Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms

Mohsen Gitizadeh, Ali Azizi Vahed and Jamshid Aghaei

Applied Energy, 2013, vol. 101, issue C, 655-666

Abstract: The main goal of this paper is to present a Multistage Distribution network Expansion Planning (MDEP) problem in the presence of Distributed Generations (DGs) in a multi-objective optimization framework. The proposed model simultaneously optimizes two objectives: minimization of investment and operation costs and maximization of reliability index. The proposed optimization model is solved subject to AC power flow constraints to obtain the optimal configuration of feeders (adding and removing lines) including the optimal size of branch conductor, replacement of conductor for reserve feeders, and generated power of DGs. To include reliability concerns in the proposed MDEP problem, an analytical approach on the basis of graph theory is implemented to evaluate the Energy-Not-Supplied (ENS) index as an extra objective function. Also, in this paper, in order to identify Pareto optimal solutions of the multi-objective MDEP problem, a hybrid Particle Swarm Optimization (PSO) and Shuffled Frog Leaping (SFL) algorithm is implemented. A synthetic distribution test system is considered for the MDEP problem in a 4-year planning horizon. The results of the hybrid PSO and SFL algorithm are compared with those of the classical PSO and SFL methods.

Keywords: Multi-objective MDEP; Distributed generation; Energy-not-supplied; Hybrid evolutionary algorithms (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (21)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261912005223
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:appene:v:101:y:2013:i:c:p:655-666

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2012.07.010

Access Statistics for this article

Applied Energy is currently edited by J. Yan

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