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

Deadline for manuscript submissions: closed (15 February 2021) | Viewed by 48657

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Special Issue Editors

Dr. Benedetto Nastasi

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Guest Editor

Department of Planning, Design & Technology of Architecture, Sapienza University of Rome, Via Flaminia 72, 00196 Rome, Italy
Interests: building physics; building services engineering; building simulation; renewable energy technologies; indoor environmental quality; open data & energy analytics; energy efficiency; zero energy buildings; power-to-X solutions; buildings, district and national energy systems
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Dr. Massimiliano Manfren

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Guest Editor

Faculty of Engineering and the Environment, University of Southampton, Highfield, Southampton SO17 1BJ, UK
Interests: building physics; building services engineering; renewable energy technologies; data mining; operation research; analytics; sustainability transitions; energy transitions; open data; open science
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Dr. Michel Noussan

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Guest Editor

Future Energy Program (FEP), Fondazione Eni Enrico Mattei, Corso Magenta 63, 20123 Milan, Italy
Interests: energy systems; transport; renewable energy sources; data analysis; open data; energy statistics; decarbonization; digitalization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the Special Issue “Open Data and Energy Analytics”, also published as an e-book, we invite you to contribute to this second Special Issue focussed on Open Data and Models for Energy and Environment.

Cutting-edge solutions provided by Research and Development funded by the European and International Framework are of interest for this editorial initiative.

Energy engineers and planners must provide the simplest and most robust tools to collect, process, and analyse data in order to offer solid data-based evidence for future projections in building, district and regional system planning.

This Special Issue aims at providing recent advancements on open data and models. Energy and Environment are the fields of applications.

For all the aforementioned reasons, we encourage researchers and professionals to share their original works. Topics of primary interest include but are not limited to:

Open data and models for energy sustainability;
Open data science and environment applications;
Open science and open governance for Sustainable Development Goals;
Key performance indicators of data-aware energy modelling, planning and policy;
Energy, water and sustainability database for building, district and regional systems;
Best practices and case studies.

Dr. Benedetto Nastasi
Dr. Massimiliano Manfren
Dr. Michel Noussan
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. 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 2600 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.

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Published Papers (11 papers)

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Editorial

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2 pages, 157 KiB

Open AccessEditorial

Open Data and Models for Energy and Environment

by Benedetto Nastasi, Massimiliano Manfren and Michel Noussan

Energies 2021, 14(15), 4413; https://doi.org/10.3390/en14154413 - 22 Jul 2021

Cited by 3 | Viewed by 1583

Abstract

An increasing number of data sources and models to handle them call for transparency and openness in assessing their goodness and practical use for people [...] Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

Research

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25 pages, 68601 KiB

Open AccessArticle

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

by Sofia Agostinelli, Fabrizio Cumo, Giambattista Guidi and Claudio Tomazzoli

Energies 2021, 14(8), 2338; https://doi.org/10.3390/en14082338 - 20 Apr 2021

Cited by 125 | Viewed by 10466

Abstract

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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32 pages, 62895 KiB

Open AccessArticle

Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

by Kristian Skeie and Arild Gustavsen

Energies 2021, 14(4), 802; https://doi.org/10.3390/en14040802 - 3 Feb 2021

Cited by 5 | Viewed by 2720

Abstract

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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23 pages, 1005 KiB

Open AccessArticle

The Use of Energy Models in Local Heating Transition Decision Making: Insights from Ten Municipalities in The Netherlands

by Birgit A. Henrich, Thomas Hoppe, Devin Diran and Zofia Lukszo

Energies 2021, 14(2), 423; https://doi.org/10.3390/en14020423 - 14 Jan 2021

Cited by 13 | Viewed by 3233

Abstract

In 2018, the Dutch national government announced its decision to end natural gas extraction. This decision posed a challenge for local governments (municipalities); they have to organise a heat supply that is natural gas-free. Energy models can decrease the complexity of this challenge, but some challenges hinder their effective use in decision-making. The main research question of this paper is: What are the perceived advantages and limitations of energy models used by municipalities within their data-driven decision-making process concerning the natural-gas free heating transition? To answer this question, literature on energy models, data-driven policy design and modelling practices were reviewed, and based on this, nine propositions were formulated. The propositions were tested by reflecting on data from case studies of ten municipalities, including 21 experts interviews. Results show that all municipalities investigated, use or are planning to use modelling studies to develop planning documents of their own, and that more than half of the municipalities use modelling studies at some point in their local heating projects. Perceived advantages of using energy models were that the modelling process provides perspective for action, financial and socio-economic insights, transparency and legitimacy and means to start useful discussions. Perceived limitations include that models and modelling results were considered too abstract for analysis of local circumstances, not user-friendly and highly complex. All municipalities using modelling studies were found to hire external expertise, indicating that the knowledge and skill level that municipal officials have is insufficient to model independently. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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28 pages, 8358 KiB

Open AccessArticle

A Data Analytics-Based Energy Information System (EIS) Tool to Perform Meter-Level Anomaly Detection and Diagnosis in Buildings

by Roberto Chiosa, Marco Savino Piscitelli and Alfonso Capozzoli

Energies 2021, 14(1), 237; https://doi.org/10.3390/en14010237 - 5 Jan 2021

Cited by 25 | Viewed by 4510

Abstract

Recently, the spread of smart metering infrastructures has enabled the easier collection of building-related data. It has been proven that a proper analysis of such data can bring significant benefits for the characterization of building performance and spotting valuable saving opportunities. More and more researchers worldwide are focused on the development of more robust frameworks of analysis capable of extracting from meter-level data useful information to enhance the process of energy management in buildings, for instance, by detecting inefficiencies or anomalous energy behavior during operation. This paper proposes an innovative anomaly detection and diagnosis (ADD) methodology to automatically detect at whole-building meter level anomalous energy consumption and then perform a diagnosis on the sub-loads responsible for anomalous patterns. The process consists of multiple steps combining data analytics techniques. A set of evolutionary classification trees is developed to discover frequent and infrequent aggregated energy patterns, properly transformed through an adaptive symbolic aggregate approximation (aSAX) process. Then a post-mining analysis based on association rule mining (ARM) is performed to discover the main sub-loads which mostly affect the anomaly detected at the whole-building level. The methodology is developed and tested on monitored data of a medium voltage/low voltage (MV/LV) transformation cabin of a university campus. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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23 pages, 1320 KiB

Open AccessArticle

A Parametric Study of Wave Energy Converter Layouts in Real Wave Models

by Erfan Amini, Danial Golbaz, Fereidoun Amini, Meysam Majidi Nezhad, Mehdi Neshat and Davide Astiaso Garcia

Energies 2020, 13(22), 6095; https://doi.org/10.3390/en13226095 - 20 Nov 2020

Cited by 22 | Viewed by 3228

Abstract

Ocean wave energy is a broadly accessible renewable energy source; however, it is not fully developed. Further studies on wave energy converter (WEC) technologies are required in order to achieve more commercial developments. In this study, four CETO6 spherical WEC arrangements have been investigated, in which a fully submerged spherical converter is modelled. The numerical model is applied using linear potential theory, frequency-domain analysis, and irregular wave scenario. We investigate a parametric study of the distance influence between WECs and the effect of rotation regarding significant wave direction in each arrangement compared to the pre-defined layout. Moreover, we perform a numerical landscape analysis using a grid search technique to validate the best-found power output of the layout in real wave models of four locations on the southern Australian coast. The results specify the prominent role of the distance between WECs, along with the relative angle of the layout to dominant wave direction, in harnessing more power from the waves. Furthermore, it is observed that a rise in the number of WECs contributed to an increase in the optimum distance between converters. Consequently, the maximum exploited power from each buoy array has been found, indicating the optimum values of the distance between buoys in different real wave scenarios and the relative angle of the designed layout with respect to the dominant in-site wave direction. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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11 pages, 2517 KiB

Open AccessArticle

Numerical Simulation and Experimental Validation of an Oil Free Scroll Compressor

by Massimo Cardone and Bonaventura Gargiulo

Energies 2020, 13(22), 5863; https://doi.org/10.3390/en13225863 - 10 Nov 2020

Cited by 11 | Viewed by 3016

Abstract

This paper presents a virtual model of a scroll compressor developed on the one-dimensional analysis software Simcenter Amesim^®. The model is semi-empirical: it needs some physical details of the modelled machine (e.g., the cubic capacity), but, on the other hand, it does not require the geometrical features of the spirals, so it needs experimental data to calibrate it. The model also requires rotational speed and the outlet temperature as boundary conditions. The model predicts the power consumption and the mass flow rate and considers leakages and mechanical losses. After the model presentation, this paper describes the test bench and the obtained data used to calibrate and validate the model. At last, the calibration process is described, and the results are discussed. The calculated values fit the experimental data also in extrapolation, despite the model is simple and performs calculations within 7 s. Due to these characteristics, the model is suitable for being used in a larger model as a sub-component. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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23 pages, 2231 KiB

Open AccessArticle

A New Bi-Level Optimisation Framework for Optimising a Multi-Mode Wave Energy Converter Design: A Case Study for the Marettimo Island, Mediterranean Sea

by Mehdi Neshat, Nataliia Y. Sergiienko, Erfan Amini, Meysam Majidi Nezhad, Davide Astiaso Garcia, Bradley Alexander and Markus Wagner

Energies 2020, 13(20), 5498; https://doi.org/10.3390/en13205498 - 20 Oct 2020

Cited by 22 | Viewed by 3752

Abstract

To advance commercialisation of ocean wave energy and for the technology to become competitive with other sources of renewable energy, the cost of wave energy harvesting should be significantly reduced. The Mediterranean Sea is a region with a relatively low wave energy potential, but due to the absence of extreme waves, can be considered at the initial stage of the prototype development as a proof of concept. In this study, we focus on the optimisation of a multi-mode wave energy converter inspired by the CETO system to be tested in the west of Sicily, Italy. We develop a computationally efficient spectral-domain model that fully captures the nonlinear dynamics of a wave energy converter (WEC). We consider two different objective functions for the purpose of optimising a WEC: (1) maximise the annual average power output (with no concern for WEC cost), and (2) minimise the levelised cost of energy (LCoE). We develop a new bi-level optimisation framework to simultaneously optimise the WEC geometry, tether angles and power take-off (PTO) parameters. In the upper-level of this bi-level process, all WEC parameters are optimised using a state-of-the-art self-adaptive differential evolution method as a global optimisation technique. At the lower-level, we apply a local downhill search method to optimise the geometry and tether angles settings in two independent steps. We evaluate and compare the performance of the new bi-level optimisation framework with seven well-known evolutionary and swarm optimisation methods using the same computational budget. The simulation results demonstrate that the bi-level method converges faster than other methods to a better configuration in terms of both absorbed power and the levelised cost of energy. The optimisation results confirm that if we focus on minimising the produced energy cost at the given location, the best-found WEC dimension is that of a small WEC with a radius of 5 m and height of 2 m. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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22 pages, 5368 KiB

Open AccessArticle

Multi-Objective Optimization Model EPLANopt for Energy Transition Analysis and Comparison with Climate-Change Scenarios

by Matteo Giacomo Prina, Giampaolo Manzolini, David Moser, Roberto Vaccaro and Wolfram Sparber

Energies 2020, 13(12), 3255; https://doi.org/10.3390/en13123255 - 23 Jun 2020

Cited by 31 | Viewed by 4121

Abstract

The modeling of energy systems with high penetration of renewables is becoming more relevant due to environmental and security issues. Researchers need to support policy makers in the development of energy policies through results from simulating tools able to guide them. The EPLANopt model couples a multi-objective evolutionary algorithm to EnergyPLAN simulation software to study the future best energy mix. In this study, EPLANopt is applied at country level to the Italian case study to assess the best configurations of the energy system in 2030. A scenario, the result of the optimization, is selected and compared to the Italian integrated energy and climate action plan scenario. It allows a further reduction of CO₂ emissions equal to 10% at the same annual costs of the Italian integrated energy and climate action plan scenario. Both these results are then compared to climate change scenarios through the carbon budget indicator. This comparison shows the difficulties to meet the Paris Agreement target of limiting the temperature increase to 1.5 °C. The results also show that this target can only be met through an increase in the total annual costs in the order of 25% with respect to the integrated energy and climate action plan scenario. However, the study also shows how the shift in expenditure from fossil fuels, external expenses, to investment on the national territory represents an opportunity to enhance the national economy. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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14 pages, 613 KiB

Open AccessArticle

Cross-Country Comparison of Hourly Electricity Mixes for EV Charging Profiles

by Michel Noussan and Francesco Neirotti

Energies 2020, 13(10), 2527; https://doi.org/10.3390/en13102527 - 16 May 2020

Cited by 18 | Viewed by 4554

Abstract

Electric vehicles, when coupled to electricity generation from renewable energy sources, can become a viable solution to decarbonize the transport sector. However, given the high variability of electricity mixes on a daily and seasonal basis, high-resolution profiles are needed for a precise analysis of the impacts of electric vehicles in terms of greenhouse gases emissions. This paper presents a comparison of different charging profiles evaluated on 10 European countries over four years, to highlight the effects of national electricity mixes and of the type of charging location on the specific emissions of EVs charging. This study, based on three archetypal charging profiles, provide a quantification of the potential influence of different charging strategies on the average emission factor of the electricity supplied to electric vehicles. The results show that the variability related to charging profiles is generally limited, with an average variation range of 6% for any given country and year, while in several countries the variability from one year to another is much larger, with an average range of 18% for any given country and charging profile. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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Review

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29 pages, 1877 KiB

Open AccessReview

Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector

by Massimiliano Manfren, Maurizio Sibilla and Lamberto Tronchin

Energies 2021, 14(3), 679; https://doi.org/10.3390/en14030679 - 28 Jan 2021

Cited by 44 | Viewed by 5723

Abstract

Decarbonisation and efficiency goals set as a response to global warming issue require appropriate decision-making strategies to promote an effective and timely change in energy systems. Conceptualization of change is a relevant part of energy transitions research today, which aims at enabling radical shifts compatible with societal functions and market mechanisms. In this framework, construction sector can play a relevant role because of its energy and environmental impact. There is, however, the need to move from general instances to specific actions. Open data and open science, digitalization and building data interoperability, together with innovative business models could represent enabling factors to accelerate the process of change. For this reason, built environment research has to address the co-evolution of technologies and human behaviour and the analytical methods used for this purpose should be empirically grounded, transparent, scalable and consistent across different temporal/spatial scales of analysis. These features could potentially enable the emergence of “ecosystems” of applications that, in turn, could translate into projects, products and services for energy transitions in the built environment, proposing innovative business models that can stimulate market competitiveness. For these reasons, in this paper we organize our analysis according to three levels, from general concepts to specific issues. In the first level, we consider the role of building energy modelling at multiple scales. In the second level, we focus on harmonization of methods for energy performance analysis. Finally, in the third level, we consider emerging concepts such as energy flexibility and occupant-centric energy modelling, considering their relation to monitoring systems and automation. The goal of this research is to evaluate the current state of the art and identify key concepts that can encourage further research, addressing both human and technological factors that influence energy performance of buildings. Full article

(This article belongs to the Special Issue Open Data and Models for Energy and Environment)

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