An MIP-Based Heuristic Decomposition Approach for Distributed Energy Resource Scheduling

Leopold Kuttner (), Martin Scheffler and Udo Buscher
Additional contact information
Leopold Kuttner: Technische Universität Dresden
Martin Scheffler: Technische Universität Dresden
Udo Buscher: Technische Universität Dresden

A chapter in Logistik in Wissenschaft und Praxis, 2021, pp 437-457 from Springer

Abstract: Zusammenfassung The decentralization of the power infrastructure poses new challenges for power plant operators and aggregators. A large number of power plants must be coordinated to successfully participate in energy markets. This requires to take uncertain exogenous influences, such as weather and market price, into account when determining operational schedules of energy resources and quantity-price tuples for bids to energy and reserve markets. Stochastic programming techniques are commonly applied to these decision problems. But, the resulting models are usually large-scale and hard to solve. We propose a temporal decomposition heuristic to speed-up the solution process of such models. The heuristic is based on mixed-integer programming formulations. Therefore, it is flexible with respect to the kinds of power plants and market environments that can be considered. We validate our findings on a realistic benchmark set of large stochastic programs and confirm its suitability to significantly reduce computational effort while retaining near-optimal solution quality.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-3-658-33480-2_18

Ordering information: This item can be ordered from
http://www.springer.com/9783658334802

DOI: 10.1007/978-3-658-33480-2_18

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().