Optimal discharge scheduling of energy storage systems in MicroGrids based on hyper-heuristics

R. Mallol-Poyato, S. Salcedo-Sanz, S. Jiménez-Fernández and P. Díaz-Villar

Renewable Energy, 2015, vol. 83, issue C, 13-24

Abstract: In this paper we tackle the optimal Discharge Scheduling of Energy Storage systems Problem (DSESP) in MicroGrids, considering renewable generation, and applying hyper-heuristic (HH) algorithms. The problem consists of, given the generation and load profiles in the MicroGrid, obtaining the optimal discharge scheduling of the Energy Storage System (ESS) that minimizes the consumption from the utility grid. HHs are a novel methodology in optimization problems that constructs a solution to a given problem by means of the application of basic heuristics, evolved using a global search algorithm. This methodology can be easily adapted to solve the DSESP, in this case by using an evolutionary algorithm as global approach. In this paper we detail the adaptations performed to a HH to tackle the DSESP, mainly in the encoding of solutions, and new evolutionary operators that improve the evolution of good solutions to the problem. The performance of the proposed approach has been evaluated in a real Microgrid, with different scenarios of generation and load profiles, obtaining around 5% reduction of the energy consumption from the utility grid.

Keywords: MicroGrids; Energy storage systems; Discharge scheduling problem; Hyper-heuristics; Algorithms (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096014811500289X
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:renene:v:83:y:2015:i:c:p:13-24

DOI: 10.1016/j.renene.2015.04.009

Access Statistics for this article

Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides

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