Multiobjective fixed head hydrothermal scheduling using integrated predator-prey optimization and Powell search method

An integrated methodology that embeds global and local search technique is explored for solving multiobjective hydrothermal scheduling. Predator-prey optimization (PPO) is used as a base level search in the global search space and Powell's method as a local search technique. Predator-prey model is based on particle swarm optimization (PSO). In spite of several advantages of PSO as compared to other evolutionary methods, it has some major drawbacks such as local optimal trapping and lack of efficient capability to treat the constraints. PPO model includes predator and prey particles in population. The prey objective is to escape from the predators reaching to its lair, while predator's goal is to capture the prey that increase exploration and exploitation capability of PSO. Powell's method aims to fine tune the solution obtained from PPO and to enhance the search capability of proposed method. In addition, a penalty less constraint handling method is employed for considering equality and inequality constraints. Fuzzy methodology has also been exploited to find the best compromised solution. The proposed integrated technique is applied to three hydrothermal scheduling problems with valve-point effect of thermal generators and transmission losses. The proposed method yields high quality solution while satisfying all constraints.