A new approach of grid integrated power system stability and analysis through fuzzy inference PSO algorithm for handling of islanding PDCS mode datasets

Abstract

A network with large number computing nodes during the operation is a big challenge and complex task for system safe and secure operation. Data acquisition from large network has been well defined from the many methods in present scenario of world science and technology. Fuzzy-based inference system is elaborately presented with variable weighted random parameter of Particle Swarm Optimization (PSO), cognitive, and social terms. The distance between personal dataset and global set data points positions, at two previous instants, is taken for modified PSO. Main content this paper is that of data handling and concentrated in elaborating the modeling to complete this task for Peculiar Disturbance Conditional State (PDCS), operating mode of network. From application point of view, grid network with non-conventional energy systems like distribution generators and micro-grids is considered to manage and handle data in practical environment. Information from data availability is defined zone to be classified as accurately and precisely. This paper presents fuzzy inference-modified PSO algorithm for essential analysis and identification and differentiation of data on user-required satisfy level. When a network is extended by means of new small-scale energy systems and operating with main grid network, the possibility of re-existence of global best with PSO data is also reconsidered for acquisition of optimization.