1195results about "Ac network circuit arrangements" patented technology

This invention discloses a preventive zoning method and system for resilient distribution networks considering the uncertainty of typhoon paths. First, a set of scenarios considering fault conditions under different typhoon paths is constructed. Then, through multi-round detection, the damage status of nodes and lines under different typhoon path scenarios is identified, and a node and line damage status detection model considering fault propagation is constructed. Next, combined with the node and line damage detection model, a preventive zoning model for resilient distribution networks considering the uncertainty of typhoon paths is constructed based on a stochastic optimization method. Finally, the constructed model is linearized to reduce the solution difficulty and then solved to obtain optimized distribution network islanding and node power supply strategies. The technical solution of this invention can properly handle the uncertainty of typhoon paths during distribution network islanding, effectively improving the risk resistance capability of post-disaster distribution network power supply restoration schemes.

Systems and methods are described herein for facilitating the switching of a power transfer direction in wireless power transfer systems. A ground unit comprises: one or more power transfer coils configured for providing wireless power transfer on an inductive power transfer frequency band; one or more positioning coils configured to emit position data suitable for detection, measuring or sensing by, the vehicle; and one or more communication antennas configured to communicate with the vehicle by way of a bidirectional communication channel; wherein the bidirectional communication channel operates on a frequency band which is different to the inductive power transfer frequency band.

Systems and methods are described herein for reducing communication latency in a wireless power transfer system. A method of switching the wireless power transfer direction between wireless power transfer coils of a vehicle unit and a ground unit comprises: receiving at the ground unit, one or more vehicle unit coil parameters, the one or more vehicle unit coil parameters including a vehicle unit coil position relative to the ground unit coil; determining, based on the vehicle unit coil position relative to the ground unit coil position, a coupling factor between the vehicle unit coil and the ground unit coil; determining, based on the coupling factor, one or more power transfer direction swap parameters; receiving at the ground unit, instructions to perform a power transfer direction swap; and performing, based on the determined one or more power transfer direction swap parameters, the power transfer direction swap.

This invention discloses a method for determining the unloaded bus current and a busbar switching control method using the same method. The method for determining the unloaded bus current includes the following steps: A1. Installing current sensors on the porcelain bushings of the circuit breakers on the unloaded busbar side of each phase; A2. Connecting each current sensor to a multi-channel waveform recorder to obtain the maximum capacitive current of each phase unloaded busbar through the multi-channel waveform recorder; A3. Obtaining the maximum capacitive current value of the unloaded busbar. The busbar switching control method includes selecting the threshold value for operating the unloaded busbar with the disconnecting switch according to the rated voltage level of the busbar; and selecting the disconnecting switch or the circuit breaker on the unloaded busbar side to control the switching operation of the corresponding unloaded busbar according to the maximum capacitive current and the threshold value. This invention can flexibly adjust the threshold values ​​for operating the unloaded busbar with the current sensors and disconnecting switches according to the rated voltage level of the busbar, which has good engineering adaptability, is more in line with the actual situation on the engineering site, has good performance, and is easy to promote and use.

This invention discloses a fault isolation method for distributed area protection and coordinated control of flexible interconnected devices. After a fault is triggered, the method first disconnects the outer loop control on the fault side of the flexible interconnected device. Considering fault support and phase angle compensation requirements, a positive-sequence current inner loop reference value is calculated using the high-inductance fault characteristic impedance angle as the target. Then, it performs real-time verification based on fault limiting requirements. If the fault limiting requirements are met, the value is input into the positive-sequence current inner loop; otherwise, the negative-sequence current inner loop reference value is calculated using the remaining short-circuit capacity to ensure that the negative-sequence fault characteristic impedance exhibits high inductance. Finally, combining the fault component direction element area protection criteria and through communication between adjacent protection devices, the fault location is determined, achieving fault isolation. This invention considers fault support and current limiting control requirements, reshapes the fault characteristic impedance of the flexible interconnected device, effectively identifies faults in the flexible interconnected system, and achieves precise fault isolation.

The application provides a power distribution network elasticity planning method, device and equipment considering extreme events, and relates to the technical field of power distribution network planning. The method comprises the following steps: fitting an influence expectation of extreme events in a region where a target power distribution network is located based on historical data of the extreme events; wherein the extreme events include meteorological extreme events, geological extreme events and human-caused extreme events; taking the influence expectation and the topological structure of the target power distribution network as inputs, taking reinforcement decision and elasticity resource allocation as outputs, constructing a target function based on node reinforcement decision cost, elasticity resource allocation cost, disaster loss cost and operation cost, constructing a constraint condition based on upper and lower limits of an expectation probability, a power distribution network resilience limit and extreme event measures, and obtaining an elasticity planning model of the target power distribution network; taking minimization of the target function as an optimization target, solving the elasticity planning model, and obtaining an elasticity planning result of the target power distribution network. The application can solve the problem of inaccurate extreme event evaluation in traditional planning.

The application discloses a kind of multi-objective collaborative regulation method and system based on dynamic electric carbon factor, belong to power system dispatching and optimization control technical field, the method is: based on original predicted load sequence, time-of-use electricity price sequence and dynamic electric carbon factor sequence, constructs multi-objective collaborative optimization model;Based on nonlinear convergence factor, the multi-objective collaborative optimization model is iteratively solved, obtains several initial solutions;If any initial solution does not satisfy the constraint requirement, then the initial solution is modified until all initial solutions satisfy the constraint requirement, obtain the Pareto optimal solution set;Based on multi-criteria decision, compromise scheduling scheme that satisfies preset score requirement is selected from the Pareto optimal solution set, complete electric carbon collaborative regulation.Therefore, by implementing the application, the dynamic electric carbon factor sensing mechanism is introduced to deeply couple electric carbon information, and the nonlinear convergence factor adjustment strategy is used to fully consider the global exploration ability in the face of multi-objective conflict, to improve the reliability of electric carbon regulation of power system.

The application discloses a switching positive system event trigger threshold optimization method and device based on parameter sensitivity analysis, comprising the following steps: constructing a switching positive system state equation based on an output power vector of the switching positive system and a received power reference instruction vector; determining a corresponding local measurement error according to a latest effective power value of each distributed power generation unit and an actual power value of each distributed power generation unit in the current continuous time; and determining a dynamic trigger threshold and an event trigger condition under each performance index in the current working condition by using system identification or a least square method based on collected trigger time stamps, power output sequences and local voltage measurement values. The application can reduce the communication trigger times by about 25% through dynamic threshold optimization while maintaining voltage stability; converts theoretical sensitivity analysis into an online algorithm, realizes self-balancing of communication resources and control performance, and provides a practical solution for smart grids.

This invention discloses a method, system, and storage medium for assessing the adjustable load of a virtual power plant in public buildings. The method includes: acquiring raw influencing factor data, including at least air conditioning system operating parameters reflecting equipment aging and building thermal parameters reflecting building thermophysical characteristics; constructing hysteresis features characterizing thermal inertia based on the air conditioning system operating parameters, and constructing multi-parameter coupling features based on their coupling relationship with building thermal parameters; inputting the obtained data into a pre-trained adjustable load assessment model to obtain the adjustable load assessment result; wherein the model is a multi-model fusion model and integrates a rolling mixed-integer linear programming solver for synchronously generating a full-chain control scheme for the air conditioning system. This invention, by introducing a quantitative expression of the thermal inertia of the air conditioning system and multi-parameter coupling features, achieves an integrated closed loop of assessment and control, significantly improving the response accuracy and overall benefits of public buildings participating in virtual power plants.

The present application relates to the technical field of distributed photovoltaic participation in grid frequency control, and particularly relates to a distributed photovoltaic classification frequency regulation method, device and terminal. The method comprises the following steps: constructing two sets of cluster division indexes of instantaneous backup capacity ratio and control mode of distributed photovoltaic; performing cluster division on the distributed photovoltaic based on the two sets of cluster division indexes, and obtaining a clustering result according to the size of frequency regulation backup capacity; calculating the total amount of frequency regulation of the distributed photovoltaic corresponding to each clustering result; decomposing the grid frequency fluctuation signal according to the grid frequency fluctuation; calculating the total amount of frequency regulation resources required by the grid for the distributed photovoltaic; and according to the clustering result, the decomposition frequency band, the total amount of frequency regulation and the total amount of frequency regulation resources, controlling the distributed photovoltaic to participate in the grid frequency regulation according to the same proportion of the clustering categories. The present application can solve the problem of regulation lag in centralized regulation, and the problem of increased equipment wear and reduced operation economy caused by the regulation strategy of the full participation mode.

The invention provides a weather process trajectory tracking method fusing a TREC algorithm and a power grid time-space characteristic, and the method comprises the steps: capturing the overall movement trend of a weather process through employing the TREC algorithm for the grid data of a weather process coverage area in continuous time, and obtaining a motion vector field; optimizing the core general index of the weather process based on the motion vector field; based on the optimized general index sequence, adopting a TREC motion vector field to extrapolate and predict a short-term trajectory; and based on the spatial correlation degree of the short-term trajectory and the power grid device, identifying a high-correlation device, and predicting a time window of the weather process affecting the key node of the power grid based on the high-correlation device in combination with the trajectory movement speed. According to the method, the TREC algorithm and the general trajectory indexes are fused, the time-space continuity of trajectory tracking in the major weather process is improved, the movement and evolution rules of the trajectory tracking are accurately described, the influence of the weather process on the power grid is pre-judged in advance, and timely and accurate decision support is provided for power grid risk prevention and control.

The present application belongs to the field of electric power engineering, and particularly relates to a new energy engineering conductor heat loss estimation method and a conductor cross section selection method, comprising obtaining power generation information of an existing new energy power station, and obtaining initial expected power of a newly built new energy power station through new energy power station output simulation simulation; according to the power generation information and the initial expected power, obtaining conductor heat loss information of the newly built new energy power station during operation under a plurality of conductor cross-sectional areas, to complete the estimation of the conductor annual average heat loss power of the newly built new energy power station during operation under a plurality of conductor cross-sectional areas; the technical problem that the existing power station conductor heat loss estimation method does not consider the actual output characteristics of the new energy project, it is difficult to accurately estimate the conductor heat loss of the new energy project, and it is difficult to accurately obtain the economic cross section of the new energy project.

A power supply apparatus (100) comprises an inverter (110), voltage and current measuring devices (120a, 120b), a temperature sensor (130), and an operation circuit (140). The inverter (110) comprises change-over switches (SW1-SW6). The voltage and current measuring devices (120a, 120b) are configured to measure the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6). The temperature sensor (130) is configured to measure an initial temperature (T[0]) in an initial state. The operation circuit (140) is coupled to the voltage and current measuring devices (120a, 120b) and the temperature sensor (130). The operation circuit (140) is configured to: execute a power model (142), and calculate a first transient power of the change-over switches (SW1-SW6) on the basis of the initial temperature (T[0]), the voltage (V1), and the current (I1); and execute a thermal model (144), and calculate a first transient ideal temperature of the change-over switches (SW1-SW6) on basis of the first transient power. The power supply apparatus (100) calculates, in real time, the transient temperature of channel interfaces of the change-over switches (SW1-SW6) by measuring the voltage (V1) and the current (I1) on the change-over switches (SW1-SW6) of the inverter (110). The present invention also relates to a temperature measurement method (500) for a power supply apparatus, and an electrical system (ES1).

This invention discloses a scheduling method, system, device, and medium based on dynamic evaluation of the source and load sides, belonging to the field of power grid technology. The method includes: acquiring resource data corresponding to each regulating resource on the source and load sides, as well as the real-time operating status of the power grid, and acquiring at least two demand models; inputting the real-time operating status into each demand model to obtain demand information corresponding to each first stability type, and calculating the resource data for each regulating resource based on each demand information to obtain an evaluation value corresponding to each first stability type; responding to the stability request corresponding to the target stability type, sorting all regulating resources according to the evaluation value corresponding to the target stability type to obtain a resource sequence; determining and executing scheduling instructions based on the resource sequence to realize power grid scheduling. Therefore, by implementing this invention, resource scheduling efficiency and power grid stability can be improved.

This invention relates to the field of power system demand response technology, and provides a user demand response method based on master-slave game theory under cost control constraints. The method includes: establishing a demand response model using master-slave game theory, where electricity retailers design time-of-use pricing strategies, and electricity users respond based on a convex utility function; the utility function includes a quantification term for electricity usage satisfaction and a calculation term for electricity costs; the electricity retailers' revenue function includes four functions: user electricity costs, long-term market electricity purchase costs, current market electricity purchase costs, and conditional risk value, coupled with the characteristics of the electricity spot market and risk management requirements; proving the existence of a Nash equilibrium solution using backward induction; and optimizing the strategy based on a slime mold optimization algorithm. This invention provides important support for electricity retailers to formulate flexible pricing mechanisms and tap demand-side resources in terms of cost control for users with high response potential and optimization of peak-valley load differences.

This invention discloses a method for improving the grid-load interaction capability of high-energy-consuming industrial users under carbon emission constraints. The method includes: real-time acquisition of dynamic power output characteristic data from new energy sources, capturing key dynamic features such as instantaneous power fluctuations, ramp rate changes, and spatiotemporal correlations of wind farms and photovoltaic power plants; constructing an adaptive generation model for multimodal risk scenarios, and using cluster analysis and stochastic process theory to summarize the complex stochastic fluctuations of new energy power output into several representative typical risk modes. The robustness-first rolling decision optimization mechanism of this invention prioritizes ensuring system power balance and safety under all generated risk scenarios in its core objective function and constraints. This fundamentally overcomes the decision failure risk caused by prediction bias in traditional methods, thus providing the power grid with excellent resilience and anti-interference capability under complex and uncertain operating conditions.

This specification provides an adaptive processing system for cable cross-connection. This system, by constructing a complete processing system integrating environmental perception, output prediction, strategy pre-planning, and real-time closed-loop correction, achieves a fundamental shift in cable cross-connection from "passive response" to "active prediction and adaptation." The system can proactively adjust operating parameters, effectively mitigating the impact of photovoltaic output fluctuations, significantly reducing circulating current losses and fault risks. Simultaneously, its adaptive sealing and connection protection mechanisms greatly improve long-term operational stability and reliability under extreme environments, thereby enhancing overall power transmission efficiency and reducing maintenance intervention needs and costs.

The application discloses an electric-carbon factor driven vehicle-network interaction scheduling method and device, terminal equipment and storage medium, and belongs to the technical field of electric power systems. The method is as follows: acquiring an electric-carbon factor sequence and corresponding meteorological data sequence of a preset time window; performing difference processing on the electric-carbon factor sequence to obtain an electric-carbon factor difference sequence; constructing a period time covariant sequence; inputting the electric-carbon factor difference sequence, the corresponding meteorological data sequence and the period time covariant sequence into a sequence model to make the sequence model output a future electric-carbon factor difference sequence; generating a vehicle-network interaction decision sequence based on the future electric-carbon factor difference sequence; and performing vehicle-network interaction scheduling according to the vehicle-network interaction decision sequence. Therefore, the application can solve the vehicle-network interaction scheduling and new energy output mismatching problem existing in the prior art.

The application discloses a power grid load prediction method and system based on deep learning, which comprises the following steps: collecting multi-dimensional load correlation data through an intelligent power grid data fusion calculation platform, cooperatively capturing space-time correlation characteristics through a space-time residual gated recurrent model, enhancing network and strengthening key feature representation through a gated recurrent unit, then inputting a multi-modal load prediction deep model to build feature mapping relationship, generating preliminary prediction results through feature weight distribution, abnormal value elimination and smoothing optimization, and outputting final data after platform verification. The space-time residual gated recurrent model, the gated recurrent unit enhancement network and the multi-modal load prediction deep model all have exclusive feature processing mechanisms, and the processing accuracy is guaranteed through feature classification, gate initialization, mode division, fusion calculation and other subdivided processes. The application effectively improves the comprehensiveness and reliability of load prediction, and is suitable for accurate scheduling and optimized operation of intelligent power grids.

The application relates to the field of power systems and artificial intelligence security, and discloses a simulation attack and defense method of a power grid load frequency control system adopting a DRL controller, which comprises the following steps of: simulation attack: identifying system state variables most critical to DRL decision; setting an attack target and calculating an initial disturbance amount of the critical state variables, limiting the generation of a final disturbance amount; deducing disturbance amounts of the remaining dependent state variables to obtain an adversarial disturbance vector, which is superimposed to the DRL controller to implement the attack. Simulation defense: applied to a hybrid system containing DRL and a backup PID controller: real-time monitoring of the Q value sequence output by the DRL evaluation network to detect whether it is continuously lower than the normal benchmark; once the statistical quantity exceeds the threshold, it is determined that an attack is suffered, and the control right is immediately switched from the DRL to the PID controller to maintain the stability of the system. The method can generate a hidden and physically regular adversarial attack to evaluate the vulnerability of the system, and provide a fast and low-cost active defense mechanism to improve the security and resilience of the LFC system in the adversarial environment.

This invention discloses a method and system for visualizing and optimizing energy flow in microgrids. The method includes: obtaining an oscillation index based on the original power characteristic data of microgrid monitoring points; selecting several first monitoring points when the oscillation index is less than a first preset threshold; and repeatedly performing detailed judgments on the monitoring points when the oscillation index fluctuation coefficient is greater than or equal to a second preset threshold, until the oscillation index fluctuation coefficient is less than the second preset threshold or the number of iterations reaches a preset upper limit; selecting several second monitoring points to obtain an oscillation risk cumulative deviation coefficient; and increasing the monitoring frequency of the smallest circuit loop to which the second monitoring point belongs to a preset frequency and issuing an early warning when the coefficient is greater than or equal to a third preset threshold. This invention can automatically switch power control modes, adjust monitoring frequencies, inject damping current, balance reactive power output, and dynamically optimize carbon flow management according to different early warning levels, realizing multi-level risk inspection and adaptive collaborative control throughout the entire microgrid grid connection process.

The application provides a coal-fired power plant SCR denitration system limited load output and peak capacity evaluation method and device, computing equipment and storage medium, relates to the coal-fired thermal power generating unit technical field. The method is based on online monitoring parameters and equipment design parameters, and the total amount of real-time removal of NO x X is calculated; combined with the key constraints including catalyst activity, ammonia supply capacity and reaction temperature, the operation status of the SCR denitration system is evaluated; the removal of NO x X of the three core constraints of catalyst activity, ammonia supply and reaction temperature is quantified respectively, and the total NO x X removal margin is obtained; based on the coupling relationship between the total NO x X removal margin and the load, the unit load margin and the peak capacity are calculated, the technical blank of denitration system performance evaluation under high load conditions is filled, and support is provided for safe and economic operation of the unit.

The invention discloses an XGBoost-based power generation quotation rationality evaluation method, system and equipment and a medium, and relates to the technical field of power market operation and supervision, and the method comprises the steps: collecting historical operation and market environment data, obtaining five evaluation indexes through a prediction model, elastic analysis, matching degree calculation and clustering analysis, fusing the indexes to construct a feature vector, and obtaining a power generation quotation rationality evaluation result. And training a classification model to evaluate the rationality of quotation, and generating a monitoring early warning signal when the matching degree is too low, the price response is too strong, the quotation deviation is too large and the behavior mode is abnormal by continuously tracking the change trend of key indexes. According to the invention, by fusing the multi-dimensional dynamic features and adopting the elastic time sequence matching and interpretable machine learning model, a power generation quotation behavior intelligent supervision closed loop integrating comprehensive evaluation, accurate quantification and active early warning is constructed, and the comprehensiveness, accuracy, objectivity and timeliness of market supervision are significantly improved.

This invention discloses a method, apparatus, computer equipment, and storage medium for coordinated voltage regulation of the main and distribution networks, relating to the field of smart grids. It addresses the problem of insufficient accuracy in existing coordinated voltage regulation methods. The method includes: Step S1: acquiring information from the main power grid and distribution network; Step S2: classifying distribution network nodes to obtain consumer nodes and transmission nodes, analyzing the energy demand of the distribution network, transmitting energy based on the energy demand, calculating the actual voltage at the consumer nodes, calculating the voltage deviation value based on the rated voltage of the consumer nodes, and adjusting and optimizing the voltage of the transmission nodes; Step S3: statistically analyzing the energy demand of the distribution network, and controlling the voltage of the main power grid nodes based on the energy demand and the optimized voltage to obtain the control voltage; Step S4: performing coordinated voltage regulation of the main and distribution networks in the power system. This invention can effectively improve the accuracy of coordinated voltage regulation of the main and distribution networks.

A distribution transformer for use in a providing electrical power to sites, includes a ferromagnetic core; a primary winding configured to be connected to a source grid at source grid voltage; and a secondary winding configured to be coupled to service cables to supply electrical energy to at least one of the sites at a first line voltage and at least another of the sites at a second line voltage, wherein the second line voltage is higher than the first line voltage.

The application discloses a multi-time scale time series data interval prediction and robust risk control method for green electricity transaction information systems, and relates to the technical field of power control. The method comprises the following steps: acquiring multi-source data and aligning them according to a unified time step to generate an information arrival time set; constructing a probability prediction model containing cross-scale consistency regularization to output price probability distributions of each time scale; generating a future path based on conditional diffusion and constructing a multi-stage scenario tree satisfying non-prospective consistency to solve a multi-stage value evaluation to obtain a marginal opportunity value; adopting online conformal calibration to update risk control variables to form a risk bandwidth set and obtain a robust risk index; and outputting interval prediction results / curves and quantitative risk explanation quantities. The method can realize multi-time scale time series data interval prediction and quantitative risk explanation quantity output, and improve the robust risk control capability of the green electricity transaction information system under dynamic information and distribution drift conditions.