Short-Term Hydrothermal Scheduling of an Indian Utility System Using an Enhanced Bacterial Foraging Algorithm

Abstract

The Short-Term Hydrothermal Scheduling (STHTS) problem is treated as a dynamic large scale optimization problem. The Bacteria Foraging Algorithm (BFA) is a recently developed evolutionary optimization technique which is based on the foraging behavior of the E. coli bacteria. The BFA has been successfully implemented to solve various optimization problems. To solve STHTS problem, considering its high dimension search space, some critical improvements are introduced into the basic BFA to improve convergence. Here the chemotactic step is modified, so that better exploration of the search space can be obtained. An Enhanced Bacteria Foraging Algorithm (EBHA) is presented to solve the short term hydrothermal coordination problem. The developed algorithm is illustrated for a test system consisting of four hydro and seven thermal plants of an Indian Utility system. It is found that convergence characteristic is excellent and the result obtained by the proposed method is better in terms of fuel cost.

Conventional and Metaheuristic Optimization Algorithms for Solving Short Term Hydrothermal Scheduling Problem: A Review

“…The modifications in canonical BFA were made to improve its convergence behaviour. Reference [237] implemented bacterial foraging algorithm on a real Indian power system to solve the CSTHTS problem.…”