17 results about "Cone programming" patented technology

The present invention discloses a method for siting and sizing a flexible soft switch of a distribution network based on mixed second-order cone programming, including: acquiring interconnected flexible distribution system data; establishing and optimizing, based on the interconnected flexible distribution system data and an interconnected flexible distribution system constraint, a flexible soft switch siting and sizing model with a minimal daily comprehensive operation cost as an objective; and acquiring an optimal flexible soft switch siting and sizing solution by using combination of an improved sparrow algorithm and second-order cone programming to solve. The present invention is both reliable and economic.

The application provides a kind of based on second-order cone relaxation energy storage power distribution network multi-objective optimization method and system, the method includes: constructing the power flow model of power distribution network, and constructing node power balance constraint, voltage drop constraint, operating boundary constraint;Second-order cone relaxation is used to constrain the alternating current power flow relationship of power flow model, and second-order cone relaxation constraint is obtained;With the minimum network loss as the first goal, the minimum generation cost as the second goal, all constraints and optimization goals are summarized to obtain a second-order cone programming model;According to the adjacency matrix, the loop phase angle consistency constraint about the set of mesh is constructed;The second-order cone programming model is solved, and the solving result is checked according to the loop phase angle consistency constraint, if the check fails, the solving result is adjusted, and the solving is re-performed, until the latest solving result meets the loop phase angle consistency constraint.The application can consider high accuracy, high efficiency and high real-time energy storage optimization.

The invention discloses an active power distribution network robust optimization method and system based on adaptive data driving, and relates to the technical field of power system optimization, and the method comprises the steps: sampling historical data of distributed new energy output, and constructing a box type set to envelope all historical output data points; based on the box-type set, cutting the box-type set by using a hyperplane, and further constructing a hyperplane polyhedron set to envelope historical data; coupling is carried out based on a hyperplane polyhedron set and distributed new energy output, and an active power distribution network robust scheduling model based on adaptive data driving is established; a strong duality theory is utilized to perform duality conversion on a max-min problem, a mixed integer second-order cone programming method is adopted, Yalmip of a Matlab toolbox is utilized to perform modeling, and a commercial solver is called to perform solving. The novel power distribution system optimization operation method based on data driving can bear prediction errors, and the decision result has certain accuracy.

This invention relates to an optimal scheduling method and system for an electro-hydrogen coupling system based on truck flexibility and relaxation-repair warm-start technology. The method includes: acquiring basic data of the electro-hydrogen coupling system; constructing a power system model, a hydrogen energy system model, a pipeline congestion management model, and a hydrogen truck transportation model, wherein the pipeline congestion management model is a truck-based pipeline congestion management model that treats hydrogen trucks as flexible resources; establishing constraints and constructing an optimal scheduling model with the goal of minimizing the total system operating cost over the entire scheduling cycle; transforming the optimal scheduling model into a convex programming model using a mixed-integer second-order cone programming reconstruction technique; and solving the convex programming model using a relaxation-repair warm-start algorithm, considering the physical state information of the system, to obtain the optimal scheduling result. Compared with existing technologies, this invention has the advantages of actively alleviating pipeline physical congestion and high computational efficiency.

The invention discloses a sliding bearing fault diagnosis model construction method and device, equipment and a medium. The method comprises the steps of generating a training set based on historical operation data of a sliding bearing and corresponding multi-dimensional target features; constructing a convex quadratic programming problem of a support vector machine by using the training set according to an interval maximization strategy, and converting the convex quadratic programming problem into a second-order cone programming problem; and solving the second-order cone programming problem by using a solver to obtain an optimal sparse weight vector and offset, and obtaining a sliding bearing fault decision function based on the optimal sparse weight vector and offset to obtain a sliding bearing fault diagnosis model so as to carry out sliding bearing fault diagnosis. By fusing the multi-source operation data and the multi-dimensional target characteristics of the sliding bearing, the defect of single-dimensional data is overcome, and the accuracy of fault state diagnosis is improved; and moreover, the convex quadratic programming problem of the support vector machine is converted into the second-order cone programming problem for efficient solving, so that the solving efficiency is improved.

The invention discloses an integrated energy system dynamic optimal power flow method based on second-order cone relaxation and convex approximation, and the method comprises the steps: constructing an optimal power flow model of an integrated energy system which is an electric, thermal and gas integrated energy system; a two-dimensional cone relaxation technology is adopted to restrain the non-convex power flow of the power distribution network in the optimal power flow model, and controlled convex approximation is carried out on nonlinear equations of a gas network and a heat network in the optimal power flow model to obtain a convex optimization model; adding an optimization framework of multi-time scale dynamic characteristics into the convex optimization model to form a mixed integer second-order cone programming model; and solving the mixed integer second-order cone programming model by adopting a Gurobi solver to obtain a load flow calculation result of the integrated energy system.

The invention provides a non-convex nonlinear steady-state airflow collaborative optimization method suitable for a hydrogen energy system, and the method comprises the steps: carrying out the layering processing of an original optimization model according to the structural characteristics, and constructing an upper-layer problem into a centralized second-order cone programming model which can be efficiently solved, decomposing the lower layer problem into a plurality of mutually independent quadratic programming sub-problems with a non-convex quadratic constraint; equivalently converting the quadratic programming sub-problem into a characteristic value sub-problem; estimating the optimal characteristic value of the target matrix based on the target function and the constraint condition of the characteristic value sub-problem, and performing dynamic correction by adopting transformation to obtain a lower-layer optimization variable solution; and performing information interaction between the lower-layer variable and the upper-layer decision variable on the basis of an alternating direction multiplier method framework, and performing iterative correction on the upper-layer variable by utilizing a lower-layer optimization variable solution until the global residual error meets a preset convergence criterion, thereby obtaining an optimal decision variable and an optimal value. According to the method, the solving efficiency and the physical precision are both considered.

The invention relates to a millimeter wave ISAC system perception performance optimization method based on sub-connection hybrid precoding. The method comprises the following steps: establishing an echo signal model containing an interference source; constructing an optimization problem with the aim of minimizing the Cramer-Rao bound; solving a digital and analog precoder by adopting an alternating optimization strategy; wherein the digital precoding is converted into second-order cone programming through successive convex approximation, and the analog precoding realizes efficient solution under constant modulus constraint through Riemannian manifold optimization. According to the method, collaborative optimization of the communication performance and the sensing performance of the millimeter wave ISAC system is realized through a hybrid precoding algorithm of alternate iteration optimization, a digital precoder design based on a successive convex approximation method and an analog precoder design based on Riemannian manifold optimization.

The application discloses a sliding bearing fault diagnosis model construction method and device, equipment and medium. The method comprises the following steps: generating a training set based on historical operation data of a sliding bearing and corresponding multi-dimensional target features thereof; constructing a convex quadratic programming problem of a support vector machine by using the training set according to an interval maximization strategy, and converting the convex quadratic programming problem into a second-order cone programming problem; obtaining an optimal sparse weight vector and a bias by using a solver to solve the second-order cone programming problem; obtaining a sliding bearing fault decision function based on the optimal sparse weight vector and the bias to obtain a sliding bearing fault diagnosis model and to perform sliding bearing fault diagnosis. By fusing multi-source operation data of the sliding bearing and multi-dimensional target features thereof, the shortcomings of single-dimensional data are made up, and the accuracy of fault state diagnosis is improved. Furthermore, the convex quadratic programming problem of the support vector machine is converted into the second-order cone programming problem for efficient solving, and the solving efficiency is improved.

The application discloses a second-order cone relaxation-based optimal power flow solving method containing transient stability constraints of wind power, and comprises the following steps: step 1, wind speed is predicted, wind power output scenarios are generated by combining Latin hypercube sampling (LHS), and K-means clustering is used to reduce the scenarios to obtain typical scenarios of wind power output and corresponding occurrence probabilities, so as to represent and process the uncertainty of wind power; step 2, an initial architecture of a transient stability-constrained optimal power flow (TSCOPF) model containing an objective function, static constraints and transient stability constraints is constructed; step 3, a second-order cone relaxation (SOCR) is used for non-convex items in a power balance equation in the TSCOPF model, and a successive inscribed polygon method is used to reduce a relaxation gap, then, the relaxed power balance equation is integrated with linear inequality constraints obtained by transformation in step 2 and other static constraints, and the original TSCOPF model is overall converted into a mixed integer second-order cone programming problem; and step 4, an optimal power flow solving result satisfying the transient stability constraints is obtained.

This invention discloses a method and apparatus for estimating automobile dismantling waste based on cone programming, comprising: Step 1, establishing a coupling equation between vehicle model and waste based on pre-defined parameters related to automobile dismantling waste; Step 2, establishing a waste weight estimation model based on the coupling equation in Step 1; Step 3, optimizing the solution based on the estimation model in Step 2 to obtain the optimal solution for the weight of the j-th type of waste dismantled from the i-th vehicle model. This invention achieves high-precision estimation of waste output through mathematical optimization, solving the technical problem in existing technologies that make it difficult to accurately quantify the waste output and weight loss after dismantling different vehicle models, and providing a scientific basis for resource recycling and environmental management in the automobile dismantling industry.

The application provides a second-order cone programming robust state estimation method for an electric-thermal integrated energy system, and comprises the following steps: obtaining measurement of the electric-thermal integrated energy system; inputting the measurement into a pre-constructed second-order cone programming state estimation model of the electric-thermal integrated energy system to obtain an estimated value of a node voltage amplitude of a power system, an estimated value of a node phase angle of the power system, an estimated value of a node pressure of a thermal system, an estimated value of a node heating temperature and an estimated value of a node regenerative temperature; the measurement of the electric-thermal integrated energy system comprises a power system measurement and a thermal system measurement; and the application of the method can compensate for the loss of measurement redundancy in the power grid and improve the accuracy of the state estimation of the power system in the electric-thermal integrated energy system.

The invention discloses a novel power system equipment maintenance plan optimization method considering distribution and micro cooperation, and the method comprises the steps: constructing a first-stage optimization model of an equipment maintenance plan, and enabling the first-stage optimization model to determine a maintenance plan decision variable with the minimum sum of maintenance cost, unit start-stop cost and expected operation cost as a target; a second-stage optimization model of the equipment maintenance plan is constructed, and the second-stage optimization model carries out optimization scheduling for different typical operation scenes with the purpose of minimizing the comprehensive operation cost of the distribution micro-grid system on the premise that maintenance plan decision variables are fixed; performing second-order cone relaxation processing on power flow constraints of the power distribution network in the first-stage optimization model and the second-stage optimization model, and converting an original nonlinear model into a mixed integer second-order cone programming model; and solving the mixed integer second-order cone programming model, and outputting an optimal equipment maintenance plan.

The invention discloses a rocket sub-level recovery online trajectory planning method considering attack angle constraints, and solves the problems of trajectory safety boundary failure, pneumatic overload overrun and flight stability risk caused by neglecting the attack angle constraints in an existing convex optimization trajectory planning method. According to the method, an attack angle safety boundary constraint model is established, nonlinear attack angle constraint is converted into a second-order cone programming problem (SOCP), and a strict attack angle safety boundary of a planning track is ensured by combining sequence convex optimization with an adaptive trust region adjustment mechanism for solving. According to the method, the defect that the trajectory is not feasible due to the fact that the attack angle is not restrained in a traditional convex optimization method is effectively avoided, and the engineering adaptability of the trajectory to a guidance system and attitude control and the safety of a recovery task are remarkably improved while the sub-problem feasibility and the optimal solution interpretability are guaranteed.

The invention discloses a power distribution network fault recovery method considering island division and fault reconstruction, and relates to the technical field of power distribution network fault recovery, and the method comprises the following steps: constructing a first constraint based on a network topology constraint, a load constraint and an island operation constraint; constructing a collaborative planning model by taking the minimum load outage loss and the system operation cost as objective functions; converting the collaborative programming model into a mixed integer second-order cone programming model through a second-order cone relaxation technology; and integrating the maintenance constraint to the mixed integer second-order cone programming model, and outputting a power distribution network fault recovery strategy. The method is used for solving the problems that in power distribution network fault recovery, collaborative optimization of network reconstruction and island operation is difficult, the calculation efficiency is low, and multi-fault scene coping is insufficient.

The invention relates to the field of hydrogen energy application, and provides an accurate optimization method suitable for steady-state non-convex hydrogen flow. For the problem that a hydrogen flow non-convex model described by a Weymoth equation is difficult to solve, an upper-layer and lower-layer optimization framework is designed. Firstly, according to an airflow pipeline, a pipeline head node, a pipeline tail node and auxiliary variables of pipeline airflow are added, an original problem is decomposed into an upper-layer second-order cone programming problem (SOCP) and a plurality of lower-layer quadratic programming problems, and each quadratic programming problem comprises a non-convex quadratic constraint; secondly, representing a plurality of quadratic programming problems as an equivalent strong dual form-semi-definite programming problem (SDP), and solving a dual problem to obtain a solution of QP1QC; and then, the optimization results of the upper layer and the lower layer are coordinated and corrected until a high-quality solution meeting an original non-convex hydrogen flow equation is converged, so that potential safety hazards such as pressure over-limit and flow velocity abnormality in operation can be reduced, and powerful support is provided for stable operation of a hydrogen energy system.

The application discloses a power distribution network economic reactive power coordinated dispatch optimization method and device, a terminal and a medium. The scheme forms a closed-loop feedback of economic and reactive power optimization by constructing a cooperative optimization framework, and dynamically adjusts the optimization direction in the iteration process. At the same time, the combination of the Pareto solution and the second-order cone programming ensures the comprehensiveness of multi-objective optimization and overcomes the difficulty in solving non-convex optimization problems. In combination with the cross-iteration mechanism, the adaptability of the system to distributed power output fluctuation is enhanced, and the coordinated control of flexible load and energy storage improves the operation flexibility of the power distribution network. Therefore, the feasibility of the optimization scheme can be maintained under complex operation scenarios.