32 results about "Robust optimization problem" patented technology

The invention provides a dispatching method for restoring system security of an electric power system after multiple failures, and relates to the technical field of electric power systems. First a safe economic dispatching model is established and is converted to a two-stage decision model, a multi-stage robust optimization model is decomposed into a main problem and a sub problem, the main problem and sub problem are solved repeatedly, an upper bound and a lower bound of the main problem are updated, the worst scene is identified again, till a difference value of the lower bound and the upper bond of the main problem does not exceed a convergence level or reaches a maximum alternation number of items, and an optimal solution to the main problem is output. The dispatching method adopts an N-K safety criterion that satisfies power grid operation conditions, thereby enabling a calculated result to have practical guiding significance, and the thought of adopting robust optimization avoids the problem that under the N-K safety criterion, an equipment failure accident set is large in amount, and the dispatching problem cannot be solved; and a column constraint generating algorithm is adopted to decompose the multi-stage robust optimization problem into the main problem and the sub problem, thereby improving solving efficiency.

The invention relates to a power allocation method in a cognitive radio network (CRN) and application thereof in a smart transportation network, belonging to the technical field of radio communication. The technical solution comprises steps of acquiring non-ideal channel state information through a non-blind channel estimation method; setting an interference power threshold which ensures that primary user communication is not affected by secondary users; constructing a robustness optimization problem by using a safe, effective capacity as a target function and a power limit as a constraint, resolving an optimal dual factor through a Lagrange duality theory, so as to resolve an optimal transmit power to realize optimal power allocation; and transmitting data by secondary users according toan allocated power. The method enables the safe cognitive radio network to meet the QoS requirement of user statistics delay, and has advantages of low calculation complexity and high channel adaptability, thereby having important theoretical and practical significance.

The invention discloses an AC / DC microgrid robust scheduling method considering power tracking of an uncontrollable generator, comprising the following steps: step 10) obtaining uncertainty prediction parameters and establishing an uncertainty set; step 20) based on step 10 ) to establish the source-load uncertainty set, linearize the output constraint of the uncontrollable generator set; step 30) obtain the operating cost coefficient and operating limit of each device in the microgrid, and establish the AC / DC microgrid based on step 10) and step 20). Robust optimization model of the grid; step 40) Solve the robust optimization problem: use the nested column constraint generation algorithm to iteratively solve the robust problem, and obtain the robust operation plan of the AC and DC microgrid. This method takes into account the non-adjustable power characteristics of renewable energy generating units in the microgrid, and realizes the robust optimal scheduling of AC and DC microgrids through the coordinated scheduling of unit start-stop and output, and meets the power tracking requirements of uncontrollable generating units. The operation plan of the AC / DC microgrid provides important reference guidance.

The invention discloses an AC / DC hybrid microgrid robust scheduling method based on energy storage dynamic loss, which comprises the following steps of step 10) acquiring energy storage test parameters and constructing an energy storage dynamic loss model in a bilinear form; step 20) performing linearization processing on the energy storage dynamic loss model constructed in the step 10); step 30)obtaining the operation cost coefficient and the operation limit value of each equipment, and establishing a robust optimization scheduling model of the alternating-current and direct-current hybrid microgrid; step 40) solving robust optimization scheduling problems, which means to solve robust optimization problems by utilizing a nested column constraint generation algorithm, and obtain a robustcoordination operation mode of the alternating-current and direct-current hybrid microgrid. The method is advantageous in that the characteristics of energy storage dynamic loss in the alternating current and direct current hybrid microgrid can be considered, and robust optimal scheduling of the alternating-current and direct-current hybrid microgrid can be realized; the economic benefit of energystorage operation is improved on the basis that the energy storage loss cost is accurately calculated; important guidance and help can be provided for making an operation plan of an AC / DC hybrid microgrid.

The invention discloses a method for dispatching multi-time-scale energy of micro power grids on the basis of real-time electricity price mechanisms. The method for dispatching the multi-time-scale energy of the micro power grids on the basis of the real-time electricity price mechanisms includes day-ahead dispatching time scales and intra-day dispatching time scales. Priority dispatching strategies are connected with the day-ahead dispatching time scales and the intra-day dispatching time scales, and robust optimization problems can be solved for multiple time scales of the micro power gridsby particle swarm optimization algorithms. The method has the advantages that requirements of the real-time electricity price mechanisms can be met, the method is applicable to peak and valley time-of-use electricity price systems and includes concise steps, real-time and definite dispatching priority can be provided for various distributed power sources in the micro power grids in each dispatching time frame, renewable energy can be sufficiently utilized, wind and light abandoning can be reduced, and the load power supply reliability can be improved; dispatching strategies on the basis of real-time electricity price information and multi-time-scale theories are combined with one another, accordingly, intra-day dispatching guiding effects of day-ahead dispatching can be enhanced, coordination and matching of dispatching of two time scales can be promoted, and burden due to short-time-scale dispatching can be relieved.

Aiming at the problem that the detection performance of multiple-input multiple-output (MIMO) radar space-time adaptive processing (STAP) is sensitive to parameter estimation errors, which leads to poor robustness of system detection probability, the present invention proposes a method in which the prior information of the target is not known. Joint robust optimization method of transmitting waveform and receiving weights. According to the principle of maximizing the output signal-to-interference-noise ratio (SINR), under the constraints of the constant mode model of the transmission waveform, sidelobe and clutter suppression, this patent constructs a joint robust optimization problem of the transmission waveform and the receiving right based on the parameter estimation error convex set. In order to solve the obtained complex nonlinear problem, the present invention proposes an iterative algorithm, and each step in the proposed algorithm can be transformed into a semi-definite programming problem (SDP), thus obtaining an efficient solution. Numerical simulations show that the proposed algorithm can significantly improve the detection robustness of MIMO‑STAP radar compared with non-robust algorithms and uncorrelated waveforms.

The invention relates to a spacecraft robust rendezvous trajectory design method considering uncertain factors. With utilization of the characteristic of constructing an uncertain factor propagation equation rapidly and precisely according to a covariance analysis method, influences on a nominal track by uncertain factors are analyzed. A robust optimization problem is constructed by using the analysis results as the constraints of the optimization problem. Calculation is carried out based on a genetic algorithm to realize the robust rendezvous trajectory design. Therefore, the traditional optimal system rendezvous determination problem is transformed into a robust rendezvous problem considering uncertain factors; and calculation is carried out based on the genetic algorithm, so that an objective of the robust rendezvous trajectory design is achieved.

The invention provides a dispatching method for restoring system security of an electric power system after multiple failures, and relates to the technical field of electric power systems. First a safe economic dispatching model is established and is converted to a two-stage decision model, a multi-stage robust optimization model is decomposed into a main problem and a sub problem, the main problem and sub problem are solved repeatedly, an upper bound and a lower bound of the main problem are updated, the worst scene is identified again, till a difference value of the lower bound and the upper bond of the main problem does not exceed a convergence level or reaches a maximum alternation number of items, and an optimal solution to the main problem is output. The dispatching method adopts an N-K safety criterion that satisfies power grid operation conditions, thereby enabling a calculated result to have practical guiding significance, and the thought of adopting robust optimization avoids the problem that under the N-K safety criterion, an equipment failure accident set is large in amount, and the dispatching problem cannot be solved; and a column constraint generating algorithm is adopted to decompose the multi-stage robust optimization problem into the main problem and the sub problem, thereby improving solving efficiency.

Disclosed is a robust optimal coordinated dispatching method for an alternating-current and direct-current hybrid micro-grid. The method comprises the following steps: step 10) acquiring source load prediction data and creating an uncertainty set; step 20) acquiring an objective function of an optimal dispatching model; step 30) creating constraint conditions of the optimal dispatching model; and step 40) solving a robust optimal dispatching problem: using a column constraint generation algorithm to solve a robust optimization problem to obtain a robust coordinated operation manner of an alternating-current and direct-current hybrid micro-grid. The method takes the uncertainty of multiple source loads in an alternating-current and direct-current hybrid micro-grid into consideration, can realize the robost optimal dispatching of the alternating-current and direct-current hybrid micro-grid and provides guidance and assistance to work out an operation manner of the alternating-current and direct-current hybrid micro-grid.

The invention discloses a method for robust energy-efficient transmission in a cognitive network. The channel state information of the relevant channel is measured by the receiving end of the secondary user and fed back to the sending end of the secondary user; the sending end of the secondary user performs multiple measurements Determine the uncertain set of each channel gain; the secondary user models the problem of maximizing the energy efficiency of the secondary user according to the robust optimization method; solves the worst channel gain and converts the primary user service quality requirement constraint into a convex constraint; according to the power allocation The algorithm solves the optimal transmission power, and transmits on each channel according to this power, and solves the robust optimal transmission power when the channel state information is uncertain, which can be used in cognitive network communication. In the present invention, under the condition of uncertain channel information, the maximum energy efficiency of the secondary user is guaranteed; the interference power to the receiving end of the primary user is strictly controlled, the service quality of the primary user is guaranteed, and the impact of information uncertainty is effectively eliminated. Deterioration of cognitive network performance.

The invention discloses a space non-cooperative target attitude joint takeover control method utilizing tether thrusters. The Space non-cooperative target attitude joint takeover control method comprises the steps of: generating an error instruction according to a control instruction and a state measured value by adopting a formula, updating part of parameters of a controller online in real time, and then generating a pseudo control quantity (control torque) by utilizing an attitude self-adaptive control law; converting an allocation problem of the control quantity into a robust optimization problem, converting the robust optimization problem into a conic quadratic optimization problem, solving the conic quadratic optimization problem by adopting an interior point method to obtain real control quantities (thrust and tension); and finally driving 12 thrusters and tether tension, and achieving attitude joint takeover control of a non-cooperative target.

The invention proposes a power system multi-stage robust unit combination decision-making method considering the double uncertainty of source and load, which establishes a power system multi-stage robust unit combination model considering wind power and load uncertainty. Firstly, aiming at the uncertainty of wind power output and electric load, construct a high-dimensional uncertainty set based on its upper and lower boundaries; then, combined with the sequential decision-making characteristics of power system dispatching, establish a multi-stage Robust unit combination model; finally, combined with linear affine rules and robust equivalent transformation, the above-mentioned robust optimization problem of min-max form is transformed into a mixed integer linear programming problem for solution. This method can be applied to the decision-making of unit combination in power systems including wind power, which is conducive to improving the reliability and effectiveness of power system scheduling decisions under uncertain operating conditions.

The invention discloses a robustness optimization method of a proton-heavy ion intensity modulated radiation therapy for range uncertainty. Basic information of a proton-heavy ion intensity modulatedradiation therapy and data for calculation preparation are inputted; a range uncertainty mathematical model based on combination of optimality and robustness is built according to a robustness measurement method of a mean value and a variance; and then a robustness optimal solution is obtained by employing filter-algorithm-based adaptive particle swarm optimization. Therefore, a range uncertaintymodel for a robustness optimization problem is established accurately; the method has characteristics of fast solution speed, high stability of the algorithm and strong robustness and the like; and the user is able to use the robustness optimal solution to reduce the influence on the radiotherapy plan by the range error.

The invention discloses an optimization design method for robustness measurement and equilibrium for different kinds of multi-target performances of a mechanical structure. The method comprises the following steps: considering uncertain factors within an interval, establishing a robust optimization design model containing different kinds of target performances such as a cost type, a fixed type, anincome type, and a deviation type for the mechanical structure; nesting an inner layer of a genetic algorithm into double layers and calculating left and right boundaries of all structures of performance indices; performing feasibility discrimination on design vectors in an outer layer of the genetic algorithm; classifying robust equilibrium of a feasible solution on the basis of a robust equilibrium coefficient of an interval constraint performance and a robust equilibrium coefficient of an interval different-kind target performance, sequencing design vectors on the basis of the overall distance of different-kind target performance robustness. Therefore, robust equilibrium optimization of different kinds of multi-target performances for the mechanical structure is achieved. With the method, unified modeling is achieved in order to resolve a robust optimization problem of different kinds of multi-target performances. High robustness level of the constraint performance is ensured. Theoptimization result is objective. All kinds of structures are robust and balanced in overall performances.