5results about How to "Fully consider the impact" patented technology

The invention provides a wind turbine generator self-adaptive network construction method and device, and the method comprises the steps: collecting the related operation state data of a wind turbine generator based on the active output power, the reactive output power, the rotor speed and the frequency deviation in real time, and comprehensively and accurately mastering the operation conditions of the wind turbine generator at different moments. A small signal stability analysis model and a mapping relation are determined based on state-space equations of a machine-side converter, a grid-side converter and an energy storage converter of the wind turbine generator, so that the model can more accurately describe dynamic characteristics of the wind turbine generator in different converter working states, and the stability of the wind turbine generator in different operation conditions is evaluated. The virtual inertia correction, the damping coefficient correction and the voltage droop coefficient correction required by network construction are obtained through analysis, then adaptive control parameters and converter modulation signals are determined, the running state and power output of the converter can be adjusted in real time according to the change of the power grid frequency, and virtual inertia, damping and voltage support are provided.

The invention provides an ocean current flow velocity modeling method and system based on a wind wave flow coupling relation, and the method comprises the steps: building a first fluctuating wind speed model based on sea wind characteristic parameters and sea wave characteristic parameters under different sea conditions, calculating the power spectrum density of fluctuating wind speed through employing a specific calculation method, and carrying out the calculation of the power spectrum density of the fluctuating wind speed in an angular frequency interval range; constructing a relational expression between the power spectrum density and the amplitude of the fluctuating wind speed; a second fluctuating wind speed model is obtained through the relational expression and the first fluctuating wind speed model, and then the absolute wind speed of the sea wind is calculated; according to the method, the sexual wave height of sea waves is calculated according to the absolute wind speed, the flow velocity of wind-induced flow and the flow velocity of wave-induced flow are respectively calculated by adopting a specific calculation method, then an ocean current flow velocity model is constructed, and the more accurate and comprehensive ocean current flow velocity model can be provided by fully considering the mutual influence among sea wind, sea waves and ocean currents. The method is of great significance in understanding and coping with a complex marine environment.

The application relates to the technical field of maritime traffic, in particular to a maritime traffic flow complexity acquisition method. The specific steps are as follows: multi-source data of a target sea area is acquired, and the multi-source data is preprocessed, the multi-source data comprising ship data, channel data and hydro-meteorological data; an effective attribute field of the ship in the target sea area is calculated based on the hydro-meteorological data; parameters in the effective attribute field comprise effective speed, safe draught, turning flexibility and safety distance; real-time traffic flow complexity is calculated according to the effective attribute field; a dynamic traffic flow complexity threshold value is calculated according to the multi-source data, and a complexity grade is divided according to the real-time traffic flow complexity and the dynamic traffic flow complexity threshold value. The above maritime traffic flow complexity acquisition method fully considers the influence of hydro-meteorological conditions and the influence of actual ship conditions. The traffic flow complexity threshold value is dynamically adjusted according to the multi-source data, so that the complexity grade division is more reasonable.

This invention discloses a fixed-time formation control method and system, belonging to the field of formation control. The method includes: establishing a heterogeneous multi-agent system model corresponding to the system to be controlled, and establishing an ODE-PDE error system model; at any given time, each sparsely distributed agent, according to the calculated control signal, and each densely distributed agent, according to the calculated control signal, transmitting their position errors back to themselves; setting a virtual agent at a location, and having the virtual agent calculate the control signal; where , , and represent the position errors of the sparsely distributed agent, the densely distributed agent, and the virtual agent, respectively; if the ODE-PDE tracking error system converges, the formation control ends; otherwise, the control signal continues to be updated and the entity objects execute corresponding actions. This invention enables fixed-time formation control, improving system formation efficiency.

Embodiments of the present disclosure disclose an article flow control method, device, terminal equipment and computer medium. A specific implementation of the method includes: obtaining a historical article outbound information set; generating a feature set based on the historical article outbound information set; generating an article flow result data pair set; generating an article flow prediction result data pair set; and sending the article flow prediction result data pair set to a target terminal equipment, wherein the target terminal equipment controls a prepositioned equipment connected by communication to complete an article flow related operation according to the article flow prediction result data pair set. This implementation generates the article flow prediction result data pair set according to the historical article outbound information set and the feature set, which can improve the accuracy and stability of article flow prediction, thereby improving the article flow control level and avoiding problems such as untimely article flow or excessive article flow, and further avoiding waste of flow transportation resources.