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Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter

Author

Listed:
  • Hannes Schwarz

    (Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP), Chair of Energy Economics)

  • Valentin Bertsch

    (Economic and Social Research Institute (ESRI)
    Trinity College Dublin)

  • Wolf Fichtner

    (Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP), Chair of Energy Economics)

Abstract

The expansion of fluctuating renewable energy sources leads to an increasing impact of weather-related uncertainties on future decentralized energy systems. Stochastic modeling techniques enable an adequate consideration of the uncertainties and provide support for both investment and operating decisions in such systems. In this paper, we consider a residential quarter using photovoltaic systems in combination with multistage air-water heat pumps and heat storage units for space heating and domestic hot water. We model the investment and operating problem of the quarter’s energy system as two-stage stochastic mixed-integer linear program and optimize the thermal storage units. In order to keep the resulting stochastic, large-scale program computationally feasible, the problem is decomposed in combination with a derivative-free optimization. The subproblems are solved in parallel on high-performance computing systems. Our approach is integrated in that it comprises three subsystems: generation of consistent ensembles of the required input data by a Markov process, transformation into sets of energy demand and supply profiles and the actual stochastic optimization. An analysis of the scalability and comparison with a state-of-the-art dual-decomposition method using Lagrange relaxation and a conic bundle algorithm shows a good performance of our approach for the considered problem type. A comparison of the effective gain of modeling the quarter as stochastic program with the resulting computational expenses justifies the approach. Moreover, our results show that heat storage units in such systems are generally larger when uncertainties are considered, i.e., stochastic optimization can help to avoid insufficient setup decisions. Furthermore, we find that the storage is more profitable for domestic hot water than for space heating.

Suggested Citation

  • Hannes Schwarz & Valentin Bertsch & Wolf Fichtner, 2018. "Two-stage stochastic, large-scale optimization of a decentralized energy system: a case study focusing on solar PV, heat pumps and storage in a residential quarter," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(1), pages 265-310, January.
    • Handle: RePEc:spr:orspec:v:40:y:2018:i:1:d:10.1007_s00291-017-0500-4
    DOI: 10.1007/s00291-017-0500-4
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    1. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2017. "Optimal operation, configuration and sizing of generation and storage technologies for residential heat pump systems in the spotlight of self-consumption of photovoltaic electricity," Applied Energy, Elsevier, vol. 188(C), pages 604-619.
    2. Evins, Ralph & Orehounig, Kristina & Dorer, Viktor & Carmeliet, Jan, 2014. "New formulations of the ‘energy hub’ model to address operational constraints," Energy, Elsevier, vol. 73(C), pages 387-398.
    3. R. T. Rockafellar & Roger J.-B. Wets, 1991. "Scenarios and Policy Aggregation in Optimization Under Uncertainty," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 119-147, February.
    4. Alonso-Ayuso, A. & Escudero, L. F. & Garín, A. & Ortuño, M. T. & Pérez, G., 2005. "On the product selection and plant dimensioning problem under uncertainty," Omega, Elsevier, vol. 33(4), pages 307-318, August.
    5. Schicktanz, M.D. & Wapler, J. & Henning, H.-M., 2011. "Primary energy and economic analysis of combined heating, cooling and power systems," Energy, Elsevier, vol. 36(1), pages 575-585.
    6. Yazdanie, Mashael & Densing, Martin & Wokaun, Alexander, 2016. "The role of decentralized generation and storage technologies in future energy systems planning for a rural agglomeration in Switzerland," Energy Policy, Elsevier, vol. 96(C), pages 432-445.
    7. Valentin Bertsch & Hannes Schwarz & Wolf Fichtner, 2014. "Layout Optimisation of Decentralised Energy Systems Under Uncertainty," Operations Research Proceedings, in: Dennis Huisman & Ilse Louwerse & Albert P.M. Wagelmans (ed.), Operations Research Proceedings 2013, edition 127, pages 29-35, Springer.
    8. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    9. Willem Klein Haneveld & Maarten van der Vlerk, 1999. "Stochastic integer programming:General models and algorithms," Annals of Operations Research, Springer, vol. 85(0), pages 39-57, January.
    10. Shang, Ce & Srinivasan, Dipti & Reindl, Thomas, 2017. "Generation and storage scheduling of combined heat and power," Energy, Elsevier, vol. 124(C), pages 693-705.
    11. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    12. Kovacevic, Raimund M. & Paraschiv, Florentina, 2012. "Medium-term Planning for Thermal Electricity Production," Working Papers on Finance 1220, University of St. Gallen, School of Finance.
    13. Raimund Kovacevic & Alois Pichler, 2015. "Tree approximation for discrete time stochastic processes: a process distance approach," Annals of Operations Research, Springer, vol. 235(1), pages 395-421, December.
    14. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    15. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    16. Lorenzi, Guido & Silva, Carlos Augusto Santos, 2016. "Comparing demand response and battery storage to optimize self-consumption in PV systems," Applied Energy, Elsevier, vol. 180(C), pages 524-535.
    17. Georg Ch Pflug & Werner Römisch, 2007. "Modeling, Measuring and Managing Risk," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6478, December.
    18. Hawkes, Adam & Leach, Matthew, 2005. "Impacts of temporal precision in optimisation modelling of micro-Combined Heat and Power," Energy, Elsevier, vol. 30(10), pages 1759-1779.
    19. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    20. Hayn, Marian & Bertsch, Valentin & Zander, Anne & Nickel, Stefan & Fichtner, Wolf, 2016. "The impact of electricity tariffs on residential demand side flexibility," Working Paper Series in Production and Energy 14, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
    21. Jochem, Patrick & Schönfelder, Martin & Fichtner, Wolf, 2015. "An efficient two-stage algorithm for decentralized scheduling of micro-CHP units," European Journal of Operational Research, Elsevier, vol. 245(3), pages 862-874.
    22. Shirazi, Elham & Jadid, Shahram, 2017. "Cost reduction and peak shaving through domestic load shifting and DERs," Energy, Elsevier, vol. 124(C), pages 146-159.
    23. Yang Yuan & Suvrajeet Sen, 2009. "Enhanced Cut Generation Methods for Decomposition-Based Branch and Cut for Two-Stage Stochastic Mixed-Integer Programs," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 480-487, August.
    24. Johann Hurink & Rüdiger Schultz & David Wozabal, 2016. "Quantitative solutions for future energy systems and markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(3), pages 541-543, July.
    25. Mustajoki, Jyri & Hamalainen, Raimo P. & Lindstedt, Mats R.K., 2006. "Using intervals for global sensitivity and worst-case analyses in multiattribute value trees," European Journal of Operational Research, Elsevier, vol. 174(1), pages 278-292, October.
    26. Kaschub, Thomas & Jochem, Patrick & Fichtner, Wolf, 2016. "Solar energy storage in German households: profitability, load changes and flexibility," Energy Policy, Elsevier, vol. 98(C), pages 520-532.
    27. Andrzej Ruszczynski, 1999. "Some advances in decomposition methodsfor stochastic linear programming," Annals of Operations Research, Springer, vol. 85(0), pages 153-172, January.
    28. Escudero, L.F. & Garín, M.A. & Merino, M. & Pérez, G., 2010. "An exact algorithm for solving large-scale two-stage stochastic mixed-integer problems: Some theoretical and experimental aspects," European Journal of Operational Research, Elsevier, vol. 204(1), pages 105-116, July.
    29. Diagne, Maimouna & David, Mathieu & Lauret, Philippe & Boland, John & Schmutz, Nicolas, 2013. "Review of solar irradiance forecasting methods and a proposition for small-scale insular grids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 65-76.
    30. L. Escudero & A. Garín & M. Merino & G. Pérez, 2007. "A two-stage stochastic integer programming approach as a mixture of Branch-and-Fix Coordination and Benders Decomposition schemes," Annals of Operations Research, Springer, vol. 152(1), pages 395-420, July.
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    Cited by:

    1. Iegor Riepin & Thomas Mobius & Felix Musgens, 2020. "Modelling uncertainty in coupled electricity and gas systems -- is it worth the effort?," Papers 2008.07221, arXiv.org, revised Sep 2020.
    2. Lynch, Muireann Á & Devine, Mel & Bertsch, Valentin, 2018. "The role of power-to-gas in the future energy system: how much is needed and who wants to invest?," Papers WP590, Economic and Social Research Institute (ESRI).
    3. Bertsch, Valentin & Devine, Mel & Sweeney, Conor & Parnell, Andrew C., 2018. "Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model," Papers WP585, Economic and Social Research Institute (ESRI).
    4. Mel T. Devine & Valentin Bertsch, 2023. "The role of demand response in mitigating market power: a quantitative analysis using a stochastic market equilibrium model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 45(2), pages 555-597, June.
    5. Bertsch, Valentin & Devine, Mel, 2019. "The Role of Demand Response in Mitigating Market Power — A Quantitative Analysis Using a Stochastic Market Equilibrium Model," Papers WP635, Economic and Social Research Institute (ESRI).
    6. Olivella, Jordi & Domenech, Bruno & Calleja, Gema, 2021. "Potential of implementation of residential photovoltaics at city level: The case of London," Renewable Energy, Elsevier, vol. 180(C), pages 577-585.
    7. Russo, Marianna & Bertsch, Valentin, 2020. "A looming revolution: Implications of self-generation for the risk exposure of retailers," Energy Economics, Elsevier, vol. 92(C).
    8. Lynch, Muireann & Devine, Mel T. & Bertsch, Valentin, 2019. "The role of power-to-gas in the future energy system: Market and portfolio effects," Energy, Elsevier, vol. 185(C), pages 1197-1209.
    9. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    10. Oliver Gregor Gorbach & Jessica Thomsen, 2022. "Comparing the Energy System of a Facility with Uncertainty about Future Internal Carbon Prices and Energy Carrier Costs Using Deterministic Optimisation and Two-Stage Stochastic Programming," Energies, MDPI, vol. 15(10), pages 1-39, May.
    11. Henrik C. Bylling & Salvador Pineda & Trine K. Boomsma, 2020. "The impact of short-term variability and uncertainty on long-term power planning," Annals of Operations Research, Springer, vol. 284(1), pages 199-223, January.

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