217 results about "Load modeling" patented technology

A tabular method of non-intrusive electrical load decomposition includes the following steps of: conducting off-line statistics of unit current parameters of various pieces of electric equipment; selecting the type of main electric equipment according to electrical load; selecting a power proportion spacing to combine the power proportion vectors of all possible main electric equipment inside the electrical load; obtaining the electrical load unit estimation current corresponding to the power proportions in an off-line way and forming a corresponding table of the power proportions and the unit estimation current; thinning the corresponding table of the power proportions and the unit estimation current into a plurality of sub corresponding tables according to the size of parameters of the unit estimation current; according to the size of a practically detected load current parameter, judging a sub corresponding table therein; and finding the load unit estimation current closest to the practically detected load current in the sub table, obtaining the power consumption proportion of the main electric equipment inside the load and realizing load decomposition. The tabular method can decrease the calculation quantity of load decomposition effectively and can be applied to the fields of load monitoring, electrical energy consumption analysis, load energy saving, load prediction, load modeling and the like in an electric power system.

The invention relates to a load fuzzy modeling device and a method of power distribution system. The device comprises a lower computer and an upper computer consisting of a sensor, a signal conditioning and filtering module, an A/D conversion module, a DSP module, a memory module, a display and keyboard operation module and a communication module, wherein the upper computer is connected with the communication module; a voltage transformer and a current transformer are used for collecting the voltage and the current of the system and inputting the voltage and the current into a voltage and a current signal conditioning circuit; the voltage amplified by an amplifier is inputted into the A/D conversion module for sampling; and the digital signal is transmitted to the DSP for processing to obtain the final result, which is transmitted to the upper computer by the communication module. The method is characterized in that a data making-up method of a novel combined cloud data generator and fuzzy modeling are combined, a normal cloud generator is restricted by constraint equations and effectively combined with a backward cloud generator to reproduce the specific apparent distribution of an observed object, and the improved T-S fuzzy modeling method is adopted according to the characteristics of load modeling.

The present invention relates to a non-invasive power load decomposition method, and belongs to the field of power measurement technologies. The method comprises: first collecting instantaneous current when each power device is switched, and introducing a primary function to decompose the instantaneous current, so as to obtain a current amplitude when each power device is switched; using a minimum value of a difference between a current amplitude at a user power inlet and a current amplitude of each input power device as an objective function; and solving the objective function by using an optimization algorithm, wherein an obtained result is a switching situation of each power device in power load. According to the method provided by the present invention, the switching situation of power load can be acquired online in real time, the decomposition method has relatively high precision and relatively good stability, and a computation speed is high. The present invention can be applied to a plurality of technical fields such as power system load monitoring, power analysis, load energy saving, load prediction and load modeling, and has a significant meaning to energy saving of the whole society and power system planning and operation.

The invention discloses a method for modeling a power load based on a measurement-based method. The method sequentially comprises the following steps of (1) preprocessing recording data to obtain data required by load modeling; (2) performing damped least-squares iterative equation solving on the preprocessed data required by the load modeling to obtain optimal load model parameters; (3) establishing an optimal load model by adopting the load model parameters; and (4) checking the obtained load model parameters, and verifying a load model with practical values comprising higher extrapolation capability, higher interpolation capability and higher capability in the comprehensive description of different load compositions to be the optimal load model. According to the method, the modeling cost is reduced; and the load model is more consistent with the actual condition of a field, high simulation accuracy and credibility are ensured, contrary conclusions under a clinical condition are completely avoided, the load model can be coordinated with the conventional power generation and distribution model, and the analysis of a power system is accurate and credible, so that the simulation analysis accuracy and credibility of the power system are remarkably improved.

The invention discloses an electric system load dynamic characteristic classifying method based on characteristic mapping. The electric system load dynamic characteristic classifying method comprises the steps of (1) carrying out load modeling on disturbance data, (2) confirming mapping of load dynamic characteristic classifying characteristic quantity, (3) calculating an association degree between data of a modeling group and data of a training group, (4) estimating a load model parameter of each datum in the training group, (5) correcting index mapping in a self-adapting mode, and (6) classifying load dynamic characteristics. According to the electric system load dynamic characteristic classifying method based on the characteristic mapping, a classifying characteristic quantity mapping data table is formed through the preexisting voltage disturbance data in a load modeling platform so that the load dynamic characteristics can be rapidly classified, and the electric system load dynamic characteristic classifying method based on the characteristic mapping is beneficial for solving the problem of time-varying characteristics during a load modeling process.

The invention relates to a power system load modeling method based on a typical load group. The power system load modeling method comprises the steps of: 1) establishing a typical load group model: generating the typical load group model according to node load information; 2) and establishing a node load model: performing weighted aggregation to obtain node load model parameters according to parameters of the typical load group model and proportions of typical load groups, and establishing a node load model based thereon. Compared with the typical load parameters adopted in simulation at present, the power system load modeling method obtains load parameters of the node load model parameters by performing weighted aggregation on the typical load groups, thus the node active voltage response characteristics and reactive voltage response characteristics are closer to the actual measured situation.

The invention discloses a train diagram-based traction load modeling method. The modeling method comprises the following steps of: obtaining train number of each power supply arm in each time interval of a running period according to a train diagram, equalizing each train on one power supply arm to an induction motor, equalizing each traction load to a parallel model of multiple induction motor models and static index models, performing parameter identification on a traction load model by using particle swarm optimization (PSO) according to the measured voltage and power waveform, and establishing the traction load model. Compared with the conventional traction load modeling method, the train diagram-based traction load modeling method has the advantages that: the influence of running time variance of a train on the traction load voltage and power is taken into consideration, the generality and the accuracy of the traction load model are greatly improved on the premise of keeping good astringency, the established traction load model is more accordant with the actual conditions, and the requirements of railway/power related departments on traction power supply quality assessment, electrical energy quality assessment and power system stability assessment are met.

The invention discloses a transverse time axis clustering method in generalized load modeling on the basis of time periods. According to the method, root bus data formed by wind power and loads of the whole year are obtained; the data are processed, all the processed data are connected end to end, the data in rows form the transverse continuous data which are divided into M sections according to transverse time units THN, and all the data are transversely clustered; based on the transverse cluster result, a sample data source to be analyzed is divided into q transverse classes, and each class is represented by the respective clustering center; feature vectors are intersected and matched. The classes to which samples belong are judged through intersecting and matching of the feature vectors, generalized load modeling is utilized for setting up an accurate model and testing the effectiveness of the clustering strategy, and the simulation result shows that generalized load modeling carried out after clustering analysis makes the model practical on the basis of meeting the requirement for accuracy, and is beneficial for improving the simulation accuracy and the simulation effectiveness of an electrical power system.

The invention discloses a method for electricity-saving potential estimation on load involved demand response and load grouping aggregation of variable-frequency air conditioners. Based on load modeling of the variable-frequency air conditioners, an electricity-saving potential estimation model of the load involved demand response of the variable-frequency air conditioners is established according to the comfortable degree of human bodies, and a reference is provided for a variable-frequency air conditioner load dispatching objective formulated by the power grid dispatching department. Meanwhile, the corresponding method for the load grouping aggregation of an air conditioner group is provided, accordingly the total load of the air conditioner group can be scientifically and effectively kept as the dispatching objective stably, and finally the energy-saving and emission-reduction work of resources on the demand side is promoted.

A system configured to receive and automatically analyze various types of information, including, without limitation, information from energy generators, information from non-generation resources, information on the facility status, information on user behavior, information on user's short-term energy needs (e.g. over-ride any algorithm due to immediate charging need), information on renewable generation, including, without limitation, solar, wind, biomass and/or hydro, and information on environmental conditions including, without limitation, barometric pressure, temperature, ambient light intensity, humidity, air speed, and air quality. In one or more embodiments, a sole novel charging station or selected, aggregated groupings of the aforesaid novel charging stations are configured to start, modulate or stop charging, or start, modulate (down) or stop discharging over specific time intervals based on the electrical grid needs as automatically determined based on the totality of the received diverse information. To this end, a system and an associated method are provided to perform complete electrical charging load modeling to optimize power grid objectives.

This invention provides a real load module establishing system, which comprises load module establishing system, micro machine load dynamic characteristic recorder, load module establishing plat, remote management system, background analysis software system and power system artificial software interface. Its detail project is as the following: to adopt the digit collection, process, management and exchanging system centered as computer technique; the micro load dynamic characteristics recorder main functions are accomplished by software; the hardware system comprises CPU, BIOS device, data buffer, memory device and human to machine dialogue device and communication device.

The invention provides a load modeling method and a loading modeling system based on a comprehensive information theory and a modern interior point theory. The method comprises the following steps that the load data of a plurality of transformer substations is counted; the load characteristic index of each transformer substation is calculated according to the counted load data; each transformer substation is classified by a clustering method according to the load characteristic indexes obtained through calculation, and in addition, the typical transformer substation is selected; a synthetic load model is built for the selected typical transformer substation; and the modern interior point theory is utilized for identifying the parameters to be solved of the synthetic load model, and an optimal synthetic load model is built. The load modeling method and the loading modeling system have the advantages that precise parameter identification results can be effectively and fast obtained in the identification of the load model parameters, so the accuracy of the built load model is improved.

The invention discloses a non-invasive unitized current on-line measurement method of electric equipment, which is used for conducting the decomposition and monitoring of load and power consumption, electricity consumption analysis, load and energy conservation, load prediction and load modeling for an electric system; the method comprises the following steps: information on voltage and current is monitored at the entrance of electrical load and whether the electric equipment is input, if not, monitoring continues; if so, the next step is conducted; steady voltage and current data of the electrical load before and after the input of the electric equipment are recorded; harmonic analysis is conducted to data recorded at the previous step to obtain a current expression; difference value of the steady current of the electrical load before and after the input of the electric equipment is calculated; and the difference value of the current calculated in the previous step is unitized to obtain parameters of unitized current of the electric equipment. Without influence on the regular production and life of power consumers, the method can obtain the parameters of the unitized current of the main internal electric equipment and is more beneficial to the implementation of non-invasive electrical load decomposition.

A load modeling device based on real-time disturbance data comprises an analog quantity signal input board, a switching signal input board, an acquisition board, a backboard data bus, a GPS clock synchronization board, a monitor board and a supervisor unit, wherein the backboard data bus is connected with the analog quantity signal input board, the switching signal input board and the acquisition board respectively; the GPS clock synchronization board and the monitor board are connected with the acquisition board respectively; the supervisor unit is connected with the monitor board through the Ethernet. The real-time disturbance data obtained through field measurement are used for load modeling; parameter identification can be conducted on a static load model, a dynamic load model, a synthetic load model and a synthetic load model considering a distribution network to obtain the optimal load model within a selected load model range; the load modeling device records the data which can be directly used for load modeling, thereby being capable of providing a reasonable and practical load model for a grid and conducting real-time on-line identification on power load model parameters; moreover, the load model parameters can be used for realizing stable computational analysis of a data interface of simulation software BPA with a power system in common use.

The invention relates to an online dynamic load modeling method based on fault recorder data. The method is correct and effective, simple and high in precision compared with a parameter weighted average method and a clustering center method based on standard actual measured samples and can facilitate online dynamic load modeling based on the fault recorder data. The method includes that (1) on the basis of historical samples for identifying load model parameters, voltage excitation of new samples is exerted on a load model, and load power response is obtained; (2) the power response and actual measured power response of the new samples are fitted integrally and optimized to be a target, parameter optimization is conducted by adopting a curve fitting method, and a modified comprehensive load model is obtained, and only modified model parameters are stored instead of all historical samples.

The invention belongs to the technical field of power system measurement, and particularly relates to an online load analysis and modeling system and method for a power system. The system comprises adata recognition module, a load modeling data integrity checking module, a load analysis module, a load modeling module, a fault recording management module, and a fault fitting automatic adjustment module, collects the model data, network topology data and real-time data of a transformer substation and a power distribution network provided by a power dispatching technology support system and a power distribution automation system on line and the industry load classification and load actual measurement data provided by a marketing comprehensive data platform, and realizes the online load analysis and modeling functions of the load nodes by combining the load classification situation of a modeling system and adopting a comprehensive aggregation equivalence method. According to the present invention, by adopting the normalized load analysis and modeling work, the timeliness and accuracy of the load modeling are improved, the safe, reliable and economical operation of a power grid is guaranteed, and the implementation difficulty and workload of the load analysis and modeling are effectively reduced.

The invention discloses a distribution network reliability assessment method. Through element reliability modeling, load modeling, system state selection, system state analysis, and reliability indexes, reliability of a distribution network is calculated, and reliability of the distribution network is effectively assessed. The method comprises: using an equivalent model of elements based on frequency and duration as foundation of element reliability modeling; using a bisection method clustering method to establish a load model, using a quick sort and clustering analysis method to establish a corresponding load model; using a state duration sampling method to determine element state and state duration time of elements or subsystems in given time, to obtain state and state duration time of a system, as system state selection; using an optimal load shedding model based on DC power flow as system sate analysis; reliability index comprehensive assessment including system severity index SI, system cut-down electricity quantity index BPECI calculation and parameter reliability sensitivity, and through a parameter perturbation method, finding an element which has high influence on system reliability.

The invention discloses a generalized load modeling method for a distribution network containing a direct-drive permanent magnet wind farm. A simplified model of a direct-drive permanent magnet synchronous generator (DDPMSG) is proposed, and the direct-drive permanent magnet synchronous generator is connected in parallel with a traditional load to be used as a distribution network generalized load model structure containing a direct-drive permanent magnet wind farm. Based on a trajectory sensitivity method, the identifiability and identification difficulty of the parameters in the generalized load are analyzed. For parameter identification, global optimization is performed first using a particle swarm optimization (PSO) algorithm, and then, local optimization is performed on the basis of the PSO result using a Levenberg-Marquardt (LM) algorithm. The model structure of the direct-drive permanent magnet synchronous generator is simplified, and the proposed parameter identification method is of high precision. The modeling method can provide reference for generalized load modeling of other renewable energy access distribution networks containing a full-bridge converter.

The invention discloses a macrozone load modeling method in an intelligent power system, which comprises the following steps: establishing a macrozone load modeling system architecture with layers and grades for intelligent electricity meters installed at homes according to voltage grades; collecting and concentrating power information measured by the intelligent electricity meters and identified relevant load information in layers through an automatic message recording system; processing collected load through load modeling algorithm and establishing an accurate load model; establishing a macrozone load modeling system by voltage grades and the intelligent electricity meters installed at homes; collecting relevant information such as power of the electricity meters or load identification results and the like through the automatic message recording system; and comprehensively utilizing the existed load modeling algorithm to process the information. According to the macrozone load modeling method, the macrozone load modeling for the power system can be realized, and long-acting mechanism and widest coverage area for the load modeling can be realized based on the intelligent electricity meters.