Energies

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19 pages, 4892 KiB

Open AccessArticle

Drone-Assisted Image Processing Scheme using Frame-Based Location Identification for Crack and Energy Loss Detection in Building Envelopes

by Sukjoon Oh, Suyeon Ham and Seongjin Lee

Energies 2021, 14(19), 6359; https://doi.org/10.3390/en14196359 - 5 Oct 2021

Cited by 14 | Viewed by 3656

Abstract

This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a [...] Read more.

This paper presents improved methods to detect cracks and thermal leakage in building envelopes using unmanned aerial vehicles (UAV) (i.e., drones) with video camcorders and/or infrared cameras. Three widely used contour detectors of Sobel, Laplacian, and Canny algorithms were compared to find a better solution with low computational overhead. Furthermore, a scheme using frame-based location identification was developed to effectively utilize the existing approach by finding the current location of the drone-assisted image frame. The results showed a simplified drone-assisted scheme along with automation, higher accuracy, and better speed while using lower battery energy. Furthermore, this paper found that the cost-effective drone with the attached equipment generated accurate results without using an expensive drone. The new scheme of this paper will contribute to automated anomaly detection, energy auditing, and commissioning for sustainably built environments. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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43 pages, 15285 KiB

Open AccessArticle

Toward the Renewal of the Sustainable Urban Indicators’ System after a Global Health Crisis. Practical Application in Granada, Spain

by Pilar Mercader-Moyano, Ana Mª Estable-Reifs and Homero Pellicer

Energies 2021, 14(19), 6188; https://doi.org/10.3390/en14196188 - 28 Sep 2021

Cited by 1 | Viewed by 2574

Abstract

The aim of this study is to highlight the need for sustainable urban development by reviewing the different Indicator Systems (SI) and contrasting them with those factors that have had a correlation in the spread of the virus in order to detect its [...] Read more.

The aim of this study is to highlight the need for sustainable urban development by reviewing the different Indicator Systems (SI) and contrasting them with those factors that have had a correlation in the spread of the virus in order to detect its deficiencies. This research carries out an urban diagnosis and analyzes the influence of these factors in order to detect deficiencies and propose a new IS adapted to current needs. Lastly, the new SI is validated through its practical application in one of the Autonomous Communities most affected by the pandemic in Spain. It is concluded that most of the factors causing a worse incidence of the virus are hardly evaluated by the existing IS. The practical analysis shows that there are deficiencies in urban design, resulting in poor environmental quality and urban morphology. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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25 pages, 11243 KiB

Open AccessArticle

HVAC Operation Schemes and Commissioning Process Resolving Stack Effect Problem and Adjusting According to Changes in the Environment: A Case Study in High-Rise Building in South Korea

by Jungyeon Yu, Angie Kim, Sanghwan Bae, Dongwoo Cho and Kee Han Kim

Energies 2021, 14(8), 2299; https://doi.org/10.3390/en14082299 - 19 Apr 2021

Cited by 6 | Viewed by 3084

Abstract

Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we [...] Read more.

Various problems often arise in high-rise buildings during the winter months due to the stack effect. In this study, the high-rise building of interest, located in South Korea, was experiencing constant loud noises in the winter due to the stack effect. Thus, we created a noise level reduction plan by creating a method for pressurizing the high-rise zones of the building according to outdoor conditions. To discover the appropriate pressurization operating modes, we applied a two-year commissioning process to the 50-story building of interest. The 1st- and 47th-floor elevator halls were identified to have the highest noise levels of all other floors. Prior to applying the reduction plan, the maximum noise level on the first floor with the HVAC system turned off was 85 dB(A) and with the HVAC system turned on it was 70 dB(A). Both values exceeded the criteria of 57 dB(A) for a lobby space of a commercial building. In the case of the 47th floor, the maximum noise level with the HVAC system turned off was 58.7 dB(A) and with the HVAC system turned off was 56.0 dB(A), despite the latter having increased airtightness performance and applying preliminary pressurization (i.e., HVAC operation mode 2). These values exceeded the criteria of 48 dB(A) for an elevator hall in a commercial building. Following this initial data, we determined to pressurize the high/mid-rise zones of the building according to the outdoor air temperature and wind velocity conditions, which we categorized into four types (i.e., HVAC operation mode 4). To this effect, the first-floor elevator hall’s maximum noise level was 56.6 dB(A), meeting the criteria, and the 47th-floor elevator hall’s maximum noise level was 49.5 dB(A), still exceeding the criteria but by an insignificant amount. Although the HVAC pressurization operation we utilized resulted in favorable results for the target building A, it may not be as effective in other new high-rise buildings, creating changes to the indoor air environment or to the energy costs in maintaining a building. However, for the purposes of resolving the stack effect, we believe that the commissioning process we took to optimize the HVAC operation that is presented here can be applied to other new and existing high-rise commercial buildings. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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16 pages, 4442 KiB

Open AccessArticle

Assessment of Indoor Air Parameters in Building Equipped with Decentralised Façade Ventilation Device

by Ewa Zender–Świercz

Energies 2021, 14(4), 1176; https://doi.org/10.3390/en14041176 - 22 Feb 2021

Cited by 13 | Viewed by 2059

Abstract

The study contains an analysis of a decentralised unit installed in a building façade, where air supply and exhaust cycles are swapped by proper positioning of dampers. The analysis was carried out in real conditions in an office building. The Computational Fluid Dynamics [...] Read more.

The study contains an analysis of a decentralised unit installed in a building façade, where air supply and exhaust cycles are swapped by proper positioning of dampers. The analysis was carried out in real conditions in an office building. The Computational Fluid Dynamics (CFD) simulation is an important element of the system design, and has become more and more widely used. Simulation of the analysed unit has shown air stream distribution in a room. Moreover, it allowed for determination of indoor air temperature. Completed analysis and CFD simulations allow for the observation that façade ventilation systems provide a good way to improve the indoor microclimate, as they effectively reduce air pollution. The decentralised façade ventilation unit reduced the carbon dioxide concentration to a level lower than 1000 ppm and maintained the indoor air temperature in the range of 19.5–22 °C. The error for CFD simulation equals 0.5%, which is not much. The results of research and analysis show that the highest reduction of carbon dioxide concentration occurred when supply/exhaust time equalled 10 min. At the same time, when supply/exhaust time equalled 10 min, the indoor air temperature was the lowest of the recorded values. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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21 pages, 8514 KiB

Open AccessArticle

Estimation of Self-Sufficiency Rate in Detached Houses Using Home Energy Management System Data

by Masato Oota, Yumiko Iwafune and Ryozo Ooka

Energies 2021, 14(4), 975; https://doi.org/10.3390/en14040975 - 12 Feb 2021

Cited by 6 | Viewed by 2380

Abstract

Japan’s energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household [...] Read more.

Japan’s energy consumption in 2018 was about 2.5 times that in 1975, with the increase in the household sector being the largest at 28%. Most of primary energy is still fossil fuel, and it is urgent to reduce energy consumption in the household sector. The purpose of this paper was to identify ways to reduce household energy consumption without compromising the quality of life in residence. However, the reduction methods vary by region, building specifications, household type, equipment specifications, season, and weather. The value of this paper is based on a systematic analysis of home energy management systems (HEMS) data from about 50,000 households under various conditions. We are analyzing ways to reduce energy consumption. Few studies have analyzed this much back-up data, which is likely to lead to a reduction in CO₂ emissions across the household sector. To explore ways to reduce energy consumption in this sector, the company has introduced and provided services for home energy management systems (HEMS) since 2011 and is currently collecting HEMS data for up to 50,000 households. In order to grasp the actual state of energy consumption in each household, HEMS data are systematically analyzed, necessary conditions for energy reduction and self-sufficiency rate (SSR) improvement are analyzed, and energy consumption under certain conditions is estimated using storage batteries (SB) and heat pump water heaters (HPWH). In addition, energy consumption was investigated by actual measurement and simulation for several hundred households. Since power generation and consumption vary greatly depending on the region, building specifications, household type, equipment specifications, season, weather, etc., it is necessary to analyze these factors systematically. As a conclusion, in order to improve SSR, it is necessary to (1) reduce surplus power consumption and energy consumption of heat pump water heaters (HPWHs), (2) increase solar power generation, and (3) increase the size of SB. This study contributes to the spread of advanced housing and the reduction of CO₂ emissions in the household sector. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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17 pages, 4940 KiB

Open AccessArticle

Proposition of Design Capacity of Borehole Heat Exchangers for Use in the Schematic-Design Stage

by Seung-Min Lee, Seung-Hoon Park, Yong-Sung Jang and Eui-Jong Kim

Energies 2021, 14(4), 822; https://doi.org/10.3390/en14040822 - 4 Feb 2021

Cited by 8 | Viewed by 2274

Abstract

This study proposes a simple ground heat exchanger design capacity that is applicable in the schematic-design stage for several configurations used for borehole heat exchangers (BHEs). Three configurations—single, compact, and irregular types—were selected, and the heat transfer rate per unit BHE was calculated [...] Read more.

This study proposes a simple ground heat exchanger design capacity that is applicable in the schematic-design stage for several configurations used for borehole heat exchangers (BHEs). Three configurations—single, compact, and irregular types—were selected, and the heat transfer rate per unit BHE was calculated considering heat interference. In a case study with a typical configuration and general range of ground thermal conductivity, the BHE heat transfer rate of the compact configuration decreased owing to heat interference as the number of BHEs increased. However, with respect to the irregular configuration, the heat transfer rate increased as the same number increased. This was attributed to the relatively large increment rate of the distance between the boreholes in the irregular configurations, making the heat recovery factor more dominant than the heat interference. The results show that the average heat transfer rate values per BHE applicable to each configuration type in the schematic-design stage were 12.1 kW for the single configuration, 5.8 kW for the compact type, and 10.3 kW for the irregular configuration. However, owing to the large range of results for each case study, the error needs to be reduced by maximally utilizing the information available at the schematic-design stage. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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26 pages, 2868 KiB

Open AccessArticle

Examining the Journey of a Pay-as-You-Go Solar Home System Customer: A Case Study of Rwanda

by Vivien Kizilcec, Priti Parikh and Iwona Bisaga

Energies 2021, 14(2), 330; https://doi.org/10.3390/en14020330 - 8 Jan 2021

Cited by 17 | Viewed by 4497

Abstract

Solar home systems (SHSs) are successfully addressing energy access deficits across the globe, particularly when combined with pay-as-you-go (PAYG) payment models, allowing households to pay for energy services in small instalments. To increase energy access, it is vital to understand the PAYG SHS [...] Read more.

Solar home systems (SHSs) are successfully addressing energy access deficits across the globe, particularly when combined with pay-as-you-go (PAYG) payment models, allowing households to pay for energy services in small instalments. To increase energy access, it is vital to understand the PAYG SHS customer journey in depth. To aid this, the paper presents unique data from active customers, consisting of structured interviews (n = 100) and two focus groups (n = 24) across two districts in Rwanda. These results are presented under a novel customer journey framework, which describes all the individual stages a customer might experience, including awareness and understanding, purchase, usage, upgrade, recommendation and retaining or switching energy source. The paper reveals that the customer journey is non-linear and cyclical in nature, acknowledging that a household operates in a social network within which they could influence or be influenced by others. It also highlights the growing importance of SHS recommendations in raising awareness of SHSs, pointing to the shifts in the off-grid energy market environment where customer awareness no longer appears to be a main adoption barrier. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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16 pages, 5766 KiB

Open AccessArticle

Next-Day Prediction of Hourly Solar Irradiance Using Local Weather Forecasts and LSTM Trained with Non-Local Data

by Byung-ki Jeon and Eui-Jong Kim

Energies 2020, 13(20), 5258; https://doi.org/10.3390/en13205258 - 10 Oct 2020

Cited by 45 | Viewed by 3596

Abstract

Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation [...] Read more.

Solar irradiance prediction is significant for maximizing energy-saving effects in the predictive control of buildings. Several models for solar irradiance prediction have been developed; however, they require the collection of weather data over a long period in the predicted target region or evaluation of various weather data in real time. In this study, a long short-term memory algorithm–based model is proposed using limited input data and data from other regions. The proposed model can predict solar irradiance using next-day weather forecasts by the Korea Meteorological Administration and daily solar irradiance, and it is possible to build a model with one-time learning using national and international data. The model developed in this study showed excellent predictive performance with a coefficient of variation of the root mean square error of 12% per year even if the learning and forecast regions were different, assuming that the weather forecast was correct. Full article

(This article belongs to the Special Issue Energy-Saving, Comfort, and Healthier Strategies for Smart Buildings)

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