723 results about "Energy balancing" patented technology

The invention relates to a distributed energy management system for prolonging the cycle life of a lithium battery. The system comprises an acquisition unit used for acquiring battery state characteristic data of single batteries in a lithium battery pack; the identification unit is used for carrying out charge and discharge abnormal mode identification on the battery state characteristic data to obtain charge and discharge abnormal event data; the decomposition unit is used for performing hierarchical characteristic decomposition and multi-dimensional fusion based on the charging and discharging abnormal event data to obtain a cycle life attenuation characteristic matrix; and the equalization control unit is used for carrying out life equalization control based on the cycle life attenuation characteristic matrix to obtain a target charge and discharge coefficient. According to the invention, the local over-charge and over-discharge phenomena are effectively inhibited, the service life loss of the battery pack is reduced, and the energy balance adjustment of the multi-node control unit is realized.

The invention provides a self-adaptive power supply energy-saving configuration method and system based on energy gradient utilization, and relates to the technical field of power supply management, and the method comprises the steps: collecting the operation parameters of electric equipment, building a power utilization model, and carrying out the self-adaptive correction; constructing a multi-stage energy distribution matrix according to the corrected power utilization model, and performing energy efficiency grading on the power utilization equipment; performing spatial-temporal feature extraction by adopting a bidirectional attention mechanism, generating an electric equipment priority strategy in combination with a self-calibration network, and further calculating an energy distribution proportion of each level of electric equipment; and finally, generating a control signal according to the energy distribution proportion, adjusting the power supply power of each stage of electric equipment, distributing the exceeded power to the electric equipment with the secondary high energy conversion efficiency when the power value exceeds a target power threshold value, and outputting a self-adaptive energy balance control instruction according to the prediction control model to adjust the operation state of the electric equipment.

The invention relates to the technical field of power system dispatching, and discloses a multi-agent reinforcement learning active power distribution network area coordination method and system, and the method comprises the steps: dividing a power distribution network into a plurality of areas, and each area is managed by an agent; collecting observation information; inputting the observation information into an upper reinforcement learning strategy network, and outputting control parameters; inputting the control parameters into a target function of the lower-layer local physical optimization model, and solving an output setting point of the equipment under the condition of meeting the safety operation constraint; constructing a De-POMDP problem, and obtaining a reward signal of each agent; a sequential updating mechanism is introduced, global network parameters are optimized, and corresponding decisions are obtained; and inputting the multi-agent decision into the global active power distribution network model to obtain the total operation cost, feeding back the total operation cost as an award to the reinforcement learning strategy network, updating global network parameters, and converging to obtain an optimal decision. According to the invention, regional wind-solar-storage multi-energy scheduling can be effectively optimized, and energy balance in the region is realized.

The invention discloses a new energy project intelligent planning method and system based on a large language model, and relates to the technical field of new energy planning, and the method comprises the steps: constructing a new energy project planning knowledge base; the new energy project planning knowledge base comprises basic data required by project planning and is used for providing data support for the optimization model; based on the training data in the new energy project planning knowledge base, performing field adaptability training on the large language model to obtain a special large language model in the new energy project planning field; and based on a project demand input by a user, analyzing project parameters through the special large language model, inputting an analysis result into the optimization model, and generating a planning scheme of a new energy project. According to the method, automatic conversion from a natural language demand to a professional planning scheme is realized, the accuracy of energy balance constraint is ensured through the topological structure diagram of the energy system, a flexible switching optimization target of economic benefits and environmental benefits is supported, and finally intelligent generation and evaluation of the planning scheme are realized.

The invention discloses an airport energy balance management method, system and device and a medium, and relates to the field of energy management. The method comprises the following steps: constructing an energy topological graph according to multi-source data; predicting energy load demands of the airport in different time periods according to the energy topological graph, determining the supply amount of renewable energy in different time periods according to the predicted illumination intensity and wind power, and determining a time-sharing energy supply and demand balance probability according to the energy load demands and the supply amount; determining a preliminary energy management plan according to the cost parameter, the time-sharing energy supply and demand balance probability and the equipment operation constraint, wherein the preliminary energy management plan comprises an energy storage system charging and discharging time sequence, a standby generator starting and stopping plan and a power grid electricity purchasing proportion; and executing the preliminary energy management plan through the digital twin of the airport to obtain first energy execution data, and adjusting the preliminary energy management plan through the difference between the first energy execution data and the second energy execution data at the current moment. By implementing the technical scheme provided by the invention, the energy cost is reduced.

The invention discloses a balance scheduling system for energy management and a balance scheduling method thereof, and relates to the technical field of energy management scheduling, and the balance scheduling system comprises an energy data acquisition module, an energy demand trend analysis module, an energy supply and demand dynamic prediction module, an energy balance scheduling decision module, a scheduling execution module and a performance monitoring module. After the energy supply and demand dynamic prediction module integrates real-time external factor data of the energy data acquisition module and a long-term historical rule of the energy demand trend analysis module, a reference prediction baseline based on a long-term trend is generated, and then a dynamic correction value is superposed to respond to short-term disturbance. And meanwhile, through an error traceability mechanism for separating a trend baseline from external correction, the module performance can be optimized in a targeted manner, if an error is derived from long-term trend deviation, a trend analysis model is calibrated, and if external data is lagged, priority adjustment of a data acquisition module is triggered, so that system self-diagnosis and prediction precision closed-loop improvement are realized.

The invention discloses a source network load storage oriented regional collaborative scheduling method and system, and relates to the technical field related to power resource scheduling, and the method comprises the steps: traversing target region source network load storage to carry out real-time data collection, and constructing a source network load storage multi-dimensional data set to carry out multi-scale layered optimization; operation constraint conditions are set, limitation is carried out in combination with a power grid topological structure, a cooperative scheduling instruction set is determined, cooperative control feedback is carried out, and regional power scheduling feedback parameters are generated; and multi-channel dynamic correction is carried out, and a cooperative scheduling optimization strategy is generated to carry out energy balance cooperative scheduling on the source network load storage in the target area. The technical problems that in the prior art, intermittent fluctuation of new energy is difficult to consume, the collaboration of all links of source network load storage is poor, the dispatching flexibility of a power system is insufficient, and the resource configuration efficiency is low are solved. The technical effects of optimizing regional energy resource allocation and improving the clean energy consumption level, the power grid operation stability and the source grid load storage cooperative response capability are achieved.

The invention provides an energy storage intelligent monitoring method and system for an industrial and commercial energy storage power station, and relates to the technical field of intelligent monitoring, and the method comprises the steps: determining a current impact characteristic and a voltage fluctuation characteristic of an energy storage unit during the switching of a charging state and a discharging state through an operation record of the energy storage power station; extracting the energy conversion rate of the energy storage unit in the charging and discharging state switching process, and determining the transient energy entropy change of the energy storage unit during state switching in the charging and discharging state switching process according to the energy conversion rate and the current impact characteristics; performing compensation cost constraint on the energy inverse difference of the energy storage unit during charging and discharging state switching through transient energy entropy change and voltage fluctuation characteristics to obtain a state constraint parameter of energy compensation of the energy storage unit during state switching; according to the method and the device, the energy balance of the energy storage power station in the charging and discharging state switching process can be realized, so that the operation stability of the energy storage power station is improved.

The invention discloses an energy balance flexible guide mechanism hinge rigidity design method based on machine learning, and relates to the technical field of energy balance design. Constructing a mechanism parameter library by taking the hinge thickness as a structural parameter; converting the three-dimensional modeling software design scheme into a three-dimensional model library; performing three-dimensional grid division and finite element analysis to establish a grid library; constructing a three-dimensional simulation result database through finite element simulation results; establishing a mapping relation between the structure parameters and the performance characteristics by utilizing a machine learning method, and taking the mapping relation as a parameter library of machine learning; optimizing the design scheme through a machine learning method; and flexible guide mechanism scheme libraries under different index systems are constructed, and the flexible guide mechanism hinge meeting the requirements is obtained. An optimal flexible guide mechanism hinge design scheme is predicted through a machine learning method, mechanical properties of a hinge three-dimensional model are simulated in combination with finite element analysis, experiment and calculation requirements are reduced, and design efficiency and economic benefits are improved.

The invention discloses a multi-target computing power unloading system oriented to an unmanned aerial vehicle cooperative cluster, and aims to realize comprehensive optimization of task scheduling efficiency, energy balance and unloading intelligence on the premise of satisfying service real-time performance. The system firstly senses the operation state of each unmanned aerial vehicle in a cluster, extracts multi-dimensional information such as task data volume, residual electric quantity, local computing power and adjacent cooperative node resources, constructs a system state space, and defines action spaces such as local processing, edge unloading and cooperative unloading. And then, designing a multi-target fusion reward function, carrying out weighted integration on key indexes such as task time delay, electric quantity balance and node residual energy, dynamically adjusting reward feedback in combination with service delay constraint, and guiding a reinforcement learning agent to converge to a better unloading strategy.

The invention discloses a steam pipe network decoupling steady-state optimization method and device, a medium and a program product, and relates to the technical field of smart city guarantee. The method comprises the following steps: determining node pressure distribution data and flow distribution data when a mass and momentum balance condition is satisfied according to fluid distribution data of a pipe network simulation model corresponding to a physical structure and an actual working condition of a steam pipe network; and determining node enthalpy data meeting an energy balance condition. Determining a condensation phase change node according to the node pressure distribution data and the node enthalpy data, associating the steam enthalpy of the condensation phase change node to a saturation state under the current pressure, and updating a current fluid distribution parameter according to the determined condensation water volume, and taking the parameters of the pipe network simulation model finally reaching the dynamic balance state as the operation state parameters of the steam pipe network under the target operation condition. The problem that the steam pipe network parameters cannot be accurately determined in the prior art can be solved, and the running state parameters of the steam pipe network can be accurately determined.

The invention discloses a VSG-VDG-based autonomous control method and device for an AC-DC hybrid micro-grid interconnection converter. The equipment comprises a direct-current micro-grid, an alternating-current micro-grid and an interconnection converter connected with the direct-current micro-grid and the alternating-current micro-grid. The direct current microgrid is provided with a direct current side VDG control module which is used for controlling a direct current converter to adjust direct current power supply output by collecting internal voltage and current signals; the AC micro-grid is provided with an AC side VSG control module which is used for controlling on-off of a switching tube of a three-phase full-bridge inverter by collecting internal voltage and current signals so as to adjust AC three-phase voltage output. The interconnection converter is provided with an interconnection converter control module which is used for connecting the direct-current bus and the alternating-current bus through the bidirectional interface converter and adjusting energy balance in the subnet through bidirectional energy flow. According to the method, the robustness of the AC / DC micro-grid system is enhanced, and the fault self-healing capability of the system under extreme conditions and the transient and steady-state stability of a controlled system are improved.

The invention discloses a fire-fighting fire risk assessment and early warning method based on an AI large model, and relates to the technical field of fire risk assessment and early warning, and the method employs the collaborative design of a dual-rate time axis encoder and a deformable convolutional layer, retains the transient characteristics of a voltage, captures the gradual change trend of the temperature, and remarkably improves the early abnormality detection capability. A feature extraction window is intelligently adjusted along with the thermal runaway stage, the problem of time-effect mismatching caused by a fixed time window is solved, and continuous tracking from fine precursor capture to violent change is achieved; through electrochemical coupling and energy balance constraint, a lithium battery thermal runaway mechanism is converted into priori knowledge of model training, irrational prediction of a pure data driving model is avoided, and interpretability and reliability of early warning decision are enhanced.

The invention discloses a public building cold load short-time prediction method fusing physical information, and the method comprises the steps: collecting and preprocessing the historical cooling capacity, indoor environment, outdoor weather and equipment operation state data of a public building at a fixed time interval, and obtaining multi-dimensional input features; respectively establishing a workday sub-model and a holiday sub-model according to workday and holiday scene division; the workday sub-model and the holiday sub-model jointly form a cold load prediction model, the workday sub-model adopts a long short-term memory (LSTM) network, and the holiday sub-model adopts a light gradient elevator (Light GBM); a physical constraint loss function based on building energy balance and heat conduction residual error is introduced in the training process, and the physical constraint loss is fused into a total loss function according to a weighting coefficient so as to constrain that the output of each sub-model accords with the law of energy conservation and thermal inertia; monitoring the prediction error MAPE in real time and performing online calibration; and outputting a short-time cold load prediction result.

The invention relates to the technical field of metal smelting, in particular to a multi-gun top-blowing continuous blowing intelligent system and method. The system comprises a data acquisition module, an analysis processing module and a prediction feedback module. The method comprises the steps that the temperature, the liquid level and the material state in the furnace are monitored in real time and transmitted to the central data processing platform in real time for intelligent feedback control; dimensionality reduction is conducted on sensing data in the smelting process, the least principal components with the contribution rate exceeding 80% are extracted, and dimensionality reduction processing is achieved; carrying out thermal analysis by utilizing a material and energy balance equation, constructing a theoretical model of the blowing process, capturing a long-term dependency relationship, and predicting dynamic parameter change in the smelting process; and an interaction model of the intelligent agent and the smelting environment is constructed, a control strategy is updated in real time, and production parameters are adaptively adjusted. The problem of low-altitude pollution caused by converter blowing is solved, the defect of low efficiency of intermittent operation of current smelting is overcome, and a continuous and stable production process is realized.

Sustainable enterprise-wide energy balancing is presented herein, which describes a series of processes to make choices in favor of a sustainably sourced energy mix, grid reliability, and / or to prioritize critical systems in times of a catastrophe. An example method comprises receiving a group of input data representing a standardized phrase, wherein the group of input data is received from first equipment associated with an electric power generation and transmission operator entity; parsing the standardized phrase to identify an initiating event; in response to identifying the initiating event, determining that an initiating threshold value associated with the initiating event has fallen below a defined risk threshold value; and executing, on remote second equipment, a flow of customer defined processes representing a group of runbooks.

The invention provides a low-load combustion optimization control system for a unit, and the system comprises a sensing network module which collects key parameters of the unit in a combustion process; the data preprocessing module is used for preprocessing the collected key parameters; the index analysis module is used for analyzing the energy balance deviation degree, chemical balance and combustion uniformity evaluation indexes of the current unit based on the preprocessed key parameters; the control strategy execution module is used for carrying out threshold value judgment on the result of each index and correspondingly executing preset energy balance, chemical balance and combustion uniformity strategies; the feedback regulation module is used for acquiring the executed feedback signal and performing new index analysis and cyclic regulation to form a closed-loop feedback mechanism; energy balance, chemical balance and combustion uniformity in the combustion process are analyzed and controlled, so that combustion stability and combustion efficiency are improved, pollutant emission is reduced, the service life of equipment is prolonged, and meanwhile, the adaptability of a unit to a power grid is enhanced.

The invention discloses a heat exchange station circulating pump characteristic adaptive optimization control method and system, and relates to the technical field of circulating pump control, and the method comprises the steps: building a building terminal heat transfer model and a building energy balance model based on the temperature distribution of the surface of a radiator, and then building a building load prediction model; performing numerical modeling on the performance curve of the heat exchange station circulating pump, and establishing a circulating pump performance model; based on a depth deterministic strategy gradient algorithm, establishing a neural network control model for self-adaptive control of the circulating pump of the heat exchange station; establishing a state, an action and a reward function of an agent of the neural network control model; and training the neural network control model to obtain a trained control model, and performing real-time control on the heat exchange station circulating pump based on the trained control model. The technical problems that a traditional control method of the circulating pump is low in operation efficiency and serious in energy waste are solved.

As more power electronics apparatuses use fast switches, such as silicon carbide (SiC) or gallium nitride (GaN) switches. to improve the efficiency and reduce switching losses. significantly higher electromagnetic interferences (EMI) are generated as a result. While techniques of random pulse-width modulation (PWM) have been developed to reduce this increased EMI, the use of such techniques leads to an unbalance of the stored electric energy of the energy storing components used to balance the energy across some of the switches of these apparatuses. This issue can be solved with a novel pulse width modulation method for generating the switching signals with variable frequencies for a converter's high-frequency switches that better balance its energy balancing components. This novel method can utilize comparing a reference signal to a carrier signal that can be generated with various switching frequencies that are phase-shifted from the following set of switching frequency, by (2N−1)π radians.

The invention discloses a power distribution equipment voltage quality adjustment control method, device and equipment, and the method comprises the steps: collecting voltage waveform data in the operation process of power distribution equipment, and carrying out the feature extraction of the voltage waveform data, and constructing a voltage feature library; identifying a resonance voltage mode based on the voltage feature library, performing energy density analysis on the resonance voltage mode to position a resonance energy collection point, generating a resonance compensation signal, and converting resonance energy into adjusting power; performing voltage distribution evaluation on the resonance enhancement control domain, identifying an energy surplus region and an energy deficient region, and constructing a bidirectional energy channel between the two regions to generate an energy balance configuration table; carrying out oscillation characteristic analysis on the energy balance configuration table, and implementing oscillation type voltage regulation at a periodic regulation point; carrying out key path identification on the oscillation adjustment parameters, and optimizing a processing sequence to generate an adjustment time sequence table; and extracting execution instructions of each node according to the adjustment time sequence table to generate a hierarchical control instruction set, thereby realizing active perception, intelligent analysis and accurate regulation and control of voltage quality.

The invention relates to the technical field of power system control, in particular to a direct-current capacitor self-synchronizing grid-connected control strategy method, system, equipment and medium, a direct-current capacitor energy dynamic model is established based on an actual energy balance relation, a direct-current voltage signal is acquired in real time, and a synchronous compensation signal is calculated based on the acquired direct-current voltage signal; performing phase compensation and gain adjustment on the synchronous compensation signal through a correction link based on the calculated synchronous compensation signal, adjusting the internal frequency of the inverter based on the synchronous compensation signal after phase compensation and gain adjustment, controlling the DC voltage through the internal frequency of the inverter, and establishing a self-synchronization control model; and based on the self-synchronization control model, establishing an adaptive control algorithm, generating a damping coefficient and a virtual inertia coefficient through the adaptive control algorithm, and dynamically adjusting control parameters according to the damping coefficient and the virtual inertia coefficient.

The invention belongs to the technical field of photovoltaic network construction, and discloses a pre-synchronization start control strategy of a photovoltaic network construction type converter. According to the method, an energy balance relation between a photovoltaic array and output power of an inverter of a virtual synchronous machine (VSG) is used for replacing charging and discharging of an energy storage battery on a system, and a photovoltaic virtual synchronous machine (PV-VSG) pre-synchronization slow start control strategy is designed. The strategy can enable the photovoltaic inverter to have the capability of independently supporting the bus voltage and frequency, and can avoid the grid connection failure caused by the destructive influence of the system power shortage caused by external disturbance on the DC bus voltage at the starting moment of the energy-storage-free photovoltaic grid connection system. According to the strategy, PV-VSG network construction control in a power reserve mode is considered, and smooth grid connection of the photovoltaic on-load system is realized. In the step of stabilizing the voltage of the direct current bus, sliding mode control is adopted to replace traditional PI control, and the robustness of a network construction system is improved.

The invention relates to the field of new energy, and discloses a regional multi-energy complementary zero-carbon energy supply system coupling a reversible solid oxide battery technology and a closed CO2 network, which comprises an RSOC heat-mass-electricity reversible converter, a closed CO2 circulating network, renewable energy power, an external heat source, a chemical energy storage, a natural cold and heat source and a terminal energy consumption module. According to the invention, the RSOC bidirectionally operates in a power generation mode and an electrolysis mode, the coupling chemical energy storage module realizes regional multi-time scale energy balance, photovoltaic power generation supplies power to RSOC electrolysis and terminal users at the same time, and light condensation and heat collection and industrial waste heat in the external heat source module can be integrated with the RSOC module to reduce electrolysis power consumption. The closed CO2 network adopts pressurized low-temperature CO2 as a circulating working medium of the regional heating and cooling network, and RSOC waste heat and natural cold and heat resources can be fully utilized on the source side; the network heating and cooling capacity is greatly improved at the terminal through phase change heat transfer, passive cooling of a user is achieved, meanwhile, the water source heat pump is coupled to meet the heating power requirements of different grades, and net zero carbon emission is achieved in the whole process.

The invention discloses an elevator energy-saving control system based on an auxiliary power supply module, which relates to the field of elevator energy-saving control and comprises a battery module, the auxiliary power supply module and an energy-saving control module, the battery module is connected with a circuit breaker, the circuit breaker is connected with at least one contactor set used for being connected with at least one elevator in a one-to-one correspondence mode, the same bypass contactor is connected between the circuit breaker and all the contactor sets, and the bypass contactor is connected with an anti-reverse diode in parallel. The mains supply and the battery module are respectively connected with the auxiliary power supply module; the auxiliary power supply module is connected with the energy-saving control module; and the energy-saving control module is respectively in communication connection with the circuit breaker, the contactor group, the bypass contactor, the battery module and the auxiliary power supply module. The charging and discharging energy balance of the battery module can be realized, and the problems of conversion electric quantity loss and high cost caused by the use of a conversion module are avoided.

The invention discloses an isolated high-voltage direct-hanging energy storage converter and energy balance integrated control method. The method comprises the following steps: S1, acquiring SOC and voltage of each battery cluster in an energy storage converter; s2, establishing a controlled energy channel between the battery clusters, and performing self-balancing transfer on energy between the adjacent battery clusters according to voltage and SOC differences between the battery clusters; s3, selecting an expansion phase shift mode according to the power flow direction between the battery clusters, and selecting a phase shift ratio under the constraint of transmission power to reduce current stress and backflow power; s4, generating a modulation coefficient of a shared bridge arm according to decoupling inductive current inner loop proportion tracking; performing PR current closed loop on the main bridge arm, and generating a switching sequence of each switching tube of the shared bridge arm by adopting unipolar carrier phase-shifting modulation; and S5, outputting the modulation coefficient of the shared bridge arm and the switching sequence of each switching tube, driving the isolated bidirectional DC-DC converter and each H-bridge module to work, and realizing grid-connected energy bidirectional flow and voltage and current index satisfaction.

The invention discloses an intelligent electric vehicle queue optimization method based on congestion prediction and DRL. The method comprises the following steps: (1) modeling a queue position optimization problem of an electric vehicle queue into a mathematical model which takes energy balance as a target and is constrained by a traffic environment; and (2) solving the mathematical model in the step (1) by adopting a DRL method based on a TRPO algorithm to obtain an optimal queue adjustment strategy of the electric vehicle queue. In the step (2), congestion state information in an external traffic environment is obtained through an LSTM traffic prediction and FCM method, and the congestion state information, the remaining electric quantity of each vehicle in the motorcade and the accumulated driving distance are jointly used as state input of a TRPO algorithm; according to the TRPO algorithm, a strategy network and a value network are adopted to respectively obtain a strategy for adjusting the queue position, and the return expectation in the current state is evaluated. The TRPO algorithm dynamically adjusts the updating step length of the strategy through the KL divergence updated by the constraint strategy, and guarantees the stability and convergence in the strategy updating process.

Disclosed in the present invention are a system frequency stability control method and system taking into consideration a new-energy frequency modulation energy constraint. The method comprises: calculating a lowest-frequency-point arrival time of a system under active disturbance; determining whether the lowest-frequency-point arrival time meets a frequency stability energy balance criterion, and acquiring a determination result; when the lowest-frequency-point arrival time does not meet the frequency stability energy balance criterion, determining available frequency modulation energy of each new-energy station; and in the previous time period of the lowest-frequency-point arrival time, sequentially adding the available frequency modulation energy of the new-energy stations to a frequency modulation sequence in ascending order of the magnitude of the available frequency modulation energy until a frequency modulation stability requirement is met, so as to complete system frequency stability control. In the present invention, from the perspective of energy, frequency stability is equivalent to the problem of whether disturbance energy and frequency modulation energy can be balanced, and the contribution of new-energy frequency modulation to the frequency is then equivalent to energy square blocks, such that the frequency stability is guaranteed by means of superimposed discrimination of the energy square blocks, and the requirement for new-energy frequency modulation energy is minimized.

The invention discloses a method for processing carbon flux data obtained by a vortex correlation method. The method comprises the steps of data acquisition, original data preprocessing, data post-processing, data interpolation, data storage and additional description. The method comprises the following steps: capturing a signal by adopting an eddy correlation method, and recording original data in real time through a Smart Flux collector; in the preprocessing stage, invalid data, abnormal values, rainfall influence data and the like are removed by using Eddypro software, and necessary instrument error and inclination correction is carried out; in the post-processing stage, Eddypro and TOVI software are combined for further processing, including energy balance correction, quality control and the like; for missing data, adopting a linear interpolation method and other interpolation methods; the processed data can be stored in an Excel mode, an R language mode or a programming mode. According to the method, the carbon flux data quality can be effectively improved, and a solid foundation is provided for subsequent scientific research and data analysis.

The invention discloses an operation method and system for a cloud energy storage and sustainable distributed energy system, and relates to the technical field of energy scheduling, and the method comprises the steps: carrying out the cooperative management of the cloud energy storage and sustainable distributed energy system for electric energy storage through multi-stage dynamic configuration and dual-scene cooperative scheduling according to the charging power demand; according to a charging power demand, maximization of a comprehensive net present value for measuring investment profit is taken as a target to establish a target function, flexibility is added to the target function, and a design constraint, an energy balance constraint, a charging pile optimal scheduling constraint and a scheduling constraint of a battery energy storage system BESS and a transformer are taken as constraint conditions. Constructing an optimal scheduling model for measuring economic benefits and environmental benefits; the cloud energy storage and sustainable distributed energy system is subjected to optimization management through a collaborative management and optimization scheduling model and addition of an aggregator for energy coordinated scheduling. According to the invention, the stability of power supply can be improved.

The invention discloses an enterprise lease-oriented equipment credit evaluation system and method, relates to the technical field of equipment data processing, and aims to synchronously quantify the running temperature, power consumption and heat dissipation state of equipment by forming an original thermal state data set Hraw and avoid one-sided judgment caused by traditional single-parameter monitoring. Based on a thermal state feature set Hset of a temperature stability index Tstb, a power consumption fluctuation spectrum index Pspc and a heat dissipation anomaly integral Qint, a three-dimensional feature space reflecting equipment operation stability and energy balance can be constructed, a thermal state feature template set Htpl is further formed through clustering, and dynamic reference establishment in different operation modes is achieved. And comparing the real-time feature vector with the thermal state feature template set Htpl to calculate a thermal balance index Hc, and generating an equipment credit score Sc in combination with a historical credit mean value score Sh, so that quantitative credit of enterprise equipment use behaviors can be realized.