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Special Issue "Energy Efficiency in Buildings: Both New and Rehabilitated"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Energy and Buildings".

Deadline for manuscript submissions: 31 July 2019

Special Issue Editors

Guest Editor
Prof. Dr. José Manuel Andújar

Escuela Técnica Superior de Ingeniería, Universidad de Huelva, Campus de El Carmen, Huelva 21007, Spain
Website | E-Mail
Phone: +34959217380
Interests: control engineering; renewable energy systems; remote piloted aircraft systems applications and engineering education
Guest Editor
Dr. Sergio Gómez Melgar

Escuela Técnica Superior de Ingeniería, University of Huelva, Huelva 21819, Spain
Website | E-Mail
Interests: architecture and engineering

Special Issue Information

Dear Colleagues,

Buildings are one of the main causes of the emission of greenhouse gases in the world; in Europe, for example, they are responsible for more than 30% of emissions, or about 900 million tons of CO2 per year. Heating and air conditioning are mainly responsible for greenhouse gas emissions in buildings.

Based on the above, it is a current priority to reduce (or ideally eliminate) the waste  of energy in buildings and at the same time supply the necessary energy through renewable sources. The first can be achieved by improving the construction methods, the materials used and the efficiency of the facilities and systems; the second can be achieved through the use of renewable energies (wind, solar, geothermal, etc.) in buildings. In any case, regardless of whether the energy used is renewable or not, the efficiency must always be taken into account: the most profitable and clean energy is that which is not necessary.

Most current buildings were built with poor energy efficiency criteria and even, depending on the country and the date of construction, with none. Therefore, regardless of whether construction regulations are becoming stricter, a huge challenge is the energy rehabilitation of existing buildings.

In this Special Issue, potential topics include but are not limited to the following:

  • Methodologies, processes, methods to design/build/rehabilitate minimum energy consumption buildings.
  • Efficient electric loads: ventilation, heating, air conditioning, lighting, domestic hot water, appliances, etc.
  • Facilities in buildings for minimum energy consumption.
  • Renewable energy applications in buildings.
  • Maintenance and management of buildings for minimum energy consumption.
  • Methods and systems of energy measurement and control in buildings.
  • Home automation for energy efficiency in buildings.

Prof. Dr. José Manuel Andújar
Dr. Sergio Gómez Melgar
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy efficiency
  • passive architecture
  • heating, ventilating and air conditioning
  • nearly zero energy building
  • renewable energy systems
  • energy rehabilitation

Published Papers (9 papers)

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Research

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Open AccessArticle Prediction Model Based on an Artificial Neural Network for User-Based Building Energy Consumption in South Korea
Energies 2019, 12(4), 608; https://doi.org/10.3390/en12040608 (registering DOI)
Received: 20 January 2019 / Revised: 12 February 2019 / Accepted: 13 February 2019 / Published: 15 February 2019
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Abstract
The evaluation of building energy consumption is heavily based on building characteristics and thus often deviates from the true consumption. Consequently, user-based estimation of building energy consumption is necessary because the actual consumption is greatly affected by user characteristics and activities. This work [...] Read more.
The evaluation of building energy consumption is heavily based on building characteristics and thus often deviates from the true consumption. Consequently, user-based estimation of building energy consumption is necessary because the actual consumption is greatly affected by user characteristics and activities. This work aims to examine the variation in energy consumption as a function of user activities within the same building, and to employ an artificial neural network (ANN) to predict user-based energy consumption. The study exploited the actual 24-h schedules of 5240 single-person households and computed the respective energy consumption using EnergyPlus V 8.8.0 software. The calculated values were clustered according to gender, age, occupation, income, educational level, and occupancy period and the difference among them was analyzed. The simulation results showed that for single-person households in Korea, females used more energy than males did, and the difference increased with age. Furthermore, unemployed and low-income individuals consumed more energy whereas consumption was inversely proportional to the educational level. Energy consumption increased with the occupancy period. Based on the simulation results and six user characteristics, the ANN model indicated a correlation between user characteristics and energy usage. This study analyzed the differences in energy usage depending on user activity and characteristics that affect building energy consumption. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Using Edible Plant and Lightweight Expanded Clay Aggregate (LECA) to Strengthen the Thermal Performance of Extensive Green Roofs in Subtropical Urban Areas
Energies 2019, 12(3), 424; https://doi.org/10.3390/en12030424
Received: 17 December 2018 / Revised: 21 January 2019 / Accepted: 25 January 2019 / Published: 29 January 2019
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Abstract
Gazing at natural landscapes and participating in agricultural activities can elicit psychophysiological restoration. However, most buildings are constructed merely to meet the minimum legal requirements for structure weight load. Extensive green roofs consisting of vegetables and a lightweight growth medium can be designed [...] Read more.
Gazing at natural landscapes and participating in agricultural activities can elicit psychophysiological restoration. However, most buildings are constructed merely to meet the minimum legal requirements for structure weight load. Extensive green roofs consisting of vegetables and a lightweight growth medium can be designed to provide not only passive-cooling effects on bare rooftops, but also to convert idle rooftops into temporary retreats for stressed individuals. The purpose of this study is to both measure the surface temperature reduction and heat amplitude reduction of a bare rooftop using the extensive green roofs containing a lightweight expanded clay aggregate (LECA) and Ipomoea batata as well as conduct a weight-reduction-and-cost analysis to measure the weight loss of the extensive green roofs incurred through LECA replacement. A four-stage field experiment was performed on the flat rooftop of a dormitory in a subtropical climate during summer. The results indicated that roofs with Ipomoea batata had a significantly higher passive-cooling effect than did roofs without Ipomoea batata. The roofs with 10%–40% LECA exhibited a slightly higher passive-cooling effect than did roofs with conventional garden soil. At a slightly different average air temperature (0.56 °C; i.e., 32.04 °C minus 31.48 °C), the combined effects of LECA and Ipomoea batata helped to significantly reduce the average temperature of the bare rooftop by an additional 10.19 °C, namely, temperature reduction of the bare rooftop increased from 9.54 °C under a roof with 0% LECA and without plants in the second stage to 19.73 °C under a roof with 10% LECA and with plants in the fourth stage. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Data-Driven Evaluation of Residential HVAC System Efficiency Using Energy and Environmental Data
Energies 2019, 12(1), 188; https://doi.org/10.3390/en12010188
Received: 2 December 2018 / Revised: 31 December 2018 / Accepted: 4 January 2019 / Published: 8 January 2019
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Abstract
In the U.S., the heating, ventilation, and air conditioning (HVAC) system is generally the largest electricity-consuming end-use in a residential building. However, homeowners are less likely to have their HVAC system serviced regularly, thus inefficiencies in operation are also more likely to occur. [...] Read more.
In the U.S., the heating, ventilation, and air conditioning (HVAC) system is generally the largest electricity-consuming end-use in a residential building. However, homeowners are less likely to have their HVAC system serviced regularly, thus inefficiencies in operation are also more likely to occur. To address this challenge, this research works towards a non-intrusive data-driven assessment method using building assessors’ data, HVAC electricity demand data, and outdoor environmental data. Building assessors’ data is first used to estimate the HVAC system size, then estimate the electricity demand curve of the HVAC system. A comparison of the proposed electricity demand curve development method demonstrates strong agreement with physics-based HVAC model results. An HVAC efficiency rating is then proposed, which compares the model-predicted and actual performance data to define whether an HVAC system is operating as expected. As a case study, detailed data for 39 occupied, conditioned residential buildings in Austin, Texas, was used demonstrating the identification of the presence of potential HVAC inefficiencies. The results prove beneficial for utilities to help target residential HVAC systems in need of service or energy efficiency upgrades, as well as for homeowners as a continuous assessment tool for HVAC performance. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Simulation and Analysis of Perturbation and Observation-Based Self-Adaptable Step Size Maximum Power Point Tracking Strategy with Low Power Loss for Photovoltaics
Energies 2019, 12(1), 92; https://doi.org/10.3390/en12010092
Received: 15 November 2018 / Revised: 21 December 2018 / Accepted: 24 December 2018 / Published: 28 December 2018
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Abstract
Photovoltaic (PV) techniques are widely used in daily life. In addition to the material characteristics and environmental conditions, maximum power point tracking (MPPT) techniques are an efficient means to maximize the output power and improve the utilization of solar power. However, the conventional [...] Read more.
Photovoltaic (PV) techniques are widely used in daily life. In addition to the material characteristics and environmental conditions, maximum power point tracking (MPPT) techniques are an efficient means to maximize the output power and improve the utilization of solar power. However, the conventional fixed step size perturbation and observation (P&O) algorithm results in perturbations and power loss around the maximum power point in steady-state operation. To reduce the power loss in steady-state operation and improve the response speed of MPPT, this study proposes a self-adaptable step size P&O-based MPPT algorithm with infinitesimal perturbations. This algorithm combines four techniques to upgrade the response speed and reduce the power loss: (1) system operation state determination, (2) perturbation direction decision, (3) adaptable step size, and 4) natural oscillation control. The simulation results validate the proposed algorithm and illustrate its performances in operational procedures. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Phase Balancing Home Energy Management System Using Model Predictive Control
Energies 2018, 11(12), 3323; https://doi.org/10.3390/en11123323
Received: 31 October 2018 / Revised: 19 November 2018 / Accepted: 25 November 2018 / Published: 28 November 2018
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Abstract
Most typical distribution networks are unbalanced due to unequal loading on each of the three phases and untransposed lines. In this paper, models and methods which can handle three-phase unbalanced scenarios are developed. The authors present a novel three-phase home energy management system [...] Read more.
Most typical distribution networks are unbalanced due to unequal loading on each of the three phases and untransposed lines. In this paper, models and methods which can handle three-phase unbalanced scenarios are developed. The authors present a novel three-phase home energy management system to control both active and reactive power to provide per-phase optimization. Simplified single-phase algorithms are not sufficient to capture all the complexities a three-phase unbalance system poses. Distributed generators such as photo-voltaic systems, wind generators, and loads such as household electric and thermal demand connected to these networks directly depend on external factors such as weather, ambient temperature, and irradiation. They are also time dependent, containing daily, weekly, and seasonal cycles. Economic and phase-balanced operation of such generators and loads is very important to improve energy efficiency and maximize benefit while respecting consumer needs. Since homes and buildings are expected to consume a large share of electrical energy of a country, they are the ideal candidate to help solve these issues. The method developed will include typical distributed generation, loads, and various smart home models which were constructed using realistic models representing typical homes in Austria. A control scheme is provided which uses model predictive control with multi-objective mixed-integer quadratic programming to maximize self-consumption, user comfort and grid support. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Parametric Analysis of Buildings’ Heat Load Depending on Glazing—Hungarian Case Study
Energies 2018, 11(12), 3291; https://doi.org/10.3390/en11123291
Received: 29 October 2018 / Revised: 16 November 2018 / Accepted: 23 November 2018 / Published: 25 November 2018
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Abstract
The share of cooling is rising in the energy balance of buildings. The reason is for increasing occupants’ comfort needs, which is accentuated by the fact that the number and the amplitude of heat waves are increasing. The comfortable and healthy indoor environment [...] Read more.
The share of cooling is rising in the energy balance of buildings. The reason is for increasing occupants’ comfort needs, which is accentuated by the fact that the number and the amplitude of heat waves are increasing. The comfortable and healthy indoor environment should to be realized with the minimum amount of energy and fossil fuels. In order to meet this goal, designers should know the effect of different parameters on the buildings’ energy consumption. The energy need for cooling is mainly influenced by the glazed ratio and orientation of the facades, the quality of glazing and shading. In this paper the heat load analysis was done by assuming different types of summer days and surface cooling, depending on the glazing ratio, shading factor and solar factor of glazing. It was proven that, for a certain parameter, the sensitivity of the heat load depends on the orientation and chosen summer day. If the glazing area is doubled, the heat load increases with about 30%. Decreasing the glazed area to 50%, the heat load decreases with about 10%. The heat load decreases with about 3% if the g factor is lowered with 25% or the shading factor is reduced with 60%. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Optimization of Performance Parameter Design and Energy Use Prediction for Nearly Zero Energy Buildings
Energies 2018, 11(12), 3252; https://doi.org/10.3390/en11123252
Received: 18 October 2018 / Revised: 8 November 2018 / Accepted: 20 November 2018 / Published: 22 November 2018
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Abstract
Optimizing key parameters with energy consumption as the control target can minimize the heating and cooling needs of buildings. In this paper we focus on the optimization of performance parameters design and the prediction of energy consumption for nearly Zero Energy Buildings (nZEB). [...] Read more.
Optimizing key parameters with energy consumption as the control target can minimize the heating and cooling needs of buildings. In this paper we focus on the optimization of performance parameters design and the prediction of energy consumption for nearly Zero Energy Buildings (nZEB). The optimal combination of various performance parameters and the Energy Saving Ratio (ESR)are studied by using a large volume of simulation data. Artificial neural networks (ANNs) are applied for the prediction of annual electrical energy consumption in a nearly Zero Energy Building designs located in Shenyang (China). The data of the energy demand for our test is obtained by using building simulation techniques. The results demonstrate that the heating energy demand for our test nearly Zero Energy Building is 17.42 KW·h/(m2·a). The Energy Saving Ratio of window-to-wall ratios optimization is the most obvious, followed by thermal performance parameters of the window, and finally the insulation thickness. The maximum relative error of building energy consumption prediction is 6.46% when using the artificial neural network model to predict energy consumption. The establishment of this prediction method enables architects to easily and accurately obtain the energy consumption of buildings during the design phase. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Open AccessArticle Energy and Economic Analysis for Greenhouse Ground Insulation Design
Energies 2018, 11(11), 3218; https://doi.org/10.3390/en11113218
Received: 29 October 2018 / Revised: 15 November 2018 / Accepted: 16 November 2018 / Published: 20 November 2018
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Abstract
Energy and life cycle cost analysis were employed to identify the most-cost effective ground envelope design for a greenhouse that employs supplemental lighting located in Ottawa, Ontario, Canada (45.4° N). The envelope design alternatives that were investigated consist of installing insulation vertically around [...] Read more.
Energy and life cycle cost analysis were employed to identify the most-cost effective ground envelope design for a greenhouse that employs supplemental lighting located in Ottawa, Ontario, Canada (45.4° N). The envelope design alternatives that were investigated consist of installing insulation vertically around the perimeter and horizontally beneath the footprint of a greenhouse with a concrete slab and unfinished soil floor. Detailed thermal interaction between the greenhouse and the ground surface is achieved by considering 3-dimensional conduction heat transfer within the TRNSYS 17.2 simulation software. The portion of total heat loss that occurred through the ground was approximately 4% and permutations in ground insulation design reduced heating energy consumption by up to 1%. For the two floor designs, the highest net savings was achieved when perimeter and floor zone horizontal insulation was installed whereas a financial loss occurred when it was also placed beneath the crop zone. However, in all cases, the improvement in economic performance was small (net savings below $4000 and reduction in life cycle under 0.2%). Combined energy and life cycle cost analysis is valuable for selecting optimal envelope designs that are capable of lowering energy consumption, improving economics and enhancing greenhouse durability. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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Review

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Open AccessFeature PaperReview Simulation Tools to Build Urban-Scale Energy Models: A Review
Energies 2018, 11(12), 3269; https://doi.org/10.3390/en11123269
Received: 31 October 2018 / Revised: 13 November 2018 / Accepted: 16 November 2018 / Published: 23 November 2018
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Abstract
The development of Urban-Scale Energy Modelling (USEM) at the district or city level is currently the goal of many research groups due to the increased interest in evaluating the impact of energy efficiency measures in city environments. Because USEM comprises a great variety [...] Read more.
The development of Urban-Scale Energy Modelling (USEM) at the district or city level is currently the goal of many research groups due to the increased interest in evaluating the impact of energy efficiency measures in city environments. Because USEM comprises a great variety of analysis areas, the simulation programs that are able to model urban-scale energy systems actually consist of an assemblage of different particular sub-models. In order to simulate each of the sub-models in USEM, one can choose to use either existing specific simulation engines or tailor-made models. Engines or tools for simulation of urban-scale energy systems have already been overviewed in previous existing literature, however the distinction and classification of tools according to their functionalities within each analysis area in USEM has not been clearly presented. Therefore, the present work aims at reviewing the existing tools while classifying them according to their capabilities. The ultimate goal of this classification is to expose the available resources for implementing new co-simulation approaches in USEM, which may reduce the modelling effort and increase reliability as a result of using established and validated simulation engines. Full article
(This article belongs to the Special Issue Energy Efficiency in Buildings: Both New and Rehabilitated)
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