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Applications of Sustainable Energy Technologies and Energy Saving Technologies in Buildings

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: 20 May 2026 | Viewed by 1158

Special Issue Editors

Dr. Evangelos Bellos

E-Mail Website
Guest Editor
Department of Mechanical Engineering, School of Engineering, University of West Attica, 250 Thivon & Petrou Ralli, 12244 Athens, Greece
Interests: energy in buildings; solar thermal collectors; thermodynamics; heat pumps; organic Rankine cycle; numerical simulations
Special Issues, Collections and Topics in MDPI journals
Dr. Georgios Mitsopoulos

E-Mail Website
Guest Editor
School of Mechanical Engineering, National Technical University of Athens, 9 Heroon Polytechniou Str. 15772 Zografou, Athens, Greece
Interests: energy in buildings; refrigeration; dynamic simulation; energy modeling; heat pumps; building envelope; energy savings

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the development, implementation, and analysis of innovative sustainable energy technologies and energy-saving solutions for buildings. With the pressing need to mitigate climate change and enhance energy efficiency, the building sector plays a pivotal role in advancing sustainable practices.

This Special Issue will publish high-quality, original research papers in the following scientific areas:

  • Renewable energy integration in buildings (e.g., solar thermal, solar PV, wind, and geothermal systems).
  • Advanced energy-efficient materials and construction technologies (e.g., phase change materials, cooling coatings, and thermochromic dyes).
  • Highly efficient and novel energy systems for buildings (advanced heat pumps, cogeneration systems, etc.)
  • Smart building systems and IoT applications for energy management aiming for sustainable performance.
  • Novel dynamic modeling techniques in buildings for sustainable design.
  • Economic and environmental analysis of sustainable building technologies.
  • Case studies showcasing successful implementations of energy-saving strategies in buildings.

Dr. Evangelos Bellos
Dr. Georgios Mitsopoulos
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 submissions that pass pre-check are 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. Applied Sciences 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 2400 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 savings
  • dynamic simulation
  • positive buildings
  • sustainability
  • sustainable materials
  • renewable energy sources
  • solar thermal collectors
  • photovoltaics
  • heat pumps

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

31 pages, 8374 KB  
Article
Distributed Photovoltaic Short-Term Power Forecasting Based on Seasonal Causal Correlation Analysis
by Zhong Wang, Mao Yang, Jianfeng Che, Wei Xu, Wei He and Kang Wu
Appl. Sci. 2025, 15(20), 11063; https://doi.org/10.3390/app152011063 - 15 Oct 2025
Abstract
In recent years, with the development of distributed photovoltaic (PV) systems, their impact on power grids has become increasingly significant. However, the complexity of meteorological variations makes the prediction of distributed PV power challenging and often ineffective. This study proposes a short-term power [...] Read more.
In recent years, with the development of distributed photovoltaic (PV) systems, their impact on power grids has become increasingly significant. However, the complexity of meteorological variations makes the prediction of distributed PV power challenging and often ineffective. This study proposes a short-term power forecasting method for distributed photovoltaics that can identify seasonal characteristics matching weather types, enabling a deeper analysis of complex meteorological changes. First, historical power data is decomposed seasonally using the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Next, each component is reconstructed based on a characteristic similarity approach, and a two-stage feature selection process is applied to identify the most relevant features for reconstruction, addressing the issue of nonlinear variable selection. A CNN-LSTM-KAN model with multi-dimensional spatial representation is then proposed to model different weather types obtained by the K-shape clustering method, enabling the segmentation of weather processes. Finally, the proposed method is applied to a case study of distributed PV users in a certain province for short-term power prediction. The results indicate that, compared to traditional methods, the average RMSE decreases by 8.93%, the average MAE decreases by 4.82%, and the R2 increases by 9.17%, demonstrating the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Applications of Sustainable Energy Technologies and Energy Saving Technologies in Buildings)
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26 pages, 4124 KB  
Article
Assessment of City-Scale Rooftop Photovoltaic Integration and Urban Energy Autonomy Across Europe
by Georgios Mitsopoulos, Vasileios Kapsalis and Athanasios Tolis
Appl. Sci. 2025, 15(20), 10950; https://doi.org/10.3390/app152010950 - 12 Oct 2025
Viewed by 190
Abstract
This study suggests a newly developed model for estimating city-scale photovoltaic rooftop energy potential. This model aims to provide reasonable universal calculations regarding a city’s available space for mounting rooftop photovoltaic systems and their corresponding annual electricity production capacity. For the development of [...] Read more.
This study suggests a newly developed model for estimating city-scale photovoltaic rooftop energy potential. This model aims to provide reasonable universal calculations regarding a city’s available space for mounting rooftop photovoltaic systems and their corresponding annual electricity production capacity. For the development of the model, a thorough literature review has been conducted, which compiles and presents mathematical expressions and performance coefficients. Necessary geographic and meteorological data have been obtained from European statistical repositories and the PVGIS tool, respectively. The main inputs refer to a city’s basic geographical data, population, total actual area, geographical coordinates, and, by extension, the optimum PV unit installation angle. This analysis presents a simple and accurate model applicable to European cities for assessing rooftop photovoltaic energy potential and suitable rooftop space for PV units. The findings can aid in advancing PV development in urban areas and contribute to creating environmentally neutral cities in the future. The methodology is verified with data retrieved from the Google Environmental Insights Explorer tool, which shows a deviation of 9.72%. According to the computational analysis for 40 European countries, the photovoltaic energy potential is between 12.31 GWh and 8200 GWh. These values correspond to a net available PV space between 0.03 km2 and 31.86 km2. The greatest photovoltaic coverage potential is equal to 117.4% for Patras, Greece, while the lowest is 7.27% for Oslo, Norway. Regarding the avoided greenhouse gas emissions, they are found to vary from 5.8 ktons of CO2-equivalent for Valletta, Malta, and 8109.8 ktons for the city of London, United Kingdom. Finally, the final results of 86 additional cities located on the European continent are given. Full article
(This article belongs to the Special Issue Applications of Sustainable Energy Technologies and Energy Saving Technologies in Buildings)
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25 pages, 3358 KB  
Article
A Method for Assessing the Selection of a Photovoltaic System for a Building’s Energy Needs Based on Unsupervised Clustering
by Arkadiusz Małek, Jacek Caban, Michalina Gryniewicz-Jaworska, Andrzej Marciniak and Tomasz Bednarczyk
Appl. Sci. 2025, 15(16), 9062; https://doi.org/10.3390/app15169062 - 17 Aug 2025
Viewed by 615
Abstract
Smart Grid, integrating modern information and communication technologies with traditional power infrastructure, is already widely used in many countries around the world. Its domain is generating large amounts of energy and, at the same time, measuring data from various sources, especially Renewable Energy [...] Read more.
Smart Grid, integrating modern information and communication technologies with traditional power infrastructure, is already widely used in many countries around the world. Its domain is generating large amounts of energy and, at the same time, measuring data from various sources, especially Renewable Energy Sources. Acquiring measurement data from generators and power receivers requires appropriate infrastructure and tools. An even greater challenge is the effective processing of measurement data in order to obtain information helpful in energy management in Smart Grid. The article will present an effective method of acquiring and processing measurement data from a photovoltaic system with a peak power of 50 kWp supplying the administrative building of the university. Unsupervised clustering will be used to create signatures of both generated and consumed power. Analysis of the relationships between measured network parameters in the three-state space allows for a quick determination of the power generated by the photovoltaic system and the power needed to power the building. The applied approach can have a wide practical application, both in Energy Management in institutional buildings. It can also be successfully used to train AI algorithms to categorize operating states in Smart Grid. The traditional and AI-assisted algorithms used by the authors are used to obtain practical information about the operation of Smart Grid. Such expert-validated knowledge is highly desirable in Advanced Process Control, which aims to optimize processes in real time. Full article
(This article belongs to the Special Issue Applications of Sustainable Energy Technologies and Energy Saving Technologies in Buildings)
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