10019results about "Emergency power supply arrangements" patented technology

The invention relates to a power supply switching control optimization method and system, and the method comprises the steps: constructing a multi-dimensional data fusion monitoring system, integrating a real-time voltage ripple coefficient detection module of a main power supply, a load transient response analysis module and an environment temperature and humidity sensor array, and generating a dynamic health degree index; the method comprises the following steps: establishing a fault prediction model based on transfer learning, pre-training through multi-scene failure data in a historical database, receiving a health degree index in real time, outputting a reliability attenuation curve, and activating a dual verification mechanism when the slope of the attenuation curve exceeds a preset threshold; extracting characteristic energy distribution of a frequency band of 0.1-10 kHz; executing a transient load impact test, and measuring dynamic response parameters of voltage recovery time and overshoot amplitude; and generating a switching confidence score based on cross processing of the dual verification result and the attenuation curve, and triggering a hierarchical switching instruction. The accuracy of the switching time of the main power supply and the standby power supply can be improved.

The invention relates to the technical field of micro-grid control, in particular to a multi-layer distributed micro-grid control system and method based on edge cloud collaborative lightweight reinforcement learning. The method comprises the following steps: a cloud management unit trains a DQN model by using historical environment data, generates a lightweight DQN model through pruning and quantification, issues the lightweight DQN model to an edge node unit, and formulates day-level and weekly-level optimization scheduling strategies based on a function layering + layering cooperation strategy; the edge node unit monitors electrical quantity and environmental parameters in real time through a sensor, deploys a lightweight DQN model to monitor abnormal conditions and trigger local early warning and emergency strategies, and makes a fast decision by using the lightweight DQN model; the micro-grid subgroup units collect data of the edge node units. According to the invention, through close cooperation of the edge node layer, the micro-grid subgroup layer and the cloud management layer, a distributed cooperative control mode of edge node real-time decision, subgroup cooperative management and cloud global optimization is realized.

A method for conditioning and maintaining power with predictive load compensation using an uninterruptible power supply system is disclosed. The method includes measuring an electrical input from a primary power supply using analog sensors and transmitting the input through an impedance to introduce a controlled delay. During the delay, input parameters and downstream system effects are determined based on telemetry sensor data. Digital identities are generated for the electrical input and the downstream load and compared to a stored digital identity representing historical conditions. Using the comparison, a system simulation is performed with analog twinning to predict downstream system responses. The predicted response is used to adjust a power converter parameter, modifying the electrical input to an intermediate output that compensates for voltage fluctuations and harmonic distortions. A secondary power supply with a bidirectional high-discharge battery supplements or stores energy as needed, ensuring stable power delivery to the downstream load.

The invention discloses an intelligent control system for a current transformer, and particularly relates to the technical field of power system monitoring, which comprises a fluctuation identification unit, a redundancy acquisition unit, an error fitting unit, a protection delay unit and a fault response unit, realizes real-time identification and classification of current fluctuation, and has standby path high-speed sampling and fusion signal construction capabilities. The fluctuation trend is judged through error regression, a protection strategy is dynamically set, response is delayed to avoid misoperation, finally, a high-level protection instruction is triggered and a fault event is output when offset overruns or alignment fails, and the data accuracy and the system response stability in the power supply switching process are guaranteed; according to the method, accurate identification of current fluctuation is realized through multi-dimensional feature extraction, data reliability is enhanced by using redundant sampling and error fitting, and by combining delay control and a hierarchical response mechanism, the risk of misoperation is effectively reduced, the fault judgment accuracy and the system protection stability are improved, and the method is suitable for a complex power supply switching scene.

The present invention discloses an intelligent measurement and control system for a withdrawable switch cabinet and a control method thereof, which relate to the technical field of automatic control of electric power systems, and solve the problems of slow response speed, inflexible control strategy and difficulty in coping with extreme weather conditions in existing intelligent measurement and control systems when responding to changes in power grids; real-time data acquisition and analysis are realized by integrating an edge processing module, and state prediction and anomaly detection are performed in combination with a long short-term memory network; an adaptive control module is used to optimize the control strategy according to dynamic monitoring results; at the same time, the emergency response module monitors environmental variables through a SCADA system, and an intelligent scheduling algorithm adjusts the switch cabinet operation mode and switches standby equipment; the present invention greatly improves the safety and reliability of the switch cabinet, significantly enhances the rapid response capability and adaptive control capability of the power system to changes in the power grid, and ensures the stability and safety of the power supply.

The invention discloses a high-temperature steam pipeline stress-strain state monitoring system based on characteristic safety parameters. The high-temperature steam pipeline stress-strain state monitoring system comprises a sensor acquisition module, a data processing module, a wireless communication module, an energy acquisition module, an edge calculation module, a fault self-diagnosis module and a server. The sensor acquisition module acquires first sensing information through a heterogeneous sensor combination distributed on the surface of a pipeline, and the data processing module extracts stress concentration coefficient, strain rate, temperature gradient and vibration frequency characteristic parameters. And the wireless communication module adopts a multi-hop network mode to transmit data to the edge calculation module for secondary processing to obtain pipeline operation information. The energy acquisition module acquires energy from the pipeline surface to supply power to the sensor. And the fault self-diagnosis module realizes abnormal device positioning isolation through cross validation and link bit error rate analysis. The server comprehensively receives various kinds of information to complete continuous monitoring of the pipeline state, and a complete self-powered intelligent monitoring system is formed.

The invention relates to the technical field of power distribution networks, in particular to an environment-related intelligent regulation and control method and system for a power distribution network, and the method comprises the steps: obtaining the operation parameters of each monitoring node of the power distribution network, and enabling the operation parameters to comprise node state parameters and external environment parameters; based on the operation parameters, calculating time correlation between the node change characteristics and the environment data, and generating a node operation state report; identifying an abnormal event according to the node operation state report, and determining an abnormal influence range based on time distribution, space distribution and fluctuation characteristics of the abnormal event; according to the abnormal influence range, the load state of the node is evaluated, the emergency response priority is determined based on the influence weight of the node in the network, and a load regulation and control strategy is generated; and executing a load regulation and control strategy, dynamically adjusting node power supply capability, distributing standby power source resources, monitoring load change in real time, completing intelligent regulation and control of the power distribution network, and realizing accurate monitoring and intelligent regulation of the operation state of the power distribution network.

The invention relates to the technical field of hydrogen production, in particular to a micro-grid hydrogen production system based on dynamic optimization control and a multi-mode energy scheduling method. Comprising a renewable energy power generation unit which comprises at least two distributed power supplies with different power generation characteristics; the multi-stage hydrogen production device is configured to receive the electric energy output of the renewable energy power generation unit and perform proton exchange membrane water electrolysis hydrogen production; the hybrid energy storage system comprises a super capacitor bank and a lithium ion battery pack which are connected in parallel to the direct current bus through a bidirectional DC / DC converter; the dynamic optimization controller is internally provided with a multi-time-scale coordination algorithm and is used for acquiring meteorological prediction data, load demand data and an energy storage SOC state in real time; the multi-mode scheduling module comprises three working modes including an island operation mode, a grid-connected operation mode and an emergency standby mode; according to the scheme, hydrogen production economy, equipment durability and power supply reliability can be considered at the same time.

The invention provides an air-ground cooperative intelligent emergency material scheduling and electric power configuration optimization method and system, and the method comprises the steps: constructing an air-ground cooperative emergency resource joint scheduling frame which integrates heterogeneous resources, such as future emergency trucks, unmanned aerial vehicles, unmanned and manned new energy vehicles; the objective of the invention is to jointly optimize post-disaster emergency material distribution and power recovery processes so as to improve the overall emergency response efficiency and cooperative capability. Secondly, aiming at the complexity of air-ground cooperative scheduling under the framework, a two-stage optimization model is designed, and the objective of the two-stage optimization model is to maximize the emergency power supply capability of the key area in the first stage and minimize the material distribution time of the unmanned aerial vehicle taking off from the large power supply vehicle based on the two-stage optimization model in the second stage. And finally, in order to efficiently solve the model, a GRASP algorithm and an ALNS algorithm are respectively developed. Through simulation analysis based on actual scene data, the feasibility and potential of the whole method for realizing quick response of emergency materials and electric power under a real disaster background are proved.

The invention discloses an intelligent power distribution network fault analysis and maintenance system based on the Internet of Things, which belongs to the technical field of power distribution network fault analysis and maintenance and comprises a multi-source data acquisition preprocessing module, a dynamic digital twin modeling module, an edge cloud fusion analysis module, a transient fault topology positioning module, a self-healing control module and an intelligent maintenance scheduling module. According to the method, fault features are extracted through edge-side AI reasoning, global anomaly detection is realized in combination with cloud big data analysis, anomaly modes under different working conditions are adapted through a dynamic balance coefficient, and fault type tags are quickly generated through weighted fusion of feature vectors in edge-side real-time reasoning, so that the fault detection accuracy is improved. The global anomaly scoring mechanism greatly improves the fault classification accuracy, updates the node state and the probability density function by injecting a dynamic digital twin model, quantifies the distribution characteristics of the faults in space coordinates in combination with the topological weight, the fault influence function and the space attenuation coefficient, and accurately recognizes the fault high-incidence area.

The invention discloses an AC access flywheel UPS control method for stabilizing a dynamic load in a data center, and relates to the field of power supply management, and the method comprises the following steps: S1, predicting and analyzing the load fluctuation of the data center, collecting the operation data of a flywheel through a sensor, and carrying out the monitoring and modeling of the state of a flywheel UPS; according to the method, data fitting and pattern recognition can be more efficiently carried out, the training process needing a large amount of time and computing resources in a traditional method is reduced, the system response time is shortened, excessive dependence on a preset model and a static rule is avoided, more flexible strategy selection is effectively provided, and the capacity of the system for coping with changes is improved; the flywheel UPS system can quickly respond to load change, enhance the robustness and stability of the system, avoid overload and low-efficiency operation of single equipment, efficiently evaluate the state and performance of the flywheel UPS system, avoid excessive consumption or waste of energy, improve the energy utilization rate, prolong the service life of the equipment and reduce the maintenance cost.

The invention relates to a power equipment state self-healing operation and maintenance method, and belongs to the field of power equipment operation and maintenance, and the method comprises the steps: obtaining the real-time operation state data of a power supply in a current multi-source power supply system, collecting the data through a preset sampling frequency, and constructing a power supply state matrix; a conversion time constraint condition is set in advance, a zero-delay switching decision tree is constructed and a power supply switching decision is output in combination with a main power supply fault risk assessment result, and if the main power supply fault risk assessment result is abnormal, the standby power supplies are switched according to the determined switching priorities of the standby power supplies and the power supply switching decision; after the switching is completed, monitoring the power supply continuity index of the power equipment in real time, and if the power supply fluctuation time or the phase jump amplitude exceeds a preset allowable value, smoothing the power supply fluctuation by adopting the rapid power compensation function of the energy storage device; the stability and reliability of the multi-source power supply system are improved, and intelligent power supply switching and self-healing disaster recovery are realized.

The invention discloses an output conversion system and method for a UPS (Uninterrupted Power Supply), and the system comprises a main power input end which is connected with a bridge rectifier through a first electromagnetic relay; the energy storage module comprises a super capacitor group and a parallel lithium battery group, and is coupled with the bus capacitor through a bidirectional DC / DC converter; the input end of the multi-path regulation and control module is connected with the bus voltage sensor, and the output end is connected with the switching execution unit through a second electromagnetic relay group; the dynamic switching unit comprises an I-GBT matrix and a reverse blocking diode array which are respectively connected with the inverter and the bypass circuit in parallel; and the real-time monitoring module is provided with a current harmonic analysis unit and a load break variable detection unit, and the output end of the real-time monitoring module is connected with the ADC port of the central processor. According to the invention, systematic improvement is realized in three dimensions of electric energy quality guarantee, equipment reliability and dynamic response capability through an original multi-path regulation and control architecture and a deep cooperative intelligent control strategy.

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.

The invention provides a power network state recognition method and system based on data feature analysis, which are used for continuously improving the power network state recognition precision through a data-driven optimization mechanism, providing full-process intelligent decision support for power grid operation and maintenance, and effectively promoting the power network to be converted from a passive operation and maintenance mode to an active prevention and control mode. The method comprises the following steps: acquiring a multi-dimensional power data set of a target power network, performing dynamic feature extraction processing on the multi-dimensional power data set to generate a power network operation feature set, and inputting the power network operation feature set into a debugged power state recognition model, and carrying out conjoint analysis on the voltage fluctuation characteristics, the current phase deviation characteristics and the equipment health degree characteristics through a power state identification model to generate a power network state classification result, and generating a network operation and maintenance strategy according to the power network state classification result. And the network operation and maintenance strategy is sent to the power dispatching terminal so as to activate corresponding equipment maintenance operation or load adjustment operation.

The invention discloses a communication power supply adaptive optimization method and system based on intelligent prediction, and relates to the technical field of power grid dispatching, and the method comprises the steps: collecting dynamic data and static data of a communication system, and constructing a load prediction model; on the basis of a load prediction model, combining static data to predict future load, combining dynamic data to calculate available energy of the system, and formulating a multi-path power supply scheduling strategy; and based on the prediction result, processing the prediction error, correcting the prediction result, and adjusting the power supply strategy under the condition of power interruption. The accurate load prediction enables the configuration of the standby power supply and the UPS system to be more reasonable, and reduces the risk of excessive configuration or insufficient configuration. The overall energy utilization efficiency is improved, and unnecessary energy waste is reduced. Efficient, reliable and intelligent operation of a power supply system is achieved, more stable and more economical power supply service is provided for users, and meanwhile a new solution is provided for intelligent management of an electric power system.

The invention discloses a 10KV station electric control system of a convertor station adopting selecting 2 from 3 logic. Two PS830 boards are added, three PS830 boards are utilized to concurrently process and jointly realize a spare power automatic switching function and an operation interlocking logic function; the selecting 2 from 3 logic is added in PS853 programs of an ASI host machine and a switching value output board, i.e. the electric control system can be exported when at least two of three integrated circuit boards sends out same instructions. The damage of any one of the three PS830 boards can not lead to switch fault trip or refusing trip, the 10KV control system can be ensured to run safely and stably without being influenced by the faults of single element. The electric control system has the advantages of convenient use, safety and the like.

The invention discloses a switching method and device of a primary and secondary fusion switch, a medium and a program product, and relates to the field of electric power intelligent dispatching, and the method comprises the steps: obtaining real-time electrical parameters and historical electrical parameters of an operation power supply; determining a system disturbance level based on the change rate of the real-time electrical parameters relative to the historical electrical parameters, and determining a system sampling period according to the system disturbance level; collecting a target electrical parameter of a power supply to be switched in a system sampling period, and calculating a switching evaluation index according to the real-time electrical parameter and the target electrical parameter; according to the switching evaluation index and the system disturbance level, determining a dynamic control parameter of the power supply to be switched in; when the adjustment rate of the dynamic control parameter is greater than a first preset threshold value and the switching evaluation index is smaller than a second preset threshold value, generating a switching enable signal; and controlling the primary and secondary fusion switch to execute switching operation according to the switching enable signal. According to the invention, the transient response performance in the power supply switching process can be improved.

The invention relates to the technical field of hydrogen production, in particular to a quick response system of a double-probe hydrogen leakage explosion detector and a grading early warning method. Comprising a first hydrogen concentration detection probe and a second hydrogen concentration detection probe which are respectively arranged at two different positions of a monitored area to form a space complementation detection network; the signal processing unit is electrically connected with the two probes and is used for receiving and processing the concentration signals output by the probes; the quick response control module is used for calculating the hydrogen concentration change rate in real time based on an output result of the signal processing unit; the grading early warning module is used for generating different grades of early warning signals according to the hydrogen concentration change rate and the absolute concentration value; the communication interface module is used for transmitting the early warning signal to a remote monitoring terminal; the multi-physical-field parameter change of the electrolyte can be sensed in real time, the control instruction is dynamically corrected, and the anti-interference capability is high.

The invention discloses a self-sensing monitoring method, system and equipment based on a lightning arrester, and relates to the technical field of power equipment monitoring. The self-sensing monitoring method, system and equipment based on the lightning arrester comprises the following steps: S1, collecting lightning stroke data in real time through multi-sensing fusion, and performing data cleaning and standardization processing on the lightning stroke data; s2, adopting a three-mode sensing and three-source power supply cooperation mechanism to realize state-driven adaptive sensing and energy path switching; s3, automatically scheduling a communication path according to a communication type and link quality, dynamically analyzing and compensating transmitting power, and completing authentication encryption and multi-hop secure transmission; s4, lightning stroke characteristics are extracted, an equipment life prediction model is constructed, residual life prediction is realized, and equipment health grade division and operation strategy adjustment are carried out according to the residual life prediction model; and S5, calculating an electric leakage deviation value by reconstructing a current waveform, triggering graded early warning and linking a communication power and energy supply strategy. The problem that the operation of a power system is affected due to large leakage current monitoring errors is solved.

Methods of performing a dispatched logistics operation for delivery / pickup of items using a modular autonomous bot apparatus assembly (with a modular autonomy module, cargo storage system, auxiliary power module, and mobility base) and a dispatch server. The modular autonomy control module receives a dispatch command from the dispatch server and authenticates that each of the modular components in the assembly are compatible with the particular dispatched logistics operation. The bot assembly receives the transported item, autonomously moves from an origin location to a destination per the dispatch command using the mobility base autonomously controlled by the modular autonomy control module, receives authentication input that at least correlates to authentication information in the dispatch comment to allow selective access to the modular cargo storage system of the bot assembly, and then autonomously returns to the origin after the item is detected removed from the cargo storage system.

The invention relates to a power electronics and energy storage technology, and aims to provide a medium-voltage uninterruptible power supply system based on cascade super-capacitance energy storage and a control method. According to the system, a cascade super-capacitance energy storage module with a three-phase structure is connected between an isolation reactor and a load side switch through a filter reactor and is used for stabilizing the voltage of a load bus; according to the invention, operations of adaptive power reference calculation, voltage phase control and voltage amplitude stable control are carried out; according to the method, the over-capacitance wide voltage operation characteristic is fully considered, and the control on the over-capacitance charging and discharging process is adaptively adjusted according to the power grid fault state and the over-capacitance voltage deviation, so that the system can provide the required power support when the fault occurs, stable energy supplementation is performed after recovery, the risks of over-capacitance voltage out-of-limit and the like are favorably avoided, and the system reliability is improved. And the effectiveness of energy management and the stability of the system are improved. And during a power grid fault period, the load voltage is recovered to be close to a rated value in a short time, voltage drop and overshoot are reduced, and the response speed and the voltage supporting capability of the system are enhanced.

The invention provides a shelter rapid power supply recovery method and system suitable for an emergency rescue task. The method comprises the following steps: collecting a power interruption signal, analyzing the power interruption signal, and generating an emergency response instruction; fault points are automatically identified and accurately positioned, the importance level of each electric device in the shelter is evaluated, and a dynamic priority list and a device demand report are generated; intelligently selecting a stand-by power supply combination scheme, starting a stand-by power supply switching process, and generating a stand-by power supply activation instruction; after a standby power supply activation instruction is received, the power supply sequence and power distribution of all devices are dynamically adjusted, normal operation of key facilities is preferentially guaranteed, and a device power supply plan is generated; and continuously monitoring the working state of the standby power supply and the influence of the standby power supply on the overall power system of the cabin, dynamically optimizing the power supply strategy, and generating an optimized power supply scheme. According to the technical scheme provided by the invention, the response speed and the power supply reliability of the shelter hospital or the temporary emergency facility during power interruption are improved.

The invention discloses a power supply switching method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring running state data of a first power supply in real time, and preprocessing the running state data to generate corresponding time sequence data; inputting the time sequence data into a pre-trained LSTM prediction model, the LSTM prediction model being obtained based on sample historical operation data of the power supply and fault sample training, and outputting a fault probability value of the first power supply in a future preset time period; determining whether the first power supply has a fault trend or not according to a relationship between the fault probability value and a preset threshold value; and when the fault trend exists, controlling the first power supply to be disconnected and connecting a second power supply to carry out load power supply switching. According to the scheme, the power supply can be switched to other power supplies before power interruption possibly caused by faults, and the stability and reliability of power supply of related communication equipment are guaranteed.

The invention relates to a reconfigurable battery energy storage system grid-connected and off-grid seamless switching control method and device. The method comprises the following steps of: sensing a real-time power grid state, pre-judging a system operation mode, and acquiring a millisecond-level panoramic information flow of the power grid state through a high-speed sampling voltage sensor, a high-speed sampling frequency sensor, a high-speed sampling phase sensor and a high-speed sampling communication interface. And pre-judging the stability and disturbance trend of the power grid through a deep learning algorithm, executing a power distribution and voltage support algorithm in grid-connected and off-grid modes, and calculating an optimal switching opportunity point and a system reconstruction target topology scheme. Meanwhile, the harmonic distortion rate and the voltage sag depth are calculated in real time through discrete Fourier transform, so that a mode pre-judgment mechanism is automatically triggered. After switching, key parameters such as voltage, frequency and power are automatically corrected through real-time sampling and observation, and zero-sensing switching is achieved. The method can effectively improve the response speed and stability of the battery energy storage system when the power grid fails, and guarantees the safe operation of the power grid.

The invention discloses an integrated distributed energy storage UPS (Uninterrupted Power Supply) system, which relates to the technical field of distributed energy storage and comprises the steps of S1, data real-time acquisition, S2, parameter normalization processing, S3, dynamic weight calculation, S4, load instruction dynamic distribution, S5, multi-target coordination control execution and S6, state feedback and parameter self-tuning. According to the method, core parameters such as the charge state, the health degree, the temperature and the internal resistance of each energy storage unit are evaluated in real time, a weight function with a time-varying characteristic is constructed, the output proportion of each unit can be dynamically adjusted, and intelligent load distribution matched with the equipment aging state and the environment working condition is achieved; by introducing a health degree attenuation factor, the system can quantify the nonlinear degradation characteristics of the battery pack, preferentially dispatches the unit with an excellent state to bear the base load, and provides an intermittent rest period for the high-loss unit at the same time.

The invention discloses a digital control uninterruptible power supply parallel operation phase locking method, which relates to the technical field of digital phase locking, and comprises the following steps of: in each analysis period, acquiring an output voltage waveform signal and a current frequency disturbance control parameter of each uninterruptible power supply, and respectively executing short-time Fourier transform to obtain an output voltage waveform signal and a current frequency disturbance control parameter of each uninterruptible power supply; and converting the time domain signal into a multi-dimensional dynamic spectrum matrix, extracting frequency and amplitude parameters of a disturbance signal, and constructing a corresponding uninterruptible power supply disturbance parameter set. According to the invention, through dynamic spectrum analysis and frequency domain coupling tensor modeling, accurate extraction of UPS modulation signal features and dynamic evaluation of resonance risk indexes are realized, in combination with a risk-driven frequency intervention mechanism, frequency coupling is broken, the frequency diversity and disturbance decoupling capability of the system are improved, and the reliability of the system is improved. The stability, the anti-interference performance and the intelligent response capability of the parallel system are obviously enhanced, and early warning and active suppression of lock point resonance are realized.

The invention provides an optimal scheduling method and system for a power management system. Wherein a dynamic power distribution strategy and an equipment working mode switching rule are obtained based on the real-time geographic position, environmental parameters and task priority evaluation of the medical treatment box; generating an extra energy reserve decision and an energy-saving measure scheme by using the dynamic power distribution strategy and the equipment working mode switching rule; according to the extra energy reserve decision and the energy-saving measure scheme, optimizing prediction precision through a machine learning algorithm, implementing reliability engineering analysis, and evaluating reliability and stability of different power supply schemes under various conditions to generate a comprehensive stable power supply guarantee plan; and based on the comprehensive stable power supply guarantee plan, determining an optimal rescue path through a path optimization technology, and generating a rescue path plan. According to the technical scheme provided by the invention, the capability of providing stable power support by the medical treatment box under various conditions is remarkably improved.

The invention discloses an elevator energy-saving control system based on a conversion module, which relates to the field of elevator control and comprises a battery module, the conversion module and an energy-saving control module, the battery module is connected with at least one elevator; the AC side of the conversion module is connected with commercial power, and the DC side of the conversion module is connected with the battery module; the energy-saving control module is connected with the battery module, and the energy-saving control module is in communication connection with the battery module and the conversion module. The stable operation of the elevator is guaranteed, the electricity utilization economical efficiency of the elevator is effectively improved, and the electricity utilization cost is reduced.

The invention discloses a data center power supply system, and belongs to the technical field of power electronics. The power supply system comprises a plurality of multi-port solid-state transformers, each multi-port solid-state transformer comprises an input end, a first output end and a second output end, and the input ends are electrically connected with a medium-voltage power grid; the multi-port solid-state transformer is used for converting medium-voltage alternating current input by the input end into direct current with a first voltage value and direct current with a second voltage value; the multiple multi-port solid-state transformers supply power to multiple direct-current loads of the data center, the first output ends of the multi-port solid-state transformers are electrically connected with the corresponding direct-current loads, and the working voltage of the direct-current loads corresponds to the first voltage value; and the first inversion module is electrically connected with the second output ends of the plurality of multi-port solid-state transformers and is used for inverting the direct current with the second voltage value output by the second output ends and then supplying power to the alternating current load of the data center.