N Ahamed Hussain Asif / R Nagarajan / S SELVAPERUMAL
Librería Samer Atenea
Kálamo Books
Librería Elías (Asturias)
Librería Kolima (Madrid)
Librería Proteo (Málaga)
This Book aims to introduce two new metaheuristic algorithms, the Marine Predators Algorithm (MPA) and the Giant Trevally Optimizer (GTO), for the optimal placement of FACTS devices in power systems under deregulation to reduce congestion and maximize transmission efficiency. As a first step, the MPA algorithm is used to optimize the placement of FACTS based on contingency analysis in both a four-bus and a 24-bus EHV Indian grid. There are improvements of a large magnitude after FACTS placement: congestion quantity decreased from 8 to 4, power overload from 543.07 MW to 385.08 MW, and overall severity of overloads from 34.77 to 20.75. Comparative studies using evolutionary programming (EP) verify that MPA incurs lower generation costs, e.g., $2.732 million with UPFCs versus $2.738 million with EP in the 24-bus grid. During the second phase, the GTO algorithm solves FACTS sizing and placement in IEEE 14-bus and 30-bus models with different reactive loading conditions. The presented work proves that hybrid metaheuristic-based FACTS optimization can potentially enhance congestion management and system reliability in restructured markets.
