A new stochastic framework for optimal generation scheduling considering wind power sources

Article type: Research Article

Authors: Tabatabaei, Sajad

Affiliations: Department of Electrical Engineering, Islamic Azad University, Mahshahr, Iran

Note: [] Corresponding author. Sajad Tabatabaei, Department of Electrical Engineering, Mahshahr Branch, Islamic Azad University, Mahshahr, Iran. Tel.: +98 9166156345; Fax: +98 711 735 3502; E-mail: sajjadtabatabie@gmail.com

Abstract: This paper suggests a new stochastic framework based on 2 m+1 point estimate method (PEM) to solve the mid-term generation scheduling (SMGS) problem. The new formulation makes use of an adaptive modified bat algorithm and a novel self-adaptive wavelet mutation strategy for the establishment of new robust algorithm for the present problem. In addition, this work improves the modeling process of wind-thermal system in the MGS problem by considering the possible uncertainties when scheduling the generators of power system of the problem. The proposed model can concurrently capture the uncertainty effect of load and wind speed variations. The feasibility and efficiency of the proposed method is examined using two test systems.

Keywords: Mid-term generation scheduling (MGS), point estimate methods, wind power generation, modified bat algorithm, self-adaptive strategy

DOI: 10.3233/IFS-131015

Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 3, pp. 1571-1579, 2014