19 results about "Load margin" patented technology

The invention discloses a new energy automobile dynamic charging power adjustment method considering a power grid load, and aims to solve the problems of power grid overload and non-fine regulation and control caused by concentrated charging of new energy automobiles. The method is executed by a regional charging coordination server and comprises the following steps: acquiring a real-time load value and a safety threshold value of a target line of the power distribution network; collecting real-time charging aggregation data of each charging station in the jurisdiction, wherein the real-time charging aggregation data comprises the power of each charging pile and the state of charge of a vehicle battery; calculating the load margin of the power grid and determining the total charging power needing to be adjusted; the charging urgency degree coefficient of each charging pile is calculated based on the state of charge of the vehicle battery, the total adjustment amount is distributed to each charging station according to the coefficient and the total power of the charging stations, and the initial power adjustment amount is generated; according to the invention, the real-time, collaborative and refined regulation and control of the charging load from the global perspective of the power grid is realized, under the premise of ensuring the safe operation of the power grid, the highly urgent charging demand is preferably met, and the resource allocation and user experience are optimized.

The embodiment of the invention provides a control method, device and equipment for low-voltage side switching equipment of a main transformer, a storage medium and a program product. The method comprises the following steps: acquiring a first current in a switch loop of first switch equipment; in response to the first current greater than or equal to the target safety current, determining at least partial load according to the first current and the target safety current; transferring at least part of the load of the first switching device to at least one second switching device, the second switching device having a load margin; the first switch device and the second switch device are power distribution control devices running in parallel on the low-voltage side of the main transformer; the target safety current is determined according to the historical measurement current of the switch loop and the historical measurement temperature under the historical measurement current. The method is used for improving the control accuracy of the low-voltage side switch equipment of the main transformer.

This invention relates to the field of energy storage compartment charging control technology, and discloses an optimal charging control method, device, system, and storage medium for energy storage compartments. The invention constructs a multi-objective optimization model by integrating electricity price data and equipment operation data, iteratively solves for the optimal charging power reference value, and dynamically calculates the load margin based on the total transformer capacity and average load, switching to the transformer with the largest margin to effectively balance the load distribution of each transformer. This avoids the operational risks of overloading some transformers, fully utilizes idle transformer capacity, and improves the utilization rate of grid-side resources. Simultaneously, with the goal of minimizing charging costs and equipment lifespan losses, it achieves dual optimization of charging economy and equipment operating efficiency.

The application discloses a kind of based on real-time bearing capacity state of electric vehicle distribution network light storage and charging resource inner day rolling self-adaptive scheduling method, system, equipment and storage medium, it is related to distribution network optimization scheduling and operation control technical field, including in each rolling time of inner day scheduling, on-line evaluation distribution network to electric vehicle charging load dynamic accommodation space, based on dynamic accommodation space generation real-time can add charging load margin index;According to the state of safe interval where real-time can add charging load margin index is located, drive scheduling decision to carry out autonomous switching between scheduling mode;Solve the scheduling instruction sequence under the scheduling mode after switching and execute the scheduling instruction of current rolling time, after a scheduling step is ended, time window is promoted and system state is updated.The method disclosed in the application significantly improves the upper limit of physical safety defense of new distribution network, operation flexibility and the physical stability of closed-loop rolling control.

The invention discloses an electric power system static voltage stability prevention and control method and device, terminal equipment and a storage medium, and belongs to the technical field of electric power system stability control, and the method comprises the steps: obtaining the current generator active output, terminal voltage, reactive compensation, line load, node voltage and node power of an electric power system; inputting the active output, the terminal voltage, the reactive compensation and the line load of the generator into a preset load margin prediction model constructed based on a convex neural network to obtain a first load margin prediction value; inputting the first load margin predicted value, the node voltage and the node power into a preset voltage stability control model to obtain a current control decision parameter of the power system; and finally performing voltage stability control on the power system according to the control decision parameter. By implementing the method, the problems of complex calculation and low solving efficiency of a method for formulating a control strategy by iteratively solving non-convex nonlinear constraints in the prior art can be solved.

The present disclosure relates to a wind turbine load shedding control method and device, the method comprising: obtaining operation data of each load channel of a wind turbine; generating a load margin corresponding to each load channel based on a measured load value and a load limit value in the operation data, determining a load channel to be shed and a corresponding load shedding demand from the load channel based on the load margin; calculating a residual execution capability and a channel credibility of each control channel of the wind turbine, and determining a set of available control channels based on the residual execution capability and the channel credibility; determining a control increment of a target control channel; and controlling the target control channel of the wind turbine based on the control increment to shed the load of the load channel to be shed. The risk of excessive power loss of the execution mechanism can be reduced, and the balance of the load shedding effect can be maintained by determining the set of available control channels and the corresponding control increment to allocate the load shedding demand, thereby improving the operation safety and load control stability of the wind turbine.

This application discloses a method, system, and medium for orderly charging scheduling of electric vehicles based on power nodes, relating to the fields of smart grid and charging facility management technology. The method includes: obtaining the real-time total load power of a substation, calculating the real-time load margin of the substation, and when a charging device requests to connect for charging, determining the target power of a first target charging device based on the real-time load margin of the substation and the requested access power of the charging device; when no charging device requests to connect for charging, but the real-time load margin of the substation is greater than or equal to a set threshold, and a charging device is in a power derating state, determining the target power of a second target charging device based on the real-time load margin of the substation, and subsequently issuing power scheduling instructions to complete orderly charging scheduling. This application can efficiently meet the growing charging demand while ensuring grid security.

The invention discloses a multi-oil-pump dynamic control system and method, and the method comprises the steps: calculating the power demand increment of oil pump control nodes according to the real-time operation state data of the oil pump control nodes, and marking the oil pump control nodes of which the power demand increment is a positive value as to-be-enhanced nodes; according to the real-time operation state data of the oil pump control node, calculating the residual load margin of the oil pump control node which is not marked as the node to be enhanced; the residual load allowance of the oil pump control nodes which are not marked as the nodes to be enhanced in the current control period is distributed to the oil pump control nodes corresponding to the identifiers of the nodes to be enhanced, and when the oil pump control nodes have faults, the fault oil pump control nodes are marked, so that the fault oil pump control nodes are not put into use any more. And performing function configuration flashing on the oil pump motor of the fault oil pump control node, performing self-inspection verification on the fault oil pump motor according to the function configuration, and completing self-inspection repair of the fault oil pump motor when the self-inspection result of the fault oil pump motor has no problem.

The invention discloses a power grid disturbance section positioning method based on source load correlation and a physical mechanism. The method comprises the following steps: matching a corresponding power grid operation scene and a plurality of critical disturbance scenes from a preset scene disturbance association library according to real-time power generation net injection power characteristics of a target power grid; acquiring branch response power of the target power grid in each critical disturbance scene according to a preset branch power response function to determine a real-time disturbance scene; obtaining the degree of influence of each branch line in the target power grid according to the real-time disturbance scene so as to select a plurality of key branch lines and the electrical distance between any two key branch lines, and dividing the plurality of key branch lines into a plurality of branch line sets according to the electrical distance; and obtaining the total branch power of each branch set to obtain the load margin of each branch set according to a preset power grid power balance constraint condition, and then selecting a dangerous branch set from the plurality of branch sets, thereby improving the accuracy of power grid disturbance section positioning.

The invention provides a transformer base installation stability and bearing capacity analysis method, which comprises the steps of performing fusion processing on a static stability index and a dynamic impact risk index to obtain a comprehensive risk coefficient, and combining the comprehensive risk coefficient with an oil liquid shaking period duration to determine an oil liquid shaking amplitude expansion amount under earthquake excitation; analyzing instantaneous dynamic load distribution of the base according to the peak value of the impact force in combination with the three-axis vibration acceleration signal of the base, identifying a load peak moment in the instantaneous dynamic load distribution of the base, and extracting a maximum impact load borne by the base corresponding to the load peak moment; the bearing margin of the base is evaluated according to the maximum impact load in combination with the rated bearing capacity of the base, and the dynamic bearing capacity grade of the base is determined according to the bearing margin.

The application discloses an eGBDT-based long-term voltage stability fine evaluation method and belongs to the field of power system operation and maintenance. The bus voltage amplitude and phase angle data of wide-area online measurement can be used to calculate a load margin index and realize fine classification of voltage stability. Meanwhile, the one-side gradient sampling method and the mutual exclusion feature bundling technology are adopted in the method to realize dimension reduction and feature compression of the high-dimensional measurement data space, effectively improving the processing efficiency of the traditional GBDT method on massive measurement data. The method inherits the high-precision estimation effect of the traditional GBDT method and greatly improves the processing capacity for massive measurement data. The application has stronger robustness for the uncertainty analysis caused by large-scale access of renewable energy sources and has good applicability when incomplete measurement data and different training data set sizes are processed. Therefore, the method has good practical application value.

The invention relates to the technical field of fault diagnosis, in particular to a power equipment fault diagnosis system and method, and the system comprises a multi-parameter mutation detection module, a heat-induced risk identification module, a load structure pre-judgment module, an abnormal behavior tracking module and a fault block defining module. According to the method, time gradient calculation and abrupt change direction consistency analysis are performed on transient change data of voltage, current and temperature, so that an operation time period with potential risks can be identified at the initial stage of linkage change of multiple parameters, and high-risk fragments caused by thermal response abnormity in a load structure are accurately captured; equipment nodes in a critical state are positioned on the basis of load disturbance behavior frequency and load margin trend, and a high-risk sequence with a synchronous evolution trend is extracted in combination with continuous parameter fluctuation consistency characteristics, so that dynamic identification of early symptoms of fault evolution and accurate demarcation of regional structure aggregation risks are realized. And the coverage capability and the troubleshooting efficiency of the diagnosis result on the fault area are improved.

This invention relates to the field of smart distribution network technology, specifically to a method and system for fault location and isolation in distribution networks based on multi-source information fusion. The method includes the following steps: using a smart remote terminal to collect zero-sequence current and voltage phasors and combine them with impedance parameters to construct a topology matrix; extracting transient features of nodes to map and generate a fault map; comparing branch polarities to extract abnormal branches; calculating physical distances to generate location coordinates; obtaining parameters from adjacent nodes to calculate transfer margins and screen for reconstructed paths; issuing switch sequences to isolate faults and verify network connectivity. In this invention, by fusing transient features into the topology matrix to calculate confidence levels, the limitations of single electrical threshold judgments are effectively overcome, accurately locating complex fault intervals with weak features. Dynamic constraint equations are constructed based on the load margin of adjacent sections and power output to generate action sequences, and secondary verification of status data is collected to avoid maloperation of switches, effectively ensuring the reliability of system power supply restoration.

The application belongs to the technical field of new energy, and particularly relates to a charging station low-power capacity orderly charging management system. The system comprises: a charging station orderly charging model; the charging station orderly charging model is configured to: receive a user input charging limit state and a chargeable waiting time; obtain N chargeable time periods of an electric vehicle of the user based on the chargeable waiting time; determine a required charging time period number of the electric vehicle based on the charging limit state and the N chargeable time periods; obtain a charging load margin of each chargeable time period; wherein the charging load margin is used to represent the power consumption load of the chargeable time period; and determine a charging strategy of the electric vehicle based on the charging load margin of each chargeable time period, the rated charging power of a charging pile of the charging station and the required charging time period number of the electric vehicle. In this way, power grid resources can be reasonably utilized, both the waste of power grid resources can be avoided and the load peak-valley difference can be reduced.

The invention discloses a parallel steam turbine generator unit load distribution method and device. The method comprises the following steps: acquiring a total power generation instruction issued by a power grid, operation parameters of each steam turbine generator unit and power grid working condition parameters; determining a total load rate based on the total task load and the weighted average value of the rated power of each steam turbine generator unit; according to the total load rate, the real-time energy efficiency deviation value of each steam turbine generator unit and the peak regulation response aging requirement of the power grid, determining the operation mode of at least two steam turbine generator units operating in parallel; determining the load distribution proportion of each steam turbine generator unit according to the determined operation mode, the real-time energy efficiency deviation value of each steam turbine generator unit, the load margin, the equipment state and the power grid working condition parameter, and distributing the total task load to each steam turbine generator unit according to the load distribution proportion, thereby achieving the optimal comprehensive energy efficiency under different working conditions.

The application discloses an energy coordination scheduling method and system based on energy saving and carbon reduction, and relates to the field of energy coordination scheduling.The method comprises the following steps: collecting community power grid data and meteorological prediction data of a target community; calculating carbon emission intensity and load margin data of the target community, and planning an initial amount of charging rights for the target community; screening out high-carbon charging communities and low-carbon charging communities, and completing low-carbon electric energy scheduling; correcting the initial amount of charging rights in combination with the low-carbon electric energy scheduling result, obtaining an amount of charging rights, and generating a charging right bidding price of the target community; and completing optimal charging time period distribution of all charging pile users in the target community, and obtaining a charging scheduling scheme of the target community. The application can effectively solve the problem of unstable residential power consumption caused by concentrated charging.

The present disclosure provides a limit load control method, device, medium and wind turbine generator set. The limit load control method can comprise: obtaining a load value of a gearbox; determining a numerical relationship between the load value of the gearbox and a predetermined limit load threshold; performing a power limiting operation on the wind turbine generator set according to the range where the numerical relationship is located, so as to reduce the load value of the gearbox. The limit load control method according to the embodiments of the present disclosure can appropriately reduce the load margin of the gearbox, reduce the cost of the wind turbine generator set, and improve the safety of the wind turbine generator set.

The invention relates to the technical field of power load control, and discloses an aurora power load control system for a home elevator, and the system comprises a system state sensing unit which is configured to collect the home total electrical load power, the elevator calling signal of the home elevator and the target floor information in real time; the collaborative decision-making and optimization controller is in communication connection with the system state sensing unit and is used for executing core decision-making and optimization calculation; the elevator driving instruction reconstruction unit is connected with the collaborative decision and optimization controller and is used for receiving the optimization instruction and generating a corresponding elevator driving signal; and a load margin management pool. According to the system, the system state sensing unit collects the total household electrical load in real time, accurate sensing and prospective regulation and control of the total household power grid load are achieved on the basis of the prediction model and dynamic margin management, and the system can actively evaluate the residual capacity of the power grid and dynamically adjust the elevator operation curve before the elevator is started.

The present application relates to the technical field of comprehensive energy, and provides a safety evaluation method and system for comprehensive energy system planning based on energy path theory, a continuous flow model is constructed by combining a steady-state alternating current flow model of a power system and a dynamic gas flow model of a natural gas system, the limitations of traditional static models that cannot depict the dynamic differences of multi-energy systems are broken through, the system response characteristics under faults are more truly reflected, the linear sensitivity method of saddle node bifurcation point singularity is used to realize rapid preliminary screening of faults, the load margin is accurately estimated by combining generalized curve fitting to complete secondary screening, and the final fault set is accurately evaluated through dynamic continuous energy flow analysis, which not only solves the problems of existing partial optimism and insufficient dynamic response depiction, but also considers the influence of electric-gas faults in a unified framework, gradually identifies key vulnerable lines and load margin indicators, and significantly improves the accuracy and reliability of comprehensive energy system safety evaluation.