EconPapers    
Economics at your fingertips  
 

Decomposition method for optimizing long-term multi-area energy production with heat and power storages

Elnaz Abdollahi and Risto Lahdelma

Applied Energy, 2020, vol. 260, issue C, No S0306261919320197

Abstract: To achieve efficient transition towards climate and energy framework targets, improvement in energy efficiency is important. This paper presents a model for long-term multi-area combined heat and power production with heat and power storages, and power transmission between areas. Assuming fixed unit commitment, the model minimizes total production and transmission cost. The model can in principle be solved as a linear programming model. However, energy storages impose dynamic constraints to the model, making the long-term model very large and slow to solve. To speed up solution and to allow larger models to be solved, we develop a novel decomposition method that solves three kinds of smaller sub-models iteratively. The method is validated by comparing it with the integrated linear programming model using realistic demand data generated by a forecasting model. The method produces near-optimal solutions within three iterations. The decomposition method can also solve larger models much faster than the integrated model.

Keywords: Combined heat and power (CHP); Energy storage; Power transmission; Energy efficiency; Optimization; Decomposition (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261919320197
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:260:y:2020:i:c:s0306261919320197

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.2019.114332

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 ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:260:y:2020:i:c:s0306261919320197