12 results about "Mixed integer quadratic programming" patented technology

The application relates to the technical field of system-in-package, and discloses a functional chip SIP (System in Package) system-in-package method and system. The method constructs a reduced-order discrete thermal state predictor through multi-order exponential attenuation fitting, generates a DVFS gear-noise hazard degree spectrum mapping table based on a synchronous switching noise spectrum and an ADC noise sensitivity curve, generates a multi-DVFS working condition robust grounding network topology by optimizing a narrow bridge connection structure parameter by using a sequential quadratic programming, quantizes equivalent noise interference amounts of each DVFS gear on an ADC chip, and jointly optimizes DVFS gear selection and power consumption upper limit distribution under a rolling time domain mixed integer quadratic programming framework, simultaneously performs online model correction through exponential weighted moving average and Kalman filtering, and realizes cooperative satisfaction of thermal constraints and noise constraints.

The application discloses a low-altitude unmanned aerial vehicle route setting method and device, acquires airspace data; the airspace data is standardized, and standard airspace data is obtained; the standard airspace data is input into a space-time graph neural network, and an airspace use heat map is obtained; based on the airspace use heat map and airspace structure data, a mixed integer quadratic programming model is constructed and solved, and an initial route network is obtained; the initial route network is iteratively optimized through a neighborhood search algorithm, and a final main route network is obtained. Through the space-time graph neural network, the dynamic airspace heat map is generated, so that the main route network can be dynamically adjusted according to the flow fluctuation, thereby solving the problems of low efficiency in the peak period and idle resources in the valley period in the high-density area; meanwhile, based on the route network generated by the heat map and the optimization algorithm, the unmanned aerial vehicle can autonomously plan a branch route at the end of the main route, get rid of the response lag of centralized scheduling, and realize distributed flexible response to low-frequency and sudden areas.

The application provides a power stability control strategy decision method and system based on mechanism and data fusion driving, and belongs to the technical field of power system optimal dispatching; the method comprises the following steps: a comprehensive space-time characteristic state vector of a power grid is extracted in combination with a graph convolution network; a limited Markov decision framework is constructed, a state vector is analyzed based on a branch competition Q network, an advantage function of each control node is calculated in parallel through multiple independent branches, and a preliminary joint control strategy is obtained; a mixed integer quadratic programming model is constructed by taking the preliminary joint control strategy as an optimization target and a physical mechanism safety boundary as a constraint, an active-voltage sensitivity matrix is extracted based on a Jacobian matrix to quantize a voltage safety boundary, and a branch and bound method is used for solving and outputting a final control strategy; and the application can effectively cope with the uncertainty of new energy by fusing data driving and a mechanism model, and can directly meet the safety and stability defense demand of a large-scale new energy base sending-out power grid.

The invention discloses a data center and pumped storage power station linked electric calculation integrated economic dispatching method, which comprises the following steps of: establishing power balance and operation constraints including photovoltaic power, wind power, thermal power, energy storage, power grid interaction and pumped storage charging and discharging on the basis of 24-hour load and wind and light output prediction; calculation force space transfer, time transfer (peak clipping back-filling) and cold storage charging and discharging strategies are introduced into the data center, load controllable adjustment is achieved through cold water equivalent offset and task inventory constraint, and peak clipping and valley filling are completed together with pumping and storage two-way adjustment. A mixed integer quadratic programming model is constructed by taking electricity purchasing and selling, unit and scheduling cost as targets, the optimal output and scheduling strategy of each time period is solved by adopting CPLEX, and the system economy and the renewable energy consumption capability are improved.

The application relates to a taxiway path optimization method and system for reducing potential conflicts in a flight area, belonging to the technical field of airport scheduling methods, which considers potential conflicts between aircrafts and aircrafts and between aircrafts and ground service vehicle routes, and constructs a mixed integer quadratic programming model for aircraft taxiway path optimization, with a main target of minimizing potential conflicts between aircrafts and aircrafts and between aircrafts and vehicles, and a secondary target of minimizing ground service vehicle driving distances; the aircraft taxiway path optimization model is solved, and an optimal solution is output, including aircraft taxiing paths and ground service vehicle service paths, types and quantities of potential conflicts, and the results can be used for reanalysis by adjusting parameters, thereby providing reference for airport aircraft and vehicle scheduling decision makers. Compared with the prior art, the application considers the safety of ground traffic and the convenience of passengers, and optimizes the allocation of aircraft landing and taking-off aprons and runways and the taxiing paths in an all-round way, which helps to guarantee the safety of taxiways and improve the operation efficiency of airports.

The invention belongs to the technical field of power system optimization scheduling, and particularly relates to a new energy-thermal power collaborative scheduling method considering a section dynamic power flow limit, which comprises the following steps of: constructing a multi-region new energy output space-time correlation model, describing space-time correlation by combining a Copula function, and generating a typical scene through clustering reduction; the method guarantees the comprehensiveness of scene coverage and balances the calculation efficiency, achieves the collaborative optimization of the economic cost and the environmental protection target through defining a core parameter and variable system and constructing a target function matrix, and achieves the real-time updating of the dynamic limit along with the fluctuation of the new energy output through building a multi-dimensional constraint system containing the section dynamic power flow constraint. And finally, a CPLEX solver is combined with an adaptive differential evolution algorithm to efficiently solve a mixed integer quadratic programming problem, so that scientific and reliable technical support is provided for optimal scheduling of a power system, and the economical efficiency, the safety, the environmental protection property and the new energy consumption efficiency of scheduling are comprehensively considered.

The invention discloses a heat pump load non-intrusive identification method and system based on reactive power characteristics and operation constraints, and the method comprises the steps: obtaining a time sequence of a user, and the time sequence comprises an active power time sequence and a reactive power time sequence; establishing a load feature library of the heat pump, wherein the load feature library comprises a typical active power sequence and a typical reactive power sequence of the heat pump; establishing a mixed integer quadratic programming model, and determining parameters of the mixed integer quadratic programming model; determining constraint conditions of the mixed integer quadratic programming model; and solving the mixed integer quadratic programming model based on the constraint condition, the time sequence and the load feature library, outputting a heat pump start-stop state sequence, and determining the start-stop time of the heat pump based on the heat pump start-stop state sequence.

The invention discloses an automatic switching control method for a photovoltaic energy storage microgrid. The method comprises the following steps: S1, establishing a photovoltaic power generation model, an energy storage system dynamic model and a power balance equation; s2, defining a multi-objective optimization function including power grid interaction cost, energy storage SOC balance and equipment life loss; s3, collecting photovoltaic output, load demand and energy storage SOC data in real time, and predicting a photovoltaic and load curve in a future time domain; s4, solving a rolling optimization problem through mixed integer quadratic programming, and generating an energy storage charging and discharging instruction, power grid interaction power and a load switching decision; and S5, executing the optimal control instruction at the current moment, updating the system state and rolling to the next control period.

The invention provides a Saggoc new energy large-base scheduling method considering transmission capacity of internal and external lines, and the method comprises the steps: taking the minimization of the total operation cost of a system as a target function, and constructing an optimal scheduling model which considers the transmission capacity constraint of an internal power transmission network of a large base and the transmission capacity constraint of an extra-high voltage outgoing DC channel at the same time; and solving the optimal scheduling model by using a mixed integer quadratic programming algorithm to generate a scheduling plan considering both security and economy. According to the method, the stability, the robustness and the comprehensive operation benefit of the large-base power delivery system are improved.

The invention discloses a detection signal noise reduction method and system based on an electrochemical workstation, and relates to the technical field of detection signal noise reduction. The method comprises the following steps: acquiring an electrochemical detection curve and preset parameters in an electrochemical detection process, performing area fine division on the electrochemical detection curve to obtain fine areas, and labeling feature information; based on the fine region and the feature information, constructing a linkage association relationship model through a complex network theory method; performing noise recognition on the fine region based on the linkage association relationship model to obtain a noise recognition result in the region, and performing local noise reduction to obtain a local noise reduction result; and acquiring the global trend constraint of the electrochemical detection curve, and performing secondary global noise reduction on the local noise reduction result by using a mixed integer quadratic programming algorithm to obtain a global noise reduction result. The global noise reduction result is generated through correlation analysis, and the noise reduction of the electrochemical detection signal is realized.

The application discloses a deep stall recovery control method and system based on a hybrid model predictive control, relates to the technical field of flight control and flight safety, and solves the problem that an airplane is difficult to recover after entering a deep stall and exceeding a stall angle of attack by establishing a quadratic objective function of post-predictive control attitude stability, using a hybrid system and a quadratic objective function predictive control strategy, on-line solving a mixed integer quadratic programming, obtaining a current optimal control input and state estimation, and then through rolling optimization, obtaining a final stall recovery control sequence.

The present application belongs to the technical field of heavy haul train group operation optimization, and discloses a speed curve collaborative optimization method and system for heavy haul train group operation, comprising the following steps: for the speed curve optimization problem of heavy haul train group operation under temporary speed limit conditions, a mixed integer quadratic programming model is constructed, and a collaborative optimization method based on target-oriented multi-agent reinforcement learning is designed, aiming to cope with random interference, realize flexible adjustment of train group operation marshalling, maximize overall operation efficiency, reduce operation cost, and ensure the dynamic stability of train group operation. According to the present application, a collaborative optimization technology is used to generate an optimized reference curve for each train in the queue, thereby improving the adaptability of train group operation to random interference, and the target-oriented multi-agent reinforcement learning significantly shortens the solution time, and realizes the comprehensive goal of safe, efficient, energy-saving and stable operation of train group under the condition of sudden interference.