Search

Energy efficiency in buildings has a central role to play in reaching the climate neutrality goal set by the European Green Deal. With detailed knowledge of their building stock and the profile of their occupants, regional and local authorities can forge an important link between financiers, industry professionals and homeowners to ensure the successful deployment of financial schemes that support the uptake of energy efficiency upgrades. This paper provides a first assessment of the role of regional and local authorities by reviewing relevant initiatives and programmes on energy efficiency. Based on a questionnaire completed for more than 150 schemes, it explores how European municipalities and regions stimulate energy upgrades in residential, commercial and public buildings through public financial support. It is found that 60% of the examined schemes are offered in the form of grants and subsidies, and 45% of them targeted residential upgrades. The use of EU cohesion policy funds in supporting regional schemes, and promotion of energy efficiency investments at local level through the European Covenant of Mayors initiative are also explored. In spite of possible resource limitations at this level of governance, regional and local authorities are in a good position to utilise European structural or research funds to develop financial schemes, as standalone programmes or blended with national ones, thus providing additional support and funds for deep renovations. The results suggest that energy efficiency in buildings has become an important part of local and regional strategies in several European countries, but could be further enhanced. [ABSTRACT FROM AUTHOR]

Increased use of energy in buildings and HVAC systems requires advanced control schemes like model-based control to improve energy efficiency, which in turn requires accurate thermodynamic models of buildings. The Resistive-Capacitive (RC) method is a popular and versatile approach for thermal modeling of buildings. Despite this, it is not easy to find practical solutions of implementation of the RC method. It is the goal of this paper to clarify the RC method and demonstrate simple implementation of this method, especially for multi-zone buildings, which have more potential for energy savings from use of model-based control. This paper provides two contributions. First is a detailed explanation of the RC method, focusing on its use for developing a structure of a model and first-principles approach for estimation of parameters of a model. Second is a demonstration of an algorithm that enables automatic development of the structure of a model from basic information about a building (layout, construction elements) and its combination with data-based parameter estimation. Use of the algorithm is presented with a case-study on industrial multi-zone building, for which such a grey-box model is developed and analyzed. The resulting model is rapidly developed and used in a simulation with the measured data. The outputs of the model are compared with the measured temperatures and they show good fit. [ABSTRACT FROM AUTHOR]

Projections of building electricity consumption are used in multiple fields and for a variety of purposes, from energy utility investment decisions to global climate assessments. Existing approaches to modeling building electricity consumption span a range of structural methodologies, spatial resolutions, and temporal scales, potentially leading to divergent projections. This paper compares how two models with different structures and resolutions respond to a common set of population and climate drivers in the western U.S. The BEND model simulates hourly residential and commercial building electricity consumption at the county scale by weighting the results of simulations of thousands of representative buildings. In contrast, the projected electricity demand in GCAM-USA is determined for each state, year, sector (residential/commercial), and service (e.g., heating, cooling, and others), based on population, income, technology, energy prices, and average annual climate. This paper aggregates the two models' results to a common resolution: annual residential and commercial building electricity consumption by state. Both models show similar responses to future projected population change and climate change, with population change having the larger impact between the two. Differences are primarily due to how the models capture changes in the aggregate energy efficiency of the building stock as it evolves over time. • Models of building electricity consumption are methodologically diverse. • Two models of building electricity using very different approaches are compared. • The models mostly agree in their projections of building electricity consumption. • How the efficiency of buildings evolves drives disagreement between the models. [ABSTRACT FROM AUTHOR]

One of the main objectives of EU climate and energy policy is to reduce energy dependency and "decarbonise" the economy. These policies have a considerable influence on the building sector, and where Directive 2010/31/EU on the energy performance of buildings establishes that all new buildings in the EU shall have to consume 'nearly zero-energy' as from 2021 and that all public authority owned or rented buildings apply these measures as from 2019. The analysis presented in this paper -focusing on the case of office buildings due to their far greater energy demands with respect to residential buildings- forms part of a study that attempts to examine the technical characteristics and economic feasibility of these "nearly zero-energy" buildings. [ABSTRACT FROM AUTHOR]

Interpretable and scalable data-driven methodologies providing high granularity baseline predictions of energy use in buildings are essential for the accurate measurement and verification of energy renovation projects and have the potential of unlocking considerable investments in energy efficiency worldwide. Bayesian methodologies have been demonstrated to hold great potential for energy baseline modelling, by providing richer and more valuable information using intuitive mathematics. This paper proposes a Bayesian linear regression methodology for hourly baseline energy consumption predictions in commercial buildings. The methodology also enables a detailed characterization of the analyzed buildings through the detection of typical electricity usage profiles and the estimation of the weather dependence. The effects of different Bayesian model specifications were tested, including the use of different prior distributions, predictor variables, posterior estimation techniques, and the implementation of multilevel regression. The approach was tested on an open dataset containing two years of electricity meter readings at an hourly frequency for 1578 non-residential buildings. The best performing model specifications were identified, among the ones tested. The results show that the methodology developed is able to provide accurate high granularity baseline predictions, while also being intuitive and explainable. The building consumption characterization provides actionable information that can be used by energy managers to improve the performance of the analyzed facilities. [ABSTRACT FROM AUTHOR]

Abstract: The existing buildings stock in European countries accounts for over 40% of final energy consumption in the European Union (EU) member states, of which residential use represents 63% of total energy consumption in the buildings sector. Consequently, an increase of building energy performance can constitute an important instrument in the efforts to alleviate the EU energy import dependency and comply with the Kyoto Protocol to reduce carbon dioxide emissions. This is also in accordance to the European Directive on the energy performance of buildings (EPBD), which has come to effect on 4 January 2006. The energy performance assessment for existing dwellings (EPA-ED) is a new methodology supported by software, developed in the framework of a European project that focuses on energy related issues for existing residential buildings, in line with the EPBD. This paper presents an overview of the method and software that can be used to perform building energy audits and assess buildings in a uniform way, perform demand and savings calculations, provide owners with specific advice for measures to improve energy performance, issue an energy performance certificate for existing buildings, and include some representative results from the pilot studies performed in several European countries. Also the sister-method EPA-NR, on non-residential buildings, currently under construction, is introduced. [Copyright &y& Elsevier]

The methodology for baseline building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. In most cases, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents a holistic utility bills analysis method for baseline whole building energy consumption in the tropical region. Six commercial buildings in Singapore were selected for case studies. Correlationships between the climate data, which are monthly mean outdoor dry-bulb temperature (T0), relative humidity (RH) and global solar radiation (GSR), and whole building energy consumption are derived. A deep prediction study based monthly mean outdoor dry-bulb temperature (T0) and whole building energy consumption is stated. The result shows that variations of the energy consumption in most of these buildings are contributed by T0 and can be well predicted at 90% confidence level only with it. The analysis of such kind of model is especially useful for building managers, owners and ESCOs to track and baseline energy use during pre-retrofit and post-retrofit periods in the tropical condition. [Copyright &y& Elsevier]

Space heating accounts for the most significant share of final energy demand in buildings in colder climatic regions contributing to greenhouse gas emission. In addition, there is a lack of data available to assess spatially, the potential of space heating demand reduction in different buildings when considering typical building refurbishment measures. Hence, in this paper, a robust information socket for urban building stock is developed to assess the impact of energy efficiency measures on space heating demand savings and CO 2 emission reduction potential in the existing buildings based on a Geographical Information System tool. The model considers the topology and thermal performance of different building categories; houses with and without thermal insulation, apartments, commercial, public, office, and industrial buildings. Three scenarios, a reference and two additional scenarios using Prishtina city as a case study, have been created for standard (scenario 1), and advanced energy efficiency (scenario 2) measures based on the government's proposed policies. The findings show that space heat demand saving potential for scenario 1 and 2 in comparison to the reference scenario was 50% and 68.5% respectively. Moreover, the CO 2 emissions are reduced significantly from 502.3 mil kgCO 2 /year in reference scenario to 249.8 mil kgCO 2 /year for scenario 1 and 158.7 mil kgCO 2 /year in scenario 2 respectively. • Analysis of space heating demand for different building categories. • A novel method for robust information socket for urban building stock is developed. • A spatial based method for potential savings in space heating demand is proposed. • Spatial analysis of 23384 buildings for Prishtina is performed. • Space heating demand savings potential with energy efficiency measures is calculated. [ABSTRACT FROM AUTHOR]

• Telework impacts transportation, building, and Internet-related energy and emissions. • Telework's environmental impact is highly dependent on contextual details. • The majority of studies indicate telework decreases energy use, with some exceptions. • Rebound effects tend to significantly offset and even exceed energy savings. • Existing research methods tend to be simple, leaving room for significant improvement. Teleworking has been widely perceived as a more sustainable mode of working for knowledge workers compared to the status quo of commuting to centralized offices because of its reduced dependency on transportation and centralized office space. However, the situation is far more complex than would appear on the surface, when the scope is expanded to include home office energy use, the Internet, long-term consumer choices, and other so-called rebound effects. Few studies have quantified home, office, transportation, and communications energy or GHG emissions implications of telecommuting simultaneously. To make progress in answering the question of whether telecommuting results in less energy use and greenhouse gas emissions than conventional centralized office working, this paper reviews results and research methods of primarily quantitative studies of any and all four domains that consider operating energy and/or greenhouse gas emissions. The results ultimately show that this problem is complex, and that current datasets and methods are generally inadequate for fully answering the research question. While most studies indicate some benefit, several suggest teleworking increases energy use – even for the domain that is thought to benefit most: transportation. [ABSTRACT FROM AUTHOR]

Accurately forecasting energy consumption in a building is an important strategy for achieving the goal of reducing energy demand and improving energy efficiency. University campuses represent specific groups of diverse buildings with significant energy consumption. Therefore, they provide an excellent testbed to characterize and understand the energy consumption of a group of mixed-use buildings. This paper presents a novel methodology that considers the recommendations of ISO 50001: 2011 and ISO 50006: 2014 for establishing energy baselines and energy performance indicators in higher education institution buildings to identify electrical energy consumption reduction potentials in buildings and establish energy management strategies related to electricity use. The study was implemented in three buildings at the Federal University of Itajubá (José Rodrigues Seabra Campus). Several methods and indicators were evaluated to monitor and measure energy performance in buildings. A wide range of factors that influence operating system energy consumption in the buildings were studied and taken into account, such as the types of activities carried out in the building, weather conditions, building materials, air conditioning system and occupancy, since these contribute directly and indirectly to the difficulty of accurately measuring the building's energy consumption. The results showed that potential annual savings in electric energy consumption for the campus could be around 9.6%, which translates into a R$ 93,647.2 economic value and a 20.3 tCO 2eq emissions reduction without economic investment. It was concluded that the methodology proposed for establishing and monitoring an energy efficiency indicator can be applied to any institute of higher education because it is flexible and adaptable since each institute can define the period of analysis for the indicator. This research is expected to provide theoretical guidance and a practical data reference for relevant evaluations of building energy efficiency. Image 1 • Energetic characterization of buildings was based on constructive particulars, location and use. • ISO 50001 standard was applied for estimate baseline energy use. • The variables that have a greater influence on the electrical consumption of a building were identified. • Linear regression method applied for the analysis of the variables. • Potential savings in energy consumption and reduction of the carbon footprint were quantified. [ABSTRACT FROM AUTHOR]