IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v92y2015ip3p420-434.html
   My bibliography  Save this article

Greenhouse gases emission assessment in residential sector through buildings simulations and operation optimization

Author

Listed:
  • Stojiljković, Mirko M.
  • Ignjatović, Marko G.
  • Vučković, Goran D.

Abstract

Buildings use a significant amount of primary energy and largely contribute to greenhouse gases emission. Cost optimality and cost effectiveness, including cost-optimal operation, are important for the adoption of energy efficient and environmentally friendly technologies. The long-term assessment of buildings-related greenhouse gases emission might take into account cost-optimal operation of their energy systems. This is often not the case in the literature. Long-term operation optimization problems are often of large scale and computationally intensive and time consuming.

Suggested Citation

  • Stojiljković, Mirko M. & Ignjatović, Marko G. & Vučković, Goran D., 2015. "Greenhouse gases emission assessment in residential sector through buildings simulations and operation optimization," Energy, Elsevier, vol. 92(P3), pages 420-434.
  • Handle: RePEc:eee:energy:v:92:y:2015:i:p3:p:420-434
    DOI: 10.1016/j.energy.2015.05.021
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215005988
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2015.05.021?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Menon, Ramanunni P. & Paolone, Mario & Maréchal, François, 2013. "Study of optimal design of polygeneration systems in optimal control strategies," Energy, Elsevier, vol. 55(C), pages 134-141.
    2. Åberg, M. & Henning, D., 2011. "Optimisation of a Swedish district heating system with reduced heat demand due to energy efficiency measures in residential buildings," Energy Policy, Elsevier, vol. 39(12), pages 7839-7852.
    3. Chau, C.K. & Leung, T.M. & Ng, W.Y., 2015. "A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings," Applied Energy, Elsevier, vol. 143(C), pages 395-413.
    4. Rieder, Andreas & Christidis, Andreas & Tsatsaronis, George, 2014. "Multi criteria dynamic design optimization of a small scale distributed energy system," Energy, Elsevier, vol. 74(C), pages 230-239.
    5. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2014. "A mathematical model for the optimal operation of the University of Genoa Smart Polygeneration Microgrid: Evaluation of technical, economic and environmental performance indicators," Energy, Elsevier, vol. 64(C), pages 912-922.
    6. Åberg, M. & Widén, J. & Henning, D., 2012. "Sensitivity of district heating system operation to heat demand reductions and electricity price variations: A Swedish example," Energy, Elsevier, vol. 41(1), pages 525-540.
    7. Lozano, M.A. & Carvalho, M. & Serra, L.M., 2009. "Operational strategy and marginal costs in simple trigeneration systems," Energy, Elsevier, vol. 34(11), pages 2001-2008.
    8. Truong, Nguyen Le & Dodoo, Ambrose & Gustavsson, Leif, 2014. "Effects of heat and electricity saving measures in district-heated multistory residential buildings," Applied Energy, Elsevier, vol. 118(C), pages 57-67.
    9. Wakui, Tetsuya & Kinoshita, Takahiro & Yokoyama, Ryohei, 2014. "A mixed-integer linear programming approach for cogeneration-based residential energy supply networks with power and heat interchanges," Energy, Elsevier, vol. 68(C), pages 29-46.
    10. Costa, Andrea & Keane, Marcus M. & Torrens, J. Ignacio & Corry, Edward, 2013. "Building operation and energy performance: Monitoring, analysis and optimisation toolkit," Applied Energy, Elsevier, vol. 101(C), pages 310-316.
    11. Howard, Bianca & Saba, Alexis & Gerrard, Michael & Modi, Vijay, 2014. "Combined heat and power's potential to meet New York City's sustainability goals," Energy Policy, Elsevier, vol. 65(C), pages 444-454.
    12. Oh, Si-Doek & Lee, Ho-Jun & Jung, Jung-Yeul & Kwak, Ho-Young, 2007. "Optimal planning and economic evaluation of cogeneration system," Energy, Elsevier, vol. 32(5), pages 760-771.
    13. Lozano, Miguel A. & Ramos, Jose C. & Serra, Luis M., 2010. "Cost optimization of the design of CHCP (combined heat, cooling and power) systems under legal constraints," Energy, Elsevier, vol. 35(2), pages 794-805.
    14. Fred Glover, 1975. "Improved Linear Integer Programming Formulations of Nonlinear Integer Problems," Management Science, INFORMS, vol. 22(4), pages 455-460, December.
    15. Ommen, Torben & Markussen, Wiebke Brix & Elmegaard, Brian, 2014. "Comparison of linear, mixed integer and non-linear programming methods in energy system dispatch modelling," Energy, Elsevier, vol. 74(C), pages 109-118.
    16. Verda, Vittorio & Colella, Francesco, 2011. "Primary energy savings through thermal storage in district heating networks," Energy, Elsevier, vol. 36(7), pages 4278-4286.
    17. Pruitt, Kristopher A. & Braun, Robert J. & Newman, Alexandra M., 2013. "Evaluating shortfalls in mixed-integer programming approaches for the optimal design and dispatch of distributed generation systems," Applied Energy, Elsevier, vol. 102(C), pages 386-398.
    18. Sakawa, Masatoshi & Kato, Kosuke & Ushiro, Satoshi, 2002. "Operational planning of district heating and cooling plants through genetic algorithms for mixed 0-1 linear programming," European Journal of Operational Research, Elsevier, vol. 137(3), pages 677-687, March.
    19. Buoro, D. & Casisi, M. & De Nardi, A. & Pinamonti, P. & Reini, M., 2013. "Multicriteria optimization of a distributed energy supply system for an industrial area," Energy, Elsevier, vol. 58(C), pages 128-137.
    20. Aste, Niccolò & Adhikari, R.S. & Manfren, Massimiliano, 2013. "Cost optimal analysis of heat pump technology adoption in residential reference buildings," Renewable Energy, Elsevier, vol. 60(C), pages 615-624.
    21. Bracco, Stefano & Dentici, Gabriele & Siri, Silvia, 2013. "Economic and environmental optimization model for the design and the operation of a combined heat and power distributed generation system in an urban area," Energy, Elsevier, vol. 55(C), pages 1014-1024.
    22. Mirko M. Stojiljković & Mladen M. Stojiljković & Bratislav D. Blagojević, 2014. "Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics," Energies, MDPI, vol. 7(12), pages 1-28, December.
    23. Rezvan, A. Taghipour & Gharneh, N. Shams & Gharehpetian, G.B., 2012. "Robust optimization of distributed generation investment in buildings," Energy, Elsevier, vol. 48(1), pages 455-463.
    24. Chesi, Andrea & Ferrara, Giovanni & Ferrari, Lorenzo & Magnani, Sandro & Tarani, Fabio, 2013. "Influence of the heat storage size on the plant performance in a Smart User case study," Applied Energy, Elsevier, vol. 112(C), pages 1454-1465.
    25. Nässén, Jonas & Holmberg, John, 2013. "On the potential trade-offs between energy supply and end-use technologies for residential heating," Energy Policy, Elsevier, vol. 59(C), pages 470-480.
    26. Rinne, S. & Syri, S., 2013. "Heat pumps versus combined heat and power production as CO2 reduction measures in Finland," Energy, Elsevier, vol. 57(C), pages 308-318.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yang, Tao & Pan, Yiqun & Yang, Yikun & Lin, Meishun & Qin, Bingyue & Xu, Peng & Huang, Zhizhong, 2017. "CO2 emissions in China's building sector through 2050: A scenario analysis based on a bottom-up model," Energy, Elsevier, vol. 128(C), pages 208-223.
    2. Stojiljković, Mirko M., 2017. "Bi-level multi-objective fuzzy design optimization of energy supply systems aided by problem-specific heuristics," Energy, Elsevier, vol. 137(C), pages 1231-1251.
    3. saheb Koussa, Djohra & Koussa, Mustapha, 2016. "GHGs (greenhouse gases) emission and economic analysis of a GCRES (grid-connected renewable energy system) in the arid region, Algeria," Energy, Elsevier, vol. 102(C), pages 216-230.
    4. Stinner, Sebastian & Schlösser, Tim & Huchtemann, Kristian & Müller, Dirk & Monti, Antonello, 2017. "Primary energy evaluation of heat pumps considering dynamic boundary conditions in the energy system," Energy, Elsevier, vol. 138(C), pages 60-78.
    5. Brandão de Vasconcelos, Ana & Cabaço, António & Pinheiro, Manuel Duarte & Manso, Armando, 2016. "The impact of building orientation and discount rates on a Portuguese reference building refurbishment decision," Energy Policy, Elsevier, vol. 91(C), pages 329-340.
    6. Shi, Xing & Tian, Zhichao & Chen, Wenqiang & Si, Binghui & Jin, Xing, 2016. "A review on building energy efficient design optimization rom the perspective of architects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 872-884.
    7. Seung Hyo Baek & Byung Hee Lee, 2019. "Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage," Sustainability, MDPI, vol. 11(5), pages 1-19, March.
    8. Guzović, Zvonimir & Duic, Neven & Piacentino, Antonio & Markovska, Natasa & Mathiesen, Brian Vad & Lund, Henrik, 2022. "Recent advances in methods, policies and technologies at sustainable energy systems development," Energy, Elsevier, vol. 245(C).
    9. Seungjun Roh & Sungho Tae, 2016. "Building Simplified Life Cycle CO 2 Emissions Assessment Tool (B‐SCAT) to Support Low‐Carbon Building Design in South Korea," Sustainability, MDPI, vol. 8(6), pages 1-22, June.
    10. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mirko M. Stojiljković & Mladen M. Stojiljković & Bratislav D. Blagojević, 2014. "Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics," Energies, MDPI, vol. 7(12), pages 1-28, December.
    2. Stojiljković, Mirko M., 2017. "Bi-level multi-objective fuzzy design optimization of energy supply systems aided by problem-specific heuristics," Energy, Elsevier, vol. 137(C), pages 1231-1251.
    3. Maroufmashat, Azadeh & Elkamel, Ali & Fowler, Michael & Sattari, Sourena & Roshandel, Ramin & Hajimiragha, Amir & Walker, Sean & Entchev, Evgueniy, 2015. "Modeling and optimization of a network of energy hubs to improve economic and emission considerations," Energy, Elsevier, vol. 93(P2), pages 2546-2558.
    4. Yang, Yun & Zhang, Shijie & Xiao, Yunhan, 2015. "An MILP (mixed integer linear programming) model for optimal design of district-scale distributed energy resource systems," Energy, Elsevier, vol. 90(P2), pages 1901-1915.
    5. Stefan Blomqvist & Lina La Fleur & Shahnaz Amiri & Patrik Rohdin & Louise Ödlund (former Trygg), 2019. "The Impact on System Performance When Renovating a Multifamily Building Stock in a District Heated Region," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    6. Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
    7. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    8. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    9. Buoro, Dario & Pinamonti, Piero & Reini, Mauro, 2014. "Optimization of a Distributed Cogeneration System with solar district heating," Applied Energy, Elsevier, vol. 124(C), pages 298-308.
    10. Elsido, Cristina & Bischi, Aldo & Silva, Paolo & Martelli, Emanuele, 2017. "Two-stage MINLP algorithm for the optimal synthesis and design of networks of CHP units," Energy, Elsevier, vol. 121(C), pages 403-426.
    11. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2018. "Thermoeconomic cost allocation in simple trigeneration systems including thermal energy storage," Energy, Elsevier, vol. 153(C), pages 170-184.
    12. Yokoyama, Ryohei & Shinano, Yuji & Taniguchi, Syusuke & Wakui, Tetsuya, 2019. "Search for K-best solutions in optimal design of energy supply systems by an extended MILP hierarchical branch and bound method," Energy, Elsevier, vol. 184(C), pages 45-57.
    13. Sanaei, Sayyed Mohammad & Nakata, Toshihiko, 2012. "Optimum design of district heating: Application of a novel methodology for improved design of community scale integrated energy systems," Energy, Elsevier, vol. 38(1), pages 190-204.
    14. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    15. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    16. Gonzalez-Salazar, Miguel & Klossek, Julia & Dubucq, Pascal & Punde, Thomas, 2023. "Portfolio optimization in district heating: Merit order or mixed integer linear programming?," Energy, Elsevier, vol. 265(C).
    17. Wakui, Tetsuya & Yokoyama, Ryohei, 2014. "Optimal structural design of residential cogeneration systems in consideration of their operating restrictions," Energy, Elsevier, vol. 64(C), pages 719-733.
    18. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei, 2016. "Optimal structural design of residential power and heat supply devices in consideration of operational and capital recovery constraints," Applied Energy, Elsevier, vol. 163(C), pages 118-133.
    19. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-objective optimization of a distributed energy network integrated with heating interchange," Energy, Elsevier, vol. 109(C), pages 353-364.
    20. Dahl, Magnus & Brun, Adam & Andresen, Gorm B., 2019. "Cost sensitivity of optimal sector-coupled district heating production systems," Energy, Elsevier, vol. 166(C), pages 624-636.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:92:y:2015:i:p3:p:420-434. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.