Application of flower pollination algorithm to multi-objective environmental/economic dispatch

Abstract

Environmental/economic dispatch is a fundamental issue in power system operations as it deals with the scheduling of the generating output among available units for simultaneous minimization of fuel cost and emission output, two objectives that collide. Furthermore the violation of specific constraints must be avoided. In this paper, environmental/economic dispatch is solved applying a new meta-heuristic optimization method, namely flower pollination algorithm. The proposed method is inspired by the pollination process of flowering plants with Lévy flight to imitate the movement of insect pollinators. The multi-objective environmental/economic dispatch problem can be described by polynomial objective functions and converted into single-objective using weighted sum method that produces non-dominated solutions. The most satisfactory solution is chosen according to a decision maker that is based on fuzzy set theory. Effectiveness of the proposed approach is examined on two test systems. The first system comprises three generating units while the second one is a six-unit system. Numerical results obtained are compared to those obtained by other modern optimization methods. The proposed flower pollination algorithm seems to be a promised optimization technique as it provides fast and efficient solutions.