Intelligent control of custom power devices for power quality improvement in distributed generation system

Abstract

Distributed Generation (DG) systems are undergoing a rapid development as a new means of power generation. It refers to power generation at the point of consumption. Recently,a number of small-scale renewable energy sources such as Wind Turbine (WT) are connected to the distribution system and the number of connections is increased. However, maintaining consistent operation has become a challenge because of the practical difficulties in mitigating harmonics, managing reactive power, balancing the unbalanced load currents are concerned. The main cause of disturbance to the voltage at the Point of Common Coupling (PCC) is the frequent wind power fluctuations and variations in the load as well as changes happening to the utilities and customer s side. These variations have an undesirable effect on power quality of DG systems. In this work, the analysis of different Custom Power Device (CPD) controllers is proposed for voltage compensation and power flow control of DG on the distribution system. A novel scheme is proposed consisting of a Photovoltaic System (PV) as a DC source of DVR. The operation of the wind energy into the DG is affecting the power quality of the system due to uncertainty and fault conditions. A DVR is proposed for this work for compensation under several circumstances of sag/swell and harmonic conditions. The proposed Artificial Neuro-Fuzzy Inference System (ANFIS) based DVR controller is intended to regulate the voltage at the PCC within the limits and stabilize the operation of the system in the event of disturbances. This thesis deals with the CPD device such as D-STATCOM with an intelligent controller scheme for enhancement operation of DG system. In this research work, the control methodology for the management of the D-STATCOM, which provides reactive and renewable energy based real power support using the Adaptive Neuro-Fuzzy Inference System based Control system (ANFIS) is investigated. This thesis proposes a steady operation of hybrid (DG) system composed of dual renewable energy sources, WT and a Fuel Cell (FC) with the CPD controller. Specificallythe Unified Power Quality Conditioner (UPQC) with a Neural Network model is designed for stable operation that guarantees improved quality of power at their point of installation of the hybrid DG system. newline