A Time-series-based approach for robust design of multi-energy systems with energy storage

Paolo Gabrielli, Florian Fürer, Portia Murray, Kristina Orehounig, Jan Carmeliet, Matteo Gazzani, Marco Mazzotti

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

This work proposes a mixed-integer linear program approach to consider the uncertainty of input data in the optimal design of distributed multi-energy systems involving both conventional and renewable-based conversion technologies, as well as storage units. The design procedure determines the minimum-cost combination of technology selection, size and operation. Traditionally, distributed multi-energy systems are designed using deterministic optimization methods, implying that the input data are known when the system optimization is performed. However, such input data are commonly affected by significant uncertainty, making the deterministic solution possibly suboptimal or even unfeasible. Recently, both robust and stochastic optimization have been applied to the optimal design of multi-energy systems. Nevertheless, when including energy storage in the analysis, the traditional techniques are complicated by the short- and long-term evolution of the input data of the underlying optimization problem, as well as their complex interactions. Moreover, the analysis of the uncertainties characterizing such input data for the optimal design of multi-energy systems, as well as the evaluation of their impact on the system design, have been investigated in little details. The approach proposed in this work is based on the analysis of the historical time-series representing the input data of the mixed-integer linear program for different years. First, the most important input data in terms of optimality and robustness of the system design are identified. Moreover, the most relevant features of the corresponding time-series are determined and assessed. Then, this information is used to build a custom set of input data which translates into a system design able to guarantee both security of supply and cost optimality.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier bedrijfsinformatie b.v.
Pages525-530
Number of pages6
ISBN (Print)9780444642356
DOIs
Publication statusPublished - 1 Jan 2018

Publication series

NameComputer Aided Chemical Engineering
Volume43
ISSN (Print)1570-7946

Funding

This work was supported by the Swiss National Science Foundation (SNF) under the National Research Program Energy Turnaround (NRP70), grant number 407040-153890 (IMES project).

Keywords

  • energy storage
  • MILP
  • Multi-energy systems
  • stochastic optimization
  • time-series analysis

Fingerprint

Dive into the research topics of 'A Time-series-based approach for robust design of multi-energy systems with energy storage'. Together they form a unique fingerprint.

Cite this