10 results about "Linear optimization problem" patented technology

The invention discloses a power distribution network low-carbon high-quality scheduling method, system, equipment and medium considering distributed robust optimization segmented affine, and belongs to the technical field of power distribution network scheduling, and the method comprises the steps: taking the minimization of the carbon emission of the product of the main network carbon potential and the net load power as a target function; a Wasserstein distance is adopted to measure the deviation between historical data and real distribution, and multiple types of operation constraints are considered at the same time; the above distribution robust optimization model is converted and solved by adopting a piecewise affine theory, an original nonlinear optimization problem is converted into a linear optimization problem based on a simplex dominant uncertainty set, and the model solving efficiency and robustness are improved. According to the method, the uncertainty of new energy output and carbon potential is effectively dealt with through Wasserstein distance constraint, and the robustness is high; by means of segmented affine transformation, nonlinear robust optimization is simplified into linear optimization, and the solving speed is remarkably increased.

The invention relates to the technical field of power grid planning, in particular to a high-performance parallel automatic differential method, system, equipment and medium for main distribution micro power flow nonlinear optimization, and by adopting the method provided by the invention, modeling is carried out based on a main distribution micro power flow nonlinear optimization problem, and an expression diagram is constructed; considering that a large number of isomorphic constraints exist in the problem, the constructed expression graphs are subjected to grouping management, and an automatic differential calculation function pointer used for calculating each group of instances is generated for a plurality of obtained expression groups. And finally, based on the constructed automatic differential calculation function pointer, introducing an OpenMP parallel framework, and carrying out automatic differential parallel calculation on each expression group. Based on the experimental result of opfbenchmark, the method provided by the invention improves the calculation efficiency of automatic differentiation by 47% in the main distribution micro nonlinear optimization problem.

The application provides a sequential linearization solving method and device for network-constructed energy storage optimal control problems, comprising: establishing a system frequency dynamic characteristic representation model and an energy storage dynamic characteristic representation model; constructing a model prediction optimal control framework for network-constructed energy storage, considering the coupling characteristics of system frequency dynamics and energy storage dynamics, and optimizing the optimal control strategy under the minimum cost of network-constructed energy storage; analyzing the linearization constraint conditions of the model prediction optimal control framework, and realizing the linearization representation of the system frequency dynamics and the energy storage dynamics; analyzing the linearization objective function of the model prediction optimal control framework, and realizing the linearization mapping between the optimization objective and the system state and the energy storage state; constructing a sequential linearization solving framework, converting the nonlinear optimization problem of the optimal control framework into a group of iterative and progressive linear optimization problems, and realizing the fast and stable convergence of the algorithm through an acceptance rejection mechanism and a credible domain updating mechanism.

This invention discloses a method and apparatus for optimizing the design of a space-based natural fly-around trajectory for a medium-to-high orbit target, belonging to the field of spacecraft orbital dynamics and optimization design technology. It includes: establishing a dynamic model of a medium-to-high orbit satellite considering complex perturbations; generating initial values ​​for the fly-around trajectory using a dual-mode approach combining direct position offset and CW equation analysis; constructing a multi-objective weighted optimization objective function, jointly constraining the root mean square of the relative distance difference, the extreme difference of the relative distance, and the mean absolute value of the difference in the relative distance interval time to evaluate trajectory morphological stability; setting three-dimensional coordinate constraints in the target satellite orbital coordinate system to avoid invalid solutions, and using the interior point method to solve the constrained nonlinear optimization problem; and achieving trajectory correction through dynamic model extrapolation, quantitative evaluation of performance indicators, and iterative optimization. This invention overcomes the defect of large extrapolation errors of the CW equation under complex perturbation environments by combining an accurate dynamic model with optimization methods, resulting in a natural fly-around trajectory with high accuracy and long holding time.

The invention provides a steering and torque distribution integrated control method for a four-wheel independent drive vehicle based on nonlinear predictive control, which comprises the following steps of: firstly, establishing a nonlinear state-space equation of the four-wheel independent drive vehicle, and establishing an optimal control problem based on the state-space equation; and then the optimal control problem of the original continuous time system is converted into a nonlinear optimization problem by using a forward Euler method and a multiple targeting method, and the singularity of the nonlinear optimization problem is effectively eliminated and the convexity of the nonlinear optimization problem is improved by adding a regular term in an optimization target. Finally, a moderate-scale sequential quadratic programming mode is designed, and compared with the prior art adopting hierarchical nonlinear predictive control, an open source solver IPOPT and the like, the control precision and the solving speed can be effectively improved.

The application provides a power and price segmentation declaration method and device for a wind storage power station participating in a forward market, wherein the method comprises the following steps: constructing a forward market declaration model of the wind storage power station based on an initial energy of the storage and a wind power output-out clearing price scenario set, a target function of the forward market declaration model comprising a current period net income and a next period storage energy value function; converting the forward market declaration model into a segmented linear optimization problem about accumulated declaration power; and solving the segmented linear optimization problem by using a dynamic programming algorithm to obtain a stepwise power and price declaration curve. The method generates a stepwise power and price declaration curve for the wind storage power station under the premise of not depending on information of other market subjects, not depending on accurate probability distribution assumptions, and not needing to call an external commercial optimization solver, and the stepwise power and price declaration curve takes into account current income, power shortage risk and future storage value, and has high calculation efficiency and strong engineering implementability, and the economic income and operation reliability of the wind storage power station in the forward market are improved.

The invention discloses a large-size high-uniformity coil design method based on adaptive PSOGWO fusion optimization, and the method comprises the steps: carrying out the Taylor expansion of a central magnetic field, and converting the solving of the axial position of a coil into a multivariable nonlinear optimization problem; and under geometric and unified manufacturing constraints, a self-adaptive PSOGWO fusion optimization algorithm is provided to obtain the optimal axial position of each pair of coils. According to the algorithm, particle swarm global exploration and grey wolf hunting type local mining are combined, and adaptive factors and weight proportions are introduced, so that the search precision and robustness in a complex multi-peak problem are improved, and the convergence stability and the local extremum resistance of the algorithm are improved. Under the background of a large-size coil, the uniform interval and the center uniformity of the coil designed by the novel optimization algorithm are obviously superior to those of a traditional coil and a coil designed by a single intelligent algorithm. The design method is suitable for scenes of SERF atom magnetometer compensation / modulation coils and the like, and can be used in cooperation with a multi-channel measurement scheme to improve the spatial resolution.

The invention discloses a virtual power plant optimal configuration method and system based on a hunting optimization algorithm, and the method comprises the steps: constructing a virtual power plant model according to the operation characteristics of distributed energy resources; according to the virtual power plant model, constructing an optimization model with the goal of minimizing the operation cost of the virtual power plant and the unsupplied electric quantity in extreme weather; according to the optimization model, performing iterative optimization on the position and capacity of the virtual power plant in the radial power distribution system by using a hunting optimization algorithm to obtain an optimal configuration scheme; and performing scheduling control on the virtual power plant according to the optimal configuration scheme. According to the method, a hunting optimization algorithm is adopted, the preying behavior of a hunter is simulated, global search and local development capabilities are balanced through a position updating mechanism, and the high-dimensional nonlinear optimization problem in virtual power plant configuration is effectively solved. Compared with a traditional method, the method can remarkably improve the toughness of the intelligent micro-grid under the extreme fault condition, reduces the operation cost, and improves the power supply reliability.

The invention discloses a configuration optimization method and device for series capacitance compensators, terminal equipment and a storage medium, and the method comprises the steps: taking the equipment operation parameters of a power distribution network, the installation positions of the series capacitance compensators, and the reactance compensation coefficients of the series capacitance compensators for a line where the series capacitance compensators are located as control variables; randomly generating a plurality of groups of initial control variable sets, taking one group of initial control variable sets as an initial planet, and repeatedly performing iterative optimization operation on the plurality of initial planets under a preset constraint function for maintaining the power flow stability of the power distribution network until the fitness value of the generated target sun is greater than a preset threshold value, and stopping the iterative optimization operation, and generating a configuration optimization scheme of the series capacitance compensator. Therefore, through the advantages of the Kepler optimization algorithm in the complex nonlinear optimization problem, the Kepler optimization algorithm is applied to configuration optimization of the series capacitor compensator, and the problem that a TCSC configuration scheme output by an existing optimization configuration algorithm cannot effectively reduce the power transmission loss is solved.

The application discloses a waveform design method based on a weighted fuzzy function and relates to the technical field of radar detection. The method comprises the following steps: defining a weighted fuzzy function, constructing an optimization problem based on the weighted fuzzy function, converting a quartic objective function optimization problem into a linear optimization problem through continuous convex approximation, relaxing the constraint, converting the original problem into a convex optimization problem, normalizing the amplitude of the optimization result, repeating the step until the objective function converges, and finally obtaining an optimal waveform. The application can obtain an optimal waveform with an ideal fuzzy function shape through the response weight adjustment of each distance-Doppler pair of the fuzzy function, and supports the clutter suppression in radar coherent processing and other engineering applications.