Hierarchical Iterative Method Research Articles

Holistic analysis and optimization of distributed energy system considering different transport characteristics of multi-energy and component efficiency variation

Different natures and nonlinear transport characteristics of electric, thermal and gas energies make it so complex for analyzing distributed energy system (DES). Many researches usually ignored nonlinear heat transfer equations of heat exchange devices and assumed constant efficiencies of energy conversion devices to construct a simplified electric-analogy model of DES. This contribution develops a heat current model of thermal system to consider heat transfer constraints and their influences on energy conversion efficiencies, applies a linearized DistFlow model to describe electric power flow in radial distribution power grid, and then offers a holistic multi-energy transport model of whole DES. On this basis, a hierarchical iteration method is developed for system operation optimization under different working conditions. Results show that the proposed method fully reflects the influences of energy transport constraints on efficiencies of energy conversion devices and further the optimal operation strategy of DES. Specifically, under the consideration of time-of-use electric tariff, the heat generation rate of heat pump has a considerable decrease at 4:00 compared with the results without considering efficiencies variations and power transmission constraints. Besides, the total released heat of heat storage device from 10:00 to 18:00 has a 36.53% reduction if ignoring solar collector efficiency variations.

Robust Non-rigid Registration Based on Affine ICP Algorithm and Part-Based Method

The classical affine iterative closest point (ICP) algorithm is fast and accurate for affine registration between two point sets, but it is easy to fall into a local minimum. As an extension of the classical affine registration algorithm, this paper first proposes an affine ICP algorithm based on control point guided, and then applies this new method to establish a robust non-rigid registration algorithm based on local affine registration. The algorithm uses a hierarchical iterative method to complete the point set non-rigid registration from coarse to fine. In each iteration, the sub data point sets and sub model point sets are divided, meanwhile, the shape control points of each sub point set are updated. Then we use the control point guided affine ICP algorithm to solve the local affine transformation between the corresponding sub point sets. Next, the local affine transformation obtained by the previous step is used to update the sub data point sets and their shape control point sets. Experimental results demonstrate that the accuracy and convergence of our algorithm are greatly improved compared with the traditional point set non-rigid registration algorithms.

Identifying Method for Key Quality Characteristics in Series-Parallel Multistage Manufacturing Process

Many actual multistage manufacturing processes are not serial structure, but parallel structure or hybrid struc- ture. The quality relationship model for multistage manufacturing process with parallel structure was developed based on state space model. The quality relationship model of multistage manufacturing process with hybrid structure was devel- oped via the hierarchical iteration method based on the models for the process with serial and parallel structures. The PLSR method was using for eliminating the correlation between quality characteristics to make analysis and identify the key quality characteristics. The method in the paper provides the solving basis for quality analysis and control in multi- stage manufacturing process.

Land cover classification of remotely sensed image with hierarchical iterative method*

Abstract Based on the analysis of the single-stage classification results obtained by the multitemporal SPOT 5 and Landsat 7 ETM+ multispectral images separately and the derived variogram texture, the best data combinations for each land cover class are selected, and the hierarchical iterative classification is then applied for land cover mapping. The proposed classification method combines the multitemporal images of different resolutions with the texture, which can greatly improve the classification accuracy. The method and strategies proposed in the study can be easily transferred to other similar applications. ∗Supported by National Sciences Foundation of China (Grant No. 40372130)