Metaheuristic optimization of facts Devices in deregulated markets using Marine predators and giant trevally Algorithms

Abstract

newline In deregulated electricity markets, transmission congestion can be newlineeliminated by optimal placement of FACTS devices. This thesis aims to newlineintroduce two new metaheuristic algorithms Marine Predators Algorithm newline(MPA) and Giant Trevally Optimizer (GTO) for best placement of FACTS newlinedevices in power systems under deregulation in order to reduce congestion newlineand maximize transmission efficiency. As a first step, the MPA algorithm is newlineused for optimal placement of FACTS based on contingency-based analysis in newlineboth a four-bus and a 24-bus EHV Indian grid. There are improvements of a newlinelarge magnitude after FACTS placement: congestion quantity decreased from newline8 to 4, power overload from 543.07 MW to 385.08 MW, and overall severity newlineof overloads from 34.77 to 20.75. Comparative studies with evolutionary newlineprogramming (EP) verify that MPA provides less generation costs, e.g., newline$2.732 million with UPFCs versus $2.738 million with EP in the 24-bus grid newline