7188 results about "Generating unit" patented technology

The invention provides an intelligent detection method and system for the health state of a wind generating set in an intelligent wind field, and relates to the technical field of intelligent wind field multi-source monitoring. The method comprises the following steps: firstly, collecting multi-source operation data such as a transmission chain, structural parts and environment working conditions, and performing time reference unification; performing noise reduction, calibration, compensation and time window segmentation on the original data to form a preprocessed data set; extracting and aligning features in multiple domains to construct fusion feature representation; establishing a health baseline model based on historical normal samples and working condition variables to generate a self-adaptive alarm threshold value; inputting a health discrimination model to obtain an anomaly index, and generating an early warning event according to a trigger condition; and comprehensively fusing the features, the health base line and the judgment result to calculate a health index and output early warning information, thereby realizing accurate detection and risk early warning of the whole life cycle and the whole working condition.

The invention relates to the technical field of fault detection, and discloses a diesel generating set fault detection method and system based on deep learning, and the method comprises the steps: obtaining first vibration signal data, and carrying out the time-frequency decomposition, and obtaining a dynamic change feature; de-noising processing is carried out on the dynamic change features to obtain a time-frequency feature sequence; extracting a peak energy distribution data set, and calculating each frequency band entropy value to obtain a frequency band entropy value sequence; classifying the frequency band entropy sequence, determining a random fluctuation reference mode, and separating to obtain an abnormal frequency component; calculating a spectral line spacing and amplitude ratio, obtaining a spectral line feature data set, classifying the spectral line feature data set, and determining a fault classification result; obtaining current second vibration signal data, performing similarity calculation on the current second vibration signal data and a pre-established normal mode library, and outputting a fault feature vector; and verifying the fault feature vector to obtain a final fault detection result. According to the method, closed-loop diagnosis from signal acquisition to fault classification can be realized, and the fault detection precision of the diesel generating set is improved.

The invention discloses a fan blade state monitoring method based on multi-sensor fusion, relates to the technical field of wind power, and is suitable for wind energy prime mover equipment manufacturing and blade state monitoring technologies of onshore and offshore wind generating sets. The method comprises the following steps: acquiring operation data, a vibration signal, an acoustic signal and a pulse signal of a fan; the current working condition state of the fan is recognized, common-mode fault verification, local damage positioning and transient stress damage analysis are carried out on the vibration signals and the acoustic signals, and a fault analysis result and a first damage analysis result are obtained; performing phase-locked amplification analysis on the vibration signal and the acoustic signal through active excitation to obtain a second damage analysis result; and finally, a comprehensive state monitoring report of the fan blade is generated, so that the problems of difficulty in identification of weak damage and high false alarm rate of blades of land and offshore wind generating sets in wind energy prime mover equipment manufacturing under a non-stable working condition are solved, and the equipment operation and maintenance intelligent level in the wind energy prime mover equipment manufacturing industry is effectively improved.

The invention relates to the technical field of power system operation and control, and discloses a primary and secondary frequency modulation cooperative control system of a hybrid energy storage coupling wind generating set, which comprises a wind power generation unit, a hybrid energy storage unit and a central cooperative controller. A total power demand including inertia response and primary and secondary frequency modulation is synthesized, a primary and secondary frequency modulation cooperative distribution module generates a dynamic adjustment weight by using an S-type nonlinear function based on a frequency change rate and frequency deviation coupling relationship, and an energy relay compensation mechanism is introduced to fill a power gap in a switching process. And the SOC adaptive constraint and execution module applies direction selective boundary constraint to the state of charge, and controls hybrid energy storage to perform internal energy self-balancing in a frequency modulation dead zone. According to the invention, seamless connection of multi-time scale frequency modulation is realized, frequency secondary drop is effectively prevented, and the frequency support capability and the self-recovery capability of the system are improved.

The invention discloses a semi-submersible wave energy-wind energy integrated power generation platform and a damping regulation and control method of a damping regulation and control system of the semi-submersible wave energy-wind energy integrated power generation platform. The platform comprises a semi-submersible wind driven generator platform, a wind driven generator set, a wave energy power generation device, an energy storage system, a sea area detection system and the damping regulation and control system. The wave energy power generation devices are divided into two groups on the inner side and the outer side of the platform, each wave energy power generation device comprises a platform inner side wave energy power generation device and a platform outer side wave energy power generation device, and each wave energy power generation device comprises a swing arm floater, a universal hinge, a connecting arm and a damping adjusting module. The semi-submersible wind power generation device and the wave power generation device are combined, and offshore renewable resources are comprehensively utilized; the six-buoy design is adopted, buoyancy is dispersed, stability and safety are improved, and meanwhile space is provided for a wave power generation device; the floaters are symmetrically arranged in a hexagonal shape and carry a damping regulation and control system, and the whole structure is more easily stabilized by adjusting the damping of the floaters in all directions.

The invention discloses a dynamic monitoring method and system for settlement and inclination of a tower drum of a wind generating set, and relates to the technical field of safety monitoring of wind power generation infrastructure, the method comprises the following steps: synchronously collecting inclination data and positioning data of each monitoring point, and carrying out space-time alignment to obtain a fusion data set; decoupling the dynamic elastic response of the tower drum and the steady-state deformation of the foundation from the fused data through frequency domain analysis, and further calculating the overall inclination rate, the settlement amount and the non-uniform settlement rate of the tower drum; performing safety assessment based on the calculated parameters and a preset safety threshold, and determining a basic safety state and a risk mode; and finally, generating graded early warning information and decision information including risk positioning and trend prediction according to an evaluation result. Through the above mode, the method achieves the precise separation and monitoring of the dynamic deformation characteristics of the tower drum, improves the accuracy of safety evaluation and the timeliness of early warning, and provides an effective data support for the operation and maintenance decision of a wind generating set.

The invention discloses a network card adapter plate and a server system, and relates to the technical field of computers, the network card adapter plate comprises a power supply connector, a plurality of node connectors, a power supply and time sequence signal processing module and a plurality of network card connectors, the power supply connector is connected to a power supply board, the plurality of node connectors are respectively connected with different server nodes, and the power supply and time sequence signal processing module is connected with the network card connectors. The plurality of network card connectors are respectively configured to be connected with different interfaces of a network card; the power supply and time sequence signal processing module comprises a power supply enabling control unit, an electronic fuse and a main power supply time sequence signal generating unit; the power supply enabling control unit enables the electronic fuse to supply power to the network card when the hot plug-in condition is met and no hot pull-out operation exists; the power supply normal signal output end of the electronic fuse outputs an auxiliary power supply time sequence signal to the network card; and the main power supply time sequence signal generation unit outputs a main power supply time sequence signal to the network card when receiving the network card power supply normal signal and having no hot pull-out operation. According to the invention, hot plugging of the network card is realized in a multi-node sharing environment.

The invention discloses a wind generating set fault prediction method and system based on edge computing, and the method comprises the steps: collecting the vibration, temperature, rotating speed and other parameters of a wind generating set in real time through a data collection module deployed by edge computing equipment, carrying out the preliminary screening and packaging through a built-in data processing unit, and synchronizing to a constructed digital twinborn model; establishing an edge calculation fault analysis model based on model data, identifying potential fault features, comparing a physical unit operation state with a digital twin model simulation state parameter by parameter, performing preliminary diagnosis in combination with the fault features, evaluating a unit health state according to a fault mechanism model, and outputting a fault prediction result and part information. The system is correspondingly provided with six units including a data acquisition interaction unit, a data processing unit and a model construction updating unit, and all the units work cooperatively, so that accurate prediction and health management of faults of the wind generating set are realized.

The invention discloses a multi-energy-storage thermal power generating unit load prediction and optimal scheduling method and system, and relates to the technical field of multi-energy-storage thermal power generating units, and the method comprises the steps: collecting the operation parameters and external environment parameters of a thermal power generating unit in real time, and constructing a real-time state parameter matrix; constructing a load prediction model based on the historical state parameter matrix, importing the real-time state parameter matrix into the load prediction model, outputting a load trend prediction curve, and triggering an early warning signal through a secondary discrimination mechanism; identifying a load disturbance value based on the load trend prediction curve, obtaining a load disturbance sequence, and decoupling the load disturbance sequence into a plurality of components; inputting the plurality of vectors into a preset decision network, dynamically correcting a constraint condition built in the decision network in combination with the early warning signal, introducing an improved dragonfly algorithm for optimization iteration, and generating an optimization scheduling instruction; according to the method, the adaptability of optimal scheduling and high-precision prediction of the load trend are improved.

The invention discloses a bidding and incentive combined strategy optimization method, system and device for a source-load double-side peak regulation auxiliary service market, and a storage medium, and belongs to the technical field of electricity market transaction. The method comprises the following steps: constructing a load aggregator and thermal power generating unit-oriented double-market joint optimization model according to parameter data of a peak regulation auxiliary service market and an incentive demand response market; the double-market joint optimization model is formalized into a Markov decision process; constructing a multi-task multi-agent reinforcement learning training framework; and solving the multi-task multi-agent reinforcement learning training framework through an asynchronous training multi-task multi-agent flexible action-evaluation algorithm to obtain a load aggregator bidding and incentive optimal joint strategy and an optimal bidding amount and quotation strategy of the thermal power generating unit. According to the method, game behaviors among multiple market participants and joint decision behaviors of demand-side market subjects in double markets are considered at the same time, and the method is widely applicable to multi-task agent collaborative optimization in the electricity market.

The invention provides an AGC hydropower station intelligent control method based on multi-source data fusion. Constructing a control feature vector of the multi-dimensional feature; performing spatial-temporal feature modeling on the control feature vector, and extracting a time sequence dependency relationship between power grid load change and hydraulic dynamic response and a spatial coupling effect between units; establishing a multi-objective optimization function, and dynamically adjusting the weight coefficient of each objective through fuzzy logic according to the current working condition; a self-adaptive differential evolution algorithm is adopted to carry out on-line optimization on an active power distribution coefficient of a unit and PID parameters of a speed regulator, and the requirements of guide vane opening change rate constraint and water hammer effect avoidance are met. According to the method, multi-source heterogeneous data such as power grid, hydraulic engineering and equipment states can be effectively fused, multi-target dynamic optimization control is realized through the space-time attention model and the adaptive differential evolution algorithm, and the control precision, the response speed and the equipment operation safety of the hydropower station AGC system are remarkably improved.

Provided is a method of operating a hybrid power plant, including energy generating units including a wind park and at least one unit of another type of renewable energy source and including an energy storage system, the method including: creating a power production schedule based on an actual forecast of power production, an actual forecast of energy price and actual hybrid power plant status, the power production schedule including at least scheduled power for points in time in the future; and controlling, during the points in time in the future the energy generating units and the energy storage system based on the power production schedule, the hybrid power plant status at the points in time in the future, in particular energy storage system status, such as to dispatch power according to the power production schedule, but complying with any grid operator reference at the points in time in the future.

The invention discloses a feed pump closed-loop energy recovery system based on recirculation branch excess pressure driving, and relates to the technical field of energy recovery of a thermal power generating unit water supply system, a modular energy recovery assembly comprises a tandem type wide-area hydraulic turbine set which is formed by connecting a high-pressure micro-flow hydraulic turbine and a low-pressure large-flow hydraulic turbine in series, and the high-pressure micro-flow hydraulic turbine and the low-pressure large-flow hydraulic turbine are connected in series. Intelligent switching or cooperative work is carried out according to working condition requirements; the digital twinning intelligent control core comprises a prediction engine and a decision engine, the prediction engine identifies an operation mode through a behavior embedding vector and predicts a future state sequence, and the decision engine generates an optimal control instruction sequence through a strategy network subjected to optimal transmission theory regularization training. The system achieves cooperative control of the rotating speed of the water feeding pump and the opening degree of the recirculation valve by executing a control instruction, and triple closed-loop control of a data closed loop, an energy closed loop and a control closed loop is formed. The energy recovery efficiency is improved, the robustness of a control strategy is enhanced, and predictive maintenance is realized.

The invention relates to the technical field of electric power automation control, and discloses a coordinated control system for a generator set, which adopts an intelligent DCS integrated design architecture and performs real-time data interaction with a set decentralized control system through hard wiring or a communication protocol. According to the system, through deep fusion of a model prediction control algorithm and intelligent DCS integrated design, a boiler-steam turbine dynamic coordination model is constructed, and a control instruction is generated in real time in combination with a rolling optimization strategy. By means of the design, the main steam pressure deviation is controlled within + / -0.2 MPa, and the load response rate reaches 1.5% Pe / s and is improved by more than 40% compared with a traditional system. Particularly, under the working condition of deep peak regulation, by means of decoupling control over a fuel-air supply-water supply loop through a neural network algorithm, main steam temperature fluctuation (within + / -5 DEG C) and reheater spray desuperheating water quantity sudden change (the change rate is smaller than or equal to 10 t / min) are effectively restrained, the control quality of a unit under the conditions of variable loads and variable coal quality is remarkably improved, and the control efficiency of the unit is improved. And the high-standard requirement of the power grid on the AGC performance is met.

The invention belongs to the technical field of parameter identification, and provides a thermal power generating unit electro-hydraulic servo system PID parameter identification method and system, and the method comprises the steps: obtaining the historical operation data of a steam turbine, carrying out the preliminary screening of the data, and constructing a parameter identification data set; according to the mean square error between the actual value and the calculated value of the opening degree of the valve, an objective function of PID parameter identification of the DEH electro-hydraulic servo system is established; setting population initial parameters, and generating a chaotic initial population; based on a parameter identification data set and a target function, introducing an initial population value of the generated chaotic initial population into an improved Bayesian optimization model, and obtaining a preliminary optimization result through Gaussian modeling and kernel function prediction; and taking the preliminary optimization result as input, and utilizing a whale optimization algorithm introducing a Levy flight disturbance mechanism to carry out iterative search for multiple times to obtain a final optimization result. According to the invention, the parameter identification precision and robustness are improved.

The invention discloses a thermal power generating unit self-adaptive blending combustion method based on coal quality parameters. The thermal power generating unit self-adaptive blending combustion method comprises the following steps that S1, the coal quality parameters are obtained in real time; s2, digitizing the detected coal quality parameters, and inputting the digitized coal quality parameters into a system database; updating the digital twin model in real time based on the latest data; s3, dynamic characteristic analysis is carried out through a digital twinborn model, and the response of coal combustion is predicted; s4, generating a three-dimensional control matrix, and generating an optimal blending combustion proportion; performing dynamic compensation correction according to the real-time operation data; s5, issuing the optimized blending combustion instruction to a combustion system for execution; s6, the emission index and the combustion efficiency after combustion are monitored in real time; s7, carrying out deviation analysis on the collected operation data and an expected target; and S8, carrying out machine learning training on the actual blending combustion data and the theoretical model deviation. According to the method, the blending combustion proportion is dynamically optimized by generating the three-dimensional control matrix; the combustion boundary is predicted based on a transfer learning engine, rolling horizon optimization responds to deviation within 3 minutes, and it is ensured that pollutants do not exceed the limit.

The invention relates to the technical field of power grid operation and maintenance, and provides a generator set operation performance processing method and device, a generator set operation performance processing system, a readable storage medium and a program product. The method comprises the following steps: fusing a static parameter sequence, a historical operation data sequence, a real-time monitoring data sequence and an active disturbance test data sequence of the generator set to obtain a fused input vector sequence; according to the fusion input vector sequence and the generator set performance evaluation model, obtaining an operation performance prediction index value sequence; according to a set length time window and a set sliding step length, sliding on the operation performance prediction index value sequence to obtain a target operation performance prediction index value sequence; and determining a credibility first score, a drift statistic and a test statistic of each target operation performance prediction index value sequence so as to judge whether to correct or retrain the generator set performance evaluation model. By adopting the method, high-precision prediction of the operation performance of the generator set can be realized.

The invention relates to the technical field of generator set mixed bed operation monitoring, and discloses a fine processing mixed bed failure situation situation sensing system and method, the sensing system comprises a sampling tube, a sampling electric valve, a sampling isolation valve, a cation resin column, a conductivity meter, a mixed bed failure monitoring device and a resin regeneration system; the sampling pipe extends into the central axis of the fine treatment mixed bed; a plurality of sampling pipes are arranged along the height direction of the fine treatment mixed bed, are sequentially connected with a sampling electric valve and a sampling isolation valve, and then are connected in series to one end of a cation resin column; the other end of the cation resin column is connected with the conductivity meter; the mixed bed failure monitoring device is electrically connected with the sampling electric valve, the sampling isolation valve and the conductivity meter; and the resin regeneration system is connected with a water inlet pipeline and a water outlet pipeline of the fine treatment mixed bed through a fine treatment mixed bed resin inlet valve and a fine treatment mixed bed resin outlet valve respectively. Situation awareness of mixed bed failure is achieved by establishing a layered monitoring system, and long-term stability of water quality of a water vapor system of a power plant is guaranteed.

According to the electrical ship optimal scheduling strategy optimization method and related equipment provided by the embodiment of the invention, an electrical ship comprises a photovoltaic module, a plurality of generator sets and a battery energy storage system, and the method comprises the steps of obtaining a photovoltaic power function of the photovoltaic module based on operating environment parameters of the electrical ship in a sailing process; based on the generator set parameter of each generator set, the system state parameter of the battery energy storage system and the charging cost and the charging parameter of the electric ship at the port, obtaining an operation cost function; based on the sailing state parameters of the electric ship, the system operation parameters of the battery energy storage system and the photovoltaic power function, sailing scheduling constraints and energy scheduling constraints are obtained; based on the uncertainty of the photovoltaic power function and the charging cost, generating an uncertainty operation cost optimization model according to the operation cost function, the navigation scheduling constraint and the energy scheduling constraint; and the uncertainty operation cost optimization model is solved, an optimization decision is obtained, and the overall economy of the whole voyage of the electric ship is remarkably improved.

The invention discloses a fusion power generation system, a power generation control method, a storage medium and a controller, and relates to the technical field of fusion energy. The fusion power generation system comprises a steam generator set, a plurality of Tokamak devices and a plurality of thermal conversion units, the Tokamak devices and the thermal conversion units are in one-to-one correspondence, each thermal conversion unit is provided with a first channel and a second channel, and the Tokamak devices and the first channels of the corresponding thermal conversion units form a cladding cooling loop. The steam generator set and a plurality of second channels connected in sequence form a power generation loop; wherein the plurality of Tokamak devices are configured to operate in an alternating or complementary manner; the thermal conversion units are configured to receive heat from the corresponding cladding cooling loops and convert working media in the power generation loops into steam through the heat so as to drive the steam generator set to generate power. According to the system, the plurality of Tokamak devices operate in an alternating or complementary mode, so that heat loss can be reduced, the power generation efficiency is improved, and the plasma control difficulty is reduced.

This invention discloses a supercritical carbon dioxide cycle generator set water spray desuperheating system, comprising a supercritical carbon dioxide cycle power generation system and a water spray desuperheating system; the supercritical carbon dioxide cycle power generation system includes a heater, a screen-type superheater, a final-stage superheater, and a turbine; the water spray desuperheating system includes a first desuperheating water injection point, a second desuperheating water injection point, and a liquid-water separation system; the heater outlet is sequentially connected to the turbine inlet via the first desuperheating water injection point, the screen-type superheater, the second desuperheating water injection point, and the final-stage superheater; the turbine outlet is connected to the inlet of the liquid-water separation system; the liquid outlet of the liquid-water separation system is connected to the first and second desuperheating water injection points; and the gas outlet of the liquid-water separation system is connected to the heater inlet. This system can solve various problems caused by carbon dioxide desuperheating.

The invention relates to the technical field of generator set intelligent control, and discloses a generator set intelligent control method and system, and the method comprises the steps: obtaining the sensor data and vibration signals of a generator set; obtaining a corrected frequency characteristic value according to sensor data screening, denoising and frequency characteristic correction; generating and iteratively updating a control decision instruction sequence according to the real-time change of the vibration signal and the corrected frequency characteristic value to obtain a system stability index; and combining system stability index feedback adjustment to obtain a control decision reliability index. The method can solve the problem of noise interference under a dynamic working condition, realizes fault early warning, parameter optimization and system stability, and improves energy efficiency and operation reliability.

The invention discloses a multi-objective collaborative optimization control method for a new energy station and an energy storage system, relates to the technical field of new energy optimization control, and constructs a collaborative optimization framework with multi-time scale, multi-objective and multi-element deep coupling. The framework realizes joint optimization control of a wind power plant, a photovoltaic power station, an energy storage system and a conventional generator set through a whole process design of target modeling-scene adaptation-algorithm solution-closed loop execution. Formulating a source network storage dynamic interaction strategy based on scene self-adaption, and fully mining the adjustment potential of wind power, photovoltaic, energy storage and conventional generator sets; and solving a real-time optimal control distribution value by adopting a multi-objective optimization algorithm to form closed-loop coordination control. According to the method, the problems of poor adaptability and insufficient source network storage resource collaboration of traditional single target optimization are solved, the new energy consumption rate and the system stability are remarkably improved, and the operation cost is reduced.

The invention provides an analysis method and device for flow, efficiency and water consumption rate of a hydraulic power plant generator set. A distributed flow measurement unit based on a domestic PLC controller and a domestic operating system is constructed, and each unit is independently configured with the flow measurement unit to realize decentralization of data acquisition and processing; active power, guide vane opening, water head difference, instantaneous flow and volute inlet pressure data are collected in real time through a distributed flow measurement unit, and a unit efficiency and water consumption rate calculation model is dynamically fitted based on the data; sending an output result of the calculation model to a monitoring system through an anti-interference communication network, wherein the communication network adopts layered wiring and a double-shielded twisted pair to reduce the signal bit error rate; and the IMC integrated management and control platform is used for remote monitoring and diagnosis of the flow measurement unit, and seamless connection with a smart power plant data medium station is realized. The system reliability and the maintenance flexibility are improved, and the autonomous controllable requirements of domestic substitution and intelligent power plants are comprehensively met.

The invention relates to the technical field of generator state monitoring, in particular to a leakage detection method and system for an ORC generator set, and the method comprises the steps: firstly, synchronously collecting system key operation parameters and environment concentration data; then, matching the pressure value with a pre-generated and load-divided leakage-free reference model, and calculating a theoretical pressure value and a real-time deviation; and a three-dimensional state judgment matrix is innovatively constructed and applied to perform combined logic judgment on a pressure deviation level and an environment concentration level, so that step-by-step diagnosis from micro-leakage early warning to serious leakage alarm is realized. After the leakage is confirmed, the leakage rate can be estimated, and the possible leakage area can be positioned in an assisted manner. According to the method, early-stage, sensitive, automatic and intelligent detection and diagnosis of leakage of the ORC generator set are realized, and the operation safety and the maintenance efficiency of the set are remarkably improved.

The invention relates to a wind power blade hoisting load simulation analysis method which comprises the following steps: defining a plurality of simulation working conditions corresponding to a plurality of hoisting scenes according to a blade hoisting scheme of a wind generating set and the plurality of hoisting scenes; a multi-body coupling model established on the basis of a blade hoisting system is adopted, hoisting load simulation analysis is conducted on the basis of the multiple simulation working conditions, hoisting load data of the multiple simulation working conditions are obtained, and the multi-body coupling model comprises blades, a draught fan main engine, a hoisting tool and environment wind conditions. The invention further provides a wind power blade hoisting load simulation analysis device and a storage medium. The simulation analysis of the hoisting load of the wind power blade is realized, the load level of the blade and the whole machine in the hoisting process of the wind power blade can be evaluated, physical tests can be reduced, and the hoisting safety of the wind power blade can be enhanced.

The invention discloses an intelligent inspection system of a gas generator set, and particularly relates to the field of intelligent inspection, which comprises a multi-dimensional operation parameter real-time acquisition module, a data processing module, an equipment operation evaluation module, a dynamic adjustment module, a fault analysis module, a fault disposal and effect verification module and an equipment health trend prediction module. The multi-dimensional operation parameter real-time acquisition module is used for acquiring key operation parameters in real time in the operation process of the gas generator set by utilizing a multi-parameter sensor array; the data processing module is used for carrying out preprocessing and feature extraction on the collected key operation parameters; the equipment operation evaluation module is used for carrying out operation risk analysis according to the extracted equipment state characteristics and constructing a risk evaluation model; according to the method, comprehensive sensing of the running state of the gas generator set is achieved by deploying the multi-parameter sensor array, multiple dimension parameters are collected, deep feature extraction and analysis are carried out on each parameter, and the one-sidedness of traditional inspection is avoided.

The invention relates to the technical field of generator set mixed bed operation monitoring, and discloses an operation health degree monitoring method and system based on fine treatment mixed bed resin tracking, the monitoring system comprises a sampling tube, a sampling electric valve, a sampling isolation valve, a cation resin column, a conductivity meter, a mixed bed failure monitoring device and a resin regeneration system; the sampling pipe extends into the central axis of the fine treatment mixed bed; a plurality of sampling pipes are arranged along the height direction of the fine treatment mixed bed, are sequentially connected with a sampling electric valve and a sampling isolation valve, and then are connected in series to one end of a cation resin column; the other end of the cation resin column is connected with the conductivity meter; the mixed bed failure monitoring device is electrically connected with the sampling electric valve, the sampling isolation valve and the conductivity meter; and the resin regeneration system is connected with a water inlet pipeline and a water outlet pipeline of the fine treatment mixed bed through a fine treatment mixed bed resin inlet valve and a fine treatment mixed bed resin outlet valve respectively. Health degree monitoring is realized by establishing a layered monitoring system, and long-term stability of water quality of a power plant system is guaranteed.

The invention discloses an industrial park micro-grid optimization scheduling method based on electric furnace load active adjustment. The method comprises the following steps: constructing an economical operation objective function for generating power by using a thermal power generating unit to share blast furnace gas of a steel mill; dynamically adjusting the maximum exchange power between the micro-grid and the public grid by iterating the shrinkage constraint, and calculating a minimum feasible value to reduce basic electricity price expenditure; taking the gear of the electric furnace transformer as an adjusting variable, and constructing a load adjusting constraint model containing a fixed load and an adjustable load; the micro-grid adopts a double-bus topology, power mutual assistance is realized through a back-to-back converter, and a distributed power supply, an energy storage system and a new energy power generation set are configured. The method can efficiently utilize energy and reduce the operation cost; the public network expenditure is reduced by dynamically optimizing power exchange; the system flexibility is improved by flexibly regulating and controlling the load; new energy fluctuation is stabilized, and stability is enhanced; the double-bus structure realizes grid-connected and off-grid switching, improves reliability, and is suitable for iron and steel enterprises to improve the utilization rate of renewable energy sources and reduce operation cost.

The invention discloses a frequency modulation control method and system for a thermal power generating unit, and relates to the technical field of frequency modulation control, and the method comprises the steps: collecting a frequency modulation instruction signal of a power grid, decomposing the frequency modulation instruction signal, and obtaining a plurality of intrinsic mode function components and residual components; performing spectral analysis on each intrinsic mode function component, marking the component of which the main frequency exceeds a high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculating a fluctuation amplitude and a change rate; a thermal system control instruction is generated through a PID control algorithm, the coal feeding amount and the main steam pressure are adjusted, and an auxiliary compensation control instruction is generated for the high-frequency disturbance component through a fuzzy control algorithm; a thermal system control instruction and an auxiliary compensation control instruction are converted into operation parameters of a thermal power generating unit control mechanism and issued for execution, when the control effect deviation continuously exceeds a deviation threshold value, an optimization process is triggered, and the frequency modulation stability and the equipment safety of a unit in the environment that new energy is accessed to a power grid in a high proportion are remarkably improved.