Research On Modeling And Conflict Detection Of Fuel System Collaborative Design In Digital Power Plant

As an important means of informatization in power plant, digital power plant has been widespread attracted by power design institute and plant operational business. It realizes the design of whole life circle in power plant so that it could guide the process of procurement, construction and management. What's more, digital power plant helps the later period of operational management by supporting data. On the basis of current research analysis of digital power plant and collaborative design, the collaborative design has been introduced into fuel system design of digital power plant. The system architecture, database modeling and conflict detection of the collaborative design system were further studied, providing a theoretical and technical support for the collaborative design system of fuel system in digital power plant. The main contents and results are as follows:1. Research on architecture of fuel system collaborative design in digital power plant. According to the characteristic of fuel system design in digital power plant, the system architecture of fuel system collaborative design was studied from three aspects as frame structure, network topological structure and technical system. A frame structure of four-layers and multi-Agent for fuel system collaborative design in digital power plant was established by the strategy of hierarchical structure. Furthermore, the design process of the multi-Agent system was also analyzed. A distributed network topologic structure of the system was built by using the distribution-centralized system structure. A technical system with three-layer was built by C/S structure mode. Besides, the component technology of the system was studied as well as the interaction process of client and application software. Meanwhile, for the problem of product information model in fuel system, a hierarchical model of fuel system collaborative design was set up based on discipline dimension, schedule dimension, data dimension and cost dimension. The components of product information model were analyzed. Taking the application of coal conveying system in thermal power plant as an example, the description of information model and multiple view model based on XML were studied.2. Research on database modeling of fuel system collaborative design in digital power plant. According to the characteristics of collaborative data, the data was divided into unstructured data and structured data. For the storage of unstructured data, a distributed file storage system was established and its structure was analyzed. The file storage system was stored as the underlying database for the distributed collaborative database. While for the storage of structured data, a distributed collaborative database model with multi-Agent and middle layer was built and its frame structure was studied. On the issues of database performance, the database was optimized from three aspects of storage, query and expansion. Firstly, the influence of horizontal storage and vertical storage on the database access performance was analyzed by testing the response time. Secondly, a dynamic programming algorithm was designed to optimize the query performance of database, which has been illustrated by an example. In addition, the expansion of distributed collaborative database was studied from the aspects of vertical and horizontal expansion. For the concurrent control of collaborative database, a concurrent control strategy was proposed based on role and multi-version timestamp. In order to ensure the consistency and stability of the data, conflict affairs were scheduled by the factor balanced principle of role and version.3. Research on conflict detection method of fuel system collaborative design in digital power plant. Hierarchical constraints and constraint satisfaction were analyzed, and constraints were described by XML. On this basis a conflict detection model based on constraint satisfaction is proposed. The constraints were divided into two sets:one set consisted of known constraints and the other of unknown constraints which were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, and algorithm flow of conflict detection was studied with verification of instance. While a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the BP neural network, and the steps were designed for the optimization process. Compared with BP neural network optimized by Genetic Algorithm, the results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm.4. Considering the above theoretical results and methods, a collaborative design system of fuel system collaborative design in digital power plant was developed with a combination of actual power plant project, and the architecture and database were designed. Taking coal conveying system in thermal power plant as example, the system has been studied from the aspects of structure design,3D modeling, collaborative working, design detection and generation of equipment lists, etc. Designers can select other cooperative personnel and complete the design process by sharing and exchanging information. The system has achieved three-dimensional, parametric and automatic, which greatly improves the design efficiency and quality.