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An optimization methodology for identifying robust process integration investments under uncertainty

Artikel i vetenskaplig tidskrift
Författare Elin Svensson
Thore Berntsson
Ann-Brith Strömberg
Michael Patriksson
Publicerad i Energy Policy
Volym 37
Nummer/häfte 2
Sidor 680-685
ISSN 0301-4215
Publiceringsår 2009
Publicerad vid Institutionen för matematiska vetenskaper, matematik
Sidor 680-685
Språk en
Länkar dx.doi.org/10.1016/j.enpol.2008.10....
Ämnesord stochastic programming, process integration, investment planning
Ämneskategorier Optimeringslära, systemteori, Kemisk energiteknik, Övrig industriell teknik och ekonomi

Sammanfattning

Uncertainties in future energy prices and policies strongly affect decisions on investments in process integration measures in industry. In this paper, we present a five-step methodology for the identification of robust investment alternatives incorporating explicitly such uncertainties in the optimization model. Methods for optimization under uncertainty (or, stochastic programming) are thus combined with a deep understanding of process integration and process technology in order to achieve a framework for decision-making concerning the investment planning of process integration measures under uncertainty. The proposed methodology enables the optimization of investments in energy efficiency with respect to their net present value or an environmental objective. In particular, as a result of the optimization approach, complex investment alternatives, allowing for combinations of energy efficiency measures, can be analyzed. Uncertainties as well as time-dependent parameters, such as energy prices and policies, are modelled using a scenario-based approach, enabling the identification of robust investment solutions. The methodology is primarily an aid for decision-makers in industry, but it will also provide insight for policy-makers into how uncertainties regarding future price levels and policy instruments affect the decisions on investments in energy efficiency measures.

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