An optimization study on a typical renewable microgrid energy system with energy storage

J. Graça Gomes, H.J. Xu, Q. Yang and C.Y. Zhao

Energy, 2021, vol. 234, issue C

Abstract: In isolated microgrids and remote regions, the challenge of developing reliable and self-sufficient renewable energy systems is amplified due to the lack of grid flexibility options. One of the leading solutions to increase renewable energy usage in isolated systems is the commission of energy storage. The current study proposes a novel optimization model that sizes the most cost-efficient renewable power capacity mix of an autonomous microgrid supported by storage technologies. The proposed algorithm considers operational, technical and land-use constraints. The problem is formulated using linear programming, is tested and scrutinized with sets of historical weather, load demand and installation prices data, and is modelled hour-by-hour. The method is applied to Corvo, an island in the Azores archipelago, Portugal. The results obtained exhibit that the proposed approach provides the optimal configuration of the renewable-based microgrid with an LCOE (Levelized Cost of electricity) of 0.21 €/kWh, a value lower than a diesel-based alternative, and while ensuring minimum land area occupation. Furthermore, sensitivity analysis is also presented to examine the effect of variables on the LCOE and PC (present cost) of the system. The present study shows that the developed optimal sizing model can improve electricity planning and facilitate energy transition in distributed power systems.

Keywords: Renewable microgrid; Optimization; Energy storage; Distributed generation; Bayesian artificial neural network (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544221014584
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:234:y:2021:i:c:s0360544221014584

DOI: 10.1016/j.energy.2021.121210

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 ().