Open AccessCombined Emission and Economic Dispatch Problems using Hybrid of Particle Swarm and Teaching Learning Based Optimizations
Author(s) -
Rajanish Kumar Kaushal,
Praveen Saini,
Tilak Thakur
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i8719.078919
Subject(s) - particle swarm optimization , economic dispatch , mathematical optimization , computer science , energy consumption , transmission (telecommunications) , population , electric energy consumption , electric power , electricity generation , electric power system , energy (signal processing) , power (physics) , engineering , mathematics , electrical engineering , electric energy , telecommunications , statistics , physics , demography , quantum mechanics , sociology
with day by day increasing population and standard of human being increases the consumption of electrical energy and this increasing in the consumption of electrical energy, increases the number of generators, transmission lines to full fill the daily needs of the electrical energy. So the power system has become more complex and main source of gaseous emission. So arranging and the task of intensity framework of power system must be done in such a way that energy and emission arising due to power generation, the retribution paid by the power plant because of emission and cost paid in generation need to tackle all the while. This paper shows a reliable and effective hybrid of particle swarm optimization (PSO) algorithm and teaching learning based optimization (TLBO) for combined emission and economic dispatch (CEED) problems. The outcomes have been shown for combined emission and economic dispatch issues of standard 3 and 6-generators frameworks with consideration of transmission losses.