An Improved Self-Adaptive Teaching-learning Based Optimization for Multi-area Economic Dispatch

Abstract

The multi-area economic dispatch (MAED) is a hot and vital research topic for energy saving and emission reduction. Multi-areal economic dispatch refers to the most economical distribution of load requirement among the output units under the premise of satisfying the physical and operational constraints of multiple areas. Each area is connected by a transmission line. In this paper, an improved algorithm (SA-TLBO), which uses adaptive teaching factor to replace the teaching factor in the original teaching-learning based optimization, is developed. Since, adaptive teaching factor can achieve a good balance between convergence speed and search ability, thus improving the overall performance of the algorithm. The method is tested on a system with ten areas, and each area has a 130-unit system. Compared with other two improved strategies and conventional algorithms, the proposed SA-TLBO is shown to yield better solutions for multi-area economic dispatch problems.