461 results about "Energy balancing" patented technology

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 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 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 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.

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 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.

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 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.

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.

The invention relates to an industrial park-based comprehensive energy flow direction on-line monitoring system and method, and the system comprises an energy modeling module which is used for representing instrument information, carrying out the modeling of collection labels and collection frequencies of different types of instruments, constructing nodes of different energy layered structures, carrying out the modeling of a directed flow direction relation between the nodes, and carrying out the modeling of the directed flow direction relation between the nodes; binding the logic relationship between the node and the instrument; the data acquisition module is used for performing data acquisition through an instrument, performing edge processing and encrypted transmission through communication equipment, and storing the data in a database; the energy monitoring module is used for monitoring and counting the state of the instrument and monitoring the energy flow direction of the enterprise in real time according to the directed flow direction of the node; and the statistical analysis module is used for providing energy balance analysis for different links of the enterprise energy in the conversion and use process according to the nodes, evaluating the energy consumption loss degrees of the different links, visualizing the nodes with abnormal loss and giving an alarm. Through the real-time and accurate calculation of the energy loss among the nodes at all levels, the backtracking of the nodes with abnormal loss and the timely pushing of the alarm information, the enterprise can timely discover the problems occurring in the energy supply, and can quickly find out the corresponding solution, reduce the energy consumption loss and guarantee the robustness of the energy flow network.

The embodiment of the invention provides a thermal power plant waste heat gradient utilization management method and system, belongs to the field of energy and power engineering, and aims at solving the problems that in the prior art, waste heat gradient matching is unreasonable, the low-temperature waste heat recovery efficiency is low, and the system integration degree is insufficient. The method comprises the following steps: constructing a multi-physics field coupling digital twinborn model and performing real-time correction; establishing a dynamic matching matrix of the residual heat source and the heat consumption load based on balance analysis; solving a Pareto optimal operation scheme through a multi-objective optimization model; and generating and issuing a cooperative control instruction. The system comprises a panoramic data sensing module, a digital twin modeling module, a balance and optimization decision module and a cooperative control instruction generation module. Through global optimization and dynamic regulation and control, the waste heat utilization efficiency, the economical efficiency and the equipment reliability are remarkably improved.

The invention discloses a self-adaptive photovoltaic energy storage comprehensive optimization method and system, and belongs to the technical field of photovoltaic energy storage optimization control. According to the method, a system operation model is established based on historical and real-time operation data of a photovoltaic unit, an energy storage unit and a load side, a hybrid robust-stochastic optimization framework is introduced, a collaborative optimization model with energy balance and system stability as targets is constructed, and an initial control parameter set is solved; in the system operation process, a power fluctuation mode and energy storage response characteristics are identified through a multi-layer agent algorithm, and a dynamic energy storage control instruction is generated and corrected; and according to the cross-cycle change trend of the operation performance index, adaptively adjusting the weight and step length of the control parameter, and realizing strategy evolution and dynamic closed-loop optimization. According to the invention, cooperative operation of photovoltaic and energy storage can be realized under complex operation conditions, and the energy utilization rate and the operation stability are improved.

The invention relates to an anti-reflux control method based on time interval distribution. The method comprises the following steps: acquiring a multi-source fused operation data set; obtaining a trend prediction result set according to the operation data set; according to the trend prediction result set, dividing the prediction time window into a plurality of continuous control time periods, and based on the power generation prediction value, the load prediction value and the uncertainty index of each time period, calculating a corresponding time period countercurrent risk level, and generating a time period risk assessment result; obtaining a time period budget allocation table according to a time period risk assessment result; according to the time period budget distribution table, performing time-division power adjustment on the photovoltaic inverter, the energy storage unit and the controllable load, and realizing smooth transition between adjacent time periods through a cross-time period energy balance mechanism; and monitoring the grid-connected point power and the equipment operation state in real time, and when power deviation or load sudden change is detected, dynamically correcting the current output according to the residual capacity of the time period budget allocation table. According to the invention, the photovoltaic anti-reflux control effect can be improved.

The present invention discloses a method for self-clearing DC faults in a new energy island power grid transmission system. The sending end adopts a constant AC voltage and frequency control strategy, and there is only one receiving end that adopts a constant DC voltage control strategy, while the remaining receiving ends adopt a constant active power control strategy. At the same time, each pole of the flexible DC converter station at the sending end real-time detects the DC current flowing out of this pole, and each pole of the flexible DC converter station at the receiving end real-time detects the DC current flowing into this pole. After detecting the occurrence of a DC fault, the DC fault is automatically cleared according to their respective control strategies, and the energy balance of the sending end island is achieved in cooperation with the AC energy consumption at the sending end. It solves the technical problems of coordinated control between flexible DC and new energy, power surplus, and self-clearing of DC faults on the DC side, and improves the power regulation ability and system stability of the new energy island power grid transmission system.

The invention discloses a power control method, system, equipment and medium for a modular multilevel converter, and belongs to the technical field of power electronics and power system application, and the method comprises the steps: collecting the bridge arm current, the sub-module capacitor voltage, the DC bus voltage and the AC side power of the modular multilevel converter; calculating a power error according to the AC side power and a power reference value, and calculating a sub-module capacitor voltage error according to the sub-module capacitor voltage and a voltage reference value; constructing a Lyapunov function comprising a plurality of control targets, wherein the Lyapunov function comprises a power error term, a sub-module capacitor voltage error term, a circulating current suppression term and a total energy balance term; and determining a control law on the basis that the Lyapunov function meets a stability condition, and controlling the modular multilevel converter according to the control law. According to the method, the coupling control problem of multi-terminal direct current system power distribution and sub-module energy balance is considered and improved.

The invention relates to the technical field of intelligent water affairs, in particular to a three-level combined processing method for urban water consumption prediction, which comprises the following steps: S1, data restoration: correcting abnormal values in an urban water consumption time sequence by using a dynamic threshold correction method based on multi-scale wavelet decomposition; s2, performing feature decoupling; and S3, performing prediction fusion. According to the method in the technical scheme, a dynamic threshold correction method based on multi-scale wavelet decomposition is adopted, signal hierarchical analysis is achieved through discrete wavelet transformation, a dynamic threshold mechanism is constructed in combination with MAD robust statistics, and abnormal points are effectively recognized and corrected; constructing a dynamic frequency band division joint model of variational mode decomposition and spectrum energy balance, proposing a dynamic frequency band recombination strategy guided by amplitude ranking, and performing energy balance division and inverse transformation reconstruction on VMD high-frequency sub-components through fast Fourier transform spectrum analysis; fine separation and multi-band phase synchronization of high-frequency abrupt change characteristics and periodic fluctuation are realized; and finally, constructing a long-short-term memory network to predict and reconstruct all sub-components.

The invention provides a multi-microgrid energy collaborative optimization method and system. The method comprises the following steps: S1, establishing an energy collaborative network topology structure comprising a plurality of microgrid nodes; s2, constructing an energy balance model based on the real-time power demand, the new energy output prediction and the power grid dispatching instruction; s3, taking the minimization of the total operation cost of the multi-microgrid system as a target to form an optimization function; s4, an improved whale optimization algorithm is adopted to solve the optimization function, and an energy scheduling scheme of each microgrid in each time period is obtained; s5, regulating and controlling an energy storage device, a charging pile and an adjustable load in each micro-grid according to the energy scheduling scheme, and coordinating the energy flow direction and the transmission power between the micro-grids; and S6, monitoring the actual operation state and the energy interaction effect of each micro-grid, and when it is detected that the predicted deviation exceeds a preset threshold value, re-executing the steps S2 to S5 based on the real-time data. According to the invention, energy collaboration among multiple microgrids can be realized, the new energy consumption capability is improved, the operation cost is reduced, and the economy and stability of power grid operation are enhanced.

The invention relates to the technical field of power systems and energy storage, and discloses a new energy and pumped storage coordinated cross-time energy balance method and system. The method comprises the following steps: performing feature extraction and dynamic modeling on wind power output night monitoring data and solar waste heat power generation night monitoring data to obtain a new energy excess power prediction value; performing water level trend analysis and energy storage capability evaluation on the real-time water level data of the pumped storage upper reservoir and the watershed incoming water forecast data to obtain a pumped storage acceptance power upper limit value; performing power adjustment on the new energy power generation end based on a comparison result to obtain new energy actual output data; performing threshold judgment and response coefficient calculation on the supply-demand deviation value to obtain a demand side adjustment scheme; and performing dynamic planning optimization and constraint condition correction on the time-phased power data sequence to obtain a multi-energy collaborative power regulation instruction sequence covering the whole time period. According to the method, accurate response to new energy output fluctuation and efficient utilization of pumped storage resources are achieved.

The invention discloses an electric power system resource scheduling method and device, and belongs to the technical field of electric power systems, and the method comprises the steps: obtaining the resource data of an electric power system when the natural climbing amount of the electric power system is not greater than the climbing demand of the electric power system, and taking the minimization of the total operation cost of the electric power system and the maximization of the climbing service demand response as targets; constructing an objective function, a system power balance constraint, a transmission capacity constraint, an energy storage charging and discharging constraint, an energy storage energy balance constraint, a climbing ability constraint and a climbing service demand constraint; and solving the target function under each constraint to obtain the output of each thermal power generating unit and each energy storage system in each scheduling period and the up-climbing demand quantity and the down-climbing demand quantity of each flexible climbing price interval in each scheduling period, and scheduling the resources of the power system according to the solving result. By implementing the invention, the problem that the power supply and demand of the power system are unbalanced when the natural climbing amount is not greater than the climbing demand in the prior art can be solved, and the operation stability of the power system is improved.

The invention discloses a grid-connected control method and system based on a three-port energy router. The grid-connected control system comprises a photovoltaic power generation system, an energy storage system and a grid-connected inverter system, the photovoltaic power generation system adopts a perturbation and observation method and is used for performing photovoltaic maximum power generation; the energy storage system comprises a storage battery, adopts direct current bus voltage stabilization control, and is used for performing peak load shifting of energy and maintaining the direct current bus voltage; the preceding stage of the grid-connected inverter system adopts fuzzy VSG + pre-synchronization control so as to realize grid-connected and off-grid seamless following and provide voltage support; the post-stage of the grid-connected inverter system adopts double closed-loop + optimization compensation control, performs power regulation and control through weighted cooperation with a VSG double closed-loop system, and is responsible for long-term energy balance. According to the invention, photovoltaic maximum power tracking, energy storage charging and discharging coordination and grid-connected and off-grid seamless switching are realized, and the method is suitable for distributed power supply grid connection, a DC micro-grid and a novel power distribution system.

The invention provides a solar energy-radio frequency energy dual-driven low-altitude polarization switching dynamic power management system, and relates to the technical field of low-altitude flight. The system integrates a high-efficiency solar energy collection unit and a radio frequency energy collection unit with dynamic polarization adaptive switching capability, is assisted by a high-performance hybrid energy storage unit, and carries out unified coordination control through an intelligent power management unit. The radio frequency energy collection unit adopts a reconfigurable antenna technology, can sense the polarization characteristic of an environment radio frequency signal in real time, and dynamically switches the polarization state of an antenna to maximize the instantaneous energy capture efficiency; the intelligent power management unit executes a dynamic and collaborative energy flow scheduling strategy based on comprehensive analysis of solar irradiance, environment radio frequency spectrum and polarization characteristics, energy storage unit state, future energy income and expenditure prediction and real-time load demand; and the energy self-sustaining capability, the task endurance time and the working stability of low-altitude equipment in a complex and changeable environment are improved.

A method of real-time energy-tracking including: measuring the energy produced by an energy generator and the energy consumed by an energy consumer; collecting generated energy measurements and consumed energy measurements over a specified time period; receiving data packets containing these measurements along with associated temporal metadata, wherein by aligning the generated energy measurements with the consumed energy measurements based on this temporal data, the method creates matched sets of measurements, wherein for each matched set, it assesses the energy balance by comparing the generated energy to the corresponding consumed energy, thereby identifying any real-time energy deficit or excess.

The invention discloses a large-scale cruise ship water chilling unit pipe network cold storage intelligent energy-saving control method based on double-layer deep reinforcement learning, which comprises the following steps: 1, carrying out inherent cold storage engineering modeling on a chilled water pipe network of a water chilling unit to obtain an energy balance relationship between equivalent cold storage capacity and cold release sustainable time of the pipe network and bearable cold capacity; the relationship is used as a physical prior to introduce strategy learning and a security boundary; 2, constructing a double-layer deep reinforcement learning architecture; 3, a safety layer is additionally arranged in the double-layer deep reinforcement learning architecture, the safety layer cuts and projects output feasible regions of a target layer and a sublayer through a hard constraint and barrier mechanism, the water supply temperature, the temperature difference, the start-stop interval, the condensation temperature and the power change rate are ensured, and the maritime affair safety requirement is met; and 4, on the basis of a pipe network inherent cold storage model, a double-layer deep reinforcement learning framework and a safety layer, peak load shifting control of low-load cold charging-high-load cold discharging is achieved, and unit cold energy consumption of the water chilling unit is reduced.