Combining simulation and optimization to derive operating policies for a concentrating solar power plant

Jesse G. Wales, Alexander J. Zolan, William T. Hamilton, Alexandra M. Newman () and Michael J. Wagner
Additional contact information
Jesse G. Wales: Colorado School of Mines
Alexander J. Zolan: Thermal Energy Systems
William T. Hamilton: Thermal Energy Systems
Alexandra M. Newman: Colorado School of Mines
Michael J. Wagner: Thermal Energy Systems

OR Spectrum: Quantitative Approaches in Management, 2023, vol. 45, issue 1, No 5, 119-150

Abstract: Abstract Optimizing short-term decisions over a rolling horizon and/or using deterministic penalties to capture system stochasticity can lead to myopic policies that fail to consider unplanned events and their long-term adverse effects. We present a methodology that integrates an off-line optimization model with a simulation procedure to determine the profitability of different operating strategies; specifically, the latter is used to generate additional constraints for the former when failures occur according to system component operating lifetimes that (i) are subject to exogenous uncertainty, and (ii) may degrade more quickly under specific operating conditions. We use the feedback provided by the simulation model in a parametric analysis to obtain penalties that can be used in short-term operations scheduling to maximize the long-term revenues obtained by the optimization model. We apply this research to a concentrating solar power plant; our results show that the methodology can be used to choose an operating policy that balances maximizing profit while accounting for maintenance costs. Integrating the optimization model with a simulation procedure reveals that aggressive prices for cycling yield about 55% fewer startups and 30% fewer failures compared to using a more typical start-up operating strategy, and can save hundreds of thousands to millions of dollars in repair costs over the lifetime of the plant.

Keywords: Optimized dispatch; Maintenance simulation; Monte Carlo; Concentrating solar power (CSP) (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s00291-022-00688-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:orspec:v:45:y:2023:i:1:d:10.1007_s00291-022-00688-7

Ordering information: This journal article can be ordered from
http://www.springer. ... research/journal/291

DOI: 10.1007/s00291-022-00688-7

Access Statistics for this article

OR Spectrum: Quantitative Approaches in Management is currently edited by Rainer Kolisch

More articles in OR Spectrum: Quantitative Approaches in Management from Springer, Gesellschaft für Operations Research e.V.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().