A new combined clustering method to Analyse the potential of district heating networks at large-scale

Julien F. Marquant, L. Andrew Bollinger, Ralph Evins and Jan Carmeliet

Energy, 2018, vol. 156, issue C, 73-83

Abstract: For effective integration of large amounts of renewables and high-efficiency energy technologies, their benefits have to be quantified. Network-level energy optimisation approaches can determine the optimal location of generation technologies within a region and the optimal layout of energy distribution networks to link them. Mixed-integer linear programming (MILP) formulations are generally employed and this is often a burden for large scale models as the computational time drastically increases with the problem size.

Keywords: Combined clustering; Energy hubs; Distributed energy systems; Genetic algorithm; MILP energy optimisation (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544218308478
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:156:y:2018:i:c:p:73-83

DOI: 10.1016/j.energy.2018.05.027

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 ().