment between sensor nodes, energy state information can be shared between the nodes, and the communication mode is cooperatively adjusted based on the information, so that optimal utilization of energy is realized.

The invention provides a method for reducing power transmission and distribution loss of a power grid, which belongs to the technical field of power transmission and distribution and comprises the steps of collecting and analyzing historical power consumption data in a region, extracting power time characteristics, acquiring historical weather data related to power consumption requirements and extracting power weather characteristics. Establishing a load prediction model based on the electric quantity time characteristics and the electric quantity weather characteristics; identifying distributed energy resources in the area, classifying and positioning the distributed energy resources, generating a resource distribution heat map, establishing an energy database, and developing a virtual power plant; the virtual power plant outputs a power grid electric energy transmission and distribution strategy according to a predicted load curve output by the load prediction model, performs defect analysis on the power grid electric energy transmission and distribution strategy, deploys an energy storage system and formulates an energy storage scheduling strategy; a final scheduling strategy is obtained by combining an energy storage scheduling strategy and a power grid electric energy transmission and distribution strategy, so that the stability and flexibility of power supply are improved, the utilization rate of renewable energy sources is improved, resource allocation is optimized, and diversified requirements are met.

The invention relates to the technical field of electronic equipment battery management, and discloses a battery charging management method and an electric quantity accurate display method based on electronic equipment. The dynamic adjusting module generates a multi-dimensional strategy through a staged charging control unit (including a fast, balanced and trickle charging sub-unit), a parameter transition processing layer and a global charging state pooling layer; the environment adaptation module adjusts the charging power and the temperature threshold according to the environment data, and has the functions of environment feature extraction, self-adaptive compensation and anti-interference switching; and the strategy fusion module outputs a control instruction in a weighted manner, and is additionally provided with an exception handling and wireless charging optimization mechanism. When the electric quantity is displayed, the collected data is dynamically calibrated to compensate polarization errors, and the capacity is fused with a matching historical curve to generate a high-precision electric quantity percentage which is dynamically rendered and displayed. According to the scheme, the charging safety, efficiency and electric quantity display precision are improved.

The invention discloses a battery health state assessment method based on real-time electric quantity detection, which relates to the technical field of battery management and comprises the following steps: acquiring state data of a battery in a charging and discharging process, and forming a time sequence data set; calculating a battery charge state value according to the time sequence data set, and comparing the battery charge state value with a preset health state threshold value to generate an initial health assessment result; performing segmentation processing on the time sequence data set, and extracting a voltage change rate and a current integral value in each time window to obtain a characteristic parameter set; inputting the characteristic parameter set into a battery capacity prediction model, and outputting a battery residual capacity value; and according to the initial health assessment result and the battery residual capacity value, combining a temperature compensation coefficient to generate a final battery health state assessment report. According to the invention, through a comprehensive data acquisition system and multiple algorithms, a comprehensive health state assessment report is generated in combination with the temperature compensation coefficient, and accurate assessment and early warning of the battery health state are realized.

A method and system for equalizing an power level of a vehicle battery pack, and a vehicle. The method comprises: when a vehicle is in a power-on state and the vehicle meets an equalization condition for triggering equalization, acquiring battery data of a vehicle battery pack; by means of calculation on the basis of the battery data, obtaining an equalization time and a power level required for equalizing, and selecting an equalization mode on the basis of a use scenario and a use habit; and obtaining the number of low-voltage battery cells, when the number of the low-voltage battery cells is less than or equal to a preset number of battery cells, selecting a storage battery having a preset voltage to supplement power to the low-voltage battery cells until equalization is achieved and a target power level is reached, and when the number of the low-voltage battery cells is greater than the preset number of battery cells, reducing a power level of a high-power level battery cell to the target power level by using a resistance power consumption mode. According to the system, the equalization condition for triggering battery equalization is added, the equalization mode is intelligently selected, the equalization time is accurately calculated, so that occurrence of false equalization is avoided, and power supply equalization or discharge equalization is selected on the basis of a situation, thereby improving the performance of the vehicle battery pack and prolonging the service life thereof.

The invention provides a hybrid vehicle energy management method, device and equipment and a medium, and the method comprises the steps: obtaining the real-time traffic information and configuration information of a vehicle, and calculating the demand power and demand torque of the vehicle according to the real-time traffic information and configuration information; calculating energy consumption of the battery according to the battery remaining capacity, the capacity information and the temperature information to obtain energy consumption information of the battery; power parameters of the vehicle are obtained, and the actual power and the actual torque of the vehicle are calculated according to the energy consumption information and the power parameters; actual energy consumption of the vehicle is calculated according to the actual power and the actual torque, and an energy distribution strategy is made according to the actual energy consumption; and constructing a dynamic programming algorithm to perform power distribution on an engine and a motor of the vehicle according to the energy distribution strategy. According to the technical scheme of the embodiment, through real-time interaction of the Internet of Vehicles, the vehicle can complete efficient energy distribution according to the processing information, and energy consumption and environmental pollution of the hybrid power vehicle are reduced.

The invention discloses a power supply method and a power supply system for on-line monitoring equipment of a lightning arrester, and the method specifically comprises the steps: activating a multi-source energy module according to a preset priority order based on the operation state and environment parameters of the lightning arrester, and supplying power to the on-line monitoring equipment; based on the output characteristics of the multi-source energy module and the residual electric quantity of the on-line monitoring equipment, a constant voltage-constant current hybrid power supply strategy in a conventional mode or an anti-interference power supply strategy in an abnormal mode is executed on the on-line monitoring equipment; and processing the historical leakage current, environmental temperature and humidity and vibration spectrum characteristics of the lightning arrester acquired by the online monitoring equipment through the LSTM prediction model, predicting the energy supply trend of the online monitoring equipment in the preset future time, and dynamically adjusting the working parameters of the online monitoring equipment according to the energy supply trend. According to the invention, stable power supply of the lightning arrester on-line monitoring equipment in a complex environment is realized, and the power supply reliability and the equipment availability are improved.