A simplified geo-cluster definition for energy system planning in Europe

Kuster, Corentin; Hippolyte, Jean-Laurent; Rezgui, Yacine; Mourshed, Monjur

doi:10.1016/j.egypro.2019.01.1001

Cited by 5 publications

(4 citation statements)

References 9 publications

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“…The importance of creating standardized procedures for large scale statistical analysis of building data has been stressed, for example, by institutions such as NIST (National Institute of Standards and Technology) in the US [42]. In fact, in the next few years, the possibility of collecting and processing data at large scale will be crucial for informing future policies for built environment [43].…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, energy signature can essentially complement (for long-term monitoring) co-heating test, which needs measures of indoor air temperatures as an input and short term measurements under controlled conditions. Further, extensions of this methodology can be achieved by means of integration with variable-base degree-days method, as shown in recent literature [44], potentially extending the applicability for large scale energy system planning [43].…”

Section: -3mentioning

confidence: 99%

“…Further, the formulation of psychrometric equations for air-handling processes using linear algebra [50] offers interesting perspectives for optimization of air-handling systems in HVAC with surrogate models [51]. Finally, extensions of the variable base degree days method [44] could enable large scale energy performance analytics, ideally linking it with energy system planning and policy studies [42,43] together with R&D strategies [52].…”

Section: Future Prospects For Modelling Research Developmentmentioning

confidence: 99%

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From in-situ measurement to regression and time series models: An overview of trends and prospects for building performance modelling

Manfren

Nastasi

2019

AIP Conference Proceedings

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Data analysis methodologies are crucial to learn insights from data and to create more trust in the assumptions used for energy performance assessment. Indeed, continuous performance monitoring should become a more diffuse practice in order to improve our design and operation strategies for the future. This is an essential step to reduce incrementally the gap between simulated and measured performance. In fact, assumptions in simulation represent a significant source of uncertainty when estimating the energy performance of buildings. This uncertainty affects decisionmaking processes in multiple ways, from design of new and refurbished buildings to policy making. The research presented aims to highlight potential links between experimental approaches for test-facilities and methods and tools used for continuous performance monitoring, at the state of the art. In particular, we start by exploring the relation between in-situ measurement of thermal transmittance (U) and regression-based monitoring approaches, such as co-heating test and energy signature, for heat load coefficient (HLC) and solar aperture (gA) estimation. After that, we highlight some recent developments in simplified dynamic energy modelling using lumped parameter models. In particular, we want to underline the scalability of these techniques, considering relevant issues in current integrated engineer design perspective. These issues include, among others, the necessity of limiting the number of a sensors to be installed in buildings, the possibility of employing both experimental and real operation data (and compare them with design data as well) and, finally, the possibility to automate performance monitoring at multiple scales, from single components, to individual buildings, to building stock and cities.

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Section: Methodsmentioning

confidence: 99%

Section: -3mentioning

confidence: 99%

Section: Future Prospects For Modelling Research Developmentmentioning

confidence: 99%

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From in-situ measurement to regression and time series models: An overview of trends and prospects for building performance modelling

Manfren

Nastasi

2019

AIP Conference Proceedings

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“…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%

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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Open data and energy analytics - An analysis of essential information for energy system planning, design and operation

Manfren

Nastasi

Groppi

et al. 2020

Energy

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A simplified geo-cluster definition for energy system planning in Europe

Cited by 5 publications

References 9 publications

From in-situ measurement to regression and time series models: An overview of trends and prospects for building performance modelling

From in-situ measurement to regression and time series models: An overview of trends and prospects for building performance modelling

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

Open data and energy analytics - An analysis of essential information for energy system planning, design and operation

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