Solar and Wind Farms Interconnected Generation Scheduling of Thermal Generators using Improved ALO algorithm

Abstract

A Population based optimization algorithm of Improved Ant Lion Optimizer (IALO) is proposed to solve the renewable energy constrained generation scheduling problem. An IALO is having ability to obtain the global optimal solution because the local optima avoidance is inherently high and exploration of such space is guaranteed by random selection of ant and ant lions. The purpose function is to reduce the cost of hybrid system with satisfying standard operating constrains of plants. Initially the variables of the problem are optimized using ALO algorithm and then they obtained results are tuned using PSO algorithm for getting accurate solution. Numerical example with IEE 39 bus test system (ten thermal twenty four hour) with an equivalent Solar and Wind generators are considered. The obtained results of UC schedule power dispatch, start-up cost, fuel cost and total cost are presented. The results show that this method efficiently minimizes total operating cost with less computational effect. The graphical representation and comparative study are also done to express the superiority of the applied algorithm. From the comparison, it is evident that the ALO is a promising technique to solve non linear engineering optimization problem.