37 results about "Mixed integer quadratic programming" patented technology

The invention relates to a power distribution network structure estimation method based on a mixed integer quadratic programming model and belongs to the technical field power system dispatching automation and power network simulation. The method includes the steps of using branch switch states, node voltage amplitude and branch active and reactive power of a power distribution network as decision variables, using state estimation values and minimum measured value residual as targets and using the mixed integer quadratic programming model for solving power distribution network topology; calculating to obtain the switch state of every branch through real-time measured values and pseudo-measured values of the power distribution network and using the topology obtained through model solution as actual topology of the power distribution network. The power distribution network structure estimation method based on the mixed integer quadratic programming model makes full use of branch power measurement, node voltage measurement and load data of the power distribution network and is high in calculation speed and accurate in result.

The invention discloses a regional comprehensive energy system layout planning method considering topological characteristics of an energy network, and belongs to the field of integrated energy systemplanning. The method comprises: providing topological characteristics of the energy network; establishing a topology description model of the regional comprehensive energy system based on the energyflow balance constraint; establishing a regional comprehensive energy system layout planning model by taking minimization of the sum of initial investment construction cost and later operation cost ofenergy stations and energy supply pipelines of the regional comprehensive energy system as a target; using an orthogonal polynomial approximation and piecewise function linearization method to reasonably simplify the planning model, and converting an original problem into a mixed integer quadratic programming problem which is easy to solve; and finally, solving the simplified target function based on a branch and bound method and an interior point method to obtain a comprehensive energy system layout planning scheme. According to the planning method, problems are considered more comprehensively and reasonably, the problem that the physical meaning of a planning target is not clear in an existing planning method is solved, and the solving efficiency is higher.

The invention discloses a parallel hybrid electric vehicle energy management method with gearbox gear control, and relates to the field of hybrid electric vehicle energy management. The parallel hybrid electric vehicle energy management method analyzes an evolution law of a state of charge change rate of a battery and engine specific fuel consumption under each gear, combines with a hybrid logic dynamic modeling method, establishes a parallel hybrid electric vehicle energy management system model including gearbox discrete gear information, further introduces a model predictive control idea, defines motor torque as a continuous control variable, and defines gearbox gears as discrete control variables and translates an optimization problem into a mixed integer quadratic programming problemto solve, the strategy optimizes the torque distribution of each power source and decides an optimal gearbox gear. The parallel hybrid electric vehicle energy management method aims at the energy management problem of a parallel hybrid electric vehicle with a gearbox, and has the advantages of high pertinence, high practicability, good optimization effect, high integration and the like.

The hybrid dynamic modeling and optimization control method for the intelligent automobile longitudinal dynamics system comprises the steps of establishing a whole automobile longitudinal dynamics model, and conducting segmented affine approximation on a nonlinear part existing in the model; based on hybrid dynamic model of the longitudinal dynamic system of the whole vehicle and a prediction control method, converting an intelligent vehicle longitudinal motion control problem into a mixed integer quadratic programming problem for solving to achieve the integration of a system optimization control law, and determining the optimal values of the driving torque and the braking torque and the optimal switching sequence between the driving mode and the braking mode in the intelligent vehicle longitudinal motion control process. The method solves the problems that an existing automobile longitudinal motion control method cannot accurately describe hybrid dynamic characteristics existing in asystem and a driving mode and a braking mode are smoothly switched in the automobile speed adjusting process.

The invention provides a linearized power flow-based network reconstruction method for a power distribution network and belongs to the technical field of operation control of power systems. The methodcomprises the steps of firstly building a network reconstruction model, formed by an objective function and constraint conditions, of the power distribution network; transforming the objective function and the constraint conditions separately and transforming an original model into a mixed integer quadratic programming model; and solving the transformed model to obtain open and closed state variables of various branches and carrying out corresponding switching actions according to the solving result to achieve network reconstruction. The linearized power flow-based network reconstruction method is high in computation speed and good in convergence and is suitable for being applied to the scenes of real-time network reconstruction of the power distribution network.

The invention discloses a source network co-scheduling method including a controllable series connection compensation device. The method comprises the following steps: step 1, relevant calculation parameters are given; step 2, the operation mode of a controllable series connection compensation device is modeled; step 3, an optimized model is constructed, the optimized model is based on the target that the sum of the power generating cost of a power system and the cost of abandoned wind power is minimal, and the optimized model includes a number of constraints; and step 4, the optimized model is simplified and employs a mixed-integer quadratic programming method to solve the problem, and a final source network co-scheduling scheme is obtained. The method integrates the controllability of current flow control equipment and energy storage systems and the like into economic scheduling decision-making of a power grid, and constructs the source network co-scheduling model of the wind and electricity coexistence in the power grid to determine the economic operation mode under the restriction of the security constraint level, can enhance the consumption of fluctuation of wind power, load, and so on injected into nodes under the premise of ensuring the safe operation of the power grid, and improves the economic benefit of power grid operation.

The invention discloses a weight-based hybrid integer quadratic programming multi-target scheduling method. According to the method, coal consumption, network loss, emission and electricity purchasingcost are taken as multiple reference targets for scheduling, from the perspective of conversion, according to the weight of the different targets, a multi-target problem is converted into a single-target problem for solution, and thereby solution complexity of an original multi-target optimization model is reduced, and stability and robustness of the single-target solution algorithm can be utilized to the large extent.

The invention relates to an industrial process fault diagnosis method based on the Bayesian information criterion. The method comprises: collecting normal industrial data and calculating several kindsof detection statistics amounts based on normal data; carrying out fault detection on a to-be-detected sample; expressing a fault isolating task into a combinatorial optimization problem; convertingthe problem into a mixed integer nonlinear programming problem by combining the Bayesian information criterion; on the basis of a forward selection algorithm, simplifying the problem into a mixed integer quadratic programming problem; on the basis of a branch-and-bound algorithm, solving a series of similar mixed integer quadratic programming problem to obtain a fault variable combination causingthe sample fault. The industrial process fault diagnosis method has high universality; and the fault variable can be identified without predetermining a fault direction or a known historical fault data set. When the amplitude of the fault is small, an accurate diagnosis result is obtained. Besides, the combination optimization problem is transformed into the quadratic programming problem with sparse constraints for calculation, so that the computational efficiency is improved substantially.

The invention discloses a dynamic scheduling method of a mixed-integer quadratic programming power system. The dynamic scheduling method comprises the steps that a dynamic scheduling mathematic model of the power system is built, wherein the model comprises an objective function and conditional constraints; the conditional constraints include a power balance constraint, a unit output constraint, a unit ramping constraint, a unit embargo area constraint and positive and negative standby constraints; the conditional constraints are converted into corresponding linear constraints by employing a mixed-integer encoding technology to convert the dynamic scheduling mathematic model into a mixed-integer quadratic programming model; and the mixed-integer quadratic programming model is solved by employing a default engineering optimization software package to obtain a corresponding power system scheduling scheme. Therefore, firstly, the feasibility of the finally obtained power system scheduling scheme and the dynamic scheduling effectiveness of the power system are ensured; and secondly, a global optimal solution, namely the optimal power system scheduling scheme can be obtained, and the dynamic scheduling method is suitable for large-scale calculation of an active scheduling plan of a unit.

The invention relates to a mixed height unit legalization method for minimizing average and maximum movements. The method comprises the steps of representing a circuit as a hypergraph model; after directions are set for units, aligning the units to a power supply rail line which is adjacent and correctly matched; preprocessing the multi-line high-standard unit, and by analyzing and reconstructingan objective function and a constraint, planning a mixed height standard unit legalization model as a mixed integer quadratic programming model; converting the mixed integer quadratic programming model into a quadratic programming model; converting the quadratic programming model into a corresponding linear complementary model; solving the linear complementary model by using a matrix splitting iteration method based on modulus; carrying out line redistribution and restoring the multi-line high-standard unit; and legalizing the minimum movement unit by adopting a linear programming-based methodand a Kuhn-Munkres algorithm. According to the method provided by the invention, all the units are optimized at the same time, so that the requirements of a mixed height standard unit legalization stage of current VLSI can be met.

The invention is applicable to the technical field of intelligent network connection management and control, and provides a vehicle-road cooperative bus control method and device and terminal equipment. The method comprises the steps of acquiring traffic information of a target road network in a vehicle-road cooperative environment; determining whether a target bus exists in the target road network or not according to the traffic information; dividing the target road network into at least one sub road network by taking the bus station as a node; when the target bus exists in the target road network, calling a mixed integer quadratic programming model corresponding to the sub-road network where the target bus is located, carrying out optimization solution, and sending the optimized drivingspeed and parking time of the target bus to a vehicle-mounted terminal of the target bus, and sending the optimized timing scheme to traffic lights to adjust the time headway of the target bus, so that the regularity of arrival time of the same bus line can be effectively improved, the waiting time of passengers is stable, the passenger capacity of each bus is balanced, the overall efficiency of bus operation is improved at the same time, and road space-time resources are saved.

The invention, which belongs to the technical field of automatic scheduling automation field of the power system, especially relates to a robust state estimation method in a mixed integer quadratic programming mode. The method comprises: a voltage vector a node i is expressed in a right-angle coordinate mode and an injected active power and an injected reactive power of the node i are obtained; three equivalent two-winding transformers are used for expressing a three-winding transformer and all branch circuits in the power system network are expressed by using a unified pi type branch circuit; according to an equivalence circuit graph of the pi type branch circuit, branch circuit active powers and reactive powers from the node i to a node j as well as a voltage amplitude measurement equation of the node i are obtained, and a robust state estimation model in a mixed integer quadratic programming mode is also obtained; an initial value of an MIQCP robust state estimation model is obtained by using a WLS state estimation method; the MIQCP robust state estimation model is resolved and a defective measurement value is found and eliminated; and the corrected measurement value is calculated again by using the WLS state estimation method.

The invention relates to a generator set and heat exchange station joint start-stop control decision making method, which belongs to the technical field of power system operation. A generator set andheat exchange station joint start-stop control decision making model is established. The objective function of the model is to minimize the total power generation and heat supply cost of conventionalthermal power units and heat supply thermal power units, and the constraints include power system constraints and heat supply system constraints. In the method, the established generator set and heatexchange station joint start-stop control decision making model is transformed equivalently by a large M method, and finally, an obtained mixed integer quadratic programming problem is solved to obtain a generator set and heat exchange station joint start-stop plan. The method can avoid the risk of insufficient power and heat supply caused by the risk of traditional experience-based control decision making, ensure the safety and reliability of power supply and heat supply, fully tap the thermal inertia and heat storage characteristics of the heat supply system and significantly improve the wind power absorption of the power system.

The invention discloses an InSAR (Interferometric Synthetic Aperture Radar) multi-baseline phase unwrapping method, and belongs to the technical field of interferometric synthetic aperture radars. According to the method, an optimization model of phase gradient ambiguity is established by using 2-norm constraint, and a solving problem is converted into a mixed integer quadratic programming problem; the energy function expression form of the Markov random field model is improved, so that the model is converted into a quadratic programming problem to simplify the solving process. Through the method provided by the invention, the execution efficiency and the solving precision of InSAR multi-baseline phase unwrapping can be effectively improved, the solving result has the characteristics of certainty and uniqueness, and the execution time is controllable under the given precision.

The invention discloses a comprehensive energy system optimization scheduling method considering multiple heat supply modes of combined heat and power generation, and the method comprises the steps: building an optimization scheduling model which comprises a combined heat and power generation unit full-mode operation model, a heat supply network model and a building model, wherein the combined heat and power generation full-mode operation comprises an extraction condensing operation mode, a heat supply network operation mode and a building operation mode; and adopting a back pressure mode operation and a switching operation mode, and giving out constraint conditions under full-mode operation. Finally, a Fortuny-Amat-McCarl method is adopted to convert the proposed optimal scheduling method into a mixed integer quadratic programming model for solving, so that collaborative optimization of the electric heat energy flow under the full-mode operation of the cogeneration unit is realized, and the flexibility and economical efficiency of the comprehensive energy system are improved.

The invention provides a calculation method for an alternating current power flow model of a radial power distribution network, which comprises the following steps of: S1, constructing a non-directional second-order cone relaxation radial power distribution network alternating current power flow model for eliminating a predefined power flow path requirement according to a second-order cone power flow model of a power distribution system; s2, describing a radial power distribution network power flow state according to the non-directional second-order cone relaxation radial power distribution network alternating current power flow model, and constructing a power distribution system economic dispatching optimization model with a mixed integer quadratic programming structure; s3, judging whether the system, connected with the high-proportion distributed power supply, in the step S2 meets a given beforehand sufficiency condition or not, and determining that a power flow solution obtained by the constructed economic dispatching optimization model of the power distribution system can meet operation requirements; and S4, for the power distribution system economic dispatching optimization model of which the obtained power flow solution can meet the operation requirement, performing parallel calculation by using an improved Lp-box alternating direction multiplier method. According to the method, the problem of quickly solving the alternating current power flow state of the power distribution system connected with the high-proportion distributed power supply can be effectively solved.

The invention provides a high-quality task allocation and service deployment method for a mobile group awareness system in an edge computing environment. The method comprises the following steps: S1) communication connection between a user and an edge server; S2)task submission and allocation; S3) establishment of a target function; and S4) service deployment and task allocation. The method is advantageous in that, under the constraint of budget of application program developers, available resources of edge servers and user capacity, a mixed integer quadratic programming (MIQP) mathematical model with task quality and cost balancing as the target is provided, and the task completion quality can be improved as much as possible on the basis of ensuring that the total excitation cost is within a certain limit range and the task can be completed.

The invention provides a low-cost task allocation and service deployment method for a mobile group awareness system in an edge calculation environment. The method comprises the following steps: S1) communication connection between a user and an edge server; s2) submitting and distributing tasks; s3) establishing a target function; and S4) service deployment and task allocation. The method has the advantages that under the constraint of budget of application program developers, available resources of edge servers and user capacity, a mixed integer quadratic programming (MIQP) mathematical model with task quality and cost balancing as a target is provided. The system operation cost can be reduced as much as possible on the basis of ensuring the task completion quality.

The invention provides a power distribution-gas network distributed collaborative programming method and system considering influences of a power transmission network. The method comprises the following steps: obtaining typical operation scenes of power distribution-gas networks; according to the obtained typical operation scenes and a preset power distribution-gas network distributed collaborative programming model, obtaining an optimal distributed collaborative programming scheme of the power distribution-gas networks, wherein the power distribution-gas network distributed collaborative programming model comprises a power transmission network sub-problem mixed integer quadratic programming model, a power distribution network sub-problem mixed integer quadratic programming model and a gas distribution network sub-problem mixed integer quadratic programming model; and sequentially carrying out distributed iterative solution on the three mixed integer quadratic programming models by utilizing an analytical target cascading algorithm. According to the invention, by establishing the mixed integer quadratic programming models of power transmission networks, power distribution networks and gas distribution networks, a distributed solving process based on the analytical target cascading algorithm is constructed, and distributed collaborative programming of multiple power distribution-gas networks is realized.

The invention discloses a damping adjustable semi-active suspension hybrid model predictive control method based on damping force constraints. The method comprises steps of establishing a semi-active suspension hybrid system model; based on the model predictive control theory, performing the finite time domain optimal control of the semi-active suspension hybrid system; and transforming it into a mixed integer quadratic programming problem with real and binary variables, to achieve the hybrid model predictive control of the damping adjustable semi-active suspension. The method has the advantages of solving the contradiction between comfort and handling stability; avoiding the nonlinear constraint condition in the semi-active suspension optimization method; converting the semi-active suspension control problem into the finite time domain constrained optimal control problem; and effectively solving the rolling time domain optimization problem with nonlinear constraints.

The invention discloses an alternate iterative optimization scheduling method based on the non-convex output characteristic of a cogeneration unit. The method comprises the steps: dividing the non-convex output region of each cogeneration unit into a plurality of subregions, converting the segmented constraint of each subregion into the continuous linear constraint, and building an active power economic scheduling model for the non-convex output characteristic of the cogeneration unit; simplifying the above model into an optimized scheduling model of one cogeneration unit, and performing the further decomposition to form a thermal supply optimized scheduling submodel and an active power optimized power scheduling submodel, and respectively employing a hybrid integer secondary planning algorithm and a secondary planning algorithm for solving; employing an alternate iteration method for iterative optimization, and controlling the cogeneration unit to work according to an optimization result, so as to enable the active power economic scheduling of the cogeneration unit to be optimal. The method is suitable for the non-convex output region of the cogeneration unit, and can achieve thereal-time online scheduling of the cogeneration unit.

The invention discloses a multi-zone electricity-heat comprehensive energy system optimization control method considering quantitative heat storage, which comprises the following steps: considering the thermal dynamic characteristics of a heat supply pipe network and the computational efficiency demand of multi-zone scheduling, improving and simplifying a heat supply pipe network model based on first-order windward difference, and establishing a virtual heat storage tank model of the heat supply pipe network; establishing a heat storage quantitative index based on the virtual heat storage tank model for quantifying the heat storage level of the primary pipe network, and establishing a quantitative regulation and control index of pipe network heat storage; constructing a regulation and control target penalty term of the heat storage capacity of the pipe network by utilizing the quantitative regulation and control indexes; and constructing a multi-region IPHS optimization scheduling model in combination with the 1-bin unit commitment model, wherein a mixed integer quadratic programming solver is used for solving to obtain an optimization control result of IPHS day-ahead unit commitment and economic scheduling. According to the method, the calculation efficiency is improved, and collaborative optimization of the heat storage capacity of the heat supply pipe network in IPHS scheduling is realized.