11results about How to "Achieve coordinated optimization" patented technology

The invention provides a multi-path main road signal cooperative control method considering speed fluctuation, and the method comprises the steps: firstly collecting traffic data, including road network geometric data, traffic flow data and signal control data, and determining a plurality of main paths according to the traffic flow data; then, based on the running speed of each vehicle on each main path, the vehicle running average speed and the speed fluctuation quantity on each main path are calculated; and finally, constructing a signal control optimization model: constructing a target function by taking weighted green wave bandwidth maximization of all paths as a target, adding a loop integer constraint, an interference constraint, a speed fluctuation space-time constraint, a highest speed fluctuation constraint and a lowest speed fluctuation constraint, solving the signal control optimization model, and obtaining an optimized signal period and green wave bandwidth. And outputting the optimized signal timing strategy. The signal timing generated by the method has a good prospect in the aspect of reducing travel delay and parking times, and a better multi-path collaborative effect can be realized.

The invention discloses a resource optimization method and apparatus, a computer device and a storage medium. The method comprises the steps of obtaining a to-be-managed crowd and current crowd feature data and historical crowd feature data of the to-be-managed crowd; providing the current crowd feature data and the historical crowd feature data to a preset prediction model, so that the prediction model outputs a resource operation state index of the crowd; determining a resource scheduling priority of the to-be-managed crowd based on the resource operation state index; determining a target resource optimization strategy of the to-be-managed crowd based on a mapping relationship between the resource scheduling priority and a resource optimization strategy; and performing resource optimization processing on the to-be-managed crowd based on the target resource optimization strategy. Resource allocation such as computing power, bandwidth and task execution rhythm can be adaptively adjusted under different service loads and crowd scale changes, and coordinated optimization of multi-dimensional system resources and improvement of overall operation efficiency are achieved.

The invention relates to the technical field of comprehensive energy, in particular to a city-level electricity-gas-heat-storage multi-energy cooperative regulation and control method and a city-level electricity-gas-heat-storage multi-energy cooperative regulation and control system. The regulation and control method comprises the steps of obtaining operation data and parameters of the integrated energy system; based on an energy conversion and storage device, a comprehensive energy system structure of electricity-gas-heat storage combined power supply is constructed; introducing a stepped carbon transaction mechanism, and establishing a hierarchical calculation model; a comprehensive energy system low-carbon scheduling model based on hierarchical carbon transaction is established, and power balance constraint, P2G constraint, gas storage tank constraint and gas turbine constraint are constructed. The hierarchical carbon transaction mechanism is considered, the energy system integrating electric power, natural gas, heat energy and energy storage is created, coordinated optimization of various energy storage devices in the comprehensive energy system is achieved, the energy supply potential and the energy storage adjustment potential of the comprehensive energy system are fully played, and the optimized operation capacity of the comprehensive energy system is improved; and a low-carbon scheduling model is established, so that networking of the cleaning unit is facilitated, and the carbon dioxide emission is effectively reduced.

The application provides a kind of urban trunk multi-path signal timing and guiding vehicle speed dynamic coordination optimization method considering lap phase, comprising: collecting road network geometry data and traffic flow data;Current cycle length and current control time length are increased by 1s, update traffic flow data;If the current cycle length has reached the cycle length, the intersection level signal control optimization model is constructed with the minimum intersection delay value as the target, and the optimal signal timing is obtained;If the current control time length has reached the control time length, the trunk level signal control and guiding vehicle speed optimization model is constructed with the maximum weighted green wave bandwidth of all key paths as the target, the optimal signal cycle and the maximum green wave bandwidth are obtained, and the optimized key path phase difference and guiding vehicle speed are output.The signal timing and guiding vehicle speed coordination optimization scheme generated by the application can ensure that vehicles can still smoothly pass through multiple intersections under fluctuation, realize the coordination optimization of traffic signal and vehicle speed control, improve the operation efficiency of traffic flow, and reduce waiting time and parking times.

The application discloses a kind of planning and control method and computer device of mobile manipulator autonomous handling, including based on planning domain definition language, the total handling task of mobile manipulator is decomposed into atomic action sequence containing navigation, operation and end operation;In response to the current atomic action in atomic action sequence, call fast exploration random tree algorithm in the redundant configuration space of mobile manipulator search discrete geometric path point sequence satisfying obstacle avoidance constraint;Discrete geometric path point sequence is carried out time parameterization processing, generates continuous reference trajectory, based on nonlinear model prediction control framework, trajectory tracking error, end pose keeping constraint, actuator physical constraint and the obstacle avoidance soft constraint constructed by environment obstacle distance field gradient are fused in objective function, the optimal control instruction of current time is solved by rolling horizon optimization, mobile manipulator is driven based on optimal control instruction, realize the efficient and safe handling of mobile manipulator in complex environment.

The invention discloses a rural light-biogas virtual power plant energy optimization operation method and system considering energy storage degradation. The method comprises the steps that an energy storage degradation cost model and virtual power plant basic operation constraints are established; the virtual power plant upper layer model prediction control layer considers the dynamic energy storage degradation cost, the electricity purchasing and selling cost and the total operation and maintenance cost to carry out virtual power plant energy operation optimization, and an upper layer optimization scheduling instruction is obtained; and inputting into a lower-layer model prediction controller, comprehensively considering deviation cost and energy storage scheduling cost of an upper-layer reference value to carry out source load power fluctuation stabilization to obtain a lower-layer operation result, and feeding back the lower-layer operation result to an updated upper-layer model prediction control layer to carry out virtual power plant energy loop iteration operation optimization. According to the method, the rural photovoltaic and biogas resources are flexibly adjusted, the method is suitable for a rural power distribution network to which a large number of renewable energy sources are accessed, and the average degradation cost of an energy storage battery and the average operation cost of the system are reduced on the premise of efficiently absorbing new energy.

The application discloses a power distribution network source-network-load-storage collaborative scheduling method for new energy access, relates to the technical field of power distribution network operation control, and specifically comprises the following steps: a coupling model taking node safety margin and response reliability as state variables is established by collecting power distribution network, energy storage and flexible load response data; the reliability is updated according to response deviation, online state and user constraints, and effective response capacity with a confidence boundary is formed; power flow checking is performed in each scheduling period, safety pressure values are generated by combining voltage out-of-limit, equipment load rate and reverse power flow risk, and safety and economic coordination weights are adaptively determined; a flexible load calling strategy of safety priority or economic priority is selected according to the safety pressure, and a collaborative scheduling model is solved with the minimum weighted sum of economic cost and safety risk conversion cost as the target, and source-network-load-storage joint scheduling instructions are outputted; and the method can improve the safety risk inhibition capability and economic scheduling level of the power distribution network under the new energy access scenario.

The invention relates to the technical field of aircraft design, in particular to an aircraft overall scheme generative design method based on PILO-GAN, and the method comprises the steps: converting an unstructured natural language demand into structured design parameters; then constructing a PILO-GAN network, generating initial design parameters by taking structured parameters as conditional input and combining with random noise, embedding aircraft design empirical criterion constraints, and driving physical optimization based on multidisciplinary performance evaluation; performing multidisciplinary physical performance verification on the initial design parameters to obtain quantitative performance indexes; constructing a gradient propagation path by adopting a REINFORCE algorithm, and feeding back a performance index gradient to the generator to realize parameter updating; and finally, dynamically adjusting the weight of the loss item of the constraint and physical optimization, and carrying out iterative optimization until a preset requirement is met. Through a physical closed-loop optimization mechanism, end-to-end intelligent generation of feasible schemes from demands to engineering is realized, and the physical consistency and engineering credibility of the design scheme are remarkably improved.

This invention relates to the field of motor technology, specifically to a multi-mode motor torque distribution method and system. The method includes: a drive system based on dual front axle motors and a single rear axle motor; constructing an economy control module and a power control module based on a hierarchical control architecture; calculating the driver's driving intention based on the accelerator pedal opening; if the driving intention is within the standard range of the economy control module, obtaining the optimal torque distribution coefficient by minimizing instantaneous energy consumption power, and obtaining the reference torque for the rear axle and front axle motors; if the driving intention is within the standard range of the power control module, calculating the compensation torque for the front axle and rear axle motors based on a preset fuzzy control algorithm according to vehicle speed and accelerator pedal opening change rate, and superimposing the compensation torque onto the reference torque for the front axle and rear axle motors respectively to obtain the final drive torque command; this invention solves the balance problem between economy and dynamics in four-wheel drive multi-motor electric vehicles.

The invention discloses a remote node dormant state machine control method and system based on message time sequence analysis, and relates to the field of node power consumption management control, and the method comprises the steps: obtaining an arrival timestamp and a message identifier of an inbound message, and carrying out the classified storage of the arrival timestamp and the message identifier according to service types; extracting statistical characteristics based on the adjacent arrival time interval sequence of each category of messages, constructing a message arrival probability distribution model and calculating an arrival risk degree function; carrying out weighted fusion by combining service priorities to obtain a system-level comprehensive risk degree function, and predicting that a next message arrives at an expected moment; and calculating a safety margin in combination with the current energy state of the node, and selecting a target dormant state in the multi-stage dormant state machine. Therefore, dynamic control over the sleep depth and the wake-up time is achieved, and the adaptivity and response coordination of low-power-consumption management of the far-end node are improved.

The application provides a genetic algorithm-based multi-objective optimization design method for asphalt mixture, constructs a mapping relationship model between different design parameters and volume indexes and performance indexes based on an asphalt mixture design database; determines an optimization direction according to engineering requirements, constructs an optimization objective function based on the mapping relationship model, and constructs a multi-objective optimization model with the design parameters as decision variables according to the optimization direction, the optimization objective function and preset constraint conditions; solves the optimization model by using a genetic algorithm including a non-dominated sorting mechanism and a reference point correlation mechanism to obtain an optimal solution set for the engineering requirement data; calculates the performance scores of each solution in the optimal solution set, and selects a solution with the highest performance score in the optimal solution set as an optimal design scheme for the asphalt mixture for the engineering requirement data according to the performance scores. The optimization efficiency and result reliability of the asphalt mixture design are improved, and coordinated optimization between multiple performance indexes is realized.