32 results about "Cone programming" patented technology

The present invention provides a mixed integer cone programming based intelligent distribution system synthetic voltage reactive power optimization method. The method comprises: inputting a distribution system structure and a parameter of a distribution system; establishing a time sequence optimization model of a distribution system synthetic voltage reactive power control problem considering various types of adjustment means; converting the established model into a mixed integer second-order cone model; solving the obtained mixed integer second-order cone model by using a mathematical solver capable of solving mixed integer second-order cone programming; and outputting a solution result. The method provided by the present invention greatly reduces solving difficulty and facilitates performing solution by using a solving tool, so that a complex mixed integer non-linear programming problem can be solved, cumbersome iteration and a large number of tests are avoided, and the calculation speed is greatly improved.

The invention provides a modeling method for a production scheduling problem distribution set robust model, which belongs to the field of production scheduling and operations research. A distributed set robust optimization method based on an uncertain distribution function set is adopted to model the production scheduling problem, the model is composed of an objective function and constraint conditions, the objective of the model is to search for an optimal robust scheduling sequence, and thus, in a condition in which the total flow time of the sequence obeys the worst distribution in the processing time, the minimum condition risk value is realized. In the case of solution, the model is decomposed to an assignment subproblem and an integer two-order cone programming subproblem, and a minimum average processing time priority criterion and two Cauchy relaxation algorithms designed by the invention are adopted to optimize the model and obtain the optimal solution. The distribution set robust optimization method is applied to the production scheduling problem, the method is more applicable to the actual production condition compared with the existing robust modeling method, and in a condition of ensuring the system performance, a decision risk is reduced.

The invention provides a distributed power supply local voltage control strategy setting method based on cone programming. An active power distribution system structure and parameters are inputted according to a selected active power distribution system; the sequential characteristics of distributed power supply output and load are considered according to the active power distribution system structure and parameters, and an active power distribution network distributed power supply local voltage control strategy setting model is established; the objective function in the model is linearized, and linearization or cone conversion is performed on the nonlinear constraint so that the active power distribution network distributed power supply local voltage control strategy setting model is enabled to be converted into a second-order cone model; the second-order cone model is calculated by using a mathematical solver solving second-order cone programming; and the solving result is outputted, including the relevant parameters of the distributed power supply local voltage control strategy, the voltage distribution situation of the distributed power supply, the reactive compensation situation and the active reduction situation. The distributed power supply local voltage control strategy can be obtained so that the setting problem of the distributed power supply local voltage control strategy under continuous time sequences can be solved.

The invention discloses a construction and calculation method of a random distributed robust beam former. The method comprises the following steps: step S1, setting a sensor array; step S2, receivinga signal; step S3, estimating an interference and noise covariance matrix; step S4, acquiring an expression of the beam former in an ideal state; step S5, introducing random distribution of mismatch vectors in ideal planning of the beam former, and obtaining the random distributed robust beam former; and step S6, reconstructing the random distributed robust beam former into a cone programming expression capable of being calculated by a standard software package. The invention proposes the random distributed robust beam former which is more universal and practical and better in performance andthe calculation method thereof.

The invention discloses an optimal power flow calculation method containing wind power access based on robust cone programming, and belongs to the technical field of power system dispatching automation. The method comprises the following steps: according to prediction data of day-ahead wind power output and load, taking minimum power generation cost of a unit as a target function, describing uncertainty of wind power output by an uncertain set in a polyhedron form, introducing alternating current power flow constraint to carry out safety check, and constructing a robust cone programming model based on alternating current power flow; performing cone relaxation on the non-linear constraint, and processing a non-linear term by using an auxiliary variable substitution method so as to obtain a cone programming model; in order to solve the uncertainty optimization problem, using a C&CG algorithm to decompose the model into a main problem in a basic scene and a sub-problem in an uncertain scene, substituting unit commitment decisions solved in the basic scene into safety verification in the uncertain scene, performing dual transformation of inner layer optimization, solving a dual cone programming model, and obtaining a globally optimal solution.

The invention provides a voltage optimization method for a flexible interconnection power distribution system. The method comprises the following steps: building a voltage optimization model based on distribution robust opportunity constraint, and constructing an uncertainty probability set for a random variable through a Wasserstein distance; for an objective function and constraint conditions in the model, setting the objective function by taking minimum network loss and minimum voltage deviation as objectives, meanwhile, setting power balance constraint, substation outlet power constraint, CB and OLTC operation constraint and flexible interconnection device operation constraint as hard constraint conditions, and setting node voltage and branch power as opportunity constraint conditions of the model; and constructing a voltage optimization model. The built model is difficult to directly solve, so that the mixed integer random second-order cone programming algorithm is used for solving. According to the optimization model and the solving method thereof, the uncertainty of the source load can be effectively handled, so that the operation safety of the power distribution system is guaranteed.

The invention discloses a distribution robustness optimization method suitable for a power distribution network unit combination, and the method comprises the steps: constructing a fuzzy set based onstatistical data based on the statistical data of renewable energy output; introducing an auxiliary variable, and rewriting a fuzzy set; based on the fuzzy set, establishing a power distribution network unit combination model based on distribution robustness optimization; converting the model into a mixed integer second-order cone programming model by applying an affine strategy, a strong dual theory and a second-order cone dual theory; and solving the mixed integer second-order cone programming model. According to the method, the problems that stochastic programming depends too much on accurate probability distribution and the calculated amount is too large are solved, and the problem that traditional robust optimization is too conservative is effectively avoided. According to the method,the power distribution network unit commitment model is finally converted into the mixed integer second-order cone programming model which is easy to solve, the calculation efficiency is greatly improved, the model can be directly solved on modeling software such as GAMS, and the solving difficulty is reduced.

The invention discloses an elliptical object feature extraction method based on a maximum entropy criterion, and the method comprises the steps: carrying out the preprocessing of a picture of an elliptical object so as to remove noise, and detecting all edge data points including outliers; describing an algebraic distance between a to-be-solved ellipse corresponding to the elliptical object part in the preprocessed picture and each edge data point in a model manner; introducing a maximum entropy criterion to obtain an optimization problem based on the maximum entropy criterion; converting theoptimization problem based on the maximum entropy criterion according to the property of the convex conjugate function; decomposing the converted problem into two sub-problems, wherein the first sub-problem can be converted into a standard second-order cone programming problem, and the second sub-problem has a closed-form solution; solving the parameters in a general equation of the ellipse in aniterative mode, obtaining the ellipse corresponding to the ellipse object part in the preprocessed picture through fitting, and then determining the position of the ellipse object is determined. The method has the advantage that the position features of the elliptical object can be accurately extracted.

Compared with the conventional technology, the variable decimal time-delay filter design method based on segmented frequency domain optimization has the main advantages that the frequency response error function of the variable decimal time-delay filter is segmented, and the filter coefficient is solved independently through second-order cone programming in each segment; and therefore, the designed variable decimal time delay filter has lower implementation complexity under the condition of meeting the requirements of design indexes. According to the method, the joint optimization of the polynomial order and the sub-filter order can be realized, so that the polynomial orders of different segments are different, the sub-filter orders in the same segment are different, and the realization complexity is further reduced.

The invention discloses a power supply recovery method and system based on second-order cone programming. The method comprises the steps of bringing an obtained on-off state, line parameters and distributed power supply output of a power distribution network into a pre-constructed power distribution network power supply recovery model; performing cone relaxation on the power distribution network power supply recovery model based on a set relaxation variable; and solving the power distribution network power supply recovery model after cone relaxation by adopting a second-order cone programming algorithm to obtain the on-off state of the power distribution network and the output of the distributed power supply. According to the power distribution network power supply recovery model, a power distribution network on-off state, a branch node relationship and distributed power supply output are taken as control variables, virtual nodes are added in branches containing switches according to the positions of the switches in the branches, virtual branches are formed based on the virtual nodes, and construction is performed on the basis of branch power flow. Different operation characteristics of sources and loads in the power distribution system are considered, and when a user power failure accident occurs, the maximum power supply recovery level can be rapidly guaranteed.

The invention discloses a method and device for establishing a weir body model. The method comprises the following steps: obtaining the geometric dimension of a weir body, and constructing a second-order cone programming model according to the geometric dimension of the weir body; calculating dissipated energy of each unit in the second-order cone programming model; determining and marking an encryption unit and a sparse unit in the second-order cone programming model according to the dissipated energy sequence of each unit; adding a new node on the long edge of the encryption unit, adding a new node on the common edge of the two sparse units, and deleting two end points of the common edge to form a node cloud set; a second-order cone programming model based on Delaunay triangulation redivision is established according to the node cloud set, and when the new second-order cone programming model meets preset initial and boundary conditions, the new second-order cone programming model serves as a weir body model; according to the method, the second-order cone programming model can achieve the effect of simulating the sliding surface in a long, narrow and dense grid form, the key parameters of the sliding surface are accurately defined, and a basis is provided for formulating engineering measures.

The invention provides an active power distribution network distributed energy storage system optimal configuration method and device. A traditional energy storage optimal configuration method and a shared energy storage idea are combined to establish a three-layer planning model of shared energy storage optimal configuration, namely an upper-layer model, a middle-layer model and a lower-layer model, and the model is solved by adopting a method of combining a genetic algorithm and cone programming.

The invention discloses an active power distribution network hierarchical optimization method based on second-order cone programming and demand side management. The user layer divides the load into peak-valley-normal periods, determines peak-valley electricity prices, and makes different management means for different load types to achieve a peak-clipping and valley-filling effect; the power distribution network layer takes the minimum network loss as a target, considers the control of active regulation and control objects such as photovoltaic power generation, wind power generation, an energy storage system, a static var compensator and a grouped switched capacitor bank, and converts the optimal power flow problem into a second-order cone programming model by a second-order cone relaxation technology. According to the method provided by the invention, peak clipping and valley filling can be realized by performing different demand side management on different loads, the power supply pressure of the system is relieved, and the active power distribution network hierarchical optimization model considering the demand side management not only can effectively reduce the network loss of the system, but also can reduce the power consumption cost of users.

The invention discloses a beamforming method and a heterogeneous cloud wireless accessing network based on same. The method comprises the following steps of calculating data transmission rate of a cellular user, calculating the data transmission rate of an RRH user, calculating the total data transmission rate and total power consumption of the heterogeneous cloud wireless accessing network, determining a beamforming vector combined optimization problem of an MBS and a RRH, and solving a beamforming vector combined optimization problem of the MBS and the RRH. The heterogeneous cloud wireless accessing network comprises a baseband processing unit pool and a plurality of macrocellular networks. Each macrocellular comprises a macro base station MBS, a plurality of wireless remote RF module (RRH), a plurality of cellular user and a plurality of RRH users. According to the method, an original optimization problem is converted to an easy processing two-order cone programming method, therebyimproving energy efficiency of the heterogeneous cloud wireless accessing network, suppressing interference in the network and reducing total power consumption of the network.