An improved teaching learning based optimization algorithm for optimal scheduling of short-term hydrothermal system considering valve-point loading effect [articol]

Abstract

The power system is generally planned to meet the ever increasing load demand of the consumers at a reasonable tariff by properly handling the fuel cost. The short-term hydrothermal scheduling problem received the attention of researchers, in arriving the minimum fuel cost of power plants. It advocates the scheduling process of hydro and thermal plants with a view to minimise the fuel cost over the planning horizon by considering system constraints. The problem of scheduling of generation mixture of hydro and thermal problems involves non-linear, non-convex curves comprising valve-point loading effects with a set of equality and inequality constraints. The interpretation of hydrothermal plants with hydro dominance is seems to be complex than a hydro system. Hence, the conventional techniques may not yield the perfect solution for this kind of problem. In this article, a simple concept of improved teaching learning based optimization (ITLBO) algorithm for the solution of short-term hydrothermal scheduling has been presented. It is an exceptional distinct optimization algorithm stimulated by the effect of repercussion of a teacher on the productivity of learners in the domain. The proposed methodology has been applied on two standard test systems for 24 hours time period. The results are evolved in terms of water discharge, reservoir storage volume and fuel cost of thermal units with/without Valve-Point loading effects. The performance of the proposed method is validated by comparing with other methods available in the literatures. From the findings, it is evident that ITLBO based approach is able to provide a global optimal solution