70results about How to "Good convergence properties" patented technology

A method for calculating power flow solution of a power transmission network with unified power flow controllers is adapted to calculate the power flow on a large-scale power transmission network. The unified power flow controller has a series transformer, a series converter, a direct current coupling capacitor, a shunt converter, and a series transformer. The shunt transformer is connected electrically to a sending-end bus. The series transformer is connected electrically to the sending-end bus and a receiving-end bus. The unified power flow controller is represented by equivalent active and reactive loads on the sending-end and receiving-end buses of the power transmission network.

The invention discloses a self-adaptation compression reconstruction method based on energy effectiveness observation in a cognitive sensor network. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network comprises the steps that (1) a node carries out local detection and compression measurement on data which are actually sensed through an analog transcriber according to the characteristic that power consumption of the node of a cognitive sensor is limited, (2) a space-time relevance structure of sensing signals is used, sensing data are mapped to a wavelet orthogonal basis cascading dictionary to carry out sparse conversion and to carry out self-adaptation observation through a weighting energy subset function, appropriate observation values are obtained in an energy effectiveness mode, orthogonalization is carried out on selected observation vectors to construct a measurement matrix, (3) the sensing data after compression measurement are fed back to an aggregation node through a report channel, the aggregation node carries out self-adaptation reconstruction on the sensing data by using a gradient projection sparse reconstruction Barzilai-Borwein method based on a convex relaxation method, and effective compromise between reconstruction performance and energy consumption of the node is achieved. The self-adaptation compression reconstruction method based on the energy effectiveness observation in the cognitive sensor network can carry out accurate reconstruction on the sensing signals, ensures energy effectiveness of the sensing node, and has actual application significance.

An electric power steering apparatus for applying an assisting steering force to a steering mechanism of a vehicle by driving an electric motor according to a steering operation includes: an electric current command value calculation unit which calculates an electric current command value; a drive control unit which controls the drive of the electric motor based on the electric current command value; and a convergence control unit which determines a damping compensation value so that a quantity of steering operation is converged to a neutral point. The convergence control unit includes: a compensation electric current setting unit determines a basic damping compensation electric current value corresponding to the correction value of the target value, and a compensation electric current adjusting unit which adjusts the basic damping compensation electric current value based on the steering torque and the quantity of the steering operation, thereby calculating the damping compensation value.

The invention discloses an improved fuzzy neural network bus intelligent scheduling method based on a chaos theory, and belongs to the field of intelligent transportation. According to the improved particle swarm bus intelligent scheduling method based on the chaos theory, advantages and complementarity of various algorithms are fully utilized, a series of improvement measures are also introduced, such as conjugate gradient optimization, and inertia factor and constraint factor of the particle swarm algorithm etc., the mechanism and the search performance are researched from the theoretical and practical perspectives, problems of poor global search capability and premature convergence of the conventional optimization algorithm are fundamentally solved, the diversity of population can be obviously increased, the global search capability is obviously improved, the problem of fuzzy information can be effectively dealt with, the convergence speed is fast, and a new high-efficiency method is provided for bus intelligent scheduling.

The invention discloses a micro-grid energy management distribution type multi-target cooperation optimization algorithm based on a potential game. The algorithm comprises the following steps of 1) micro-grid component unit modeling which includes a determination decision main body, a decision variable, a component constraint and multi-target modeling; 2) potential game modeling, wherein an incomefunction and a potential function are vector functions; and 3) based on the distributed game solving of the multi-target optimization algorithm, mainly using a multi-target evolutionary algorithm tosolve the pareto optimal solution set of the income function, and through distributed iteration, solving nash equilibrium. In the invention, a distributed multiagent decision optimization mode is adopted, a potential game theory possessing a distributed characteristic is combined, the expansion of a microgrid is easy to realize, local management and local decision making are realized too, system reliability and flexibility are increased, through a game mode, the distributed multi-target optimization is realized, the competition and cooperate relation of the microgrid and an individual is achieved, and individual interests are guaranteed and the overall benefits of the microgrid are maximized.

The invention discloses a load flow calculation method and system for a power distribution network. The method and the system are not influenced by high resistance and reactance ratio of the distribution network on the basis that an element module of the distribution network adopts the forward-back substitution method, and have higher computational efficiency and favorable convergence characteristic. During establishing of a layered node array, a distributed power supply model is introduced, so that the method and the system meet the format of the grid to which a distributed power supply is accessed; and in the injection current computation process of nodes, the optimized open-loop model is utilized to simplify the algorithm and improve the algorithm efficiency, so that the method and the system are suitable for various occasions in the distribution network.

Disclosed is a simulated-annealing and conic optimization based power distribution network operation optimization method. The method includes: inputting basic parameters and information according to a selected power distribution system; according to the basic parameters and the information, establishing a mathematical model of power distribution network operation optimization problem concurrent with an interconnection switch and an intelligent soft switch and setting rotating cone constraints according to the network structure and scale to form a conic optimization model of the power distribution network operation optimization model concurrent with the interconnection switch and the intelligent soft switch; according to the basic principle of a simulated annealing method and network topological constraints, randomly generating a feasible switch-state combination, and performing calculation on the cone optimization model of the power distribution network operation optimization problem concurrent with the interconnection switch and the intelligent soft switch by adopting a cone optimization tool; outputting a calculation result and analyzing the optimal calculation condition by the aid of the simulated annealing principle. States of the interconnection switch in the power distribution system and transmission power of an SNOP (soft normally open point) are considered from the economic perspective of operation of the power distribution system, and the optimum switch combination of the interconnection switch in the power distribution network and the optimum transmission power of the SNOP are determined.

The invention relates to a self-adapting predistorter and a self-adapting predistortion method in an Orthogonal Frequency Division Multiplexing (OFDM) system comprising error calculation of signals after once predistortion processing and twice predistortion processing for OFDM source signals, self-adapting iteration operation of error signals and renewal of predistortion coefficients which enable the error signals to approach to zero. The self-adapting predistorter of the invention includes a first predistortion unit, a second predistortion unit, an error signal calculation unit and a self-adaptive algorithm unit. The technical scheme of the invention effectively expedites convergence rate of a query table at the same time of not increasing the algorithm complexity, obtains smaller mean error and simultaneously reduces the algorithm hardware implementing complexity.

The invention discloses a general power flow calculation method of a power system provided with a UPFC (unified power flow controller). According to the method, under a premise that the control objective of the UPFC is satisfied, a power injection model and Newton-Raphson method are combined so as to solve the power flow of the power system iteratively. The method is not only suitable for UPFCs of traditional structures, but also suitable to novel UPFCs of which the parallel sides and series sides are connected with different bas-bars or novel UPFCs provided with a plurality of series branches. The present invention also provides specific calculation steps and calculation formulas of power flow calculation. Thus, when the method of the invention is adopted to carry out power flow calculation, new state variables are not needed to be added, the dimensions of Jacobian matrix will not be increased in an iteration process; and the method is easy to implement and has an excellent convergence characteristic.

The invention discloses a power distribution network energy dispersion coordination and optimization method based on reweighted acceleration Lagrangian. The method establishes a multi-time scale linear cone optimal power flow module and utilizes a virtual auxiliary variable split node to decompose the power distribution network into a plurality of area sub systems, and puts forward a dispersion coordination and optimization method based on local area reweighted acceleration Lagrangian to implement dispersion coordination and optimization of active and reactive resource of the whole network. The power distribution network energy dispersion coordination and optimization method enables each sub system to realize parallel synchronization iterative solution, and has no requirement for overall coordination, and only a small quantity of information interaction is required between adjacent sub systems. The power distribution network energy dispersion coordination and optimization method is high in calculating efficiency and is high in convergence characteristic.

The present invention provides a kind of power system environmental economic dispatching strategy based on improved multi-objective gravitational search algorithm, and the method comprises the following steps: 1. Constructing while considering that the minimum operating cost of the system and the minimum discharge of pollutants are objective functions, and establishing electric power System environmental economic optimization scheduling model; II. Established a power system environmental economic scheduling model that comprehensively considered system operating costs and pollutant discharge costs, and proposed an improved multi-objective gravity search algorithm to solve the model; III. For basic In order to solve the problem of slow convergence speed of the gravity search algorithm, in the process of updating the individual position, inspired by the particle swarm optimization algorithm, the position update formula of the gravity search algorithm has been improved; IV. In order to guide the group to approach the Pareto optimal solution set area and ensure the algorithm The solution set is evenly distributed, and the elite retention strategy is adopted; V. The fuzzy set theory is used to generate the best compromise solution, and a scheduling plan is provided for decision makers.

The invention relates to a self-adapting predistortion method based on a two-dimension query table in an Orthogonal Frequency Division Multiplexing (OFDM) system comprising error calculation of signals after once predistortion processing and twice predistortion processing for OFDM source signals, self-adapting iteration operation of error signals and renewal of predistortion coefficients which enable the error signals to approach to zero. The predistortion processing employs a method that obtains an amplitude predistortion coefficient and a phase predistortion coefficient through a united index of a first dimension index address X(n) and a second dimension index address Y(n), wherein the second dimension index address Y(n) is calculated by historical input amplitude values. The technical scheme of the invention effectively overcomes memory effect of a power amplifier, and effectively expedites convergence rate of the query table at the same time of not increasing the algorithm complexity, obtains smaller mean error and simultaneously reduces the algorithm hardware implementing complexity.

The invention discloses an AC-DC micro-grid distributed scheduling method based on reweighed acceleration Lagrangian. According to the method, an AC-DC mixed micro-grid linear cone optimal power flow model including converter power flow restraint is built, an AC-DC mixed micro-grid is divided into an AC micro-grid subsystem and a DC micro-grid subsystem by employing a virtual auxiliary variable method, a distributed coordination optimization method based on local reweighing Lagrangian is proposed, and distributed coordination optimization of resource scheduling of the whole grid is realized. According to the method, parallel and synchronous iterative solution of various subsystems can be realized, global coordination is not needed, only a little information interaction between the adjacent subsystems is needed, the calculating efficiency is high, and the convergence characteristic is good.

The invention belongs to the field of multi-underwater-robot cooperative control and particularly relates to a multi-AUV-hunter cooperative control method based on a lion group algorithm. For the problem that a single AUV is unable to complete a complex underwater task, the intelligent interactivity of hunting robots is insufficient and obstacles are in an actual three-dimensional environment, thepresent invention discloses the multi-AUV-hunter cooperative control method based on a lion group algorithm. The invention is for the case of three or more hunters. In the case that the moving performance of the hunters in a hunter group is equivalent, through diving and rising operations, while the same water depth as a target is maintained, a target is surrounded in a geometric center, and thehunters are uniformly distributed around the target with the target as a center and a distance r as a radius to complete the cooperative hunting. The lion group algorithm (LGA) is applied to perform AUV hunting cooperative control, the hunting efficiency is higher, and the convergence characteristic is better.

The invention discloses a fault diagnosis parameter recognition method of a realtime electronic circuit, comprising the following steps: all element parameter increment of a to-be-tested electronic circuit is substituted by an equivalent power supply; a circuit is excited repeatedly by a current source at a testable node to obtain an impedance matrix Zm of testable node voltage and testable node current excited by the testable node voltage and the mixed matrix H of the testable node voltage and the equivalent power supply; the testable node voltages of a to-be-tested circuit and a normal nominal circuit are measured and the difference value of the voltages is calculated, thereby establishing a circuit testing and diagnosis characteristic equation; the element parameter increment and node voltage increment are taken as optimizing variable to establish a parameter recognition equation through making use of the optimization theory and combining with the testing and diagnosis characteristic equation; moreover, the parameter recognition equation is solved through making use of a neural network and a transconductance neural network based on the augmented lagrangian multiplier method; finally, fault recognition is completed according to the output of the neural networks. The fault diagnosis parameter recognition method which has the advantages of realtime character and high locating accuracy is suitable to be used under quick diagnosis condition in modern industry.

The invention discloses an optimization calculation method of a wind power plant power fluctuation stabilization target value. The optimization calculation method comprises the following steps that: 1) wind power plant output power PT (t) within a time section T is selected; 2) the wind power plant output power PT (t) is divided into k segments, wherein the power offset quantity of the i-th segment can be obtained through the formula mentioned in the description, wherein the PG.i is the target power value of the i-th interval segment, the ti-1, and ti are starting time and finishing time of the i-th interval segment respectively, the t0 is the starting time of the selected time section wind power plant out power PT (t), and in a selected time section of t0 to tk, the equation of t0 <t1 <...tk-1<tk is satisfied; and 3) minimization of the total square deviation of power offset quantity P delta.k.i is adopted as a target, starting time ti-1 corresponding to each branch end and a target power value PG.i of each segment are optimized through the target function formula mentioned in the description. With the optimization calculation method of the wind power plant power fluctuation stabilization target value of the invention adopted, high-degree optimization of related evaluation indexes can be realized, and local search ability in the aspect of solution algorithms is improved, and the validity and accuracy of data calculation can be ensured, and scheduling and decision-making requirements can be satisfied.

The invention relates to an acquisition method of model parameters of the electromechanical transient state simulation of a motor based on factory data, which estimates the motor single-cage model parameters suitable for the electromechanical transient state simulation of an electrical power system on the basis of the factory data (such as rated power, rated power factor, maximum torque multiple, rotor rotation speed, and the like) of an induction motor. The algorithm sufficiently considers the torque-slip physical principle characteristics of the motor, has good convergence and high robustness and provides convenience for the selection of the motor model parameters adopted in the simulation of the electrical power system.

The invention discloses a cognitive radio network power distribution method with multichannel cooperative communication. A cognitive radio network is at least formed by two master user transmit-receive ends, two secondary user transmit-receive ends, one relay transmit-receive end and two channels based on an underlay spectrum sharing mode. Secondary users and master users can transmit respective data in the same channel at the same time, and the secondary users can transmit data with the cooperation of a relay device. Strict power control is required to be implemented when the secondary users transmit the data, so that the interference caused on the communication of the master users is ensured to be no more than interference limitation. The method aims to enable the two secondary users to reasonably distribute power on the two channels so as to maximize respective transmission capacity, and ensures that the interference on the two master users is lower than the limitation at the same time. A power distribution problem is modeled as a non-cooperative game, which is proved to meet the supermodel characteristic, so that balance exists. According to a favorable convergence property of a supermodel game, a best response updating algorithm is provided for reaching a break-even point, so that reasonable power distribution is realized.

The invention provides a load model building method of considering load frequency characteristics. The method comprises the following steps: obtaining a frequency characteristic curve of a load component; calculating an active power-frequency characteristic coefficient and a reactive power-frequency characteristic coefficient of the load component; dividing the load component into a static load and a dynamic load according to the load characteristic; calculating the active power-frequency characteristic coefficient and the reactive power-frequency characteristic coefficient of the static load; calculating the active power-frequency characteristic coefficient and the reactive power-frequency characteristic coefficient of a load node; and determining a mechanical torque coefficient of an asynchronous motor of the load node. According to the load model building method, the defect that a traditional load model cannot accurately describe the load frequency characteristics is overcome; the simulating calculation credibility of a power system is improved; and a forceful guarantee is provided for scientific planning and safe and stable operation of the power system.

The present invention discloses a cognition-type blind source separation radiant source extraction method and an evaluation method thereof. The method of spectral estimation based on matrix eigenvalue decomposition is employed to obtain the estimated values of the irradiation source direction and the number, the constant false alarm detection technology is employed to determine the number of the irradiation sources, and the blind source separation method is employed to realize the separation of the blind source signals to obtain the separation signals of the irradiation source signals. The cognition-type blind source separation radiant source extraction method and the evaluation method thereof can recover relatively independent irradiation source signals in the condition of the unknown number of the irradiation source signals and have good separation precision.

The invention provides a building method of a motor load model. The method comprises the following steps: building the motor load model; carrying out accident simulating calculation on the motor load model; and determining frequency characteristic parameters of the motor load model. According to the building method of the motor load model provided by the invention, frequency parameters of various motor loads are accurately determined; and the method has great significance in improvement of the simulation precision and guarantee of the safety and the reliability of normal operation of a power grid. Torque-slip physical mechanism characteristics of motors are fully considered; the motor load model is good in convergence characteristics and high in robustness; the defect that a traditional load model cannot accurately describe load frequency characteristics of an asynchronous motor cluster is overcome; the simulating calculation reliability of a power system is improved; and a strong guarantee is provided for scientific planning and safe and stable operation of a power system.

PCT No. PCT / JP95 / 01401 Sec. 371 Date Jan. 14, 1997 Sec. 102(e) Date Jan. 14, 1997 PCT Filed Jul. 14, 1995 PCT Pub. No. WO96 / 02935 PCT Pub. Date Feb. 1, 1996An electron energy filter includes a first pair of magnetic poles for generating a first deflecting magnetic field and a second pair of magnetic poles for generating a second deflecting magnetic field in the same direction as the first deflecting magnetic field. The incident electrons are deflected about 90 DEG with a trace radius of AM1 through the effect of the first deflecting magnetic field, passed through a free space having a distance DL2 that is about a half of the trace radius AM1 and then are incident to the second deflecting magnetic field. The electrons are deflected about 180 DEG with a trace radius AM2 that is about a half of the curvature radius AM1 and are passed through the free space DL2. Then, the electrons are incident to the first deflecting magnetic field again where those electrons are deflected about 90 DEG . The deflected electrons are traveled like a gamma trace so that those electrons outgo in the same direction as the incident one. This filter so designed is made compact and to have a smaller aberration.

The invention discloses an active power distribution network distributed type reactive optimizing method based on an equal network loss increment rate. The control method comprises steps that step 10) initialization: partition reactive optimization parameters are initialized; step 20) partition reactive optimization solution: according to a partition trend calculation result, the equal increment rate is used to solve reactive power adjustment amounts of various distributed power supplies and reactive compensation devices; step 30) inter-partition information interaction: information interaction between adjacent partitions is carried out, and the operation states of the partitions are updated; step 40) convergence determining: whether active power deviation of a main station node is smaller than a predetermined convergence threshold is determined, and when the active power deviation of the main station node is smaller than the predetermined convergence threshold, iteration is stopped, and when the active power deviation of the main station node is not smaller than the predetermined convergence threshold, whether a maximum iteration time is achieved is determined, when the maximum iteration time is achieved, the iteration is stopped, and when the maximum iteration time is not achieved, the iteration time is plus one, and the step 20) is carried out again. The control method is advantageous in that based on a distributed type communication architecture and an equal network loss increment rate rule, convergence speed is fast, and the reactive distributed type coordinated optimization of a plurality of partitions and distributed type optimization of global network losses are realized, and robustness of active power distribution network reactive optimization control and reliability of power supply are improved.

The invention relates to a load flow calculation method for an AC / DC parallel serial system based on an improved LM algorithm. The method comprises the following steps: (1) acquiring a load flow calculation equation set F(X) of the AC / DC parallel serial system, setting an initial iteration point and an initial self-adaption factor, wherein iteration K=1; (2) acquiring a jacobian matrix of the iteration at k time according to F(x); (3) gaining a damping factor of the iteration at k time according to the self-adaption factor of the iteration at k time, thereby acquiring an iterative step length and an approximate iterative step length of the iteration at k time; (4) calculating a choice factor of the iteration at k time and adjusting the iteration point and the self-adaption factor according to the choice factor, thereby acquiring the iteration point at k+1 time and the self-adaption factor for the iteration at k+1 time; and (5) judging if an iteration ending condition is met, if so, acquiring the load flow calculation data of the AC / DC parallel serial system, otherwise, assigning k=k+1 and returning to the step (2). Compared with the prior art, the method provided by the invention has excellent convergence character.

A method and a system for identifying third-order model parameters of a lithium battery based on a likelihood function are provided, which relates to a method for estimating battery model parameters of a lithium battery under different temperatures, different system-on-chips (SOCs), and charge-discharge currents. The method includes the following steps. A third-order battery model of the lithium battery is established. A battery model output voltage Ud and a total battery current I under different temperatures, different SOCs, and charge-discharge currents are collected. The likelihood function is adopted to construct an identification model, and the collected data is substituted into the identification model to calculate the battery model parameters. Identified parameters are substituted into the third-order battery model to obtain a battery terminal voltage to be compared with a measured terminal voltage. The operation method of the disclosure is simple and effective, and can accurately estimate internal resistance parameters of the lithium battery.

The invention discloses an overhaul plan making method and system for power transmission equipment. The method comprises the following steps: obtaining the construction period of each power transmission equipment and a power failure window period capable of arranging overhaul; substituting the construction period of each power transmission device and the power failure window period capable of arranging overhaul into a pre-constructed overhaul plan optimization model, and performing calculation by utilizing an improved universal gravitation search algorithm to obtain overhaul time of each device; making an overhaul plan based on the overhaul time of each device, wherein the overhaul plan optimization model is constructed by taking minimum renewable energy power generation and minimum overhaul quantity distribution variance as targets and taking overhaul time requirements, power grid safety operation requirements and daily overhaul quantity requirements of the power grid for each deviceas constraints. The improved universal gravitation search algorithm based on the simulated annealing thought provided by the invention is suitable for solving the overhaul plan problem containing discrete variables, and the equipment overhaul time can be reasonably arranged.

The invention provides a side cloud collaborative digital twin intelligent production scheduling application operation position adaptation method. An applied intelligent production scheduling system comprises a cloud layer, an edge layer and a device layer. The generated digital twinning systems are arranged on the edge layer and the cloud layer; and an adaptive strategy controller is arranged on the cloud layer. The adaptation strategy controller dynamically senses edge and cloud resource states, application attributes and the like in the production process, and carries out real-time adaptation switching on the operation position of the digital twin intelligent production scheduling application under two conditions of a determined environment and a non-determined environment by taking minimization of digital twin intelligent production scheduling decision period delay as a target; and real-time adaptive switching is performed on the operation position of the digital twin intelligent production scheduling application based on prediction in an uncertain environment. By adopting the method provided by the invention to determine the operation position of the digital twinning intelligent production scheduling application, the performance loss caused by delay of data interaction and instruction issuing based on a digital twinning system is reduced, and the guarantee based on the digital twinning production scheduling precision is improved.