Estimation of power factor by the analysis of Power Quality data for voltage unbalance

Power Quality (PQ) has been identified as a complex and diversified problem across the board in electrical power industry. It has not only confused the power utilities but also has attracted the attention of its customers and equipment manufacturers. Although extensive research work is being done in this field but one of the main problem encountered by its stake holders is the voltage unbalance in electrical power system. The problem of voltage unbalance has affected the safety, reliability and economic efficiency at all levels in power industry. In this research Computational Intelligence Techniques have been used for efficiently predicting the power factor of unbalanced load of a power distribution system. The Principal Component Analysis Technique was used to find the optimized number of new dimensions of PQ data. Finally Feed Forward Back Propagation (FFBP) algorithm was used to estimate the power factor of a distribution network by analyzing the real power system parameters. This research highlights the importance of maintaining power factor close to unity for power utilities to achieve sustainable availability of quality supply of electrical power for its customers. The outcomes of the proposed techniques were compared and tested with the field results of a power utility in Victoria, Australia.