Identifying stakeholders and key performance indicators for district and building energy performance analysis

Li, Yehong; O’Donnell, James; García‐Castro, Raúl; Vega-Sánchez, Sergio

doi:10.1016/j.enbuild.2017.09.003

Cited by 64 publications

(31 citation statements)

References 44 publications

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“…Several studies introduce ranking systems to assess and compare the smartness of cities through indexes but involve the high risk of losing information on the complexity of smart cities [27]. Li et al [28] propose a systematic approach, utilizing a bi-index method, to identify stakeholders and KPIs for multi-level (from building to district) energy performance analysis.…”

Section: Matchup-maximizing the Upscaling And Replication Potential Omentioning

confidence: 99%

A Methodological Framework for the Selection of Key Performance Indicators to Assess Smart City Solutions

et al. 2019

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Smart and sustainable cities are expected to form a cornerstone for achieving resource efficiency and sustainability worldwide. In this specific study we introduce a holistic framework for determining a repository of key performance indicators (KPIs) that are able to evaluate both business-as-usual and novel technologies and services related to smart city solutions. The framework includes six steps: (a) Clustering of the technology/service solutions into groups called Transition Tracks; (b) definition of the main groups of stakeholders; (c) definition of KPIs dimensions (or domains); (d) definition of KPIs repository per dimension; (e) definition of the scope of evaluation per KPI; and (f) threshold definition per KPI. The implementation of the proposed framework led to the development of a repository of 75 KPIs categorized in six dimensions (technical, environmental, economic, social, ICT and legal KPIs) with the corresponding levels of assessment and stakeholders’ group of interest. The proposed repository can serve as a great basis for similar projects to monitor and evaluate the performance of their solutions. Tips and guidance based on the actual implementation and lessons learned from a smart city project are provided.

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Section: Matchup-maximizing the Upscaling And Replication Potential Omentioning

confidence: 99%

A Methodological Framework for the Selection of Key Performance Indicators to Assess Smart City Solutions

et al. 2019

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“…Setting the target audience is an important development procedure given that it is a fundamental factor to establish appropriate energy benchmarks and performance assessment methods [10]. The target audience can be classified into two broad categories, depending on whether they have a direct interest in the actionable strategies to improve building efficiency or they want to establish a national standard and manage numerous buildings.…”

Section: Purpose and Requirements Of Benchmarkingmentioning

confidence: 99%

“…Thus, to develop a usable benchmark, it is important to check the state of the collected data [3,[6][7][8][9]. In addition, the benchmarking information must be communicated to stakeholders in an appropriate way [10]. For example, energy consumers may be more interested in using electricity or gas than greenhouse gas (GHG) emissions.…”

Section: Introductionmentioning

confidence: 99%

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Kim

2020

Energies

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In an effort to improve the energy efficiency of existing buildings, it is necessary to first evaluate the energy performance of those buildings. Since it is difficult to obtain detailed information on existing buildings, the challenge is how to conduct reliable energy performance assessments with this limited information. As a result, many countries have adopted evaluation systems based on measured energy consumption data for existing buildings. This study aims to analyze the building energy consumption and characteristics using Korea’s national building database and provide an energy performance benchmark for continuous management of the energy performance of existing buildings. We analyzed the relationship between the basic statistical characteristics of the information collected from the national integrated energy database and energy consumption. The total floor area was found to be closely related to energy consumption, and various regression analysis methods were applied and compared to develop a benchmark to explain the trends of energy consumption according to the increase in total floor area. Finally, the developed benchmarks were used to evaluate energy consumption and examine the feasibility of the benchmarks.

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“…In practice, quantitative performance metrics are key components for building performance assessment. However, to date researchers and industry have yet to take advantage of multi-silo rule-based performance metrics as such metrics are currently isolated from other available contextual data silos [21]. Therefore, this isolation restricts in-depth building performance assessment.…”

Section: Introductionmentioning

confidence: 99%

Building performance evaluation using OpenMath and Linked Data

Corry

Horrigan

et al. 2018

Energy and Buildings

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A pronounced gap often exists between expected and actual building performance. The multi-faceted and cross lifecycle causes of this performance gap are found in design assumptions, construction issues and commissioning and operational compromises. Some important factors are firmly rooted in the lack of interoperability around building information. New solutions to the interoperability challenge offer the potential to leverage and reuse available heterogeneous data in a manner that can significantly assist building performance assessment. Linked data provides an open, modular and extensible solution for the challenge. However, in the buildings domain, the integration of rule-based performance metrics and contextual information has yet to be formally established. This paper describes an approach to the provision of in-depth building performance assessment through the integration of OpenMath and linked data. An ontology describing performance metrics in RDF is presented, together with an automated metric evaluation solution using multi-silo queries and computer algebra systems, providing a flexible, automated and extensible mechanism for the assessment of building performance. Building managers and engineers can simultaneously analyse time-series building performance

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Identifying stakeholders and key performance indicators for district and building energy performance analysis

Cited by 64 publications

References 44 publications

A Methodological Framework for the Selection of Key Performance Indicators to Assess Smart City Solutions

A Methodological Framework for the Selection of Key Performance Indicators to Assess Smart City Solutions

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

Building performance evaluation using OpenMath and Linked Data

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