148 results about "Energy balance" patented technology

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 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 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 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 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.

The invention discloses an intelligent calibration method and system for the electric quantity of an instrument, and relates to the technical field of electric energy metering of an electric power system.The intelligent calibration method comprises the steps that an electric meter network diagram with a main meter and sub-meters as nodes is constructed, and robust composite correlation indexes are calculated on the basis of reading increments in a sliding time window; the interference of common background load and instantaneous noise is suppressed by using a threshold clipping and main table purification mechanism, so that the depiction capability of the correlation graph on a physical connection relationship is improved fundamentally, and the phase to which the sub-table belongs can be identified more accurately in a stock area with unknown phase or incomplete topology; a graph neural network model is introduced based on the network graph, electric meter embedding representation with physical meaning is obtained through neighborhood information aggregation, phase grouping is achieved in combination with unsupervised clustering, split-phase energy balance loss is designed in the training stage, and the difference between the reading of a main meter and the sum of the reading of sub-meters in each phase group is used as a constraint. Alignment of the embedding space and the energy conservation relation is pushed in a self-supervised mode.

The invention provides a three-layer nested IES collaborative optimization method fusing semantic evolution and reinforcement learning, and belongs to the technical field of integrated energy system scheduling, and the method comprises the steps: constructing an IES mathematical model, an energy balance constraint and an optimization target, and abstracting a scheduling task into a Markov decision process MDP quintuple; building an ARDRL model containing a semantic knowledge layer, an evolutionary optimization layer and a distributed evaluation layer, generating a candidate reward function population through a large language model, and quantifying the fitness through Thompson sampling optimization and SAC intelligent agent distributed evaluation; and finally, carrying out iterative optimization by taking the fitness as feedback, and outputting an optimal reward function to guide IES collaborative scheduling. According to the method, a reward function does not need to be designed manually, the robustness and comprehensive performance of a scheduling strategy are improved, and economic, safe and low-carbon multi-target optimal balance is realized.

The invention provides a hydrogen-electricity hybrid energy storage capacity optimization method and device applied to an integrated energy system, and belongs to the field of integrated energy configuration optimization. The method provided by the invention comprises the following steps: adopting a self-adaptive time sequence compression algorithm to perform self-adaptive grouping, weighted fusion and iterative updating processing on annual original time sequence data of the integrated energy system, and compressing to obtain representative time sequence data; based on the representative time sequence data, constructing a capacity planning model, and solving to obtain a capacity pre-planning value of the system core equipment; the capacity pre-planning value is substituted into the original time sequence data, the capacity planning model is reused, the hydrogen energy storage capacity is checked and corrected through full-time sequence energy balance simulation, and the final capacity configuration of the system core equipment is obtained; and based on the final capacity configuration, simulating system operation, extracting an electric and thermal power unbalance residual sequence, extracting a residual fluctuation scene and a corresponding probability, respectively constructing independent optimization models of electric energy storage and thermal energy storage, and solving to obtain the optimal capacity of the electric energy storage and the thermal energy storage.

The invention relates to the technical field of photovoltaic power generation, in particular to a regional autonomous regulation and control method and system for distributed photovoltaic groups and user side energy storage. The method comprises the following steps: obtaining photovoltaic group output data and user side load data; performing energy balance evaluation according to the photovoltaic group output data and the user side load data to determine a regional energy gap; performing energy storage autonomous adjustment analysis based on the regional energy gap to obtain energy storage autonomous adjustment data; performing peak clipping and valley filling identification based on the energy storage autonomous adjustment data to obtain peak clipping and valley filling data; positioning an energy mutual aid path by using peak clipping and valley filling data; performing power grid stability detection based on the energy mutual aid path to obtain power grid stability data; predicting a critical instability state according to the power grid stability data; and adjusting energy storage parameters according to the critical instability state to obtain energy storage adjustment parameters. Based on the photovoltaic power generation technology, the energy dispatching precision and the power grid operation stability of the regional photovoltaic and energy storage system are improved.

The invention discloses a full-process control method and system for galvanization processing, and relates to the technical field of Internet of Things production control. The invention discloses a full-flow control system for galvanization processing. The full-flow control system comprises a data acquisition module, a micro-flow field observation module, a risk calculation module, a parameter decision module, a comprehensive optimization module and a data positioning module. According to the method, a physical information neural network containing electrochemical constraint and thermal-fluid conservation constraint is introduced into a CFD digital twinborn model, and assimilation is carried out on micro-flow field observation data, so that micro-flow field state and dynamic evolution prediction synchronous with a production line are obtained; on the premise of ensuring mass balance and energy balance, the physical consistency and precision of flow field reconstruction and prediction are improved, and credible flow field state representation is provided for defect risk assessment and control decision based on the micro-flow field.

The invention discloses a hybrid energy system optimization scheduling method and system considering carbon emission of a thermal power plant, and belongs to the technical field of power system optimization scheduling. The method comprises the following steps: firstly, acquiring operating parameters and carbon emission coefficients of a thermal power generating unit, renewable energy sources, electric energy storage equipment and an external power grid in the hybrid energy system, and establishing a system energy balance model and an operating cost model containing carbon emission constraints; then, a multi-objective optimization algorithm is adopted, operation economy and carbon emission minimization serve as optimization objectives, and an optimal scheduling scheme of the hybrid energy system is obtained; and finally, real-time control and dynamic adjustment are realized through a scheduling instruction issuing module. The system comprises a data identification module and a parameter distribution module. According to the method, on the premise that system safety and power supply reliability are guaranteed, the total carbon emission amount of the thermal power generating unit is reduced, the renewable energy consumption level is improved, and coordinated optimization of economic benefits and environmental benefits is achieved.

The invention relates to the field of comprehensive energy system optimization, in particular to a multi-park collaborative comprehensive energy system optimization method considering stepped carbon transactions. The method comprises the following steps: firstly, acquiring multi-source data including energy prices, carbon transaction rules, equipment parameters and park interaction limits; constructing a target function with the purpose of minimizing the total operation cost of the system, wherein the target function covers the energy purchasing cost, the stepped carbon transaction cost and the energy abandoning punishment cost; designing composite constraint conditions of energy balance, node constraint, multi-energy conversion, energy storage dynamics, carbon emission segmented pricing and inter-park energy interaction; and finally, solving and generating a multi-park cooperative operation scheme through a state optimization algorithm. According to the invention, through integration of a stepped carbon transaction mechanism and multi-park dynamic energy flow allocation, the problems of extensive carbon cost accounting and insufficient consideration of an inter-park energy complementation strategy in an existing method are solved, and collaborative optimization of economical efficiency and low-carbon performance is realized.

The invention discloses a partition optimization scheduling control method and system for an energy storage power station, and relates to the technical field of power grid load prediction scheduling, and the method comprises the following steps: constructing a multi-scale dynamic baseline of load data, carrying out the phase calibration of a short-time fluctuation signal and a long-term trend signal under a unified time coordinate, and obtaining a multi-scale dynamic baseline; generating a cross-scale coupling mapping matrix by using a time embedding operator based on a calibration result; and establishing a gradient phase tracking network based on the cross-scale coupling mapping matrix. According to the method, time alignment and self-adaptive correction of short-time fluctuation and long-term trend signals are achieved through a multi-scale dynamic baseline and gradient phase tracking mechanism, weight energy balance is kept, and prediction continuity and accuracy are remarkably improved. Meanwhile, a causal residual error playback chain and time scale self-folding mapping enable the model to have self-correction and self-stabilization capabilities, sub-models can be automatically split during phase resonance, multi-scale response coordination is ensured, and the stability and operation efficiency of power grid load prediction scheduling are improved.

The invention discloses an energy-saving and consumption-reducing method for a sewage treatment plant based on four-level diagnosis and three-level optimization, and aims to solve the problems of high energy consumption and high medicine consumption in the existing sewage treatment technology. According to the method, data such as water quality, water quantity and energy consumption in 3-5 years are collected through a five-level technology cooperation system of historical data quantitative diagnosis, equipment energy efficiency evaluation and updating, facility function detection and transformation, technological parameter simulation regulation and control and intelligent closed-loop control, and key indexes are checked to locate anomalies; evaluating and updating energy consumption equipment, and detecting and transforming a structure, a pipeline and an aeration system; technological parameters are optimized in combination with material / energy balance, simulation analysis and small-scale tests; a four-stage intelligent control system is built to realize closed-loop regulation and control; after application, the energy consumption and the chemical consumption are obviously reduced, and the sewage treatment cost is effectively reduced; meanwhile, it is guaranteed that the effluent quality stably reaches the standard, extra treatment cost and environmental protection risks caused by the fact that the water quality does not reach the standard are avoided, the operation economical efficiency and environmental protection benefits of a sewage treatment plant are comprehensively improved, and sustainable development of the industry is promoted.

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

The invention relates to the technical field of integrated energy system dispatching, in particular to an integrated energy system low-carbon dispatching method considering fuel gas hydrogen mixing and carbon transaction, which comprises the following steps of: constructing an integrated energy system model containing electric power, thermal power, natural gas and coupling equipment, and defining an electric hydrogen production process and an electric methane production process of power-to-gas equipment by the coupling equipment model; a fuel gas mixed hydrogen energy flow calculation model is constructed, a decomposition solution method is adopted for iterative convergence and dynamic calculation of a mixed fuel gas real-time heat value, and energy balance constraints are improved; constructing an optimal scheduling model considering the stepped carbon transaction, and taking the minimization of the total operation cost as a target; and applying hydrogen mixing proportion upper limit constraint, and cooperatively deciding power distribution and a hydrogen storage tank charging and discharging strategy through an optimization algorithm to solve a target function. According to the method, the energy flow calculation precision and the renewable energy consumption capability are improved, and collaborative optimization of system economy and environmental protection benefits is realized.

The present application proposes a multi-time scale based micro-grid multi-element energy storage collaborative optimization method and system, which takes the lowest life cycle cost as the core optimization target, considers the flexible adjustment ability of hydrogen energy storage system, electrochemical energy storage system and demand response, and constructs a multi-time scale micro-grid multi-element energy storage collaborative optimization configuration model; the first stage and the second stage constraint conditions of the micro-grid multi-element energy storage collaborative optimization configuration model are constructed; the improved column generation algorithm is used to solve the micro-grid multi-element energy storage collaborative optimization configuration model, and the optimal capacity configuration scheme and real-time operation optimization strategy of the micro-grid are obtained. Through multi-time scale modeling and two-stage collaborative optimization solution, the present application quantifies the internal correlation between multi-element energy storage configuration and micro-grid energy balance, significantly reduces the system operation cost, and takes into account the effectiveness and economy of the configuration scheme, thereby providing technical support for stable and efficient operation of the micro-grid.

The application discloses a kind of integrated protection self-healing function's power distribution network energy balance regulation and control method, comprising the following steps: S1, power distribution network system normal operation, energy manager acquires the data information of power distribution network system;S2, whether there is change in power distribution network system node load, if yes, enter step S3;If no, power distribution network system if fault enters step S4;If no fault, enter step S1;S3, whether there is fault in power distribution network system, if yes, enter step S4;If no, execute energy manager individual regulation strategy;S4, whether energy manager in power distribution network system adjusts switch position, if yes, adjust distributed power output, enter step S5;If no, carry out distributed protection self-healing system regulation;S5, power distribution network system restores balance.It is realized that energy balance regulation and control under normal operation condition of power distribution network system containing distributed power supply configuration and double-end power supply and self-healing system regulation and control under fault condition and energy regulation after fault self-healing.

The application discloses a kind of shore-based breeding sea sewage outlet nitrogen phosphorus dynamic flux calculation method, comprising the following steps: S1, obtain shore-based breeding pond basic breeding parameter, species basic information and field breeding pond water body index data, provide input data for subsequent calculation;S2, construct the energy balance model of the breeding species to be studied, input basic physiological parameters, environmental parameters and breeding basic data, construct individual energy input and output balance equation;S3, the energy dynamic numerical value output by energy balance model is converted into carbon flux by energy density constant, and carbon flux is converted into nitrogen flux and phosphorus flux;S4, construct the nitrogen and phosphorus balance calculation relationship of single pond mouth, calculate the nitrogen and phosphorus pollution dynamic discharge flux of single pond sewage outlet scale;S5, the model result is verified using the actual monitoring data of breeding pond sewage outlet, the fitting effect of calculated value and measured value is compared, and model parameter is corrected;The method can realize the accurate, dynamic calculation of nitrogen and phosphorus pollution discharge flux.

This invention relates to the field of waste-to-energy incineration technology and provides an artificial intelligence-based combustion control method for waste-to-energy boilers. The method includes: collecting data from a distributed control system, flue gas monitoring, and feed metering, aligning these data with a unified time frame, and generating combustion condition data; calculating drift residuals and missing rates, classifying and labeling them to obtain confidence weights; calculating equivalent lower heating value and moisture content from steam flow and feed flow based on energy balance, updating parameters only during the stable steam and carbon monoxide windows; identifying the equivalent time delay from control quantities to steam and emissions based on cross-correlation peak values, writing this information into the prediction model after stabilization, and performing shift compensation; constructing hard constraints for steam and emissions based on aligned predictions, writing confidence into the cost function, using MPC to calculate the feasible region, selecting incremental deployments within the policy network domain, and backing down and auditing for low confidence levels.

The invention provides an interconnected multi-energy micro-grid point-to-point energy transaction method and system considering energy transaction consistency, and relates to the technical field of energy transaction. The method comprises the following steps: constructing a system, and establishing system models including a point-to-point energy transaction model, an energy conversion equipment model and an energy storage equipment model; a system optimization target is determined, and a cost function is constructed according to the point-to-point energy transaction cost of the multi-energy micro-grid, the energy transaction cost of the external network and the environment cost; physical constraints are constructed, wherein the physical constraints comprise energy conversion constraints, energy storage constraints and energy balance constraints; modeling a complex optimization problem including a point-to-point energy transaction and energy conversion process as a partial objective Markov decision process, and introducing energy transaction consistency; and optimizing an energy transaction and conversion strategy of the interconnected multi-energy micro-grid by using an MASAC method. According to the invention, unreasonable energy transaction behaviors can be avoided, and the total operation cost of the system is reduced.

1. Name of this design product: Graphical user interface for energy consumption analysis of energy management system for electronic equipment. 2. Purpose of this design product: an electronic device. 3. The key design point of this design product lies in the interface content of the graphical user interface in the electronic device. 4. The picture or photo that best illustrates the key points of the design: main view. 5. Purpose of the Graphical User Interface: This Graphical User Interface is used to monitor and analyze energy consumption data. 6. Human-computer interaction mode of the graphical user interface: The main view is the energy balance analysis, and the energy consumption data is displayed in the form of a "balance tree". The user clicks the "Energy Flow Diagram" option icon in the main view, and the interface switches to the interface change state diagram. At this time, the energy consumption data is displayed in the form of an "Energy Flow Diagram".

The application discloses a green power and computing power cooperative optimization decision method and device, equipment and a storage medium, and relates to the technical field of green power and computing power cooperation. The method comprises the following steps: acquiring a green power output fluctuation interval and a computing power task quantity fluctuation interval; generating m candidate cooperative schemes based on the energy storage system charging and discharging constraint, the green power output fluctuation interval and the computing power task quantity fluctuation interval; calculating an energy balance adaptation coefficient, an energy storage characteristic adaptation coefficient, an economic adaptation coefficient, an environmental adaptation coefficient and a computing power adaptation coefficient for each candidate cooperative scheme; determining a matching value of each candidate cooperative scheme based on the energy balance adaptation coefficient, the energy storage characteristic adaptation coefficient, the economic adaptation coefficient, the environmental adaptation coefficient and the computing power adaptation coefficient; selecting a target cooperative scheme with the highest matching value from the candidate cooperative schemes; and making an optimization decision according to the target cooperative scheme. The method can improve the accuracy of the decision of green power and computing power cooperation.

The application relates to the technical field of electric energy distribution regulation, and discloses an intelligent manufacturing execution method for regulating and controlling rubber forming temperature, which comprises the following steps: collecting voltage and current data of a controlled thermal load loop power distribution side, determining instantaneous physical power and establishing an energy efficiency audit factor, using the factor to weight and correct physical energy values to construct a virtual thermal potential energy model representing a thermal enthalpy state, introducing an external mechanical load feedback signal and adjusting a thermal potential energy saturation threshold, identifying endogenous disturbance power in a controlled object by calculating energy deviation residuals, and adjusting output duty cycle parameters of power electronic power devices. The application converts lagging temperature feedback into electric energy flow integral control through a virtual thermal potential energy balance architecture, effectively eliminates the influence of power supply side voltage fluctuation and internal disturbance of a controlled object on energy balance, and improves electric energy utilization efficiency and controlled state robustness.

The invention discloses a transient power angle stability emergency control method and system based on an actually measured track and energy balance, and relates to the field of power system transient stability control, and the method comprises the steps: a fault detection station judges the fault condition of a power system, records the fault occurrence time and switch action information after the fault, and sends the information to a control decision station; the execution station sends the up-regulation amount and the down-regulation amount information of the active power injected into the power grid by the controllable equipment in the set control period to the control decision station, receives a control instruction and sends the control instruction to the controllable equipment; the control decision station receives related data information of the synchronous generator; and receiving information sent by the fault detection station and the execution station, generating a control instruction, and issuing the control instruction to the execution station. The acceleration kinetic energy and the deceleration kinetic energy of the synchronous generator are calculated in real time according to the power grid transient actual measurement data after the fault, the acceleration kinetic energy and the deceleration kinetic energy of the synchronous generator are restrained through real-time adjustment, real-time decision making and real-time control are achieved, and the adaptability and precision of transient power angle stability emergency control are improved.

The invention relates to the technical field of power electronics, and discloses a wide-range voltage regulation method, system and device based on frequency doubling circulation injection and a medium, and the method comprises the steps: building an improved bridge arm multiplexing type modular multilevel converter topological structure, presetting a multiplexing mode switching function, and setting an independent modulation strategy; and meanwhile, voltage regulation operation is carried out by representing double frequency circulation and bridge arm energy balance constraint conditions. According to the method, accurate expression of bridge arm voltage modulation waves is ensured in a mode of independent modulation of each bridge arm, a mathematical basis is provided for energy balance analysis, and a fixed modulation ratio meeting energy balance is deduced by taking bridge arm current in a non-circulating-current state as a reference. And further taking the deviation between the expected modulation ratio of the system and the fixed modulation ratio as a control quantity, determining a frequency doubling circulating current amplitude meeting energy balance, and performing injection control, so that the bridge arm multiplexing type MMC obtains the wide-range voltage regulation capability.

The invention discloses an intelligent prediction and migration regulation and control method for key indexes of a solid waste incineration system. According to the method, firstly, a hybrid expert model is constructed based on historical operation data of a reference incinerator, and soft physical constraints such as oxygen balance, total pollution load conservation and energy balance are introduced into model training in combination with a physical information neural network structure, so that the physical consistency of a prediction result is improved. On the basis, cross-plant migration is realized through a mode of field self-adaption, parameter fine tuning or plant vector embedding, so that the model can be quickly adapted under data distribution and operation characteristics of different incineration plants, and the high-precision prediction capability of multi-pollutant emission is kept. According to the method, a carbon-pollution collaborative comprehensive risk index is further constructed, and real-time quantitative evaluation of the environmental risk in the incineration process is achieved. According to the method, the key emission indexes of the solid waste incineration system can be stably predicted under the condition that the data size is limited, and an effective decision basis is provided for incineration working condition optimization and pollution control.

The invention belongs to the technical field of energy regulation and control, and provides an energy storage regulation and control decision method and system based on energy dynamic balance, and the method comprises the steps: constructing an energy storage equipment feature set, carrying out the numerical conversion of state features in the energy storage equipment feature set, and obtaining key energy storage features; the method comprises the following steps: constructing an equivalent state-of-charge model, an intra-day time-phased capacity measurement and calculation model and a system power model of an energy storage system, setting balance conditions of the energy storage system, and carrying out quantitative solution on key energy storage characteristics to obtain quantitative data of energy storage nodes; according to the quantized data and an energy balance grading rule, an alternative regulation and control scheme is determined through a multi-energy storage system regulation and control model; and setting regulation and control constraint conditions, constructing a regulation and control cost model of the energy storage system participating in the power grid, and screening the alternative regulation and control schemes to obtain an energy storage regulation and control decision scheme. According to the scheme, the regulation and control precision is effectively improved, the energy dynamic balance of the energy storage node network is realized, and the regulation and control effect is better.

An electric power and electric quantity balance optimization method for an electricity-gas coupling system under extreme disasters comprises the following steps: firstly, establishing dynamic association between a natural gas system and an electric power system through an electricity-to-gas device and a gas power plant, and building an electricity-gas coupling model; and secondly, aiming at climate resource fluctuation caused by disasters, combining a new energy output model and source-load characteristics during the disasters, utilizing natural gas energy storage to make up an electric quantity gap of new energy output, and ensuring source-load supply and demand balance of the power system. And finally, in combination with the predicted climate data and the load side power demand, establishing a pre-disaster-disaster-time (intra-day) multi-time scale scheduling strategy by taking the maximum generating capacity of the system as a target. According to the method, the advantages of electricity-gas coupling are utilized, resources are effectively scheduled before and after an extreme disaster event occurs, through a multi-time-scale scheduling strategy, the influence of the extreme disaster on the power system source-load supply and demand relationship is reduced, and the power and electric quantity balance of the system is ensured.