212 results about "Load management" patented technology

The invention discloses a power grid intelligent scheduling decision-making system and method based on multi-source heterogeneous data fusion, and relates to the technical field of power grid intelligent scheduling, the power grid intelligent scheduling decision-making method based on multi-source heterogeneous data fusion specifically comprises the following steps: 1, collecting multi-source heterogeneous data, constructing a meteorological feature vector set, and predicting power grid load change; the method comprises the following steps of: 1, outputting a load prediction value, 2, fusing the load prediction value and an equipment health coefficient to construct a double-risk collaborative analysis matrix, generating a risk entropy value and mapping the risk entropy value into a standard risk mode, and 3, executing generator output pre-adjustment, energy storage charging and discharging control and interruptible load management in a grading manner according to the standard risk mode. Micro-grid resources are coordinated through the block chain; according to the method, the demand side prediction risk and the equipment health risk are orthogonally decomposed into multiple state modes by constructing a two-dimensional risk collaborative decision architecture, and the one-sidedness of a single risk factor decision is avoided.

The invention relates to the technical field of intelligent power control, and discloses an intelligent power control system based on the Internet of Things, and the system comprises a monitoring terminal, a power execution device and a cloud platform control center which are in communication connection. The monitoring terminal collects current and voltage signals; the power execution equipment receives an instruction to switch the switch state; a load monitoring unit of the cloud platform control center determines a fault section and generates and maps a load characteristic curve, a prediction processing unit corrects a power supply path to generate an execution strategy, and a steady state regulation and control unit and a transient state regulation and control unit of the power control unit control execution operation under normal and abnormal working conditions respectively. The monitoring terminal comprises a data acquisition device and the like, and the power execution equipment comprises a circuit breaker and other modules. The system realizes intelligent monitoring, fault positioning and load management and protection of a power system, and improves reliability and efficiency.

The invention discloses a load management system based on a load model in the plastic product industry. The load management system comprises a load time sequence model building module which classifies and marks equipment according to operation behaviors of the equipment to obtain a load time sequence model; the data acquisition and fusion module acquires power, current, voltage and start-stop state data of equipment in real time through a monitoring point position, and generates a real-time load data set in combination with real-time production state data; the load prediction and adjustability evaluation module generates a load prediction curve by using a long short-term memory network, generates an adjustability score by adopting a support vector machine model, and determines an adjustable process list in combination with real-time production state data; and the scheduling execution module determines candidate adjustment equipment according to the load prediction curve, the adjustability score and the adjustable process list, constructs a multi-objective optimization function through a multi-objective optimization algorithm, and generates a load adjustment strategy by using a particle swarm optimization algorithm to execute scheduling on the equipment. According to the invention, the refinement level of load management is improved.

An adaptive IoT power plug system for intelligent load management and remote control, consisting of: a power plug housing configured to be inserted between a power outlet and an electrical appliance; an embedded sensor array comprising at least one voltage sensor, at least one current sensor, and at least one power sensor and configured to continuously monitor the electrical parameters of the connected device; a microcontroller unit (MCU) operatively coupled to the sensor array and configured to execute a load prioritization technique that dynamically determines power allocation based on real-time consumption data and user-defined priority levels for one or more connected loads; a semiconductor switching module electrically connected to the MCU and configured to selectively interrupt or modulate the power supply to the connected device based on commands from the load prioritization technology; a wireless communication module integrated into the MCU for bidirectional data exchange via at least one wireless protocol selected from Wi-Fi, Zigbee or Bluetooth Low Energy; a user interface that can be accessed remotely via a mobile or web application and enables the configuration of load priorities, real-time monitoring of power consumption, scheduling of device operation, and manual override of switching commands; and a power management subsystem including a power harvesting module configured to provide supplemental power to the system's electronic components, thereby reducing dependence on the main power source; The system autonomously adjusts the power distribution between multiple connected devices to load fluctuations and predefined user priorities in order to optimize energy efficiency and prevent overloading of the circuit.

A facility for predicting on site electric power requirements for maintaining a fully electric fleet of vehicles in a mining operation to ensure sustainable electric operations, comprising a server comprising communications module configured to receive data and to transmit load management instructions; plurality of electrical charging stations; plurality of electric vehicles configured to be recharged by a selected electrical charging station; wherein the server comprises processor coupled with non-volatile memory, the non-volatile memory storing processing instructions that, when executed by the processor, causes the processor to simulate a total electrical power demand of the mine site due to the plurality of cabled mine equipment and the plurality of electric vehicles for each electric vehicle and each charging station within the facility over a prescribed period thereby to simulate and determine an energy storage capacity requirement of the charging stations of the facility through the prescribed period; thereby to forecast the electrical load management needs of the facility through the prescribed period.

The invention relates to the technical field of load management, in particular to a model and data driving combined user side load non-intrusive identification method. Comprising the following steps: extracting steady-state features and transient-state features of typical electric equipment; constructing a user side load non-intrusive identification architecture based on decision tree classification; the invention discloses a user side load non-intrusive identification algorithm based on multi-feature fusion. According to the design of the invention, through extraction of steady state features and transient state features of typical electric equipment, multi-dimensional feature quantity identification is carried out on load samples based on a decision tree classification criterion, and non-intrusive load identification is realized through feature quantity matching of similar loads; an identification criterion based on decision tree classification is established, and various types of electric equipment can be quickly decomposed from a user sample; the steady-state and transient-state multi-feature fusion of the electric equipment is applied to a load non-intrusive identification algorithm, so that the accuracy of the algorithm can be improved, and the calculation amount and time of the algorithm can be greatly reduced.

The invention belongs to the technical field of power equipment, and discloses a smart energy system based on a power electronic transformer and a monitoring method, and the method comprises the steps: installing a sensor; equipment operation data is collected in real time, and environment monitoring equipment collects environment data; the data processing module preprocesses the collected data; the abnormity monitoring module judges whether an abnormal condition exists or not; the fault detection module judges whether the system has a fault hidden danger or has a fault; the energy scheduling control module formulates an energy scheduling strategy; the electric energy quality collaborative optimization module ensures that the electric energy quality of the whole system meets the standard; and the load management unit manages different types of loads according to the hierarchical load control strategy. According to the invention, abnormal conditions and potential fault hidden dangers can be found; intelligent energy scheduling can be realized, energy utilization efficiency can be improved, electric energy quality can be cooperatively optimized, hierarchical load management can be realized, and key load power supply can be guaranteed; and a hierarchical load control strategy is adopted to carry out differential management on loads.

The invention relates to the technical field of automobile charging station load systems, in particular to a new energy automobile charging station dynamic load optimization integration system and method based on multi-source data collaboration and elastic compensation. According to the system, charging pile power, meteorological data and user behavior information are fused in real time through a multi-source time sequence data set construction module, an LSTM neural network optimized by an improved sparrow algorithm is adopted to predict the remaining power capacity of a charging station, and Bootstrap resampling is combined to generate a confidence interval to realize safety boundary control; the self-adaptive firefly algorithm dynamically adjusts the charging pile power, establishes a multi-dimensional priority queue including SOC emergency degree, compensation willingness and social value, and guides users to charge in a peak shifting manner; the system comprises a 5G communication gateway, an IGBT power control module and a three-level early warning mechanism, and millisecond-level flexible adjustment of charging power is realized. The utilization rate of the transformer is improved to 91%, the peak-valley load ratio is reduced to 1.7: 1, the user waiting time is shortened by 63.5%, and a dynamic load management system of power grid-station-user collaborative optimization is formed.

The invention relates to the technical field of power equipment, in particular to an intelligent thermal management system for a cleaning robot, which comprises a state sensing unit, a risk assessment unit, a thermal state calculation unit, a data decision unit, an execution unit and a feedback correction unit, and is characterized in that the state sensing unit is used for acquiring internal temperature and humidity and key component temperature; the risk assessment unit calculates the characterization values of the dew formation trend and the overheating trend; the thermal state calculation unit quantifies the overall thermal state of the system; the data decision-making unit determines the actual adjustment amount of the heating and cooling power according to the parameters; the execution unit comprises a heating module, a cooling module and a load management module and correspondingly adjusts output power. And the feedback correction unit corrects the thermal state according to the operation deviation. According to the invention, through multi-parameter fusion decision and dynamic power adjustment, collaborative management of heat dissipation and condensation prevention is realized, and the working reliability of the cleaning robot in a severe environment is improved.

The invention provides a virtual power plant demand side response and load management method and system, and relates to the technical field of power system scheduling, and the method comprises the steps: obtaining a demand side response request and a historical response track of each distributed energy source; performing time-frequency domain decomposition on the historical response trajectory, extracting a transient component and a steady component, constructing a dynamic response model containing the current output power and the load deviation cumulant, and calculating load deviation distribution through Kalman filtering; a Markov decision process is constructed based on load deviation distribution, an optimal power distribution strategy is solved by adopting a value iteration algorithm, and a response execution scheme is generated; collecting a power change sequence after execution of each distributed energy source, converting the power change sequence into a load recovery demand vector, constructing a recovery capacity constraint cone based on the current available adjustment margin of the power grid, and solving an optimal projection point; and performing hierarchical division according to the optimal projection point to obtain a staged recovery sequence. According to the method, the accuracy of virtual power plant demand response and the coordination of load recovery are improved, and the power grid regulation pressure is reduced.

This invention discloses a power grid intelligent dispatch decision-making system and method based on multi-source heterogeneous data fusion, belonging to the field of power grid intelligent dispatch technology. The specific steps of the power grid intelligent dispatch decision-making method based on multi-source heterogeneous data fusion include: Step 1, collecting multi-source heterogeneous data, constructing a meteorological feature vector set, predicting power grid load changes, and outputting load forecast values; Step 2, fusing load forecast values ​​and equipment health coefficients to construct a dual-risk collaborative analysis matrix, generating risk entropy values ​​and mapping them to standard risk models; Step 3, according to the standard risk models, performing generator output pre-adjustment, energy storage charging and discharging control, and interruptible load management in a tiered manner, and coordinating microgrid resources through blockchain. This invention avoids the one-sidedness of single-risk factor decision-making by constructing a dual-dimensional risk collaborative decision-making architecture, orthogonally decomposing demand-side forecast risk and equipment health risk into multiple state modes.

The invention relates to the technical field of power dispatching, and discloses a power supply system dispatching method and a power supply system thereof, and the power supply system comprises a monitoring module, a dispatching module, a protection module, a data prediction module, an energy storage module, a remote control and communication module, an artificial intelligence and adaptive dispatching module, a power quality monitoring module and an intelligent load management module. The power quality monitoring module collects harmonic wave and voltage fluctuation data in real time, gives an alarm immediately when the harmonic wave and voltage fluctuation data exceed the standard, and pushes governance suggestions; and the scheduling module is matched to adjust the non-linear load operation time, so that quality problems are reduced from the source. Scene features are identified through deep learning, and an emergency strategy is automatically generated; and the scheduling module receives feedback in real time and corrects the strategy. The protection module accurately locates a fault point through multi-sensor cross validation and automatically cuts off a fault loop; the remote control module pushes fault information to the operation and maintenance terminal in real time, remote diagnosis is supported, and the on-site inspection frequency is reduced.

The invention discloses an intelligent self-adaptive solar power supply system and an energy management method, and relates to the technical field of solar intelligent power supply. A multispectral dynamic capture module improves the spectrum utilization rate and the photoelectric conversion efficiency; the global environment sensing module accurately predicts shadow and weather; the multi-mode MPPT cooperative control module reduces the power loss under the shadow; the heterogeneous energy storage cooperative scheduling module optimizes energy storage distribution; the intelligent load interaction module realizes accurate load management; the edge intelligent decision center realizes high-efficiency energy decision and safety guarantee, and all the modules work cooperatively, so that intelligent adaptive management of the solar power supply system is realized. Through multi-module innovation and cooperation, the performance of a solar power supply system is remarkably improved, the power generation efficiency is improved, environmental changes are accurately coped, power loss is reduced, energy storage and load management are optimized, efficient energy decision is achieved, safe operation of the system is guaranteed, the operation and maintenance cost is reduced, and intelligent development of solar power supply is promoted.

A meter collar adapter including a housing, a plurality of contacts to electrically connect the meter collar adapter to a meter socket and to a utility meter, a load management device within the housing to manage electrical load to an interface circuit with external, co-located electric equipment, and an overcurrent protection device electrically connected in series with an interface circuit. The load management device includes the interface circuit to electrically connect to either the line side or load side of an electrical service via the utility meter an external, co-located electric equipment. An interface contact to electrically connect the co-located electric equipment to the interface circuit, an adjustable electrical switch electrically configured to control electric load, and an energy management unit to control, monitor, and / or report a position of the adjustable electrical switch to manage the electrical loads.

The invention provides a load management data processing method in a power grid construction supervision project, and the method comprises the steps: carrying out the matching analysis of power fluctuation feature data and a pre-established load feature model, determining a corresponding load type if the matching degree meets a preset condition, and obtaining a multi-dimensional power decomposition result; carrying out quantitative calculation on the harmonic content of each electrical load based on the multi-dimensional power decomposition result, judging whether the harmonic content exceeds a standard limit range or not, and obtaining a to-be-treated harmonic component set; according to correlation analysis of the to-be-treated harmonic component set and the reactive power component, if the reactive power component is dominant, determining a compensation processing priority, and generating a targeted reactive power compensation strategy scheme; and carrying out classification processing on the load characteristics by adopting the reactive compensation strategy scheme, and if a classification result shows a high harmonic pollution characteristic, judging that the load type is a non-linear load type, and obtaining a load characteristic identification result.

The invention discloses a feed processing load management method based on a staged strategy gradient algorithm, and relates to the technical field of industrial automation control, and the method comprises the steps: collecting a feed processing dynamic state set, and obtaining a standardized decision input vector through preprocessing; based on the standardized decision input vector, dynamically adjusting equipment parameters through a two-factor cooperative compensation algorithm, and obtaining an equipment control instruction; executing an equipment control instruction, and generating an efficiency feedback data packet by monitoring equipment energy consumption change and output material granularity in real time; a load management decision model is constructed, and optimization strategy parameters are obtained by combining the efficiency feedback data packet and adopting a staged strategy gradient algorithm; and updating the load management decision model based on the optimization strategy parameters, and generating a closed loop verification report through load management verification. According to the method, the load management decision model is constructed through a quantum annealing mechanism, the local optimal limitation of traditional reinforcement learning is broken through, and global optimization efficiency jump is realized.

The invention discloses a lunar dust protection system for a low-energy particle detector. The lunar dust protection system comprises a protective cover, a nitrogen blowing opening, a pressing device, an unfolding device, a power supply subsystem and a control subsystem, wherein the protective cover and the nitrogen blowing opening are integrally designed; the protective cover covers the head of the sensor and is consistent with the head of the sensor in shape; the nitrogen blowing port blows nitrogen into the sensor in a ground test stage to prevent pollution; the blocking cap is used for blocking before the satellite is launched to prevent dust pollution; when the system is in a protection state, the pressing device presses the protective cover and the head of the sensor, and the protective cover is released through thermal cutting according to an instruction of the control subsystem; the unfolding device is matched with the pressing device to achieve unfolding of the protective cover, and the protective cover is locked after being released to a designated position. The power supply subsystem supplies power to the pressing device according to an instruction of the control subsystem; the control subsystem periodically collects state monitoring parameters and transmits the state monitoring parameters to the load management unit, controls power-on and power-off of the pressing device according to a ground remote control instruction, and executes unfolding operation of the system.

The invention discloses a load management-oriented intention identification and electric quantity data analysis method and device, and belongs to the technical field of electric power system analysis. According to the method, feature extraction is performed on the input text of the load management personnel through the preset natural language processing method, intelligent analysis is performed on the load electric quantity data in linkage, modal component decomposition is performed on the first historical electric quantity data, short-time fluctuation and long-term tendency features of new energy can be accurately captured, and the new energy management efficiency is improved. The method comprises the following steps: carrying out prediction on electric quantity data, carrying out feature division in combination with the prediction load data to obtain first historical electric quantity feature data and second historical electric quantity feature data, carrying out time sequence feature analysis to obtain periodic feature data and abrupt change electric quantity data in an electric power system, and generating electric quantity probability distribution data through a preset large model. According to the method, the load fluctuation of the power system can be quantified, so that the more accurate electricity consumption valley time period and electricity consumption peak time period of the power system can be obtained, and support is provided for novel load management work of a power grid company.

The invention discloses a diesel storage photoelectric network system which comprises a photovoltaic system, a diesel generator set, a load, an energy storage device and a control unit. The control unit comprises a monitoring module, and the monitoring module is connected with the diesel generator set, the photovoltaic system, the load and the energy storage device. The monitoring module is connected with a control module, and the control module is connected with a switching execution module and a communication module; the switching execution module is connected with the diesel generator set and the energy storage device. The communication module is connected with a diesel generator controller, a photovoltaic inverter, an energy storage BMS, a load management system and a control center. The invention further discloses a control method of the diesel storage photoelectric network system. The control method comprises a diesel generator set fault control method and a photovoltaic power sudden drop control method. According to the system and the method, rapid cooperation of the energy storage and the diesel generator can be realized, seamless switching between power supplies is ensured when the system encounters a fault, and continuous and stable power supply of a key load is ensured.

An electric power and electric quantity balancing method for a clean energy base containing a high-energy load comprises the steps that firstly, the fluctuation rule of the high-energy load is recognized based on the historical operation condition of the high-energy load, and a high-energy load model is established; secondly, according to the operation mechanism of the clean energy base, establishing an output model for each new energy unit in the base, and predicting the output and load demand of the new energy units in combination with weather forecast and historical data; then, according to the characteristics of a high-energy load and a conventional load, establishing a load management system, introducing a demand response mechanism, constructing a flexible scheduling resource platform considering different time scales by relying on the load management system and an adjustable power supply in a base, and setting priorities and adjusting costs for all adjustable resources in the flexible scheduling resource platform; and different adjustment resources can be reasonably selected in the scheduling process of the power grid. And finally, establishing a high-energy load-containing optimal scheduling model considering electric power and electric quantity balance, and ensuring that the electric power and electric quantity balance on the two sides of the source load can be realized in the scheduling of the power grid on different time scales.

The invention relates to a hybrid plug connector system (100) for transmitting power and data. The plug connector system has a plug (110) with a plug / cable interface (110a) for wired data and energy transmission, and a plug interface (112) for wired energy transmission and wireless data transmission. The plug connector system (100) also has at least one complementary socket (120) with a socket interface (122) which is designed to be complementary to the plug interface (112). The plug connector system allows energy and data to be transmitted between devices (consumers and generators) connected to the plug / cable interface (110a) and the socket / cable interface (126), wherein the radio plug wireless transmitter and / or receiver (114) and the radio socket wireless transmitter and / or receiver (123) allow wireless transmission with a high bandwidth and short range, in particular in the 60 GHz band. As a result of the wireless data transmission within the plug connector system, the fragile and error-prone data contacts of the plug connection which are otherwise necessary are dispensed with, as a result of which the connector mechanism can have a simpler design and the data connection is more reliable. As a result, the use of hybrid connections between generators and consumers of high power is simplified and allows plug 'n' play, for example for load management or current direction reversal in electrical systems.

A charging load management method oriented to a pulse charging method, belonging to the field of lithium-ion batteries. The charging load management method comprises: a staggered sequencing method for different charging pulses, a pulse current waveform adjustment method, a grouping and staggered sequencing method for a series of pulses having equal periods, a grouping and staggered sequencing method for a series of pulses having unequal periods, and an overall coordination method for charging pulses. A method for grouping and temporally sequencing different pulses can reduce the total charging current of all loads and the fluctuation amplitude thereof without reducing an individual charging load. When applied to a battery pack consisting of a plurality of cells, the method of the present invention can suppress the overall charging power fluctuation of the battery pack; and when applied to a plurality of electric vehicles, the method of the present invention can suppress the charging power fluctuation of an electric vehicle charging station, and assist the vehicle charging station in participating in power grid demand-side response, thereby facilitating an enhancement in the stability of a power grid.

The application discloses a low-carbon energy dispatching system of wisdom park source network load storage cooperation, relates to the wisdom park energy dispatching technical field, and the system includes the data acquisition module and gathers the distributed power output, the energy storage charge and discharge state and the load power demand time series data; the prediction analysis module is associated with the power output data and the weather forecast data, generates the short-term output prediction curve; the net load calculation module calculates the difference value of supply and demand, generates the net load fluctuation curve; the energy storage dispatching module plans the energy storage charge and discharge plan by overall planning the peak valley arbitrage and the frequency modulation standby capacity; the load management module generates the load reduction instruction containing the reduction time length and the compensation price by combining the adjustable load response potential and the net load low valley period. The system can improve the energy storage utilization efficiency and the power grid stability, reduce the influence of load reduction on the park power consumption, realize the wisdom park energy low carbonization and fine collaborative scheduling.

The application provides a production capacity and energy consumption collaborative load management system for pneumatic conveying and weighing feeding, relates to the technical field of energy consumption collaborative load management, and comprises: a device initialization module, which is used for marking a powder pneumatic conveying collaborative control production line as a target production line, acquiring initial production capacity of the target production line, and performing initialization configuration of operation parameters of each operation device belonging to the target production line; a coefficient construction module, which is used for extracting adjustment steps corresponding to each operation device from the initialization configuration after the initialization configuration is completed, so as to construct a plurality of collaborative response coefficients; and a compensation management module, which is used for determining a load abnormality degree of the target production line according to energy consumption and load state of the target production line, and judging whether to perform synchronous compensation management on each operation device based on the initialization configuration, so that the system has self-adaptive optimization capability, can dynamically adjust control strength under the conditions of working condition fluctuation, material property change and pipe network resistance change, and realizes balance and stability between production capacity targets and energy consumption control.

The invention discloses a portable oxygenerator control system and method based on altitude self-adaption, and relates to the technical field of program control, the altitude value of a portable oxygenerator is obtained and corrected, then solar energy available energy, VPSA oxygen production capacity and user oxygen demand are predicted, and supply and demand matching and balance judgment of three curves are completed; and energy distribution and priority scheduling are implemented according to a judgment result, a decision is converted into specific compressor power, valve caliber and auxiliary load control, and finally, a regulation effect characterization value of the portable oxygen generator is obtained for closed-loop reregulation until the system returns to a safe and optimal state. The altitude is embedded into prediction, matching and execution links as throughout and throughout baseline information, so that the oxygen generator can identify supply and demand gaps in advance and preferentially guarantee the safety of core oxygen supply at different heights and environments, and can dynamically optimize energy utilization and auxiliary load management; therefore, stable oxygen supply under the conditions of high altitude and low air pressure is realized, and the energy efficiency is maximized.

The invention discloses a disconnection detection implementation method applied to a load management branch device, and the technical scheme comprises the steps: enabling equipment to be capable of distinguishing a disconnection detection instruction and a remote control tripping instruction through the difference of the widths of pulse signals received by a remote signaling port by expanding a DL / T645-2007 protocol; therefore, on the basis that the on-site stock station area does not have the condition of control loop disconnection detection hardware, the disconnection detection function is achieved in the mode that software is matched with existing hardware, and meanwhile the disconnection detection function is achieved by expanding disconnection detection instructions and remote control tripping instruction enabling commands. It is stipulated that the load management branch apparatus must only respond to the relevant signal within the enable command valid time period. According to the invention, the problem that the on-site stock area does not have a broken line detection function is solved, the tripping success rate is improved, the error tripping rate is reduced, the reliability of load management work of the transformation area is greatly improved, and meanwhile, by expanding remote signaling and remote control event records, the reliability of the load management work is improved. And abundant field orderly power utilization management data is provided for theoretical analysis of load management work.

The application discloses a base station load balancing method and device, a storage medium and an electronic device, and relates to the technical field of communication. The method comprises the following steps: predicting the distribution characteristics of network service demand of a target scene in a target time period based on historical service data; adjusting the resource distribution of the base station according to the distribution characteristics; receiving a target service combination in the target time period, wherein the target service combination comprises M services and the priority of each service, and M is an integer greater than or equal to 1; based on the resource distribution of the base station, adjusting the target model according to the target service combination and a target algorithm, and generating a load balancing strategy for the target service combination based on the adjusted target model. The application solves the technical problem that the traditional load balancing algorithm is inefficient and cannot realize active load management when the base station load balancing scheme in the prior art faces rapid changes and burst conditions.

The present application relates to the technical field of power equipment, and more particularly to an intelligent thermal management system for a cleaning robot, comprising a state sensing unit, a risk assessment unit, a thermal state calculation unit, a data decision unit, an execution unit and a feedback correction unit, the state sensing unit collects internal temperature, humidity and key component temperature; the risk assessment unit calculates dew condensation trend and overheating trend representation values accordingly; the thermal state calculation unit quantifies the overall thermal state of the system; the data decision unit determines the actual adjustment amount of heating and cooling power based on the above parameters; the execution unit includes heating, cooling and load management modules, and adjusts the output power accordingly; the feedback correction unit corrects the thermal state according to the operation deviation. Through multi-parameter fusion decision and dynamic power adjustment, the present application realizes the collaborative management of heat dissipation and dew condensation prevention, and improves the working reliability of the cleaning robot in harsh environments.

The invention discloses a super capacitor charging and discharging management method for a load management branch device, and the technical scheme comprises a power loop and a management loop, and the power loop is used for achieving the charging, energy storage and discharging functions of a super capacitor on a hardware level; the management loop is used for collecting information of the power loop and managing the real-time working state of the power loop according to the collected information. The power loop comprises a power supply module, a charging module, an anti-reverse diode VD1, an energy storage module, a discharging module and an anti-reverse diode VD2; the management loop comprises a sampling module 1, a charging management module, a sampling module 2, a discharging management module 1, a discharging management module 2 and a main processor. Compared with the prior art, through a software and hardware dual control method, accurate management of charging and discharging of the super capacitor can be realized, a management strategy is adjusted according to different environment states, and the method has the advantages of wide application range, high reliability, low cost, flexible configuration and the like.

1. The name of this design product: controller. 2. Application of this design product: used for power switching and load management. 3. The key point of the design of this product lies in its shape. 4. The picture or photo that best illustrates the key points of the design: Design 1 Stereoscopic Drawing 1. 5. Designate Design 1 as the base design.