Study On Key Problems In DFSM And Its Distributed Intelligence System

Environmental protection, technological progress, social development and national policy, all the factors together makes the choice of Smart Grid be inevitable for the world electric power industry. Because of urgent needs to improve the self-healing ability, utilization efficiency of electric infrastructure, power quality and reliability, the construction and development of Smart Grid will start from distribution system and terminal consumers.The research and practice on Smart Grid is still at the initial stage, which involve a great number of technical fields. Distribution Fast Simulation and Modeling (DFSM) is the basis and one of the key functions of Smart Distribution. This dissertation focuses on the key issues of DFSM and its Distributed Intelligence System (DIS). The aim is to design and develop the DIS of DFSM, and achieve substantive results on kernel application and related fields in DFSM.The distribution state estimation is the core function of DFSM. A three-phase state estimation algorithm based on the branch current for distribution network is realized by practical programming using Java. Large numbers of tests prove that this algorithm can perform decoupled three-phase calculation, and deal with many types of meter data, which is the foundation of later studies.The theories of Moore-Penrose generalized inverse matrix and the only minimal least squares solution of the weighted least squares problem are applied to deduce the formula, which expresses the mathematical relationship between the meter data error and the state vector estimation error in distribution state estimation; and a novel method for meters evaluation and configuration optimization in distribution network is proposed. This method can avoid the combinatorial explosion problem, and determine the type and the optimal installation site of measurement devices simply and exactly, thus provide theoretical and methodological support for the construction and continuous optimize of measurement system.The theory and perspective of intelligent science are introduced into the study on Smart Grid, and an improved human intelligence model is proposed. It explores that the conversion process of"information→knowledge→intelligence"is the kernel mechanism of the formation of intelligence, which is used to direct the study on DIS of DFSM. The theory and methodology of Agent and Multi-Agent System (MAS) is applied in the study on DFSM and its DIS, an eight-elements structure model of Agent is proposed. Furthermore, DIS of DFSM based on MAS (masDFSM) is being designed and developed.By applying the eight-elements structure model of Agent, the distribution three-phase state estimation program is embedded in the action database of Agent, and a parallel distributed computing environment for distribution three-phase state estimation (masDSE) is established based on the MAS. This work provides new methods and templates for developing other simulation software and performance improvement of DFSM.A suitable mathematical model is built for the study of the task scheduling problem in masDSE. And a new optimal method for task scheduling based on fuzzy C-means clustering algorithms is proposed, which can achieve optimal balance of calculation load for all computers, thus further improve the whole performance of masDSE.