520 results about "Load regulation" patented technology

The invention belongs to the technical field of power grid regulation and control, and particularly relates to a park-level adjustable load-oriented resource regulation and control method and system, and the method comprises the steps: formulating an initial energy scheduling scheme according to the predicted energy demand in combination with the output characteristics of distributed energy in a park and the load condition of a power grid; and training a load regulation and control strategy model by adopting a reinforcement learning algorithm based on the initial energy scheduling scheme, and generating a personalized load regulation and control instruction for each energy consumption unit. According to the scheme, the real-time energy consumption data of the plurality of energy consumption units in the park, the output characteristics of the distributed energy and the power grid load condition can be comprehensively considered, a scientific and reasonable energy scheduling and load regulation and control strategy is formulated, and efficient utilization and green low-carbon development of park energy are realized. Meanwhile, the method also needs to have the characteristics of data sharing, accurate prediction, intelligent scheduling, rapid response and the like so as to adapt to complex and changeable energy requirements and environmental protection requirements of the park.

The invention relates to the technical field of charging pile group load intelligent regulation and control, and particularly discloses a charging pile group load intelligent regulation and control method and system based on dynamic power equalization, and the method comprises the steps: collecting the oil temperature of a transformer in real time, calculating a total output power threshold value, and correcting the actual output power of a charging pile through combining the line loss and the equipment aging degree; a multi-dimensional load regulation and control decision matrix including user priority, equipment health degree and power regulation sensitivity is established, a dynamic power strategy is allocated through matrix weight, power allocation is inclined to high-priority users and health equipment, emergency power allocation and progressive readjustment during newly-added demands are supported, and the power regulation and control efficiency is improved. Impact of sudden power change on a power grid is avoided, system stability is ensured when newly added loads are accessed, refined intelligent regulation and control of loads of the charging pile group are finally realized, transformer safety, charging efficiency and user experience are improved, and power grid stability and resource optimization configuration are ensured.

The invention relates to a transformer area self-healing optimization control method and system based on flexible interconnection. The method comprises the following steps: S1, constructing an operation monitoring network based on equipment ledgers in a transformer area; s2, deploying flexible interconnection equipment at key nodes of a transformer area to realize fault isolation and power failure transfer, dynamic load transfer and voltage regulation, and flexible cooperative control of a distributed power supply and energy storage equipment; s3, introducing an equipment state evaluation model based on the transformer area operation data obtained by the operation monitoring network, and obtaining state evaluation and risk early warning of each equipment in the transformer area; s4, constructing a flexible interconnection dynamic topology management mechanism between the stations, and dynamically adjusting the interconnection topology between the stations according to the load transmission demand and the power supply condition; and S5, based on state evaluation and risk early warning of each device, performing load regulation and control and fault recovery according to a dynamic topology management mechanism of flexible interconnection. According to the invention, efficient and intelligent transformer area operation and power supply reliability improvement are realized.

The invention relates to the technical field of intelligent control, in particular to an intelligent power optimization scheduling method in a new energy grid-connected scene, which comprises the following steps of: acquiring a current load, a rated load, an adjustment rate and a temperature rise value through a data interface, and normalizing to generate a characteristic parameter matrix; the product of the adjusting rate and the temperature rise value is used for calculating the correlation degree with the aging factor to obtain an elastic weight, extracting the voltage stability and the weight, inputting the voltage stability and the weight into a Dijkstra algorithm to screen a path meeting the safety margin, monitoring the slope of an inertia change curve, adjusting a compensation coefficient through fuzzy PID control, and feeding back the compensation coefficient to correlation degree calculation. According to the method, multi-source parameters are fused through a rule tree structure, the load regulation rate and the aging factor weight are dynamically distributed, bus voltage stability and elastic weight path optimization are combined, a synchronous inertia margin safety correction system is constructed, the system response precision, the state cooperation efficiency and robustness are improved, local optimum is avoided, and the system reliability is improved. And the standby capacity configuration and the frequency advance correction capability are optimized.

The invention relates to a transformer area load regulation and control prediction method based on a multi-gating hybrid long short-term memory network. The method comprises the following steps: S1, obtaining historical power load data and influence factor characteristics which need to be considered and have influences on power loads; s2, constructing an input / output data set model; s3, constructing a core network composed of a plurality of LSTMs, wherein the core network is used for extracting periodic and uncertain feature data; s4, constructing a multi-gating unit network associated with the output task, and performing fusion output on the multi-dimensional features to obtain a load component prediction value; and S5, constructing and training a multi-gating hybrid long-short-term memory network prediction model, fusing different frequency load components, and adding a Huber normal form into a quantile loss function to correct a front-end model error to obtain a final power load prediction result. According to the invention, the power distribution area power load flexible resource credible regulation and control prediction precision can be improved.

The invention discloses an electric reactor load adjusting method and system based on electrical performance optimization, and relates to the technical field of power equipment control and optimization, and the method comprises the steps: carrying out the real-time monitoring of an electric reactor, and obtaining the monitoring data and load data; and obtaining an evaluation result through the three electrical performance evaluation channels, and judging whether an electrical performance evaluation constraint is met or not. If not, generating a first optimization strategy according to the load data and the evaluation constraint; and if yes, trend prediction is carried out based on the load data, and a second optimization strategy is generated in combination with the evaluation constraint. And finally, carrying out adaptive load adjustment on the reactor according to the first optimization strategy and the second optimization strategy. The technical problems that in the prior art, due to the fact that adjustment of an electric reactor cannot adapt to complex load changes, the adjustment precision of the electric reactor is low, and the electrical performance is poor are solved, and the technical effects of improving the adjustment precision of the electric reactor and optimizing the electrical performance are achieved.

The invention discloses a multi-effect rectification system control method and a control system thereof.The method comprises the steps that technological parameter data in a multi-effect rectification system are collected in real time, and the technological parameter data comprise the steam flow, the feeding flow, the reflux flow and the recovery quantity of each stage of rectification tower; the temperature and the pressure of each tower plate in each stage of rectifying tower are measured; for each stage of rectifying tower, acquiring static operation parameters of the rectifying tower in a set load section based on a full-automatic load regulation algorithm; the static operation parameters comprise the steam flow, the reflux quantity and the extraction quantity of each stage of rectifying tower; for each stage of rectifying tower, on the basis of the static operation parameters, dynamic operation parameters in the load change process are obtained through a load transition algorithm, and the multi-effect rectifying system is controlled according to the dynamic operation parameters. The method can automatically adapt to feeding change and production load adjustment, optimizes energy efficiency and product quality in the rectification process, automatically adjusts system parameters when the production load fluctuates, and realizes optimal control of energy efficiency and product quality.

The invention discloses an electric power collaborative operation method, system and device based on new energy and a medium, and belongs to the technical field of electric power collaborative operation, and the method comprises the steps: obtaining the real-time output data of a new energy access point and the demand data of a load node, and constructing a collaborative operation unit according to the topological information of a power grid; evaluating the load regulation capability of each cooperative operation unit in combination with the new energy access condition, and generating a first regulation and control instruction; when the new energy load regulation capacity in the cooperative operation unit is insufficient, a second regulation and control instruction is generated; the scheduling process is monitored in real time, the cooperative operation strategy is dynamically corrected according to the difference between the new energy output and the load demand, and the overall operation efficiency of the power system is improved. According to the method, the cooperative operation unit is constructed, new energy output prediction and load regulation capability evaluation are fused, local quick response and cross-regional intelligent cooperation of new energy fluctuation are realized, and the operation flexibility and new energy consumption capability of a power system are effectively improved.

The invention relates to the technical field of power conversion, and discloses an intelligent power converter system based on adaptive load regulation and a control method thereof. Comprising a power converter body, a plurality of sockets of different types are arranged on the power converter body, and a load sensing sensor, a micro-control unit, a step-down circuit and a bridge circuit are arranged in the power converter body; the load sensing sensor is electrically connected with the micro-control unit and is used for monitoring the power requirement of equipment connected with each socket in real time and transmitting a corresponding monitoring signal to the micro-control unit; the micro-control unit is electrically connected with the step-down circuit and the bridge circuit, and is used for controlling the step-down circuit and the bridge circuit to adjust output voltage and current according to a monitoring signal transmitted by the load sensing sensor; the micro-control unit controls the step-down circuit and the bridge circuit to automatically adjust the output voltage and current of the corresponding jacks according to the equipment power requirement monitored by the load sensing sensor, so as to realize the self-adaptive load adjustment of each jack.

The invention provides a power generation regulation and control method for a photovoltaic power generation system. The power generation regulation and control method for the photovoltaic power generation system comprises the following steps: S1, real-time monitoring and data acquisition: (1) various sensors are deployed in the photovoltaic power generation system, and solar radiation intensity data, photovoltaic module temperature data, cell panel output voltage data, current data and inverter output data are monitored in real time through the various sensors; (2) combining external meteorological data of environment temperature, humidity and air pressure to realize all-around system state acquisition; s2, maximum power point tracking (MPPT) and optimal load adjustment: (1) when the illumination condition changes, a multi-objective optimization algorithm is adopted, so that the working mode of the inverter can be adjusted in real time; the power generation regulation and control method for the photovoltaic power generation system has the advantages that the power generation efficiency of the photovoltaic system can be effectively improved, the stability and the reliability of the photovoltaic system are enhanced, and meanwhile the operation cost is reduced.

The invention discloses a high-load regulation and control method and system for a power distribution network, and relates to the technical field of power distribution network regulation and control, and the method comprises the following steps: obtaining first data of the power distribution network in real time, carrying out the dynamic partitioning of the power distribution network based on the first data, and generating a sub-region set; establishing a multi-time scale optimization model, and obtaining an optimal regulation and control instruction set by taking the sub-region set as a unit; executing the regulation and control instruction through a master-slave game coordination mechanism, and verifying a regulation and control effect; and when voltage out-of-limit or reverse power is detected, rolling correction is triggered, and constraint conditions of the optimization model are updated. According to the method, communication delay of centralized regulation and control and global mismatch of distributed regulation and control are avoided through a master-slave game mechanism, when voltage out-of-limit or reverse power is detected, distributed power supplies with high influence nodes are preferentially adjusted based on voltage-power sensitivity sorting, and robustness and economical efficiency of a power distribution network in a high-fluctuation scene are improved.

A load control device for regulating an electrical load includes: a support component including a connection portion; a knob frame including a gripping portion and an elastic portion, the gripping portion at least partially surrounding the support component and configured to drive the knob frame to rotate in response to a rotational force acting thereon, the elastic portion configured to move toward the connecting portion in response to the knob frame moving in a first direction, thereby undergoing elastic deformation; a first circuit board component; a switch trigger component; a switch component coupled to the first circuit board component, for controlling the load in response to triggering and releasing the triggering from the switch trigger component; and an adjustment component coupled to the first circuit board component, for adjusting the load in response to the rotation of the knob frame. The load control device simultaneously realizes rotation and pressing functions of the knob frame. A system including the load control device is also disclosed.

A load control device for regulating an electrical load includes: a support component including a connection portion; a knob frame including a gripping portion and an elastic portion, the gripping portion at least partially surrounding the support component and configured to drive the knob frame to rotate in response to a rotational force acting thereon, the elastic portion configured to move toward the connecting portion in response to the knob frame moving in a first direction, thereby undergoing elastic deformation; a display assembly disposed on a side surface of the knob frame facing away from the support component; a circuit board component disposed adjacent the display assembly; a switch component disposed on the circuit board component, for controlling the load in response to triggering and releasing the triggering; a switch trigger component for applying the triggering and releasing the triggering to the switch trigger component; and an adjustment component for adjusting the load in response to the rotation of the knob frame. The load control device allows for a more flexible arrangements of the switch trigger component, and makes the structure more reliable. A system including the load control device is also disclosed.

The invention discloses a dynamic load regulation-based DC charging pile power optimization device and optimization method, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining electric energy quality data through extracting a voltage deviation and a total harmonic distortion rate, outputting a prediction value of the electric energy quality data through an electric energy quality prediction model, and calculating a deviation rate; constructing a regional charging network, inputting the regional charging network into the multilayer graph attention network, and outputting a regional electric energy quality evaluation value; a time dimension weight vector is calculated based on the deviation rate, a space dimension weight vector is calculated based on the regional power quality evaluation value, an adaptive weight vector is calculated according to the time dimension weight vector and the space dimension weight vector, a reinforcement learning model is constructed, and an optimal strategy is obtained; the optimal strategy is executed, the actual charging power and the actual charging time period are collected, the total charging amount, the total charging demand, the charging demand response rate and the charging expenditure are calculated and fed back to the reinforcement learning model, the reinforcement learning model is continuously optimized, and the electric energy quality is improved.

The invention discloses an intelligent monitoring and regulation system for a power transformer, and relates to the technical field of intelligent monitoring and regulation of power transformers. Comprising an initial automatic regulation module, a data acquisition and transmission module, a data preprocessing and feature extraction module, a feature analysis and prediction module, a load classification module, a conventional load regulation and control module and a high-frequency load adaptive regulation and control module. Load data are collected in real time through the Internet of Things, the load change type is predicted through machine learning, and for a conventional load, the initial frequency is kept to reduce abrasion; for a high-frequency load, the frequency of the tap switch is adaptively increased, rapid response of the transformer is ensured, and equipment faults caused by unstable voltage are avoided, so that efficient operation of the transformer is ensured in different load scenes, the overvoltage or undervoltage risk is reduced, reliable power supply is provided for industrial equipment and a medical system, and the stability and safety of a power grid are improved.

The invention discloses a power distribution method and device for an urban power grid, a medium and equipment, and belongs to the field of power distribution.The method comprises the steps that firstly, electric heavy truck, air conditioner and resident load data of all parks in the urban power grid are collected in real time, and the charge state, power capacity and power grid time-of-use electricity price information of shared energy storage are synchronously obtained; and then inputting the data into a double-layer flexible resource-shared energy storage decision model obtained by'historical data + income maximization 'training, and cooperatively optimizing upper-layer energy storage economic benefits and lower-layer multi-park flexible resource utilization under power coupling constraint through mixed integer programming. Outputting a charging and discharging power distribution instruction of shared energy storage and a flexible resource regulation and control instruction of each park; finally, energy storage charging and discharging and park load adjustment are controlled in a closed-loop mode according to the instruction, accurate, real-time and economical distribution of urban power grid power is achieved, and the problem that in the prior art, optimal adjustment of a power grid cannot be achieved with economic maximization as the target is effectively solved.

The invention provides a deep intelligent coordination method for a thermal power generating unit, which comprises the following steps of: acquiring and preprocessing data, introducing a coefficient based on coal quality analysis and dynamically adjusting in a dry state coordination optimization stage, calculating and adjusting the coal feed quantity and the feed-forward quantity of the water feed quantity according to the conditions of the unit and a power grid by combining predictive control and an intelligent feed-forward technology, and improving the load adjusting capability. In the wet-dry and dry-wet conversion steps, the water level of a separator, steam and feed water flow are continuously monitored, conversion is triggered according to set conditions, equipment such as a feed pump is coordinated to act, and stable conversion is guaranteed. During wet state coordinated optimization, the water level of the separator and the feed water flow are stabilized by using a PID or intelligent algorithm, main steam pressure and load are adjusted by using model predictive control and the like, and meanwhile, a wet state characteristic and an equipment limitation constraint instruction are considered. According to the method, the intelligent coordination level of deep peak regulation of the thermal power generating unit is comprehensively improved, and the operation efficiency, stability and flexibility of the unit are enhanced.

The invention discloses a method for optimizing the AGC load regulation rate of a power station, and the method comprises the steps: building a digital twinborn body of a unit, building a boiler thermal positive and negative balance model, a fuel heat value prediction model and a self-adaptive control parameter library based on the historical operation data of a target unit, and receiving and processing the operation data of the unit in real time; dynamically predicting a boiler theoretical calorific value demand corresponding to the AGC instruction by using a long-short-term memory recurrent neural network, and calculating a deviation between an actual calorific value and a theoretical calorific value; when the deviation exceeds a preset threshold value, multi-mode cooperative compensation control of feed-forward compensation, parameter self-tuning and energy closed-loop calibration is implemented in parallel; the AGC instruction response time is controlled within 50-55 seconds, and model self-updating is achieved through online tracking. According to the method, the defects that traditional thermal power station fuel calorific value calibration is slow in response, a single control model is difficult to deal with complex problems, AGC response time is long and the like are overcome, the power station AGC load regulation rate and thermal power generating unit frequency modulation performance are remarkably improved, and power grid frequency stability is guaranteed.

The invention relates to the technical field of deep learning, in particular to an airport charging pile load management method and system based on load prediction and a medium. Acquiring a current load data set in the airport power grid; inputting the current load data into an improved particle swarm algorithm-long short-term memory neural network model, and predicting predicted load data in a future preset time period, the improved particle swarm algorithm including an adaptive Cauchy variation mechanism; determining a plurality of charging pile load management strategies of the airport according to the predicted load data; on the basis of an improved raccoon optimization algorithm, an optimal charging pile load management strategy in the multiple charging pile load management strategies is determined, and the improved raccoon optimization algorithm comprises a first-time improved search strategy; and carrying out load regulation and control on each charging pile in the airport based on the optimal charging pile load management strategy. The objective of the invention is to solve the problems of how to predict load changes of different power utilization systems in an airport in advance and how to optimize and adjust the load state of an electric vehicle charging pile system in a transformer substation.

The present invention relates to a virtual power plant load regulation method, device and medium, belonging to the field of virtual power plant load regulation technology, comprising the following steps: obtaining load instruction data of the virtual power plant; determining the load resource scheduling cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant based on the load instruction data; constructing a load instruction decomposition objective function of the virtual power plant with the goal of minimizing the load resource scheduling cost, demand response capacity deviation penalty, and load response willingness and reliability equivalent cost of the virtual power plant; formulating constraints corresponding to the load instruction decomposition, solving the load instruction decomposition objective function based on the constraints to obtain the load regulation instruction of the virtual power plant; and regulating the load of the virtual power plant according to the load regulation instruction. The present invention can achieve the goal of reducing the operating expenses of the virtual power plant while meeting the load demand.

The invention discloses a rapid load adjusting system of a steam turbine generator unit, and relates to the technical field of control of steam turbine generator units of thermal power plants. The system comprises a condenser, a circulating water input pipeline, a circulating water output pipeline, a steam turbine generator unit, a fin type heat exchanger, a cooling medium storage tank, a cooling medium conveying pipeline, an automatic temperature control flow regulating valve, a first temperature detector, a second temperature detector, a telecontrol terminal unit, a unit actual power detection mechanism and a DCS control device. The fin type heat exchanger is integrated in the circulating water input pipeline, the input end of the cooling medium conveying pipeline is connected with the output end of the cooling medium storage tank, the output end of the cooling medium conveying pipeline is connected with the fin type heat exchanger, and the automatic temperature control flow regulating valve is installed on the cooling medium conveying pipeline. Through the arrangement, the load response speed of the steam turbine generator unit under the severe working condition can be effectively improved on the premise that the complexity and the cost of the system are not obviously increased.

The invention belongs to the technical field of emergency power supply systems, and particularly discloses a diesel generator load regulation method and system based on dynamic load regulation, and the method comprises the following steps: obtaining the power generation output quantity of wind power and solar power generation, collecting the real-time load power demand, and obtaining the power generation output quantity of the wind power and solar power generation; judging whether the real-time generating capacity of wind power and solar energy meets the real-time load electricity demand or not, predicting the load electricity demand and the generating capacity of wind power and solar energy, and determining a stability index of the electricity utilization system according to the real-time load electricity demand and the predicted load electricity demand; determining the initial load of the diesel generator according to the real-time load electricity demand, the stability index and the generating capacity of wind power and solar energy; and establishing a target function, and scheduling the diesel generator based on the predicted load electricity demand and the initial load. By adopting the technical scheme, the power output of wind energy, solar energy and diesel generators is flexibly dispatched, and the energy source is timely adjusted according to the dynamic change of the load.

The utility model discloses a flexible load regulation and control framework based on a three-port flexible multi-state switch. The flexible load regulation and control framework comprises the three-port flexible multi-state switch, a first power grid module, a second power grid module and a third power grid module, the first power grid module, the second power grid module and the third power grid module are electrically connected with one another through a three-port flexible multi-state switch; the three-port flexible multi-state switch at least comprises a state A, a state B, a state C and a state D; in the A state, the first power grid module, the second power grid module and the third power grid module are mutually independent; in the B state, one power grid module in the three power grid modules is independent, and the other two power grid modules are in bidirectional power flow transfer connection; in the C state, two power grid modules in the three power grid modules are connected with the other power grid module in a tidal current transfer mode; in the D state, one power grid module in the three power grid modules is connected with the other two power grid modules in a tidal current transfer mode; and the power flow regulation and control flexibility and flexible load power supply reliability of the power distribution network are improved.

The invention belongs to the technical field of power systems, and discloses a thermal power generating unit coordinated variable load control method and system based on unit energy storage, and the method comprises the steps: constructing an energy storage quantification model and a steam turbine energy conversion model according to an energy storage unit and a conversion unit, the total energy storage capacity of the thermal power generating unit thermodynamic system is calculated in combination with a weighted summation method; calculating an energy storage regulation factor of the thermal power generating unit based on the real-time energy storage state, the regulation sensitivity and the efficiency factor, and determining the regulation priority of the thermal power generating unit according to the energy storage regulation factor; and solving a load distribution scheme satisfying collaborative optimization of coal consumption, equipment loss and tracking precision by using a multi-objective optimization algorithm, and executing load distribution through a hierarchical control architecture. According to the method, the load adjusting capacity of the thermal power generating unit can be effectively improved, coal consumption increase and equipment loss caused by load fluctuation are reduced, meanwhile, the economical efficiency and safety of unit operation are improved, and powerful support is provided for stable operation of a modern power grid.

The invention relates to the technical field of power electronics, and discloses a multi-isolation output expansion circuit of an auto-excitation type Buck converter and the auto-excitation type Buck converter, and the multi-isolation output expansion circuit comprises a first switch tube which is connected in parallel with two ends of a fly-wheel diode; the multi-winding transformer comprises a primary winding, a first secondary winding and a plurality of second secondary windings, the primary winding is configured as an output filter inductor of the self-excited Buck converter, the first secondary winding is configured as a driving winding of the first switching tube, and the second secondary windings are configured as an isolation output end of the self-excited Buck converter; and the first capacitor is configured to form a reverse follow current channel with the first switching tube under the condition that the energy storage of the multi-winding transformer is insufficient, so as to provide energy for the multi-winding transformer. According to the invention, a plurality of isolated output ports are easy to expand, and the voltage of the isolated output ports is stabilized, so that the load regulation rate of the converter is improved.

The invention relates to the technical field of charge and discharge control, in particular to a V2X charge and discharge cooperative control system based on dynamic multi-objective optimization, which comprises a voltage characteristic identification module, a response capability evaluation module, a scheduling matching mapping module, a task load distribution module and a cooperative regulation and control judgment module. According to the method, rapid adaptive response data acquisition in a voltage regulation dead zone is realized through multi-node transient voltage response identification, a synchronization vector is constructed by using response time, an instability characteristic and a precision grade, vehicle synchronization capability is normalized and measured, and dynamic scheduling layering of multiple vehicles is realized by constructing a difference sorting mechanism in combination with regulation tolerance. A regulation and control mapping relation is established according to a task load regulation rate, consistent matching and dynamic adaptation of vehicle scheduling and load change are realized, the adaptation capability of a vehicle energy response behavior to a dynamic demand of a power grid is remarkably improved, a coordinated discharge task under multi-target constraint is met, and the problems of time lag and unbalanced response are reduced.

The invention provides a comprehensive energy self-adaptive scheduling method based on meteorological prediction, and aims to solve the problems that an existing energy system lags in response to meteorological disturbance and is insufficient in load regulation precision, and the comprehensive energy self-adaptive scheduling method comprises the following steps: fusing second-level meteorological disturbance data, electrical load power data, energy storage device charge state data and power grid boundary power flow data; constructing a disturbance response feature set, and establishing a time correlation mapping structure between a disturbance variable and a load variable; according to the method, a disturbance trend is predicted based on a mapping structure, an index set of disturbance direction, intensity and sensitive sections is formed, a dynamic regulation capability vector is generated in combination with a current load state, a scheduling optimization model meeting multiple operation constraints is constructed on the basis, a cooperative control strategy set is output, and the dynamic regulation capability vector is obtained. Finally, the control strategy is converted into a control instruction, the control instruction is accurately acted on a power generation device, an energy storage device and a load device, second-level dynamic self-adaptive scheduling of the comprehensive energy system on meteorological disturbance is achieved, and the system response capacity, stability and energy utilization efficiency are improved.

The invention discloses a power grid load optimization regulation and control method and system, and the method comprises the steps: constructing a self-adaptive prediction module, an intelligent regulation and control system and a power failure risk assessment module, and enabling the self-adaptive prediction module to carry out the dynamic prediction of the operation state of a power grid based on the current state data of a power grid system, and generating a target load regulation and control strategy of the power grid; the intelligent regulation and control system generates an updated state reward value according to the target load regulation and control strategy and a state reward function used for evaluating load balance of the power grid, and regulates and controls the power grid according to the target load regulation and control strategy when it is judged that the updated state reward value is smaller than a reward value threshold value; and the power failure risk assessment module is used for identifying different operation modes of the power grid, assessing power failure risks in the modes and feeding back the power failure risks to the adaptive prediction model so as to continuously optimize the regulation and control strategy. According to the invention, the problems of untimely monitoring, slow regulation and control response, rigid scheduling strategy and the like of stable section management during the power failure of the power grid in the prior art are solved, the reliable operation of the stable section during the power failure of the power grid is ensured, and the efficiency and flexibility of power grid scheduling are improved.

The invention discloses a freezing plant load carbon emission reduction potential evaluation method fusing TimesNet and PatchTST, and belongs to the technical field of power system regulation and control, and the method comprises the steps: predicting a carbon emission factor corresponding to unit power consumption per hour based on multi-dimensional time sequence characteristics; constructing a load regulation capability prediction model to obtain the maximum load up-regulation capability and the maximum load down-regulation capability under the permission of the equipment boundary and the process constraint; based on the carbon emission factor and the maximum load up-regulation capability and down-regulation capability, establishing a load carbon emission reduction potential evaluation model, and outputting a carbon emission reduction potential; according to the load carbon emission reduction potential evaluation method, through a freezing plant load kilowatt-hour electricity carbon emission factor prediction method based on TimesNet, the capability of capturing multi-time scale periodicity and trend is fully utilized, and power grid carbon emission data and a regional load structure are combined, so that dynamic prediction of carbon factors is realized.

The utility model discloses a peak regulation and capacity increase system suitable for a supercritical unit, which is characterized in that excessive heat energy and electric energy are stored in fused salt through organic fusion of a steam-fused salt energy storage technology and an electric heating fused salt energy storage technology in the off-peak period of a power grid, and the generated output of a thermal power generating unit is reduced; and in the peak period of the power grid, the stored high-temperature fused salt is used for generating supercritical parameter steam, and the supercritical parameter steam and steam generated by the boiler enter the steam turbine together to do work through expansion, so that the power generation power of the unit is improved. The bidirectional load regulation of the supercritical thermal generator set is realized, and the flexibility of the set is greatly improved. The system disclosed by the utility model not only can reduce the power generation output of the unit in a low-load stage, but also can increase the peak capacity of the unit in a high-load stage, has double effects of downward peak regulation and upward capacity increase, is an important regulation technology for a future high-capacity thermal power generating unit, particularly a supercritical unit, and has a wide application prospect. The method plays an important role in construction of a novel power system.