Estimation of Smooth and Non-smooth Fuel Cost Function Parameters Using Improved Symbiotic Organisms Search Algorithm
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, vol.15, no.1, pp.13-25, 2020 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 15 Issue: 1
- Publication Date: 2020
- Doi Number: 10.1007/s42835-019-00291-x
- Journal Name: JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
- Page Numbers: pp.13-25
- Keywords: Improved symbiotic organisms search, Parameter estimation, Fuel cost curve, OPTIMAL POWER-FLOW, CURVE PARAMETERS, PLANTS
- Gazi University Affiliated: Yes
Abstract
The improved symbiotic organisms search (R-SOS) Algorithm is proposed to estimate parameters of smooth and non-smooth fuel cost functions for improving the solution accuracy of economic dispatch problems. Determining accurately of fuel cost curve is a crucial task, because they effect directly solution accuracy of economic dispatch and optimal power flow problems. There are two models as smooth and non-smooth forms to describe the input-output characteristics of generators in thermal power plants. This paper presents an implementation of the R-SOS algorithm in order to estimate parameters of these functions. First, second and third order smooth fuel cost functions and non-smooth fuel cost function with valve point effects are used in the study. The estimation problem is described as an optimization one. The R-SOS algorithm is proposed for solving this optimization problem and it minimizes the total error of estimated parameters. The performance of the R-SOS algorithm is tested on four different cases having different fuel types. Results obtained are compared to classical Symbiotic Organisms Search and other meta-heuristic methods and they show that the proposed R-SOS algorithm is favourite model in all test cases for estimating accurately of fuel cost function parameters.