Shading calculation methods and regulation simplifications - the Portuguese case

Citation: Oliveira, M.F.; Mendonça, P.; Tenpierik, M.; Santiago, P.; Silva, J.F.; Silva, L.T. Shading Calculation Methods and Regulation Simplifications—The Portuguese Case. Buildings 2023,13, 1521. https://doi.org/10.3390/ buildings13061521 Academic Editor: Antonio Caggiano Received: 26 April 2023 Revised: 22 May 2023 Accepted: 30 May 2023 Published: 13 June 2023 Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). buildings Review Shading Calculation Methods and Regulation Simplifications—The Portuguese Case Marta Fernandes Oliveira 1, Paulo Mendonça 2,*, Martin Tenpierik 3, Pedro Santiago 4, JoséF. Silva 5 and Lígia Torres Silva 1 1CTAC Research Centre, Engineering School, University of Minho, 4800-058 Guimarães, Portugal; [email protected] (M.F.O.); [email protected] (L.T.S.) 2Lab2Pt Research Centre, School of Architecture, Art and Design, University of Minho, 4800-058 Guimarães, Portugal 3Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands; [email protected] 4Department of Architecture and Urbanism, Fernando Pessoa University, 4249-004 Porto, Portugal; [email protected] 5PROMETEUS Research Centre, School of Technology and Management, Polytechnic Institute of Viana do Castelo, 4900-348 Viana do Castelo, Portugal; [email protected] *Correspondence: [email protected] Abstract: How to analyse the omissions of thermal regulations and evaluate methodologies that provide building execution or thermal certificates that do not correspond to reality and usually incur costs? We can start by analysing different simulation methods and shading calculations that provide solar gains and shadow optimisation. After evaluating how the regulations define the calculation assumptions and how this calculation is performed, the discrepancies (simplifications) that the regulations allow or ignore are presented, and it is exemplified using two case studies. Using the Portuguese regulation as a case study, it leads to incorrect conclusions or assumptions due to unequal access to solar radiation or the shading factor calculation that experiences the omission of angles or time periods. Therefore, the aim is to propose a calculation process (premises) that minimises the discrepancies between simulation (optimisation strategy) and reality (applicability of strategies) for sustainable output. Keywords: solar shading; political-legislative premises; shading calculation methods; solar benefits; sustainable city; ineffective enforcement of regulations; process innovation 1. Introduction One of the “Goals of the United Nations 2030 Agenda for Sustainable Development” is to ensure access to affordable, reliable, sustainable and modern energy for all (SDG7) [ 1 ]. Reducing the energy demand of buildings and prioritising urban forms that reconcile energy gains simultaneously with building/energy regulations could be one solution to achieve the goal. The European Union applies a methodology to calculate the energy performance of buildings according to the common general framework determined in Annex I of the European Directive 2010/31/EU, which determines the rules regarding the formulation of the calculation used to determine the energy performance of buildings. The implementation of the Energy Performance of Buildings Directive (EPBD) aims to develop a common strategy towards achieving nearly zero-energy buildings (NzEB) from 2020 onwards [2,3]. The purpose of this article is to provide an overview of the available literature, namely case studies that simulate or measure solar shading. This overview intends to promote future research, and considering this aim, the proposed methodology is a survey of the Global and European context but uses the practical case of Portugal. Buildings 2023,13, 1521. https://doi.org/10.3390/buildings13061521 https://www.mdpi.com/journal/buildings Buildings 2023,13, 1521 2 of 19 This study is based on the findings of a scoping literature review, which is useful for mapping the scope of information published on a given scientific topic to examine and identify knowledge gaps. In this situation, resolving knowledge gaps or performing more extensive assessments of narrower selections of papers might be appropriate. 1.1. Selecting Shadow Case Studies The objective of an investigation based on a case study focuses on exploring a theory that is intended to be put into practice or to simulate reality or a context. The importance of case studies lies in presenting proposals, detecting problems, needs and/or opportunities to correct or learn new methods so as to apply theories in practical cases. The validation of the exploration goes through the rigor and exact transposition of the theoretical proposal to a practical environment [4]. Reflecting on the various types of case study design, this technique can help answer specific research questions [ 5 – 9 ]. The chosen studies were selected and listed from the Scopus database using the following criteria: shadow studies with an experimental or practical component, facade shading calculations, omitting research exclusively focusing on rooftops or with photovoltaics interest. Table 1displays the chosen examples of shadow studies. Table 1. Shadow case studies. Context Year Case Study Objective Topics Global 1984 Ryerson [10]Compares if computed shadows and shadows measured from aerial photography are reliable and accurate during the mapping procedure. 1996 Belakehal [11] Maximises the shading on the facade by optimising its components, using experimental aesthetic facade components to control solar radiation as the energy-related function and the aesthetical expression of its design. 1996 Al-Sallal [12]Investigates the geometrical relationships between the building form and the sun’s location and motion at critical times of the year. 2000 Belakehal [13]Classifies optimal variants of the facade that can provide recommendations for a shading strategy optimisation according to solar orientation. 2003 Capeluto [14] The model allows for the generation of the building shape in a way that the building facades are self-shaded during a required period determined by the designer. 2004 Bourbia [15] Study indicates that street canyon orientation (and not only the H/W ratio) has a considerable effect on solar shading and urban microclimate. Solar access to streets can always be decreased by increasing H/W to larger values. 2010 Chua [16] Demonstrated how the design of shading devices and the selection of glazing type impact the cooling load of high-rise residential buildings. Comparing results from the model simulations, the half egg-crate louver was found to be the most suitable shading device for residential buildings facing the north and south orientations. 2011 Hayman [17] Study about solar access and overshadowing of public and private open space in urban areas as the density and the height of buildings increase. All methods of analysis require a knowledge of the relative position of the sun. 2014 Grynning [18] Solar shading systems are vital to reduce the cooling demand of an office, and the simulations show that the choice of shading strategy can have an impact on the energy. 2015 Shukla [19] Studies solar access and overshadowing of public and private open space in urban areas as the density and the height of buildings increase. Detect limited periods of the day and small differences between the real and nominal location that could result in a proposed development application being denied. 2015 Aksamija [20]Controls the physical environmental factors that must be considered during the design process. 2016 Simón-Martín et al. [21] Presentation of various methods of measuring diffuse solar irradiance; shadowing devices are some of the most commonly used in solar research all over the world. 2017 Lee et al. [22] This study explores how the pattern and different characteristics are evaluated by varying facade shading types and considering their impact on daylighting metrics, with changes in the facade shading types, input parameters and azimuth orientations. Buildings 2023,13, 1521 3 of 19 Table 1. Cont. Context Year Case Study Objective Topics 2020 Sari [23] During the early design stage, studies the process and the energy simulation, combining parametric software (Climate Consultant, Rhino/Grasshopper, Honeybee, Ladybug and DIVA) allowing more accuracy to allow a better energy analysis (solar, shade, etc.). 2020 Kimm [24]Study that describes in detail the algorithm which builds on precedents for 2.5D raster calculation of shadows. 2021 Garreau [25] Finds a compromise between the available data, the different modelling, thermal zoning models and solar shading models that analyse data using the same methodology, assessing the modelling parsimony. 2022 Dagher [26] Makes use of shadows to minimise solar transmission and heat gains in extreme weather. A study to reduce solar gains that can be an appropriate method to also improve thermal comfort without compromising the daylight factor. 2022 Wen et al. [27] Understands how buildings can be arranged to maximise the beneficial effect of shading in summer while minimising its adverse effect in winter would support the energy efficiency of urban buildings in different climate conditions (studies in China). 2022 Wen et al. [28] Studies how the different designs of surrounding buildings affect the window-transmitted solar radiation energy (WTSRE) of the target building by performing a parametric study using EnergyPlus and proposes a method that can rapidly assess the shading effect of surrounding buildings at the design stage based on the databases obtained from the parametric study. 2023 Wang et al. [29] Using the existing neighbourhood judgement criterion, shadow calculation methods evaluate its effectiveness in two case studies. Both calculations are accurate and effective and improved when the proposed criterion was integrated. European 1998 Trujillo [30] Evaluates methods to calculate building performance under direct solar radiation and the energetic benefit when two different alternatives of solar protection are applied. 2010 Carneiro, C. et al. [31] Studies urban environment quality (UEQ) using different techniques and proposes a correct definition of indicators (solar, shadow, etc.) related to urban developments. 2016 Grifoni, R.C. et al. [32] A case study that begins by estimating solar radiation and then evaluates useful parameters, such as the sky view factor and shadows. 2017 Kite [33] Chronological framework that reveals the key places and moments where shadows shape architecture in different and dynamic ways. 2017 ValladaresRendón et al. [34] The aim of this research is to establish and recommend the most effective and balanced solutions to decrease insolation and increase energy savings while balancing daylighting and visibility. Four main classes were reviewed: facade self-shading, shading devices, window-to-wall ratio and building orientation. 2017 Vartholomaios [35]Studies strategies of high urban compactness and passive solar design and the synergy that can be achieved at different urban densities. 2020 Alagoz and MBeyhan [36] Lists advantages and disadvantages of different methods aimed to reach an optimum solution by considering the potential to create shadows on the building. 2021 Kanters [37]A study of urban planners working in Swedish municipalities that identifies a baseline, gaps and needs of solar-shadow-energy analysis. Portuguese 2009 Silva [38] Study of the thermal behaviour of a building “case”, subject to different situations, including different orientations, different types of window shading and other components with impact. 2012 Silva and Henriques [39] Studies a new methodology for calculating the shading factor, namely the shading factor for horizontal elements. 2016 Lopes [40]Lists comparative studies of the four calculation methodologies to have a better understanding of the methodological differences. 2016 Ferreira [41] Analyses the differences between the current regulations provided for houses (REH) and the previous regulations (RCCTE) to study what the main changes are in the calculation methodology and energy performance rating. 2016 Costa [42]Evaluates in what way the parameters related to the assessment of heat-energetic performance influence their own performance. Buildings 2023,13, 1521 4 of 19 Table 1. Cont. Context Year Case Study Objective Topics 2017 Carreira [43] Explores procedures to estimate the shadow factor, comparing methods provided in the Portuguese regulation and evaluating their accuracy. 2019 Brito, M. et al. [44] Studies the difficulties in assessing solar potential in urban areas: contiguous or neighbouring buildings not included in the study area cast shadows on the studied buildings; thus, for a large study area, a mosaic of areas with a significant overlap is required to avoid overestimation of incident irradiation. The selected studies explore different methodologies to evaluate shadows, namely using a direct approach or indirect, using surrounding buildings that affect the transmitted solar radiation energy and shadows. 1.2. Selecting Shadow Calculation Methods Evaluation methods [ 27 ] that demonstrate greater or lesser accuracy when calculating the shade factor in buildings have economic consequences on building use, and predictive models are beneficial alternatives when analysing energy performance [45,46]. The intentional integration of shading factors to limit solar gains through windows of glazed facades, considering the thermal needs of the spaces, is one of the most captivating passive techniques. The calculation of the shading factor (Fs) during the heating and cooling seasons is used, and the market has many options that simulate, model and analyse solar shadows. The methodologies used to determine the shade in a given objective vary greatly. The literature search that was conducted classified the techniques into four categories to identify those that have the ability to calculate the shading factor: techniques in a CAD (computer-aided design) environment, methods using a digital elevation model (MDE), on-site obstruction recording devices of obstructions on-site and procedures permitted by Portuguese law are some examples of these methods, compiled in the following table. The self-shaded points, that is, the situations in which it is the facade itself that is shaded, must be taken into account in the methodology and/or software which allows one to dissociate the notions of undifferentiated shading and shading caused by obstructions according to the definition of the shading factor [47]. 1.3. Legislative Requirements Before 1990, in Portugal, there were no thermal requirements in buildings. It was only when Decree-Law no. 40/90 came into force that the first thermal legal instrument was created, namely the Regulation of Thermal Performance Characteristics of Buildings (RCCTE) [48]. In 2002, the European Directive 2002/91/CE was established including the “Energy Performance of Buildings Directive” (EPBD), establishing the minimum requirements for the built environment (new and existing). As the residential sector was responsible for more than 40% of the EU’s final energy consumption, Directive 2002/91/EC indicated that by January 2006, all member states had to implement the regulatory requirements [ 49 ]. The European Union and the member states defined goals concerning the rational use of energy resources through the Kyoto Protocol to reduce carbon dioxide gas emissions into the atmosphere. In 2013, Portugal integrated the REH—Regulations for the Energy Performance of Residential Buildings (former RCCTE) and the RECS—Regulation on the Energy Performance of Commerce and Services Buildings (former RSECE) in a single diploma after publishing Decree-Law no. 118/2013, which ensured not only the transposition of Directive no. 2010/31/EU but also a revision of the national legislation or the promotion of the energy performance of buildings through the Energy Certification System of Buildings (SCE) [ 50 ]. Moreover, Decree-Law No. 71/2022 of 14 October completes the transposition of Directive (EU) 2018/2002, amending provisions on energy efficiency and cogeneration production. Buildings 2023,13, 1521 5 of 19 The harmonisation and updating of national (energy) legislation [ 51 ] aimed not only to comply with European standards but also to promote energy efficiency in buildings, its systematisation and scope of application to reduce thermal losses and increase the quality and durability of the built constructions and its evolution as reflected in the timeline in Figure 1. Buildings 2023, 13, x FOR PEER REVIEW 6 of 21 Figure 1. Chronogram of Thermal Regulation Evolution in Portugal. 2. Methodology The strategy was to identify the research keywords, find relevant studies (specifically solar and shadow studies), select studies (namely shadow calculations) in a certain context (global, European and Portuguese) and then aggregate, summarise and present them in Tables 1 and 2. Figure 1. Chronogram of Thermal Regulation Evolution in Portugal. The system for calculating the shading factor has not changed despite the evolution of thermal regulations in Portugal in the various components, including housing (from the RCCTE to the current REH), services and commerce (from the RSECE to the current RECS) or the Energy Certification System of Buildings (SCE). Using the examples provided below, we will see that the omission of angles, undifferentiation of horizontal obstacles or the interpolations of data and angles have occurred and have an impact on the actual calculation of solar shading and the respective solar optimisation of buildings. 2. Methodology The strategy was to identify the research keywords, find relevant studies (specifically solar and shadow studies), select studies (namely shadow calculations) in a certain context (global, European and Portuguese) and then aggregate, summarise and present them in Tables 1and 2. Buildings 2023,13, 1521 6 of 19 Table 2. Selection of different shadow calculation methods available on the market (adapted: Carreira [43]). Method/Software Calculation Advantages Disadvantages Calculation Typology—CAD (computer-aided design) SOMBRERO [52]Geometric coefficient of shadow Low cost User friendly Does not calculate Fs, by default (quantifies shadow on object) SHADING [53]Geometric coefficient of shadow Low cost User friendly Does not calculate Fs, by default (quantifies shadow on object) ShadowFX [54]Geometric coefficient of shadow Low cost User friendly Does not calculate Fs, by default (quantifies shadow on object) TownScope [55]Radiation maps and shadow duration Calculates several parameters in a single simulation Implementation of auxiliary routines to obtain Fs Sunhours [56]Shading factor (complementary) Easy building (Sketchup extension) Does not calculate Fs, by definition (refers to shading loss) Calculation Typology—MDE (digital elevation models) GOSOL [57]Shadow map Sun diagrams Allows the importation of CAD models Use an MDT Needs routine calculation for Fs Existence of auto-shaded spots SOL [58] Shadow map and global direct and diffuse radiation Uses multidimensional scaling data (MDS) (obstructions already represented) Lacks Fs calculation routine Existence of auto-shaded spots Solar Analyst [59] Sun diagrams, shadow map and global direct and diffuse radiation Uses MDS An extension of ArcGis Needs the algorithm for calculating Fs Non-existence of auto-shaded spots On-site obstruction recording devices SunEye 210 Shade Tool [60]Sun diagrams Portability Easy to use Adaptability High cost Lacks algorithm for calculating Fs Solar Pathfinder [61] Sun path diagram It can be used any time of the day or the year, in either cloudy or clear weather Works on a reflective principle rather than actually showing shadows HORIcatcher [62] Sun diagrams Easy and fast tool Supplied with a digital camera Lacks algorithm for calculating Fs The methodologies defined in Portuguese law Calculation methodologies [63]Shading factor Calculation of Fs, as a function of the specific angles of obstruction and orientation Requires auxiliary tool to calculate the obstruction angles Time-consuming process Simplification rules [63] Shading factor Easy application Fast No auxiliary tools needed May prove inaccurate by including only 3 shading classes Local analysis Other combined methods Envi-met [64]Shadow casting Reflection analysis Calculates several parameters in a single simulation High cost Ladybug [65] Shadow map Sun path diagram Sun diagrams Global direct and diffuse radiation Free Calculates several parameters in a single simulation A plugin for Rhino and Revit Interaction with CAD and BIM Not a stand-alone Needs a definition to calculate The purpose of this study is to investigate the premises and the calculation methods that estimate the solar shading factor, presenting different methodologies, and to compare the findings with the two methods suggested by Portuguese law. Buildings 2023,13, 1521 7 of 19 The approach is also utilised to uncover research generalisations through a thorough and valid strategy for mapping the study area, as well as to discover the measures and characteristics of previous research on the subject. The intention of the article is not to present comparative results of calculations or software but rather, regardless of the software used, to present the assumptions of the calculation that is defined. 2.1. Portuguese Calculation Methodology There are two ways to determine a building’s shading factor according to Portuguese law. The first applies the calculation methodology described in Order (extract) no. 15793K/2013 (Ministry of Economy and Employment, 2013c) based on the current obstruction angles, and the second takes into account the simplification criteria that assign a shade class to each glazed element in accordance with Order (extract) no. 15793-E/2013 [66]. The calculation methodology is the most detailed process in the Portuguese legislation to calculate the shading factor ( Fs ). It presupposes the calculation of the obstruction angles of the existing shading sources. It is not completely necessary to analyse possible obstacles on-site. This approach considers three components of the shading factor, according to Equation (1): Fs=Fh×Fo×Ff(1) where Ff corresponds to the shading factor from vertical elements next to the window, including vertical canopies, other bodies or parts of a building, and Fo represents the shading factor by horizontal elements overlying the window, including canopies and balconies [ 63 ]. Fh is the horizon shading factor by obstructions external to the building, and it is represented in Figure 2. in addition to the horizontal and vertical shading factors. 2.1.1. Horizon Shading Factor As shown in Figure 3, a straight line is drawn between the centre of the window and the highest point of the largest existing obstruction between two vertical planes at 60 degrees to either side of the window based on the calculation of the shading caused by the obstruction in the horizon in the heating season. The current law assumes that the horizon has a value of 1 in all orientations because it ignores the horizon’s contribution to shading in the cooling station [ 66 ]. The horizon angle (Figure 2) is the angle formed by the provided trace and the horizontal plane, and it is determined by Equation (2): α=tan−1hobstr −henvidr ∆x(2) where hobstr is the obstruction elevation(m), henvidr is the window’s centre point elevation (m), and ∆x is the horizontal separation between the obstruction and the window facade (m). The information in Figure 3is used to assign a horizon shading factor after assigning the facade orientation to each value acquired from the previous procedure. The values of the horizon shading factor for eight different azimuths can be seen in Figure 3. If the facade’s orientation differs from those specified, the current value of the nearest orientation is used. The corresponding horizon shading factors are averaged for situations where the facade has an intermediate orientation between two of the azimuths indicated in Figure 3. Buildings 2023,13, 1521 8 of 19 Buildings 2023, 13, x FOR PEER REVIEW 9 of 21 Figure 2. Example of a horizon angle (images and table) (a), horizontal angle overhang (image and table) (b) and vertical (left and right overhang) (c). Values in the tables are for cooling station and in the heating season for Portugal mainland. Adapted from Ministry of Economy and Employment [63]. Figure 2. Example of a horizon angle (images and table) ( a ), horizontal angle overhang (image and table) ( b ) and vertical (left and right overhang) ( c ). Values in the tables are for cooling station and in the heating season for Portugal mainland. Adapted from Ministry of Economy and Employment [ 63 ]. Buildings 2023,13, 1521 9 of 19 In the absence of available information for determining the reference angle, the value of Fh should be estimated by using a default horizon angle of 45 ◦ in the case of urban environments and 20 ◦ in the case of isolated buildings located outside of urban regions. After defining this, the value of the horizon shading factor is derived from Table 15 of Order No. 15793-K/2013, and for horizon angles greater than 45 ◦ , a horizon shading factor equivalent to the 45◦angle is adopted. The shading factor is interpolated to account for the range of values according to Equation (3) , where Fh,in f and Fh,sup represent the shading factor of the inferior and superior bounds of the interpolation interval, respectively, and αsup and αin f correspond to the horizon angles of these same limits. This is done to overcome the limitation mentioned above. Fh =Fh,in f +Fh,sup −Fh,in f αsup −αin f α−αin f (3) 2.1.2. Shading Factor for Horizontal or Vertical Obstruction Similar to the procedure mentioned above, the contributions of the horizontal and vertical elements are estimated as functions of the horizontal ( θ ) and vertical ( β ) blind spot angles, respectively. The angle formed by the plane of the facade and a straight line between the shading source’s tip and the window’s centre is known as the horizontal visor angle or vertical visor angle, respectively [66]. From the previous tables, only three parameters need to be determined by the evaluator at the site: the desired season (summer or winter), the orientation of the glazed facade and the angles between the centre of the glazing and the edge of the overhangs (horizontal θ or vertical β ), that is, to determine whether the overhang’s length (or the height of the obstacle) is greater or less than the distance from the obstacle to the facade under study. It is now simpler to compute the shade factor in buildings due to this short assessment that streamlines the entire procedure described in the previous point [67]. The shading factor by horizontal elements is one of many factors taken into account by the current regulation, which recommends an approach for estimating the solar benefits achieved through the glazed regions. The values of the shading factor are given in Figure 3 by the current regulation for this purpose. The angle is the intersection of two planes: the plane containing the wall’s outside surface and the plane enclosed by the midline and end of the horizontal shading element. The factor’s value, which ranges from 0 to 1, shows how much solar radiation actually enters the glazed facade as opposed to how much would fall in the absence of the horizontal shade. It can be deduced that the higher the horizon angle, as well as the obstruction angles for horizontal and vertical elements, the lower the values of Fh , Fo and Ff and, consequently, the lower the value of the obstruction factor Fs[41,42]. It is essential to strive to maximise these advantages during the winter, promoting a low Fs value and minimise them during the summer to reduce the global nominal energy consumption for air cooling, promoting a high Fs value. As Portugal is one of the European nations with more intense solar radiation. Regulations in Portugal require using a procedure for assessing solar gains during both the heating and cooling seasons to determine the building’s energy requirements. 3. Results and Portuguese Case Portugal has about 3.6 million residential buildings, which contribute to about 30% of the national primary energy consumption (electricity), mainly for heating and cooling systems, domestic hot water, lighting and electrical equipment use. These values have increased in recent years due to the need for greater indoor comfort, especially in residential buildings. Thus, new measures needed to be adopted to reduce energy consumption in this sector and, preferably, through passive and sustainable solutions [68]. Buildings 2023,13, 1521 16 of 19 tions (Tables 3and 4). Since this process is occurring and usually it incurs costs, typically in the insulation or heating/cooling of the buildings, this reality might not lead to real nearly zero-energy buildings (nZEBs). In the given scenario, it is possible to consider that the validity of the proposal sometimes clashes with the political-legislative premises, and the decisions are taken regardless of whether the executed proposal was the best technical option. The lack of interaction between systems, including legislation, may add incongruities by excess or by omission, as has been seen, that prevent the optimisation of solutions, in this case, energy reduction or urban sustainability [80]. Author Contributions: Conceptualisation, M.F.O., P.M. and L.T.S.; Funding acquisition, M.F.O., P.M. and L.T.S.; Investigation, M.F.O., P.M. and L.T.S.; Writing—original draft, M.F.O.; Writing—review and editing, M.F.O., P.M., M.T., P.S., J.F.S. and L.T.S. All authors have read and agreed to the published version of the manuscript. Funding: This work was financed by Foundation for Science and Technology (FCT) (Grant SFRH/BD/ 2018)/MCTES through national funds (PIDDAC) under the R&D Centre for Territory, Environment and Construction (CTAC), under reference UID/04047/2020, and the Landscapes, Heritage and Territory Laboratory (Lab2PT) Center of Design and Technology (DeTech). Data Availability Statement: Not applicable. Acknowledgments: The authors gratefully acknowledge the funding support of the Foundation for Science and Technology (FCT) and the Centre for Territory, Environment and Construction (CTAC). Conflicts of Interest: The authors declare no conflict of interest. References 1. Development Goals|United Nations Development Programme. Available online: https://www.undp.org/sustainabledevelopment-goals (accessed on 3 April 2023). 2. Aelenei, L. NZEB, Passive Solutions and Integration in Façades. 2022. Available online: https://www.lneg.pt/wp-content/ uploads/2022/05/laura-aelenei-4-maio-2022.pdf (accessed on 4 May 2022). 3. Silva, S.M.; Mateus, R.; Marques, L.; Ramos, M.; Almeida, M. Contribution of the Solar Systems to the NZEB and ZEB Design Concept in Portugal—Energy, Economics and Environmental Life Cycle Analysis. Sol. Energy Mater. Sol. Cells 2016 ,156, 59–74. [CrossRef] 4. Crowe, S.; Cresswell, K.; Robertson, A.; Huby, G.; Avery, A.; Sheikh, A. The Case Study Approach. BMC Med. Res. Methodol. 2011 , 11, 100. [CrossRef] 5. Reinhart, C.F.; Cerezo Davila, C. Urban Building Energy Modeling—A Review of a Nascent Field. Build. Environ. 2016 , 97, 196–202. [CrossRef] 6. Swan, L.G.; Ugursal, V.I. Modeling of End-Use Energy Consumption in the Residential Sector: A Review of Modeling Techniques. Renew. Sustain. Energy Rev. 2009,13, 1819–1835. [CrossRef] 7. Li, W.; Zhou, Y.; Cetin, K.; Eom, J.; Wang, Y.; Chen, G.; Zhang, X. Modeling Urban Building Energy Use: A Review of Modeling Approaches and Procedures. Energy 2017,141, 2445–2457. [CrossRef] 8. Harish, V.S.K.V.; Kumar, A. A Review on Modeling and Simulation of Building Energy Systems. Renew. Sustain. Energy Rev. 2016 , 56, 1272–1292. [CrossRef] 9. Allegrini, J.; Orehounig, K.; Mavromatidis, G.; Ruesch, F.; Dorer, V.; Evins, R. A Review of Modelling Approaches and Tools for the Simulation of District-Scale Energy Systems. Renew. Sustain. Energy Rev. 2015,52, 1391–1404. [CrossRef] 10. Ryerson, C.C. Mapping Solar Access in High Relief Areas for Regional Energy Planning. Prof. Geogr. 1984 ,36, 345–352. [CrossRef] 11. Belakehal, A.; Tabet, A.K. Shading and shadowing: Concepts for an interactive strategy between solar control and aesthetics in the design of the facade. Reference to arid zones. Renew. Energy 1996,8, 323–326. [CrossRef] 12. Al-Sallal, K.A. Solar Access/Shading and Building Form: Geometrical Study of the Traditional Housing Cluster in Sana’a. Renew. Energy 1996,8, 331–334. [CrossRef] 13. Belakehal, A.; Tabet, A.K. Experimental Assessment of Shading and Shadowing Strategy, Case of Facade’s Cantilevered Volumes. Reference to Dwellings in Arid Lands. Int. J. Ambient Energy 2000,21, 179–186. [CrossRef] 14. Capeluto, I.G. Energy Performance of the Self-Shading Building Envelope. Energy Build. 2003,35, 327–336. [CrossRef] 15. Bourbia, F.; Awbi, H. Building Cluster and Shading in Urban Canyon for Hot Dry Climate: Part 2: Shading Simulations. Renew. Energy 2004,29, 291–301. [CrossRef] 16. Chua, K.J.; Chou, S.K. Evaluating the Performance of Shading Devices and Glazing Types to Promote Energy Efficiency of Residential Buildings. Build. Simul. 2010,3, 181–194. [CrossRef] 17. Hayman, S. Limits of Accuracy of Graphical Solar Access and Shadow Studies. Archit. Sci. Rev. 2011,32, 15–20. [CrossRef] Buildings 2023,13, 1521 17 of 19 18. Grynning, S.; Time, B.; Matusiak, B. Solar Shading Control Strategies in Cold Climates—Heating, Cooling Demand and Daylight Availability in Office Spaces. Sol. Energy 2014,107, 182–194. [CrossRef] 19. Shukla, K.N.; Rangnekar, S.; Sudhakar, K. Comparative Study of Isotropic and Anisotropic Sky Models to Estimate Solar Radiation Incident on Tilted Surface: A Case Study for Bhopal, India. Energy Rep. 2015,1, 96–103. [CrossRef] 20. Aksamija, A. Design Methods for Sustainable, High-Performance Building Facades. Adv. Build. Energy Res. 2015 ,10, 240–262. [CrossRef] 21. De Simón-Martín, M.; Díez-Mediavilla, M.; Alonso-Tristán, C. Shadow-Band Radiometer Measurement of Diffuse Solar Irradiance: Calculation of Geometrical and Total Correction Factors. Sol. Energy 2016,139, 85–99. [CrossRef] 22. Lee, K.S.; Han, K.J.; Lee, J.W. The Impact of Shading Type and Azimuth Orientation on the Daylighting in a Classroom-Focusing on Effectiveness of Façade Shading, Comparing the Results of Da and Udi. Energies 2017,10, 635. [CrossRef] 23. Sari, D.P.; Laksana, P.J.B. Optimization Building Performance in Early Design Stage Using Integrated Dynam-Ic Model. Modul 2020,20, 151–156. [CrossRef] 24. Kimm, G. Actual and Experiential Shadow Origin Tagging: A 2.5D Algorithm for Efficient Precinct-Scale Modelling. Int. J. Archit. Comput. 2020,18, 41–52. [CrossRef] 25. Garreau, E.; Berthou, T.; Duplessis, B.; Partenay, V.; Marchio, D. Solar Shading and Multi-Zone Thermal Simulation: Parsimonious Modelling at Urban Scale. Energy Build. 2021,249, 111176. [CrossRef] 26. Dagher, S.; Akhozheya, B.; Slimani, H. Energy Analysis Studying the Effect of Solar Shading on Daylight Factors and Cooling Hours in an Extreme Weather. Energy Rep. 2022,8, 443–448. [CrossRef] 27. Wen, J.; Yang, S.; Xie, Y.; Yu, J.; Lin, B. A Fast Calculation Tool for Assessing the Shading Effect of Surrounding Buildings on Window Transmitted Solar Radiation Energy. Sustain. Cities Soc. 2022,81, 103834. [CrossRef] 28. Wen, J.; Xie, Y.; Yang, S.; Yu, J.; Lin, B. Study of Surrounding Buildings’ Shading Effect on Solar Radiation through Windows in Different Climates. Sustain. Cities Soc. 2022,86, 104143. [CrossRef] 29. Wang, X.; Zhang, X.; Zhu, S.; Ren, J.; Causone, F.; Ye, Y.; Jin, X.; Zhou, X.; Shi, X. A Novel and Efficient Method for Calculating Beam Shadows on Exterior Surfaces of Buildings in Dense Urban Contexts. Build. Environ. 2023,229, 109937. [CrossRef] 30. SalazarIi Trujillo, J.H. Solar Performance and Shadow Behaviour in Buildings. Case Study with Computer Modelling of a Building in Loranca, Spain. Build. Environ. 1998,33, 117–130. [CrossRef] 31. Carneiro, C.; Morello, E.; Desthieux, G.; Golay, F. Urban Environment Quality Indicators: Application to Solar Radiation and Morphological Analysis on Built Area. In Proceedings of the 3rd WSEAS International Conference on Visualization, Imaging and Simulation, Faro, Portugal, 3–5 November 2010; pp. 141–148. 32. Grifoni, R.C.; Lapucci, D.; Petrucci, E.; Prenna, E. Method to Define a Solar Energy Platform for Historical City Centers and Identification of New Scenarios for Sustainability. In Proceedings of the IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), Florence, Italy, 7–10 June 2016. 33. Kite, S. Shadow-Makers: A Cultural History of Shadows in Architecture; Bloomsbury Academic: London, UK, 2017. 34. Valladares-Rendón, L.G.; Schmid, G.; Lo, S.L. Review on Energy Savings by Solar Control Techniques and Optimal Building Orientation for the Strategic Placement of Façade Shading Systems. In Energy and Buildings; Elsevier: Amsterdam, The Netherlands, 2017; pp. 458–479. 35. Vartholomaios, A. A Parametric Sensitivity Analysis of the Influence of Urban Form on Domestic Energy Consumption for Heating and Cooling in a Mediterranean City. Sustain. Cities Soc. 2017,28, 135–145. [CrossRef] 36. Alagoz, M.; Beyhan, F. Methods to Discover the Optimum Building Envelope in the Context of Solar Data. Gazi Univ. J. Sci. 2020 , 33, 318–340. [CrossRef] 37. Kanters, J.; Gentile, N.; Bernardo, R. Planning for Solar Access in Sweden: Routines, Metrics, and Tools. Urban, Plan. Transp. Res. 2021,9, 347–367. [CrossRef] 38. Silva, A.P.D. Energy Efficiency of Buildings Located in the Municipality of Évora: A Case Study. Master’s Thesis, University of Évora, Évora, Portugal, 2009. Available online: http://hdl.handle.net/10174/13004 (accessed on 14 December 2022). 39. Silva, J.J.C.; Henriques, P.M.C. Proposal for a New Methodology for Calculating the Shading Factor of Glazed Spans by Horizontal Elements. Construction Congress 2012, Ed.; University of Coimbra: Coimbra, Portugal, 2012; pp. 1–9. 40. Lopes, A.B. Harmonised Methodology for Evaluating Thermal Behaviour and Energy Performance of Buildings: Study of Solar Gains; University of Coimbra: Coimbra, Portugal, 2016; Available online: http://hdl.handle.net/10316/38729 (accessed on 1 May 2023). 41. Ferreira, S.F. Impact of the New Regulations on Energy Certification of Buildings, Superior Institute of Engineering, University of Algarve, Faro, Portugal. 2016. Available online: http://hdl.handle.net/10400.1/8448 (accessed on 3 April 2023). 42. Costa, J.M.S. Evaluation of the Potential for Optimising the Thermo-Energetic Behaviour of Residential Buildings. Master’s Thesis, School of Engineering, University of Minho, Braga, Portugal, 2016. Available online: https://hdl.handle.net/1822/49816 (accessed on 4 June 2023). 43. Da Carreira, R.F.C. Determination of Shading Factors Using 3D Models. Master’s Thesis, Energy and Environmental Engineering, Faculty of Sciences, University of Lisbon, Lisbon, Portugal, 2017. Available online: https://repositorio.ul.pt/handle/10451/32041 (accessed on 3 April 2023). 44. Brito, M.C.; Redweik, P.; Catita, C.; Freitas, S.; Santos, M. 3D Solar Potential in the Urban Environment: A Case Study in Lisbon. Energies 2019,12, 3457. [CrossRef] Buildings 2023,13, 1521 18 of 19 45. Silva, S.M. Sustainability and Comfort in Buildings. Ph.D. Thesis, Civil Engineering, University of Minho, Braga, Portugal, 2009. Available online: https://hdl.handle.net/1822/10245 (accessed on 5 April 2023). 46. Fortunato, V.; Rato, V. Architectural Integration of Optimised Solar Shading. ISTAR-RN 2017 ,15, 4–23. Available online: http://hdl.handle.net/10071/18144 (accessed on 5 April 2023). 47. Cascone, Y.; Corrado, V.; Serra, V. Calculation Procedure of the Shading Factor under Complex Boundary Conditions. Sol. Energy 2011,85, 2524–2539. [CrossRef] 48. Decree-Law No 49/90 (RCCTE); Official Journal of the Republic No 31/1990, Series I of 6 February 1990: Portugal. 1990. Available online: https://dre.pt/dre/detalhe/diario-republica/31-1990-4394525 (accessed on 5 April 2023). 49. Directive 2002/91/EC of the European Parliament and of the Council of 16 December 2002 (EPBD). 2002. Available online: https://eur-lex.europa.eu/legal-content/PT/TXT/?uri=celex%3A32002L0091 (accessed on 5 April 2023). 50. Decree-Law No. 118/2013 (SCE, REH, RECS); Portugal. 2013, pp. 4988–5005. Available online: https://drehttps//dre.pt/ application/conteudo/499237 (accessed on 5 April 2023). 51. Letras, S.G.M. Nominal Energy Demand in Residential Buildings Comparison between the Methodologies of the RCCTE, REH and 5R1C Model. Master’s Thesis, University of Lisbon, Lisbon, Portugal, 2014. Available online: http://hdl.handle.net/10451/16107 (accessed on 5 April 2023). 52. Sombrero. Available online: http://nesa1.uni-siegen.de/softlab/download/SOMBRERO_Manual.pdf (accessed on 5 April 2023). 53. Shading Analysis. Available online: http://andrewmarsh.com/software/app-shading/ (accessed on 5 April 2023). 54. ShadowFX—Sun and shadow analysis. Available online: http://www.shadowfx.com/ (accessed on 5 April 2023). 55. TownScope. Available online: http://www.townscope.com/ (accessed on 5 April 2023). 56. Sunhoursplugin. Available online: https://www.sunhoursplugin.com/ (accessed on 5 April 2023). 57. Gosol. Available online: http://www.gosol.de/gosol-software.html (accessed on 5 April 2023). 58. Analysis SOL-AR-Laboratório de Eficiência Energética em Edificações. Available online: https://labeee.ufsc.br/downloads/ softwares/analysis-sol-ar (accessed on 5 April 2023). 59. ArcGIS Spatial Analyst -Solar Analysis. Available online: https://www.esriuk.com/software/arcgis/extensions/spatialanalyst/ key-features/solar (accessed on 5 April 2023). 60. SunEye 210 Shade Tool. Available online: https://www.solmetric.com/buy210.html (accessed on 5 April 2023). 61. Solar Pathfinder—Solar Site Analysis. Available online: https://www.solarpathfinder.com/ (accessed on 5 April 2023). 62. Horicatcher -Meteonorm. Available online: https://meteonorm.com/en/product/horicatcher (accessed on 5 April 2023). 63. Order (Extract) No. 15793-K/2013; Official Journal of the Republic No 234/2013, 3rd Supplement, Series II of 2013-12-03, Portugal. 2013, pp. 35088-(58)–35088-(87). Available online: https://dre.pt/dre/detalhe/despacho-extrato/15793-k-2013-29752 24 (accessed on 5 April 2023). 64. ENVI-Met. Available online: https://www.envi-met.com/pt-pt/estudantes/#analise-solar (accessed on 5 April 2023). 65. Ladybug. Available online: https://www.ladybug.tools/ladybug.html (accessed on 5 April 2023). 66. Order (Extract), No. 15793-E/2013; Official Journal of the Republic No 234/2013, 3rd Supplement, Series II de 2013-12-03, Portugal. Available online: https://dre.pt/dre/detalhe/despacho-extrato/15793-e-2013-2975218 (accessed on 5 April 2023). 67. Cunha, M.M.F. Glazed Openings—Insolation Geometry—Optimisation of the Dimensioning of Solar Protection Elements; 2005. Available online: https://paginas.fe.up.pt/~vpfreita/mce04004_geometria_de_insolacao.pdf (accessed on 5 April 2023). 68. Agency for Energy (ADENE). Available online: https://www.adene.pt/ (accessed on 14 May 2023). 69. National Institute of Statistics (INE). Portugal 2021 Census. Available online: https://censos.ine.pt/xportal/xmain?xpgid= censos21_main&xpid=censos21&xlang=pt (accessed on 5 April 2023). 70. Decree-Law, No. 38 382 (RGEU); The Journal of the Government n. 1951. Available online: https://dre.pt/dre/legislacaoconsolidada/decreto-lei/1951-120610500-201155062 (accessed on 5 April 2023). 71. Order (Extract) No. 15793-F/2013; Portugal. 2013, pp. 35088-(26)–35088-(31). Available online: https://dre.pt/dre/detalhe/ despacho-extrato/15793-f-2013-2975219 (accessed on 5 April 2023). 72. Coutinho, H.M.S. Relation between Urban Form and Solar Radiation on Buildings. Master’s Thesis, Civil and Environmental Engineering, Higher School of Technology and Management, Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal, 2018. Available online: https://repositorio.ipvc.pt/handle/2 (accessed on 2 May 2023). 73. Archicad—BIM. Available online: https://graphisoft.com/solutions/archicad#archicad (accessed on 15 May 2023). 74. Grasshopper—Algorithmic Modeling for Rhino. Available online: https://www.grasshopper3d.com/ (accessed on 14 May 2023). 75. Rhino 6 for Windows and Mac. Available online: https://www.rhino3d.com/ (accessed on 14 June 2020). 76. Ouria, M. Solar Energy Potential According to Climatic and Geometrical Parameters of Cities and Buildings: A Case-Study from Tabriz CityIran. Urban Clim. 2019,28, 100469. [CrossRef] 77. Elwy, I.; Ibrahim, Y.; Fahmy, M.; Mahdy, M. Outdoor Microclimatic Validation for Hybrid Simulation Workflow in Hot Arid Climates against ENVI-Met and Field Measurements. Energy Procedia 2018,153, 29–34. [CrossRef] 78. Kharvari, F. An Empirical Validation of Daylighting Tools: Assessing Radiance Parameters and Simulation Settings in Ladybug and Honeybee against Field Measurements. Sol. Energy 2020,207, 1021–1036. [CrossRef] Buildings 2023,13, 1521 19 of 19 79. Forouzandeh, N.; Tahsildoost, M.; Zomorodian, Z.S. A Review of Web-Based Building Energy Analysis Applications. J. Clean. Prod. 2021,306, 127251. [CrossRef] 80. Merline, M.A.; Vimalathithan, R. Smart City: Issues and Research Challenges in Implementation. In Proceedings of the 2017 IEEE International Conference on Smart Grid and Smart Cities (ICSGSC), Singapore, 23–26 July 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 263–266. Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.