A Novel Approach of Non-dominated Sorting TLBO for Multi Objective Short-Term Generation Scheduling of Hydrothermal-Wind Integrated System

Abstract

Generally, wind energy resources have characteristics of randomness and uncontrollability, which leads to uncertainty, intermittency and volatility of its outputs Therefore, great challenges in coordinating it with a large hydrothermal system. In this article, solves multi-objective short-term hydrothermal scheduling (MOSTHTS) problem integrated wind power generation using an effective and specific parameter less algorithm of Non-dominated Sorting Teaching Learning Based Optimization (NSTLBO) algorithm. The problem has been modelled in the form of multi-objective functions which includes fuel cost of thermal and wind generators, transmission loss and environmental emissions such as NOx, SOx and COx with various constraints of hydrothermal and wind systems. The interaction of the present NSTLBO algorithm is to decrease the operating cost of thermal and wind generators, transmission losses and different kinds of emissions. By applying this algorithm a set of non-dominated solutions are created. A fuzzy decision making approach has been involved on these solution in order to identify the best comprise solution among the group of solutions. The practicability of the proposed approach has been demonstrated on a sample test system which consists of four hydro, four thermal and two wind units. The experimental finding of this method has been compared with that of well established techniques in order to validate the performance of the test results.