Simulated Annealing-Based Optimization (SA) Approach for Solving Economic Load Dispatch Problems

Abstract

The economic dispatch problem with non smooth cost function has become a major issue with depletion of coal and increasing fuel prices. A proper schedule of available generating units may save millions of dollars per year in production cost. In this paper, Simulated Annealing Optimization (SA) algorithm is proposed for solving economic load dispatch (ELD) problems. Simulated annealing is a random-search technique which exploits an analogy between the way in which a metal cools and freezes into a minimum energy crystalline structure (the annealing process) and the search for a minimum in a more general system; it forms the basis of an optimization technique for combinatorial and other problems Simulated annealing can deal with highly nonlinear models, chaotic and noisy data and many constraints. It is a robust and general technique. Its main advantages over other local search methods are its flexibility and its ability to approach global optimality. In all cases, the proposed algorithm either matches or outperforms the solution reported for the existing algorithms. The proposed technique is also easy to implement and capable of finding feasible near global optimal solution.