A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification

Luca Moretti, Marco Astolfi, Claudio Vergara, Ennio Macchi, Josè Ignacio Pérez-Arriaga and Giampaolo Manzolini

Applied Energy, 2019, vol. 233-234, 1104-1121

Abstract: Off-grid microgrids constitute an increasingly viable alternative to grid extension for rural electrification. Thanks to significant reductions in hardware cost, energy cost for off-grid users in areas sparsely covered by the national grid has become competitive with grid-connection once infrastructural costs are accounted for. Microgrids offer advantages also from an environmental and social point of view, featuring generation systems with high renewable penetration and facilitating the involvement of local communities in development projects. To further enhance microgrids economic competitiveness, it is necessary to devise innovative control strategies and design algorithms, that can ensure an optimal operating performance at the lowest overall cost. In this paper we present a new predictive design and dispatch optimization algorithm based on Mixed Integer Linear Programming (MILP). The new method is compared to a previously developed heuristic methodology, applying both to the design and yearly performance estimation of local microgrids, characterized on the basis of real data relative to a sub-Saharan African region. The potential advantages of including the proposed microgrid design method in a regional electrification planning model are illustrated in a realistic case example.

Keywords: Microgrid; Electrification; Design optimization; MILP; Economic dispatch; Off-grid systems (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (29)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261918315149
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:233-234:y:2019:i::p:1104-1121

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.2018.09.194

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 ().