Capacity determination of ultra-long flexibility investments for district heating systems
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Energy companies with district heating systems usually operate at least one combined heat and power (CHP) plant that generates power and heat simultaneously. Trading power on the spot market, energy companies strive to realize additional revenues or cost savings. However, the needed flexible operation of the CHP plant is limited as a steady supply of district heat has to be ensured. Decoupling heat demand and supply provides further flexibility for the operation of the CHP plant and trading at the spot market. Thus, energy companies consider ultra-long flexibility investments such as heat storage to improve the profitability of their district heating system. Capacity determination of such a flexibility investment constitutes a challenge because the investment has to be integrated into an existing district heating system. Due to its uncertain long-term development, the lifetime of the investment exceeds the planning horizon. Therefore, the benefit of the investment in its remaining lifetime has to be taken into account for the investment decision. For the capacity determination of such an ultra-long flexibility investment, a step-wise structured decision process is developed: an optimization model for unit commitment within the planning horizon is expanded for capacity determination to analyze the operational deployment of the investment in combination with the existing district heating system. Regarding uncertainty, the amortization time is not restricted to the planning horizon but adapted according to the decision maker’s risk attitude in order to consider the investment’s ultra-long benefit. For the remaining lifetime, the seized investment capacities are evaluated by considering their possible future operation and adaptability. The advantage of this approach is demonstrated for a heat storage investment.
KeywordsUltra-long investments Capacity sizing Operational and strategic planning Combined heat and power (CHP) plant
JEL classificationC61 M11 Q41
The authors would like to thank two anonymous referees for their valuable comments on an earlier version of this paper.
- BET Büro für Energiewirtschaft und technische Planung GmbH (29.05.2013) Abschlussbericht Perspektiven der Fernwärme im Ruhrgebiet bis 2050 (vorläufige Endversion). URL http://www.umwelt.nrw.de/ministerium/pdf/endbericht_fernwaerme_ruhrgebiet.pdf
- BMU Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit (Juli 2012) Erneuerbare Energien in Zahlen: Nationale und internationale Entwicklung. URL https://secure.bmu.de/fileadmin/bmu-import/files/pdfs/allgemein/application/pdf/broschuere_ee_zahlen_bf.pdf
- Breuer W, Dyckhoff H, Hüwe A, Letmathe P, Lorz O, Madlener R, Thomes P, Walther G (2013) Ultralanglebige Investitionen: Definition und ProblembeschreibungGoogle Scholar
- Fico (2009) Xpress-optimizer reference manual. Fico Xpress optimization suite (http://www.fico.com), Release 20.00, 3 June 2009
- Palisade (2012) Guide to Using @RISK. Palisade @Risk. Risk Analysis and Simulation Add-In for Microsoft® Excel (http://www.palisade.com), Version 6, July 2012
- Schacht M, Schulz K (2013) Kraft-Wärme-Kopplung in kommunalen Energieversorgungsunternehmen: Volatile Einspeisung erneuerbarer Energien als Herausforderung. In: Armborst K, Degel D, Lutter P, Pietschmann U, Rachuba S, Schulz K, Wiesche L (eds) Management Science: Festschrift zum 60. Geburtstag von Brigitte Werners, Dr. Kovac. Hamburg, pp 337–363Google Scholar
- Schulz K, Schacht M, Werners B (2014) Influence of fluctuating electricity prices due to renewable energies on heat storage investments. In: Huisman D, Louwerse I, Wagelmans AP (eds) Operations research proceedings 2013: Selected Papers of the International Annual Conference of the German Operations Research Society (GOR) and the Dutch Society of Operations Research, Erasmus University Rotterdam, Springer, Operations Research Proceedings, The NetherlandsGoogle Scholar
- Ströbele W, Pfaffenberger W, Heuterkes M (2012) Energiewirtschaft: Einführung in Theorie und Politik, 3rd edn. München u.aGoogle Scholar
- Weber C (2005) Uncertainty in the electric power industry: methods and models for decision support. Springer, New YorkGoogle Scholar