3results about How to "Strong global search ability" patented technology

This invention relates to the field of electrical digital data processing technology, specifically a TCR measurement method based on high and low temperature region data fusion using an improved particle swarm optimization algorithm. The method inputs the original time-series data from the high and low temperature regions, removes noise and outliers using isolated forest and Grubbs criterion, and maps the data to a unified temperature domain grid using piecewise Lagrange interpolation. An ergodic sequence is generated using Logistic chaotic mapping to initialize the particle swarm position vector, which is then transformed into node coordinate parameters in geometric space, and a cubic basis spline fitting curve is constructed. Particle fitness is evaluated using the sum of squared residuals and curvature smoothness as constraints. During iteration, the average Euclidean distance from the particle to the swarm centroid is calculated to generate a spatial dispersion factor. A multi-interval weighted decision maker based on the Mamdani framework is used to identify probe, development, convergence, and escape states, dynamically adjusting the inertia weights accordingly. This effectively solves the problems of data fragmentation and premature convergence, ultimately outputting a continuous and smooth resistance temperature coefficient distribution across the entire temperature domain.

The application relates to the technical field of micro-grid energy management, and discloses a micro-grid dynamic coordination control method for distributed energy. The method acquires a data set of multiple monitoring nodes of a micro-grid in a historical operation interval; performs multi-resolution fluctuation analysis on an energy output data set, an energy demand data set and a system frequency data set to generate an output fluctuation index, a demand fluctuation index and a frequency fluctuation index; takes the fluctuation index as a guide variable, adopts a group optimization algorithm to explore in a micro-grid control parameter space, and locates an optimal control interval; periodically adjusts distributed power generation units and load units in the micro-grid according to the optimal control interval, generates a regulation and control instruction set and executes the regulation and control instruction set to achieve dynamic coordination control. The application realizes accurate interval positioning and efficient coordinated operation of micro-grid control, and effectively improves the stability and regulation and control efficiency of a distributed energy system.

The application belongs to the technical field of heliostat target point adjustment method, and particularly relates to a heliostat target point genetic optimization method suitable for a tower type light concentration and heat collection system. The method comprises the following steps: S1. Calculating heat absorber energy flow: dividing the surface of the heat absorber into a target point matrix, calculating the light spot distribution of each heliostat at a given target point on the heat absorber, and calculating the energy flow density distribution formed by the superposition of the light spots of the m heliostats in the mirror field on the heat absorber; S2. Target point genetic optimization: randomly generating S target point strategies as the initial population, generating a group of individuals with higher fitness of the target point strategy through random selection, crossover and mutation, evolving the group, and obtaining the optimized target point aiming strategy, so that the mirror field incident energy flow is uniformly distributed on the surface of the heat absorber. The method provided by the application adopts a target point genetic optimization algorithm to optimize the aiming strategy of the tower type light concentration and heat collection system, so that the mirror field incident energy flow is uniformly distributed on the surface of the heat absorber.