34 results about "Distributed generation" patented technology

This invention discloses a multi-source collaborative optimization control method for smart microgrids, relating to the field of energy technology. The method includes: connecting to the user side to predict the power supply demand of the target microgrid in a preset time zone; acquiring a hybrid energy supply module containing multiple distributed power sources; collecting historical power supply logs of the distributed power sources and generating relevant time sequences; performing energy curtailment rate analysis based on this to generate indicators and decisions; optimizing energy storage units after determining that the indicators meet the standards; and then performing multi-source collaborative power supply control according to preset demand. This method solves the technical problems of existing new energy power generation uncertainties that are difficult to accurately predict, and unreasonable energy storage module configurations that lead to significant energy losses during power generation, storage, and distribution, resulting in low energy utilization efficiency and unstable power supply quality. By optimizing and integrating new energy power generation, energy storage modules, and energy distribution in the microgrid, it achieves the technical effect of reducing energy losses and ensuring efficient and high-quality power supply to the microgrid.

The application discloses a micro-grid distributed cooperative control method and system based on FCS-MPC and improved finite-time consensus, relates to the technical field of power system control, and comprises the following steps: configuring a hybrid energy storage system of super capacitors and storage batteries in a photovoltaic power generation unit and a fan power generation unit respectively, and constructing a distributed power generation unit; utilizing FCS-MPC to optimize the switching state of a Boost voltage-boosting circuit, a hybrid energy storage bidirectional DC / DC converter and a two-level inverter, and performing voltage dynamic regulation and fluctuation correction of a direct-current bus; constructing a micro-grid; performing secondary frequency recovery control and active power proportional distribution based on a secondary frequency recovery control strategy of the improved finite-time consensus theory; and performing secondary voltage recovery control and reactive power proportional distribution based on a secondary voltage recovery control strategy of the improved finite-time consensus theory. The application improves the operation stability and power quality of the micro-grid under high renewable energy penetration.

This invention provides a method, apparatus, and electronic device for batch generation of short drama works, belonging to the field of film and television work generation technology. The method includes: a master node acquiring the script of the short drama to be generated; decomposing the script into multiple atomic tasks and determining the dependencies between these tasks; based on the dependencies, distributing atomic tasks without dependencies to multiple slave nodes in a distributed generation system in parallel via a message queue; each slave node executing the received atomic tasks in parallel, writing the intermediate data generated as execution results into a distributed storage system; and the master node reading the execution results of each atomic task from the distributed storage system, merging them according to the dependencies and the time sequence of the script to generate the short drama video. This invention enables high-concurrency batch production of short dramas, significantly improving the efficiency and stability of short drama generation.

This invention relates to a distribution network reconfiguration method based on distributed generation and SOP (Standard Operating Procedure) optimization configuration, belonging to the technical field of new energy grid connection and distribution network optimization operation. The method includes: performing site selection and capacity determination on the original distribution network using an improved gray wolf algorithm based on a constructed distributed generation optimization configuration model; updating the distribution network structure to form a new distribution network structure, constructing an SOP optimization configuration model, and optimizing the SOP configuration using an improved sensitivity analysis method; connecting the optimal access location and capacity of the distributed generation obtained from site selection and capacity determination, along with the SOP optimized configuration capacity and location, to the distribution network, constructing a distribution network demand response model; constructing a distribution network reconfiguration model based on the distribution network demand response model, reconfiguring the distribution network, obtaining the distribution network disconnection results, and thus obtaining a new topology. It aims to solve the technical problems of increased voltage fluctuations, increased network losses, and bidirectional power flow caused by a high proportion of distributed generation access to the distribution network.

This disclosure relates to the field of voltage control technology, and proposes a distributed voltage control optimization method and system for three-phase unbalanced distribution networks. It uses the active and reactive power output by single-phase distributed power sources connected to the distribution network and the three-phase distributed power sources as the control objects. By coordinating the power injected into each phase of the distribution network by the distributed power sources, it reduces the deviation of voltage at each node from the voltage reference value and the phase-to-phase voltage deviation, thereby achieving stable control of the voltage of each phase at each node of the distribution network. Two different control modes are designed according to the different degrees of voltage deviation in the three-phase distribution network, taking into account both voltage coordination and the maximum utilization of distributed generation (DG) energy. The distributed controller only communicates with adjacent units, reducing the requirements for the controller's computing power and communication performance.

This invention relates to the field of power system operation and control technology, and particularly to an equivalent aggregation method and system for the output power of distributed generation clusters. The purpose of this invention is to construct an equivalent aggregation method and system for cluster output power. First, output models of the power of generators, photovoltaics, wind turbines, and energy storage devices in the cluster are constructed. Then, a cluster network power flow technical constraint model is constructed, and node voltage and branch power flow constraints are established based on linear branch power flow equations. Next, an inscribed ellipsoid model of the equivalent domain for cluster output power aggregation is constructed. The parameter values ​​of the inscribed ellipsoid model are solved by constructing and solving a specific optimization problem. Compared with existing methods, the proposed equivalent aggregation method for cluster output power significantly accelerates the calculation speed and greatly improves the accuracy of the solution results, enabling rapid equivalent aggregation of cluster output power and possessing significant value in practical applications.

The present application relates to the field of distributed energy response scheduling, and discloses a demand response scheduling decision method and apparatus based on electricity-carbon coupling, a device, and a system. The method comprises: acquiring information data of a user end, wherein the information data comprises an electricity-carbon coupling locational marginal price signal corresponding to a distribution system operator, the information data is determined on the basis of a locational marginal price model of electricity-carbon coupling at a distribution system end, and the locational marginal price model is determined by the distribution system operator by using a distribution system branch flow algorithm; determining a user-side demand response model, wherein the user-side demand response model is constructed on the basis of the information data and with the objective of minimizing a power factor; and using Markov decision to perform mathematical transformation on the user-side demand response model, and using a deep reinforcement learning method to perform iterative optimization calculation to obtain a scheduling decision scheme, so as to coordinate a user-side load of the user end with distributed generation. The present application aims to implement coordinated adjustment and scheduling of distributed energy and user loads.

This invention proposes a harmonic suppression method for voltage-controlled DG-Grid interface converters based on a two-step virtual impedance. This method utilizes a two-step virtual impedance control structure to actively suppress DG output current harmonics by reconstructing the harmonic voltage reference command. The effectiveness of the method is visually verified through the output voltage and current waveforms. Theoretical and simulation results show that this method not only effectively improves the DG output current quality under different harmonic severity levels but also possesses advantages such as simple structure and ease of integration, providing an effective harmonic mitigation solution for high-standard grid-connected operation of distributed generation systems.

A method for providing multi-layer protection from faults for a power generation plant is provided. The method includes monitoring, via a system-level controller, one or more parameters at a first plurality of distributed generation resources. The method also includes implementing, via the system-level controller, a fault protection mode upon the one or more parameters of the first plurality of distributed generation resources exceeding a first threshold. Specifically, the fault protection mode includes implementing a time delay, and after the time delay, commanding, via the system-level controller, a trip of the first feeder breaker on a first feeder line. The method also includes exiting the fault protection mode when the one or more parameters of the first plurality of distributed generation resources are equal to or fall below the first threshold.

The application provides a photovoltaic grid-connected system anti-reverse flow control method based on load mutation prediction, and relates to the technical field of distributed power generation and smart grid control, and the method comprises the following steps: step 1, collecting multi-element data of a photovoltaic grid-connected system in real time, and performing cleaning, alignment and standardization processing on the multi-element data to form a standardized feature vector; step 2, using a sliding window method to extract a multi-element time sequence segment of a historical time period from the standardized feature vector to generate a sample sequence; and step 3, inputting the sample sequence into a pre-trained time series convolution network model based on an attention mechanism to obtain a load mutation risk probability and a load power prediction value at a future time point. The application realizes the foresight and smoothness of anti-reverse flow by means of load mutation prediction, dynamic adjustment of a reverse flow detection threshold and collaborative control of energy storage and a photovoltaic inverter, reduces the occurrence of reverse flow and the impact on the power grid, maximizes the utilization rate of photovoltaic power generation, and adapts to long-term changes in load characteristics.

The application discloses a secondary frequency control method and device resisting false data injection and a storage medium, belongs to the technical field of micro-grid control, and is used for performing secondary frequency control on a target distributed power generation unit in a distributed micro-grid. The method comprises the following steps: acquiring local frequency compensation amounts of each distributed power generation unit; inputting the local frequency compensation amounts of the remaining distributed power generation units into a pre-trained neural network, and outputting a predicted frequency compensation amount of the target distributed power generation unit; detecting whether false data injection occurs according to the local and predicted frequency compensation amounts of the target distributed power generation unit; and when it is detected that false data injection occurs, replacing the local frequency compensation amount of the target distributed power generation unit with the predicted frequency compensation amount of the target distributed power generation unit, and compensating for a frequency deviation caused by droop control of the target distributed power generation unit. The application can solve the problem that false data injection destroys the secondary frequency control function.

This invention relates to the field of distribution network fault recovery technology, specifically an adaptive fault recovery method for hybrid switchgear distribution networks under power outage conditions. The method includes: collecting distribution network topology data, distributed generation operating parameters, and real-time power demands of load nodes under power outage conditions; unifying the format and aligning the time stamps to form an initial operating dataset; identifying disconnected tie switches and sectionalizing switches in the network, classifying them into mechanical switch groups and power electronic switch groups according to their physical type; constructing a candidate reconfiguration path set including switch action delay and transmission capacity constraints based on the differences in the operating characteristics of the two types of switches; performing radial topology verification on each path, eliminating paths that do not meet the unidirectional power supply constraint, and retaining usable recovery paths; and calculating the remaining transmission margin of each usable recovery path as the basis for path selection. This method can achieve accurate and efficient adaptive recovery of power outage faults in hybrid switchgear distribution networks.

A kind of time synchronization control method and system for distributed power generation system, comprising the following steps: obtaining the local clock deviation of each distributed unit and time calibration, collecting the running power data after calibration, generating local power parameter sequence with time label.It is encapsulated as synchronous message and sent to host end, by pre-distribution to message and obtaining each unit response data, evaluate the message reception integrity of each unit at the same time point, to determine the final distribution strategy.According to the strategy, distribute synchronous message, and calculate the deviation value of each unit local power and network average power.According to the power deviation value, the control signal of each unit is generated, and the power regulation optimization of distributed power generation system is realized.The present application effectively improves the precision and coordination control efficiency of system time synchronization, enhances the stability and economy of system operation.

This invention discloses a method for calculating the installed capacity of distributed generation (DG) in a distribution area based on the time-series power of distribution transformers. The method includes: classifying the target distribution area by DG type; matching the DG type classification results with corresponding time period filtering principles; filtering the corresponding pure load time periods according to the time period filtering principles; obtaining pure load time period data; classifying the pure load time period data by date type; extracting the load cycle features corresponding to each date type; fitting the load cycle features using a pre-trained LSTM neural network model; outputting the load prediction value corresponding to the pure load time period; calculating the DG output at the corresponding time based on the load prediction value; filtering the maximum DG output value for the pure load time period; assigning dynamic coefficients to the maximum DG output value; and outputting the actual installed capacity of the target distribution area. This method improves the accuracy of DG installed capacity calculation, enhances data robustness, is applicable to a wider range of application scenarios, and is low-cost and easy to implement.

This invention discloses a method, apparatus, terminal equipment, and storage medium for flexible load aggregation modeling based on price response, belonging to the field of load dispatching. The method includes: constructing a physical aggregation model and corresponding aggregation model constraints based on load data, energy storage operation status data, distributed generation capacity data, and grid topology data; solving the model under constraints based on the acquired electricity purchase price sequence and predicted electricity purchase price, with the objective of minimizing electricity purchase cost; obtaining the optimal model parameters by inverse optimization of the physical aggregation model based on the solved initial aggregation response power trajectory, initial power allocation results, and measured response power data from the load data, with the objective of minimizing the mean square error between the observed response and the simulated response; and performing grid dispatching based on the target aggregation response trajectory, target power allocation results, and grid topology obtained from the updated physical aggregation model. By implementing this invention, the problem of prior art neglecting the dynamics and real-time rolling of flexible loads is solved.

A method and system for equivalent aggregation of distributed generation sources for short-circuit current calculation is disclosed. The method includes: acquiring parameter information and fault response characteristics of distributed generation sources within the target power grid, analyzing the contribution of each distributed generation source to the short-circuit current at the fault point, and constructing a fault response feature vector; establishing an electromagnetic transient model of the target power grid; simulating a short-circuit fault on the main grid of the electromagnetic transient model and recording the simulated voltage and current waveforms during the fault; constructing a comprehensive criterion vector based on the fault response feature vector, path impedance, and voltage sag depth, and using weighted standardization and adaptive clustering to divide the grid into multiple equivalent clusters and calculate equivalent parameters; replacing the distributed generation sources and their controllers in the electromagnetic transient model with equivalent clusters, and comparing the simulated voltage and current waveforms until the error meets the accuracy requirements. This invention can reflect the dynamic response characteristics of distributed generation groups during power grid faults and simplifies the calculation of short-circuit current in the power grid while ensuring calculation accuracy.

This invention discloses a method for optimal scheduling of distribution networks containing distributed generation sources, comprising the following steps: Step 1, constructing an objective function considering the operating cost and load failure rate of the distribution network based on the distribution network structure and the distributed generation sources connected to the distribution network; Step 2, establishing constraints for optimal scheduling of the distribution network based on the distribution network structure and the distributed generation sources connected to the distribution network; Step 3, solving the objective function that satisfies the constraints using a multi-objective improved particle swarm optimization algorithm. The method disclosed in this invention, by employing a multi-objective improved particle swarm optimization algorithm to solve the objective function, can make the operation optimization of the distribution network more reasonable and can be applied to the optimal scheduling of actual distribution networks.

This invention discloses a gas-electric decoupling feedforward control method and an edge collaborative gateway for gas generator sets, relating to the field of distributed generation control technology. The method acquires gas composition data streams and real-time gas volumetric flow rates from the upstream gas supply network through an edge collaborative gateway. When a step change in gas composition is detected, the remaining time for the abnormal gas mass to reach the cylinder is obtained by solving an integral equation based on the pipeline volume. Within the window period, the expected Wobbe number and expected methane number are extrapolated to generate a combustion strategy bias for the native engine management system, and the target value of the grid active power to be reduced is calculated. At the moment the remaining time reaches zero, the combustion strategy bias and the grid active power target value are simultaneously issued. The aim is to overcome the feedback control lag bottleneck without disrupting the native control system, achieving highly stable operation of the unit under extreme fluctuating gas sources.

This invention discloses a distributed online energy management method for smart grids, relating to the field of smart grid energy management technology. It establishes a communication topology diagram based on the communication between each distributed generation (DG) in the grid system to determine initial data; it establishes an energy management model based on the actual constraints of generation balance and power output limitations in the smart grid; it constructs a gradient estimator to replace the true gradient information, proposing a Bandit-based distributed online energy management method to achieve optimal power output for each generator; this invention solves the energy management problem with energy storage devices under directed graphs, constructing a locally stochastic gradient-free estimator to replace the true gradient and guide the update of output power; addressing the difficulty of simultaneously sampling multiple points for online time-varying objective functions, it proposes an online distributed single-point gradient-free estimation method. Compared with two-point and multi-point gradient-free estimation methods, this method only requires sampling once at each time step, making it more convenient to operate.

This invention discloses a secondary frequency control method, apparatus, and storage medium based on graph-temporal Transformer, belonging to the field of microgrid control. It is used for secondary frequency control of attacked distributed generation sources. The method includes: constructing and inputting local and neighbor feature sequences into a pre-trained frequency prediction model, outputting predicted local and neighbor frequency values; constructing and inputting power coefficient feature sequences into a pre-trained power coefficient prediction model, outputting predicted power control gain coefficients; the frequency prediction model and the power coefficient prediction model are independent graph-temporal Transformer models; inputting the three predicted values ​​into a frequency compensation calculation formula to calculate the predicted frequency compensation amount for the attacked distributed generation source, compensating for the frequency deviation caused by droop control. This invention can solve the problem of being unable to maintain the original performance of distributed cooperative control during an attack.

An adaptive current protection method and system based on distributed generation (DG) access capacity calculation is proposed. This method establishes short-circuit current constraints for downstream faults, upstream faults, and adjacent branch faults of the DG. Three maximum and two minimum values ​​for the DG access capacity are determined. Based on multi-source information, the effectiveness of these three maximum and two minimum values ​​is dynamically evaluated for each scenario. Invalid maximum and minimum values ​​are removed to determine the feasible region for the DG access capacity. A capacity threshold is set based on this feasible region. When the actual capacity of the DG exceeds the capacity threshold, the operating thresholds of the upstream and downstream protection devices are adjusted. Protection is then performed based on these adjusted operating thresholds. This method addresses the problems of stringent limitations on DG access capacity, coupling between operating thresholds and access capacity, and low sensitivity of time-limited instantaneous protection in traditional current protection systems.

This invention relates to a multi-dimensional evaluation method and system for the carrying capacity of distribution networks based on probabilistic assessment. The method includes: collecting distribution network operation data and constructing a distributed generation processing probability model and a load demand uncertainty model; performing sampling and power flow calculations based on the distributed generation processing probability model and the load demand uncertainty model; calculating and normalizing multi-dimensional indicators based on the calculation results at each sampling time; the multi-dimensional indicators include resilience indicators, including transient voltage stability index, islanding reconstruction power, and energy storage throughput margin; calculating the subjective and objective weights of the multi-dimensional indicators and fusing them to obtain a comprehensive weight; calculating the score for each sampling and the expected score based on the comprehensive weight and the normalization result; calculating the risk probability based on the expected scores of all samplings; and classifying the carrying capacity level based on the expected score and the risk probability. Compared with the prior art, this invention improves the reliability of carrying capacity evaluation for distribution networks with uncertainties.

This invention discloses an AI-enabled microgrid energy management and economic operation system, relating to the field of microgrid energy management technology. It includes a data acquisition module that collects real-time operational data from distributed generation units, energy storage units, and load units, as well as external market environment data; a scenario construction module that builds a set of dynamic operating scenarios across multiple time scales based on multi-source data; a learning and decision-making module that inputs the scenarios into a multi-objective reinforcement learning decision model to generate scenario-adaptive energy dispatch strategies and market trading instructions; an execution and control module that controls generation and energy storage output and executes power interactions; and a rolling optimization module that monitors status and prices and provides feedback on optimization strategies. This invention replaces static libraries with dynamic scenario construction and combines multi-objective reinforcement learning to balance economic and reliability objectives, thereby improving the accuracy, economic efficiency, and power supply reliability of microgrid energy management.

The application discloses a source-grid-load-storage double-layer collaborative optimization method based on a multi-agent algorithm, and comprises the following steps: constructing a source-grid-load-storage multi-agent system; constructing a source-grid-load-storage collaborative optimization model based on the multi-agent system; solving the in-layer target of the collaborative optimization model by using a double-layer nested optimization structure to obtain minimum light abandonment and minimum operation cost, and realizing source-grid-load-storage double-layer collaborative optimization; compared with the prior art, the method combines the multi-agent system and the collaborative optimization model, solves the problem that distributed power generation has great randomness, and after superimposing various types of load fluctuations, the problem that the power grid optimization regulation and operation are challenged is solved, and scientific guidance is provided for reliable operation of a new power system.

This invention relates to the field of low-voltage intelligent power distribution technology, and provides a collaborative autonomous method and device based on distribution transformer area source-grid-load-storage. The method includes setting values ​​of L1 and L2, where L1 is a high threshold for distribution transformer load rate and L2 is a low threshold for distribution transformer load rate; then, based on the numerical relationship between distribution transformer load rate and L1 and L2, entering a safe operation mode, a photovoltaic consumption mode, and an economic operation mode; executing corresponding charging and discharging processes in different modes, and coordinating and controlling the output and load direction of distributed generation and energy storage through edge computing, so as to ensure the safe and reliable operation of the distribution transformer area, while minimizing the number of adjustments to energy storage and extending the service life of energy storage.

This invention relates to the field of distributed generation technology and discloses a three-in-one photovoltaic-storage-diesel intelligent power supply system for outdoor environments. The system includes: a photovoltaic energy acquisition module, an energy storage scheduling and execution module containing independent energy storage units, a backup power control module, and a core scheduling module. The core scheduling module acquires the pose parameters of each module and constructs a physical distribution model. Based on this model, it analyzes geometric shading to determine the shadow feature matrix and the power allocation correction amount. Simultaneously, it identifies consistency differences among energy storage units based on state feature vectors containing temperature gradients and issues differential power commands. This invention, through dynamic perception and logical reconstruction of the random evolution of physical space topology, offsets balance deviations caused by support deformation and shading offsets, ensuring the microgrid system's adaptive disturbance rejection and power supply continuity under disordered outdoor conditions.

This invention discloses a bladeless wind turbine with a magnetically tuned structure and its control method, belonging to the field of wind power generation and distributed energy equipment technology. The device includes a power generation module and a power regulation module. The power generation module includes a vibration module and a stator coil assembly. The vibration module includes a flexible central shaft, a wind-receiving mast, a permanent magnet assembly, and a slider. The wind-receiving mast generates vortex-induced lateral vibration under wind flow, driving the permanent magnet assembly to cut the stator coil assembly to generate electricity. The power regulation module obtains the vortex shedding frequency based on the external wind speed and adjusts the slider position to change the equivalent cantilever length of the flexible central shaft, matching the natural frequency of the vibration module with the vortex shedding frequency to increase power generation. Furthermore, it generates a PWM signal through PI control to drive a DC-DC converter, achieving maximum power output and constant voltage power supply. This invention features good low-wind-speed adaptability and low operation and maintenance costs, making it suitable for distributed generation and microgrid scenarios.

This invention provides a model-based predictive intelligent dispatch and control method and system for microgrids, relating to the field of microgrid technology. First, it collects a set of real-time operating status data at the start of the current dispatch cycle of the microgrid, including distributed generation output, energy storage device state of charge, and critical load power monitoring data. This data is then input into a multi-timescale prediction model to generate future operating status prediction information, covering predicted output of distributed generation, predicted state of energy storage devices, and predicted demand sequences of critical loads for multiple future dispatch cycles. Based on the prediction information, an initial dispatch and control command set is obtained by continuously solving the economic operation optimization objective function. A set of command safety margin indicators is generated after verification by a microgrid safety and stability constraint verification model. Finally, the initial commands are adjusted based on this set of command safety margin indicators to generate the final dispatch and control command sequence, which is then issued and executed, improving the economy and safety of microgrid operation.

The present invention relates to a method for the adaptive classification of transient events in electrical microgrids, particularly in microgrids that include inverter-based distributed generation resources. The method improves the selectivity and reliability of electrical protection under varying operating conditions and microgrid topological changes. The method comprises acquiring voltage and current electrical signals, filtering these signals to separate transient components, and processing the filtered signals in short time windows using processing equipment configured to obtain characteristics representative of the electrical events. In parallel, the operating states of circuit breakers and protection devices in the microgrid are acquired via standardized communications, and a dynamic representation of the network topology is generated based on these acquisitions.The electrical characteristics obtained and the topological information are combined to classify transient events and generate control signals intended to adjust protection parameters of smart electronic devices, affecting the electrical operation of the microgrid. The method is adaptable to different network configurations and operating conditions.

This application relates to a communication-free dynamic voltage droop control method and system for DC microgrids. The DC microgrid includes multiple distributed generation units, each equipped with a power electronic converter and a local controller. The method collects local voltage, current, and DC bus voltage measurements from each distributed generation unit, inputs the measurement data into the artificial intelligence control module in the local controller, and generates adaptive voltage droop control parameters in real time based on a pre-trained deep reinforcement learning model. These parameters are then applied to the voltage reference value generation stage of the power electronic converter. Through dual closed-loop control of voltage and current, DC bus voltage regulation and power sharing among distributed generation units are achieved. Each distributed generation unit operates independently, and there is no communication between units during the control process. This application eliminates the need for a secondary control layer, achieving decentralized and stable operation under load fluctuations and power supply changes.