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Dynamic Stability Improvement of a Smart Grid Using Neural Network Based STATCOM
Objectives: A micro grid is a cluster of loads and distributed resource units serviced by a distribution grid and capable of operation in a grid –connected mode, in an autonomous mode or a ride-through between the above two modes. Methods: Micro grids are significant for local reliability, considerable reduction of losses, different costs and continuity of service. Smart Grid is formed with the interconnection of different generating resources and loads, the characteristics of the grid can be modified according to the requirements. The major challenges are fault clearing, voltage regulation, islanding, and power quality and interfacing with the utility system in terms of its stability. Findings: This paper describes improvement of dynamic stability in interconnected on and off shore wind turbines with Proposed Artificial Neural Network Controller compared with the discrete Proportional–Integral–Derivative (PID) controller. As per the references indicated, the generators driven by OWF may be modeled as the parallel connection of several Doubly -Fed Induction Generators (DFIGs) and the generators driven by MCFs can be modeled by means of Squirrel Cage Induction Generators (SCIGs) well efficiently. Normally, STATCOMs or different combinations of Flexible AC Transmission System (FACTS) devices are used as large scale control devices in many applications. In the present work, Artificial Neural Network (ANN) based PID controller is used instead of Discrete PID controller for providing control pulses to the STATCOM connected to the grid system.
Artificial Neural Network, Converter, Power System Stability, Smart Grid, Static Var Compensators.
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