Economics at your fingertips  

On the solution variability reduction of Stochastic Dual Dynamic Programming applied to energy planning

Murilo Pereira Soares, Alexandre Street and Davi Michel Valladão

European Journal of Operational Research, 2017, vol. 258, issue 2, 743-760

Abstract: In the hydrothermal energy operation planning of Brazil and other hydro-dependent countries, Stochastic Dual Dynamic Programming (SDDP) computes a risk-averse optimal policy that often considers river-inflow autoregressive models. In practical applications, these models induce an undesirable variability of primal (thermal generation) and dual (marginal cost and spot price) solutions that are highly sensitive to changes in current inflow conditions. This work proposes two differing approaches to stabilize SDDP solutions to the energy operation planning problem: the first approach regularizes primal variables by considering an additional penalty on thermal dispatch revisions over time, and the second approach indirectly reduces thermal generation and marginal cost variability by disregarding past inflow information in the cost-to-go function and compensates with an increase in risk aversion. For comparison purposes, we assess solution quality with a set of proposed indexes summarizing each important aspect of a hydrothermal operation planning policy. In conclusion, we show that it is possible to obtain high-quality solutions in comparison to current benchmarks with significantly reduced variability.

Keywords: Stochastic programming; Stochastic Dual Dynamic Programming; Risk aversion; OR in energy (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
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:

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Series data maintained by Dana Niculescu ().

Page updated 2017-12-30
Handle: RePEc:eee:ejores:v:258:y:2017:i:2:p:743-760