Multi-area economic dispatch using an improved stochastic fractal search algorithm

Jian Lin and Zhou-Jing Wang

Energy, 2019, vol. 166, issue C, 47-58

Abstract: Multi-area economic dispatch (MAED) characterized by high non-convexity and non-linearity is an important issue in power system operation. This paper presents an improved stochastic fractal search (ISFS) to solve the MAED problem considering the area load demands, the tie-line limits and various operating constraints. To balance exploration and exploitation, the ISFS introduces an opposition-based learning method for population initialization as well as for generation jumping. By combining with the differential evolution strategy, a hybrid diffusion process is developed and used as the local search technique to enhance the exploitation ability. Furthermore, a novel repair-based penalty approach is presented and incorporated into the ISFS to find feasible solutions more efficiently. The effectiveness and robustness of the ISFS is evaluated on several test systems consisting of 16–120 generating units. Computational results demonstrate the superiority of the proposed ISFS scheme over the state-of-the-art algorithms.

Keywords: Multi-area economic dispatch; Stochastic fractal search; Power system; Constraint handling approach; Repair process (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544218320553
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:166:y:2019:i:c:p:47-58

DOI: 10.1016/j.energy.2018.10.065

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().