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Optimization and Multicriteria Evaluation of District Heat Production and Storage

  • Risto Lahdelma
  • Genku Kayo
  • Elnaz Abdollahi
  • Pekka SalminenEmail author
Chapter
Part of the Multiple Criteria Decision Making book series (MCDM)

Abstract

Climate change mitigation policy requires reducing dependence on fossil fuels and transition to low carbon energy production in district heating (DH). We study here inclusion of two kinds of renewable energy to a CHP based DH system in Finland: solar heat and ground source heat. In addition, we apply heat storages to balance the gap between production and fluctuating demand. The optimal operation of the extended systems is determined by a simulation and optimization model to minimize the operating costs. We evaluate the different possible extensions in terms of multiple economic, technical and environmental criteria using Stochastic Multicriteria Acceptability Analysis (SMAA). The results show that under Finnish conditions, ground source heat is more favourable than solar heat for DH.

Keywords

Carbon-neutral District heating Heat-only production Multicriteria decision analysis SMAA 

Notes

Funding

This research has been funded, in part, by the Academy of Finland, project 298317.

References

  1. Alanne, K., Salo, A., Saari, A., & Gustafsson, S.-I. (2007). Multi-criteria evaluation of residential energy supply systems. Energy and Buildings, 39, 1218–1226.CrossRefGoogle Scholar
  2. Angilella, S., Corrente, S., & Greco, S. (2015). Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem. European Journal of Operational Research, 240(1), 172–182.CrossRefGoogle Scholar
  3. Boissavy, C. (2015). Cost and return on investment for geothermal heat pump systems in France. In Proceedings World Geothermal Congress 2015, Melbourne, Australia, 19–25 April 2015.Google Scholar
  4. Burer, M., Tanaka, K., Favrat, D., & Yamada, K. (2003). Multi-criteria optimization of a district cogeneration plant integrating a solid oxide fuel cell–gas turbine combined cycle, heat pumps and chillers. Energy, 28, 497–518.CrossRefGoogle Scholar
  5. Catalina, T., Virgone, J., & Blanco, E. (2011). Multi-source energy systems analysis using a multi-criteria decision aid methodology. Renewable Energy, 36, 2245–2252.CrossRefGoogle Scholar
  6. Chinese, D., Nardin, G., & Saro, O. (2011). Multi-criteria analysis for the selection of space heating systems in an industrial building. Energy, 36, 556–565.CrossRefGoogle Scholar
  7. Corrente, S., Figueira, J. R., & Greco, S. (2014). The SMAA-PROMETHEE method. European Journal of Operational Research, 239(2), 514–522.CrossRefGoogle Scholar
  8. Dombi, M., Kuti, I., & Balogh, P. (2014). Sustainability assessment of renewable power and heat generation technologies. Energy Policy, 67, 264–271.CrossRefGoogle Scholar
  9. Durbach, I., Lahdelma, R., & Salminen, P. (2014). The analytic hierarchy process with stochastic judgements. European Journal of Operational Research, 238(2), 552–559.CrossRefGoogle Scholar
  10. EU. (2010). Directive 2010/75/EU of the European parliament and of the council of 24 November 2010 on industrial emissions (integrated pollution prevention and control). http://data.europa.eu/eli/dir/2010/75/oj.
  11. Ghafghazi, S., Sowlati, T., Sokhansanj, S., & Melin, S. (2010a). A multicriteria approach to evaluate district heating system options. Applied Energy, 87(4), 1134–1140.CrossRefGoogle Scholar
  12. Ghafghazi, S., Sowlati, T., Sokhansanj, S., & Melin, S. (2010b). Techno-economic analysis of renewable energy source options for a district heating project. International Journal of Energy Research, 34(12), 1109–1120.CrossRefGoogle Scholar
  13. Hokkanen, J., Lahdelma, R., Miettinen, K., & Salminen, P. (1998). Determining the implementation order of a general plan by using a multicriteria method. Journal of Multi-Criteria Decision Analysis, 7(5), 273–284.CrossRefGoogle Scholar
  14. Hokkanen, J., Lahdelma, R., & Salminen, P. (1999). A multiple criteria decision model for analyzing and choosing among different development patterns for the Helsinki cargo harbor. Socio-Economic Planning Sciences, 33, 1–23.CrossRefGoogle Scholar
  15. Hokkanen, J., Lahdelma, R., & Salminen, P. (2000). Multicriteria decision support in a technology competition for cleaning polluted soil in Helsinki. Journal of Environmental Management, 60, 339–348.CrossRefGoogle Scholar
  16. IEA. (2012). IEA SHC Task 45, Fact Sheets (2012), http://task45.iea-shc.org/fact-sheets.
  17. IEA. (2017). Solar district heating: inspiration and experiences from Denmark. Danish District Heating Association/PlanEnergi, Publisher: IEA SHC TASK 55, http://task55.iea-shc.org/publications.
  18. Jovanovic, M., Afgan, N., & Bakic, V. (2010). An analytical method for the measurement of energy system sustainability in urban areas. Energy, 35, 3909–3920.CrossRefGoogle Scholar
  19. Jung, N., Moula, M. E., Fang, T., Hamdy, M., & Lahdelma, R. (2016). Social acceptance of renewable energy technologies for buildings in the Helsinki metropolitan area of Finland. Renewable Energy, 99, 813–824.CrossRefGoogle Scholar
  20. Kangas, A., Kangas, J., Lahdelma, R., & Salminen, P. (2006). Using SMAA-2 method with dependent uncertainties for strategic forest planning. Forest Policy and Economics, 9(2), 113–125.CrossRefGoogle Scholar
  21. Kangas, J., Hokkanen, J., Kangas, A., Lahdelma, R., & Salminen, P. (2003). Applying stochastic multicriteria acceptability analysis to forest ecosystem management with both cardinal and ordinal criteria. Forest Science, 49(6), 928–937.Google Scholar
  22. Kangas, J., Store, R., & Kangas, A. (2005). Socioecological landscape planning approach and multicriteria acceptability analysis in multiple-purpose forest management. Forest Policy and Economics, 7(4), 603–614.CrossRefGoogle Scholar
  23. Karabay, S., Kose, E., Kabak, M., & Ozceylan, E. (2016). Mathematical model and stochastic multi-criteria acceptability analysis for facility location problem. PROMET – Traffic & Transportation 28(3), 245–256.Google Scholar
  24. Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives: Preferences and value tradeoffs. New York: Wiley.Google Scholar
  25. Kirppu, H., Lahdelma, R., & Salminen, P. (2018). Multicriteria evaluation of carbon-neutral heat-only production technologies for district heating. Applied Thermal Engineering, 130, 466–476.CrossRefGoogle Scholar
  26. Kontu, K., Rinne, S., Olkkonen, V., Lahdelma, R., & Salminen, P. (2015). Multicriteria evaluation of heating choices for a new sustainable residential area. Energy and Buildings, 93, 169–179.CrossRefGoogle Scholar
  27. Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X. N., Kumar, P., et al. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596–609.CrossRefGoogle Scholar
  28. Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations Research, 49(3), 444–454.CrossRefGoogle Scholar
  29. Lahdelma, R., & Salminen, P. (2012). The shape of the utility or value function in stochastic multicriteria acceptability analysis. OR Spectrum, 34, 785–802.CrossRefGoogle Scholar
  30. Lahdelma, R., Hokkanen, J., & Salminen, P. (1998). SMAA—Stochastic multiobjective acceptability analysis. European Journal of Operational Research, 106(1), 137–143.CrossRefGoogle Scholar
  31. Lahdelma, R., Makkonen, S., & Salminen, P. (2006). Multivariate Gaussian criteria in SMAA. European Journal of Operational Research, 170(3), 957–970.CrossRefGoogle Scholar
  32. Lahdelma, R., Makkonen, S., & Salminen, P. (2009). Two ways to handle dependent uncertainties in multi-criteria decision problems. Omega, 37(1), 79–92.CrossRefGoogle Scholar
  33. Lahdelma, R., Miettinen, K., & Salminen, P. (2003). Ordinal criteria in stochastic multicriteria acceptability analysis (SMAA). European Journal of Operational Research, 147(1), 117–127.CrossRefGoogle Scholar
  34. Lahdelma, R., & Salminen, P. (2008a). Multicriteria decision analysis for choosing the remediation method for a landfill based on mixed ordinal and cardinal information. In I. Linkov, E. Ferguson, V. S. Magar (Eds.), Real-time and deliberative decision making: Application to emerging stressors (pp. 379–396). NATO Science for Peace and Security Series—C: Environmental Security. Springer: Dordreht.Google Scholar
  35. Lahdelma, R., & Salminen, P. (2008b). Ordinal measurements with interval constraints in the EIA process for siting a waste storage area. In I. Linkov, E. Ferguson, V. S. Magar (Eds.), Real-time and deliberative decision making: Application to emerging stressors (pp. 397–414). NATO Science for Peace and Security Series—C: Environmental Security. Springer: Dordreht.Google Scholar
  36. Lahdelma, R., & Salminen, P. (2010). Stochastic multicriteria acceptability analysis (SMAA). In M. Ehrgott, J. R. Figueira, S. Greco (Eds.), Trends in multiple criteria decision analysis (Vol. 142, pp. 285–316). International Series in Operations Research and Management Science. Springer.Google Scholar
  37. Lahdelma, R., & Salminen, P. (2016). SMAA in robustness analysis. In M. Doumpos, C. Zopunidis, E. Grigoroudis (Eds.), Robustness analysis in decision aiding, optimization, and analytics (Vol. 241, pp. 1–20). International Series in Operations Research & Management Scienc. Springer.Google Scholar
  38. Lahdelma, R., Salminen, P., & Hokkanen, J. (2002). Locating a waste treatment facility by using stochastic multicriteria acceptability analysis with ordinal criteria. European Journal of Operational Research, 142, 345–356.CrossRefGoogle Scholar
  39. Lahdelma, R., Salminen, P., Simonen, A., & Hokkanen, J. (2001). Choosing a reparation method for a landfill using the SMAA-O multicriteria method. In Köksalan, Zionts (Eds.), Multiple criteria decision making in the new millenium (Vol. 507, pp. 380–389). Lecture Notes in Economics and Mathematical Systems.Google Scholar
  40. Leskinen, P., Viitanen, J., Kangas, A., & Kangas, J. (2006). Alternatives to incorporate uncertainty and risk attitude in multicriteria evaluation of forest plans. Forest Science, 52(3), 304–312.Google Scholar
  41. Loikkanen, O., Lahdelma, R., & Salminen, P. (2017). Multicriteria evaluation of sustainable energy solutions for Colosseum. Sustainable Cities and Society, 35, 289–297.CrossRefGoogle Scholar
  42. Lund, H., Möller, B., Mathiesen, B. V., & Dyrelund, A. (2010). The role of district heating in future renewable energy systems. Energy, 35(3), 1381–1390.CrossRefGoogle Scholar
  43. Lund, H., Werner, S., Wiltshire, R., Svendsen, S., Thorsen, J. E., Hvelplund, F., et al. (2014). 4th generation district heating (4GDH): Integrating smart thermal grids into future sustainable energy systems. Energy, 68, 1–11.CrossRefGoogle Scholar
  44. Mardani, A., Zavadskas, E. K., Khalifah, Z., Zakuan, N., Jusoh, A., Nor, K. M., et al. (2017). A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015. Renewable and Sustainable Energy Reviews, 71, 216–256.CrossRefGoogle Scholar
  45. Menou, A., Benallou, A., Lahdelma, R., & Salminen, P. (2010). Decision support for centralizing cargo at a Moroccan airport hub using stochastic multicriteria acceptability analysis. European Journal of Operational Research, 204, 621–629.CrossRefGoogle Scholar
  46. Mroz, T. M. (2008). Planning of community heating systems modernization and development. Applied Thermal Engineering, 28(14–15), 1844–1852.CrossRefGoogle Scholar
  47. Okul, D., Gencer, C., & Aydogan, E. (2014). A method based on SMAA-topsis for stochastic multi-criteria decision making and a real-world application. International Journal of Information Technology & Decision Making, 13(5), 957–978.CrossRefGoogle Scholar
  48. Pesola, A., Serkkola, A., Lahdelma, R., & Salminen, P. (2014). Multicriteria evaluation of alternatives for remote monitoring systems of municipal buildings. Energy and Buildings, 72, 229–237.CrossRefGoogle Scholar
  49. Pohekar, S. D., & Ramachandran, M. (2004). Application of multi-criteria decision making to sustainable energy planning—A review. Renewable and Sustainable Energy Reviews, 8, 365–381.CrossRefGoogle Scholar
  50. Rahman, M. M., Paatero, J., & Lahdelma, R. (2013). Evaluation of choices for sustainable rural electrification in developing countries: A multicriteria approach. Energy Policy, 59, 589–599.CrossRefGoogle Scholar
  51. Rahman, M. M., Paatero, J. V., Lahdelma, R., & Wahid, M. A. (2016). Multicriteria-based decision aiding technique for assessing energy policy elements-demonstration to a case in Bangladesh. Applied Energy, 164, 237–244.CrossRefGoogle Scholar
  52. Rocchi, L. (2012). Using stochastic multi-criteria acceptability analysis methods in SEA: An application to the Park of Trasimeno (Italy). Journal of Environmental Planning and Management, 55(2), 177–189.CrossRefGoogle Scholar
  53. Scheffler, A., Roth, T., & Ahlf, W. (2014). Sustainable decision making under uncertainty: A case study in dredged material management. Environmental Sciences Europe, 26, 7.CrossRefGoogle Scholar
  54. Si, J., Marjanovic-Halburd, L., Nasiri, F., & Bell, S. (2016). Assessment of building-integrated green technologies: A review and case study on applications of multi-criteria decision making (MCDM) method. Sustainable Cities and Society, 27, 106–115.CrossRefGoogle Scholar
  55. Tervonen, T., & Figueira, J. (2008). A survey on stochastic multicriteria acceptability analysis methods. Journal of Multi-Criteria Decision Analysis, 15(1–2), 1–14.CrossRefGoogle Scholar
  56. Tervonen, T., & Lahdelma, R. (2007). Implementing stochastic multicriteria acceptability analysis. European Journal of Operational Research, 178(2), 500–513.CrossRefGoogle Scholar
  57. Tervonen, T., Linkov, I., Figueira, J. R., Steevens, J., Chappel, M., & Merad, M. (2009). Risk-based classification system of nanomaterials. Journal of Nanoparticle Research, 11(4), 757–766.CrossRefGoogle Scholar
  58. Tervonen, T., van Valkenhoef, G., Buskens, E., Hillege, H. L., & Postmus, D. (2011). A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis. Statistics in Medicine, 30(12), 1419–1428.CrossRefGoogle Scholar
  59. Tsoutsos, T., Drandaki, M., Frantzeskaki, N., Iosifidis, E., & Kiosses, I. (2009). Sustainable energy planning by using multi-criteria analysis application in the island of Crete. Energy Policy, 37, 1587–1600.CrossRefGoogle Scholar
  60. van Valkenhoef, G., Tervonen, T., Zhao, J., de Brock, B., Hillege, H. L., & Postmus, D. (2012). Multicriteria benefit–risk assessment using network meta-analysis. Journal of Clinical Epidemiology, 65(4), 394–403.CrossRefGoogle Scholar
  61. Wang, E. (2015). Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach. Applied Energy, 146, 92–103.CrossRefGoogle Scholar
  62. Wang, H., Jiao, W., Lahdelma, R., Zhu, C., & Zou, P.-H. (2015a). Stochastic multicriteria acceptability analysis for evaluation of combined heat and power units. Energies, 8, 59–78.CrossRefGoogle Scholar
  63. Wang, H., Lahdelma, R., Wang, X., Jiao, W., Zhu, C., & Zou, P. (2015b). Analysis of the location for peak heating in CHP based combined district heating systems. Applied Thermal Engineering, 87, 402–411.CrossRefGoogle Scholar
  64. Wang, J., Jing, Y., Zhang, C., & Zhao, J. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews, 13(9), 2263–2278.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Risto Lahdelma
    • 1
    • 2
  • Genku Kayo
    • 1
    • 3
  • Elnaz Abdollahi
    • 1
  • Pekka Salminen
    • 4
    Email author
  1. 1.Department of Mechanical EngineeringAalto University School of EngineeringAaltoFinland
  2. 2.Department of Mathematics and Systems AnalysisAalto University School of ScienceAaltoFinland
  3. 3.School of Architecture and the Built EnvironmentKTH Royal Institute of TechnologyStockholmSweden
  4. 4.School of Business and EconomicsUniversity of JyväskyläJyväskyläFinland

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