Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings

Genku Kayo, Ala Hasan, Ivo Marinac, Risto Lahdelma

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    Decentralized or distributed energy systems can be strategy for establishing carbon neutral city by utilising on-site or renewable energy technology. Moreover, the key motivation of Zero Energy Building (ZEB) is also to utilize distributed energy resources as well as energy efficient systems. Various scales of energy systems are strongly related each other and different levels of energy efficiency improvements are gaining importance. This research, thus, focuses on the boundary of the building, thereby not being limited to only a single building but spanning over a cluster of buildings, so called "Carbon Neutral Neighborhood". Proposed optimal planning tool is designed to be useful for supporting the energy engineer's decision making to find suitable technological combinations and operations in order to minimize the target objectives such as primary energy consumption, environmental impact or life cycle cost. In order to search the optimal solution, Multi-Objective Building Performance Optimization Software (MOBO) was used as an optimization method. The validity of the methodology of the tools was verified by applying the case study on a group of existing campus building stocks with the energy demand data resource. The methodology proposed in the research presents the idea to utilise energy data resources for finding carbon neutral planning.
    Original languageEnglish
    Title of host publicationProceedings of PLEA 2016
    Pages889-894
    Volume2
    Publication statusPublished - 2016
    MoE publication typeA4 Article in a conference publication
    Event36th International Conference on Passive and Low Energy Architecture, PLEA 2016 - Los Angeles, United States
    Duration: 11 Jul 201613 Jul 2016

    Conference

    Conference36th International Conference on Passive and Low Energy Architecture, PLEA 2016
    Abbreviated titlePLEA 2016
    CountryUnited States
    CityLos Angeles
    Period11/07/1613/07/16

    Fingerprint

    Planning
    Carbon
    Energy resources
    Environmental impact
    Energy efficiency
    Life cycle
    Energy utilization
    Decision making
    Engineers
    Costs

    Keywords

    • On-site energy management
    • Combined Heat and Power systems
    • Zero energy building
    • Campus building
    • Optimisation

    Cite this

    Kayo, G., Hasan, A., Marinac, I., & Lahdelma, R. (2016). Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings. In Proceedings of PLEA 2016 (Vol. 2, pp. 889-894)
    Kayo, Genku ; Hasan, Ala ; Marinac, Ivo ; Lahdelma, Risto. / Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings. Proceedings of PLEA 2016. Vol. 2 2016. pp. 889-894
    @inproceedings{02448d6951db472e96de415f91dc07c7,
    title = "Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings",
    abstract = "Decentralized or distributed energy systems can be strategy for establishing carbon neutral city by utilising on-site or renewable energy technology. Moreover, the key motivation of Zero Energy Building (ZEB) is also to utilize distributed energy resources as well as energy efficient systems. Various scales of energy systems are strongly related each other and different levels of energy efficiency improvements are gaining importance. This research, thus, focuses on the boundary of the building, thereby not being limited to only a single building but spanning over a cluster of buildings, so called {"}Carbon Neutral Neighborhood{"}. Proposed optimal planning tool is designed to be useful for supporting the energy engineer's decision making to find suitable technological combinations and operations in order to minimize the target objectives such as primary energy consumption, environmental impact or life cycle cost. In order to search the optimal solution, Multi-Objective Building Performance Optimization Software (MOBO) was used as an optimization method. The validity of the methodology of the tools was verified by applying the case study on a group of existing campus building stocks with the energy demand data resource. The methodology proposed in the research presents the idea to utilise energy data resources for finding carbon neutral planning.",
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    Kayo, G, Hasan, A, Marinac, I & Lahdelma, R 2016, Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings. in Proceedings of PLEA 2016. vol. 2, pp. 889-894, 36th International Conference on Passive and Low Energy Architecture, PLEA 2016, Los Angeles, United States, 11/07/16.

    Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings. / Kayo, Genku; Hasan, Ala; Marinac, Ivo; Lahdelma, Risto.

    Proceedings of PLEA 2016. Vol. 2 2016. p. 889-894.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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    AU - Hasan, Ala

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    AU - Lahdelma, Risto

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    PY - 2016

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    N2 - Decentralized or distributed energy systems can be strategy for establishing carbon neutral city by utilising on-site or renewable energy technology. Moreover, the key motivation of Zero Energy Building (ZEB) is also to utilize distributed energy resources as well as energy efficient systems. Various scales of energy systems are strongly related each other and different levels of energy efficiency improvements are gaining importance. This research, thus, focuses on the boundary of the building, thereby not being limited to only a single building but spanning over a cluster of buildings, so called "Carbon Neutral Neighborhood". Proposed optimal planning tool is designed to be useful for supporting the energy engineer's decision making to find suitable technological combinations and operations in order to minimize the target objectives such as primary energy consumption, environmental impact or life cycle cost. In order to search the optimal solution, Multi-Objective Building Performance Optimization Software (MOBO) was used as an optimization method. The validity of the methodology of the tools was verified by applying the case study on a group of existing campus building stocks with the energy demand data resource. The methodology proposed in the research presents the idea to utilise energy data resources for finding carbon neutral planning.

    AB - Decentralized or distributed energy systems can be strategy for establishing carbon neutral city by utilising on-site or renewable energy technology. Moreover, the key motivation of Zero Energy Building (ZEB) is also to utilize distributed energy resources as well as energy efficient systems. Various scales of energy systems are strongly related each other and different levels of energy efficiency improvements are gaining importance. This research, thus, focuses on the boundary of the building, thereby not being limited to only a single building but spanning over a cluster of buildings, so called "Carbon Neutral Neighborhood". Proposed optimal planning tool is designed to be useful for supporting the energy engineer's decision making to find suitable technological combinations and operations in order to minimize the target objectives such as primary energy consumption, environmental impact or life cycle cost. In order to search the optimal solution, Multi-Objective Building Performance Optimization Software (MOBO) was used as an optimization method. The validity of the methodology of the tools was verified by applying the case study on a group of existing campus building stocks with the energy demand data resource. The methodology proposed in the research presents the idea to utilise energy data resources for finding carbon neutral planning.

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    KW - Combined Heat and Power systems

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    Kayo G, Hasan A, Marinac I, Lahdelma R. Optimal planning tools for carbon neutral neighborhoods by integrating existing buildings. In Proceedings of PLEA 2016. Vol. 2. 2016. p. 889-894