Implementing flexibility into energy planning models: Soft-linking of a high-level energy planning model and a short-term operational model

Dominković, Dominik Franjo; Junker, Rune Grønborg; Lindberg, Karen Byskov; Madsen, Henrik

doi:10.1016/j.apenergy.2019.114292

Cited by 35 publications

(21 citation statements)

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“…The energy modelling research community at present is emphasizing the fundamental importance of open energy data and models (Pfenninger et al, 2017;Pfenninger et al, 2018), and we can envision an evolution towards systems of models (Bollinger et al, 2018) created to tackle fundamental problems in energy transitions, eventually exploiting soft-linking approaches (Deane et al, 2012;Dominković et al, 2020). The way energy consumption data are measured, processed, and reported can be standardized in order to enable transparency and consistency of methods at multiple scales and levels of analysis, as well as to complement initiatives applying open science principles in energy research (Openmod;Hilpert et al, 2018).…”

Section: Background and Motivationmentioning

confidence: 99%

“…However, in order to enable an effective performance assessment, additional indicators have to be considered regarding IEQ (Fabbri and Tronchin, 2015;, RES on-site generation and self-consumption (Kurnitski, 2013), load matching, and grid interaction (Voss et al, 2010;Frontini et al, 2012). Further, indicators are essential to address innovative solutions (Mancini and Nastasi, 2019) and operation strategies for buildings aimed at flexibility (Clauß et al, 2017) and relevant problems, such as softlinking simulation models with energy planning tools (Noussan and Nastasi, 2018;Dominković et al, 2020). Indeed, the scalability of analysis methods and tools up to district (Adhikari et al, 2012b), city (Cipriano et al, 2017), and regional scales (Aste et al, 2014;Kuster et al, 2019) is fundamental to ensure the credibility of policies and practices.…”

Section: Linking Design and Operational Energy Performance Analysis Amentioning

confidence: 99%

“…Both the measurement of embodied energy and carbon equivalent of buildings (De Wolf et al, 2017) and operational energy consumption (de Wilde, 2017;Imam et al, 2017) represent critical (and debatable) issues that can ultimately determine a relevant "performance gap." Finally, energy transition strategies have to address complementarities (Markard and Hoffmann, 2016) which are crucial for the co-evolution of built environment and energy infrastructures (Junker et al, 2018;Dominković et al, 2020). In this framework, empirically grounded and tested methods that can help in standardizing the way energy consumption data are measured, processed, and reported are particularly valuable, because they can provide reliable evidence, inform policies, and support decision-making processes adequately.…”

Section: Introductionmentioning

confidence: 99%

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Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

2020

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The reduction of energy usage and environmental impact of the built environment and construction industry is crucial for sustainability on a global scale. We are working towards an increased commitment towards resource efficiency in the built environment and to the growth of innovative businesses following circular economy principles. The conceptualization of change is a relevant part of energy and sustainability transitions research, which is aimed at enabling radical shifts compatible with societal functions. In this framework, building performance has to be considered in a whole life cycle perspective because buildings are long-term assets. In a life cycle perspective, both operational and embodied energy and carbon emissions have to be considered for appropriate comparability and decision-making. The application of sustainability assessments of products and practices in the built environment is itself a critical and debatable issue. For this reason, the way energy consumption data are measured, processed, and reported has to be progressively standardized in order to enable transparency and consistency of methods at multiple scales (from single buildings up to building stock) and levels of analysis (from individual components up to systems), ideally complementing ongoing research initiatives that use open science principles in energy research. In this paper, we analyse the topic of linking design and operation phase’s energy performance analysis through regression-based approaches in buildings, highlighting the hierarchical nature of building energy modelling data. The goal of this research is to review the current state of the art of in order to orient future efforts towards integrated data analysis workflows, from design to operation. In this sense, we show how data analysis techniques can be used to evaluate the impact of both technical and human factors. Finally, we indicate how approximated physical interpretation of regression models can help in developing data-driven models that could enhance the possibility of learning from feedback and reconstructing building stock data at multiple levels.

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Section: Background and Motivationmentioning

confidence: 99%

Section: Linking Design and Operational Energy Performance Analysis Amentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

2020

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“…Second, advances in building data interoperability (technical, informational and organizational) [17] and data availability at multiple levels, using technologies such as the Internet of Things (IoT) [18][19][20] and cyber-physical systems [21], which can enable, in turn, innovation in end-user energy delivery [22], and in energy infrastructures [23]. Third, the increasing decentralization of energy systems where the co-evolution of built environment and energy infrastructures [24] plays a fundamental role, that can be investigated by means of "soft-linking" of energy modelling approaches, from planning to operation [25]. Finally, innovative business models proposing concepts such as prosumer [26] and prosumager [27], which are determining changes in the way energy market works and energy trading takes place, for example using Peer-to-Peer automated exchange mechanisms, exploiting Blockchain technologies [28].…”

Section: Introductionmentioning

confidence: 99%

Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector

2021

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Decarbonisation and efficiency goals set as a response to global warming issue require appropriate decision-making strategies to promote an effective and timely change in energy systems. Conceptualization of change is a relevant part of energy transitions research today, which aims at enabling radical shifts compatible with societal functions and market mechanisms. In this framework, construction sector can play a relevant role because of its energy and environmental impact. There is, however, the need to move from general instances to specific actions. Open data and open science, digitalization and building data interoperability, together with innovative business models could represent enabling factors to accelerate the process of change. For this reason, built environment research has to address the co-evolution of technologies and human behaviour and the analytical methods used for this purpose should be empirically grounded, transparent, scalable and consistent across different temporal/spatial scales of analysis. These features could potentially enable the emergence of “ecosystems” of applications that, in turn, could translate into projects, products and services for energy transitions in the built environment, proposing innovative business models that can stimulate market competitiveness. For these reasons, in this paper we organize our analysis according to three levels, from general concepts to specific issues. In the first level, we consider the role of building energy modelling at multiple scales. In the second level, we focus on harmonization of methods for energy performance analysis. Finally, in the third level, we consider emerging concepts such as energy flexibility and occupant-centric energy modelling, considering their relation to monitoring systems and automation. The goal of this research is to evaluate the current state of the art and identify key concepts that can encourage further research, addressing both human and technological factors that influence energy performance of buildings.

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“…The requirement on energy flexibility that implied possibility for the hydronic heating and connection to the district heating (DH) was diminished: (1) by decreasing the share of energy that should be delivered by the flexible solutions, and (2) by increasing the building area with the energy supply requirement. The energy system's flexibility shall be enhanced to increase the proportion of variable energy sources, which has been addressed in [4]. This meant that there was only a moderate requirement for implementing renewable sources into building stock development.…”

Section: Introductionmentioning

confidence: 99%

Energy Pathways for Future Norwegian Residential Building Areas

et al. 2021

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Owing to stricter building energy requirements, future buildings will be characterized by low base loads and occasional high peaks. However, future building areas will still contain existing and historical buildings with high energy demand. Meanwhile, there is a requirement that future building areas should obtain energy from renewable energy sources, while existing buildings need to be transited to renewables. Therefore, the aim of this study was to develop an approach for modelling energy pathways for future Norwegian residential building areas by analyzing different energy supply systems. Several calculation methods were combined: building simulation, energy supply technology simulation, heat demand aggregation, and data post-processing. The results showed that the energy pathways would be very dependent on CO2-factors for energy sources, and it is hard to predict accurate CO2-factors. An increasing housing stock development would slightly increase the CO2 emissions towards 2050, although the new buildings used much less energy and the existing buildings underwent renovation. A constant housing stock would yield a 22–27% reduction of CO2 emissions by 2050. This showed that implementing stricter building codes had a lower impact on the total CO2 emissions than CO2-factors and energy technologies. The focus should lie on energy supply systems.

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Implementing flexibility into energy planning models: Soft-linking of a high-level energy planning model and a short-term operational model

Cited by 35 publications

References 8 publications

Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

Linking Design and Operation Phase Energy Performance Analysis Through Regression-Based Approaches

Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector

Energy Pathways for Future Norwegian Residential Building Areas

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