ECONOMIC LOAD DISPATCH OPTIMIZATION USING BAT ALGORITHM WITH VARIOUS PERCENTAGES OF LOADS AT DIFFERENT TIME INTERVALS
International Journal of Recent Trends in Engineering and Research
Nowadays the economic load dispatch is the vital issue in the electrical system due to the greater requirement of the consumer. This issue can be optimized using improved technologies like BAT algorithm, Genetic algorithm, Cuckoo algorithm and Intelligence water drop methods helps to upgrade the economic dispatch issues. BAT algorithm was developed in 2010 and it is a meta-heuristic and Nature-inspired algorithm which depends on echolocation behavior of micro-bats in searching their prey. The
... rength of BAT algorithm is examined on IEEE30 bus system at various loads with different time interval. The results represent the greater convergence capability and effectiveness of the BAT algorithm. Keywords-Bat algorithm (BA), Meta-heuristic, Loudness and Pulse rate of emission I. INTRODUCTION Economic dispatch is the process of optimization of operating cost is important in operational planning issues. Nowadays organizing and utilization of power system is a demanding task due to its complexity and to satisfy the consumer requirements for electrical energy with continuity of service and reliability. The conventional approaches for solving the load dispatch issues are by applying non-linear programming technologies. This approach minimizes a convex objective function over a convex set thus insuring a single minimum. Meta-heuristic optimization is another method of resolving optimization issues. These algorithms are commonly based on process in physics and biology. The meta-heuristic algorithm is perfect for non-convex load dispatch issues as they do not affected from continuity. Bat algorithm is the population based algorithm. This algorithm emulates the echolocation capability of micro-bats which uses for recognizing and hunting the prey. The position of the Bat gives the possible result for the load dispatch issues. Aim of the solution is represented by best position of BAT to its food. BA and its constraints have been used to solve the load dispatch issues. Some well-liked nature-inspired algorithms like Ant colony optimization (ACO) based on hunting behavior, Artificial bee colony (ABC) based on behavior of honey bee, Cuckoo search based on the brooding behavior of cuckoo spices and many more methods are used to optimize the load dispatch issues among them BAT algorithm has less convergence time to operate hence it is very reliable method for power dispatch issue. The Bat algorithm also applied for the non-smooth convex and non convex problems which has unbalanced constraints which affect the economic operation of the system.