Economical design of WAMS through soft computing: co-optimal PMU placement and communication infrastructure

Abstract

Recently, utilities have developed and deployed wide area measurement systems (WAMS) to improve the electricity grid's ability to monitor, manage, and defend itself. In a typical WAMS setup, multiple measuring devices, communication systems, and energy management systems work together to gather, transmit, and then analyze data. Although there is substantial interdependence among these three capabilities, most research treats them independently. The work presented here minimizes the total cost of the communication infrastructure (CI) by taking into account the price of phasor measurement units (PMUs) and the placement of a phasor data concentrator (PDC) at the same time. The optimum CI and PDC placement has been built with Steiner tree optimization's help. There have also been practical operating scenarios of more realistic working conditions containing pre-installed PMU, pre-installed fiber optic and N-1 contingency. The optimization hurdle has been overcome by utilizing the binary firefly algorithm (BFFA), which has undergone testing on IEEE 14, 30, and 118 bus systems to demonstrate its effectiveness. A comparison has been offered, and it clearly demonstrates the proposed approach's superiority over previously published articles.