Multi-scale urban data models for early-stage suitability assessment of energy conservation measures in historic urban areas

The demand for improving the energy performance of buildings located in the historic districts of cities is as high as the current demand in other city districts. The need to reduce energy consumption and improve the comfort of inhabitants is compounded by the need to preserve an environment of heritage value. The selection of rehabilitation strategies at urban scale offers significant benefits, but makes the process long and costly. Therefore, methods or tools are necessary to establish a rapid assessment that facilitates strategic decision making and a deeper analysis of a reduced number of alternatives.This paper describes a method that supports decision making regarding the suitability of Energy Conservation Measures (ECMs) in historic districts at early stages. The method considers the improvement of the energy performance of buildings as a positive impact, balanced with the negative impacts that the implementation of ECMs could produce. A CityGML-based urban model allows the automation of a multi-scale assessment for different ECMs and provides possible global energy demand reductions. This method, combined with an economic evaluation, can be used by decision makers for large-scale energy retrofitting. The applicability of the method is demonstrated through implementation in the historic city of Santiago de Compostela.The authors gratefully acknowledge the European Commission for providing financial support during the research under the EFFESUS project (Grant Agreement Number 314678)

GIS-3D Platform to Help Decision Making for Energy Rehabilitation in Urban Environments

One of the main current challenges of European cities is to become energy self-sufficient entities. One of the vectors for this challenge is to improve the energy efficiency of the buildings and to promote the generation of renewable energies in the urban environment. The article describes a tool based on GIS-3D technologies to support the identification of the energy rehabilitation potential of neighbourhoods based on the introduction of renewable energies. The platform is based on a urban 3D model that collects the geometry of buildings, together with relevant information for the identification of rehabilitation opportunities (e.g. surfaces, heights, orientations and slopes). The project includes the generation of a cloud-based repository, which incorporates active and passive innovative solutions with metrics that allow the comparison of the solutions and the applicability of them to the real environment. The identification of rehabilitation opportunities combines information resulting from the diagnosis of the current energy performance of the district's buildings with the potential for renewable generation in the area. A multicriteria analysis process facilitates the identification of the most appropriate rehabilitation solutions for the analysed environment based on different criteria as energy, cost or applicability. The result can be visualized through a web tool that combines 2D and 3D information, with comparative information in a quantitative and geo-referenced manner. The flexibility of the architecture allows the application of the same approach to different urban challenges as the application of energy conservation measures to protected historic urban areas.The work of this paper has been done as part of the projects RE3D “Energy Rehabilitation in 3D” and RE2H “Energy Retrofitting of Historic Districts”, both partially funded by Basque Government, with references ZL-2017/00998 and ZL-2017/00981 respectively

ADAPTATION TO FLOODING EVENTS THROUGH VULNERABILITY MAPPING IN HISTORIC URBAN AREAS

Historic urban areas are complex and inter-reliant systems, vulnerable to natural hazards. Over the recent years, the increase frequency in extreme precipitation events and sea-level rise, have impacted on a large number of historic areas, growing concern over disaster mitigation related to climate change. Most of the changes in the climatological indicators may have adverse impacts on historic areas, leading to physical, social and cultural consequences and should be included in urban planning practice. The importance of addressing cultural heritage in disaster risk has also been included in The Sendai Framework, considering the dimensions of vulnerability, adaptive capacity and exposure through systematic evaluation. Urban planning decisions involve an understanding of complex interactions between different aspects of the city, in its constructive, social, economic, environmental and cultural system. The analysis of these interactions requires a systemic approach as the components operate on different spatial and temporal scales and generate a large amount of data. This information can be used to determine the vulnerability of historic areas by assessing it at the building level, through the creation of typologies representing the building stock, often characterized by similarities and common constructive elements. The comprehension of the information can be supported and homogenized by a multi-scale urban model, to facilitate the understanding of interactions and the link among the different disciplines involved. This paper describes the methodology proposed for vulnerability mapping in historic urban areas, by using a categorization method supported by an information strategy and a multi-scale urban model.Authors would like to acknowledge the funding provided by the Basque Government through the ADVICE project and the research group IT781-13 at the UPV/EHU

Energy planning and forecasting approaches for supporting physical improvement strategies in the building sector: a review

The strict CO2 emission targets set to tackle the global climate change associated with greenhouse gas emission exerts so much pressure on our cities which contribute up to 75% of the global carbon dioxide emission level, with buildings being the largest contributor (UNEP, 2015). Premised on this fact, urban planners are required to implement proactive energy planning strategies not only to meet these targets but also ensure that future cities development is performed in a way that promotes energy-efficiency. This article gives an overview of the state-of-art of energy planning and forecasting approaches for aiding physical improvement strategies in the building sector. Unlike previous reviews, which have only addressed the strengths as well as weaknesses of some of the approaches while referring to some relevant examples from the literature, this article focuses on critically analysing more approaches namely; 2D GIS and 3DGIS (CityGML) based energy prediction approaches, based on their frequent intervention scale, applicability in the building life cycle, and conventional prediction process. This will be followed by unravelling the gaps and issues pertaining to the reviewed approaches. Finally, based on the identified problems, future research prospects are recommended

Multiscale building modelling and energy simulation support tools

Building and district modelling (BIM, CityGML…) are key technologies for the deployment of energy efficiency strategies at building and district level, from the initial stages of planning and design to the operation and maintenance ones. These technologies allow satisfying the interoperability requirements that fa-cilitate the cooperation among the multiple stakeholders and provide the framework to develop more intelli-gent tools. This paper introduces five complementary European R&D projects in which TECNALIA is col-laborating, very good examples of innovative systems based on these concepts. MOEEBIUS enhances passive and active building elements modelling approaches enabling improved building energy performance simula-tions. HOLISTEEC focuses on building multi-physical simulations considering the neighborhood context. FASUDIR exploits the high potential of GIS tools for urban sustainability analysis and accurate building en-ergy performance evaluation. EFFESUS integrates district and building scales in historic districts. OPTEEMAL develops a platform at district level, based on an IPD approach.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 680517

Towards building a semantic formalization of (small) historical centres

Historical small urban centres are of increasing interest to different interacting fields such as architectural heritage protection and conservation, urban planning, disaster response, sustainable development and tourism. They are defined at different levels (international, national, regional), by various organizations and standards, incorporate numerous aspects (natural and built environment, infrastructures and open spaces, social, economic, and cultural processes, tangible and intangible heritage) and face various challenges (urbanization, globalization, mass tourism, climate change, etc.). However, their current specification within large-scale geospatial databases is similar to those of urban areas in a broad sense resulting in the loss of many aspects forming this multifaceted concept. The present study considers the available ontologies and data models, coming from various domains and having different granularities and levels of detail, to represent historical small urban centres information. The aim is to define the needs for extension and integration of them in order to develop a multidisciplinary, integrated semantic representation. Relevant conventions and other legislation documents, ontologies and standards for cultural heritage (CIDOC-CRM, CRMgeo, Getty Vocabularies), 3D city models (CityGML), building information models (IFC) and regional landscape plans are analysed to identify concepts, relations, and semantic features that could form a holistic semantic model of historical small urban centres

Assessment of the photovoltaic potential at urban level based on 3D city models: A case study and new methodological approach

The use of 3D city models combined with simulation functionalities allows to quantify energy demand and renewable generation for a very large set of buildings. The scope of this paper is to determine the solar photovoltaic potential at an urban and regional scale using CityGML geometry descriptions of every building. An innovative urban simulation platform is used to calculate the PV potential of the Ludwigsburg County in south-west Germany, in which every building was simulated by using 3D city models. Both technical and economic potential (considering roof area and insolation thresholds) are investigated, as well as two different PV efficiency scenarios. In this way, it was possible to determine the fraction of the electricity demand that can be covered in each municipality and the whole region, deciding the best strategy, the profitability of the investments and determining optimal locations. Additionally, another important contribution is a literature review regarding the different methods of PV potential estimation and the available roof area reduction coefficients. An economic analysis and emission assessment has also been developed. The results of the study show that it is possible to achieve high annual rates of covered electricity demand in several municipalities for some of the considered scenarios, reaching even more than 100% in some cases. The use of all available roof space (technical potential) could cover 77% of the region’s electricity consumption and 56% as an economic potential with only high irradiance roofs considered. The proposed methodological approach should contribute valuably in helping policy-making processes and communicating the advantages of distributed generation and PV systems in buildings to regulators, researchers and the general public

Climate change risk management for the sustainable development of the historic city: from the material to the territory

191 p.La ciencia de la conservación del patrimonio histórico se caracteriza por la amplia y articulada variedad de disciplinas que la componen. Sin embargo, no siempre existe una visión integral del sistema cultural capaz de identificar las acciones y estrategias para preservar, tutelar y valorizar el patrimonio, considerando la evolución de la sociedad contemporánea y del medioambiente.El trabajo de investigación propuesto se basa en una aproximación proactiva y conceptual de la conservación, cuyo objetivo es reducir al mínimo la perdida de los bienes culturales, a través de un estudio de vulnerabilidad para prevenir, mitigar y controlar los factores de riesgos y minimizar sus efectos en el patrimonio. La complejidad de algunos conjuntos, como son los centros históricos requieren el uso de métodos de trabajos sistemáticos y herramientas de gestión adaptables a las particularidades de cada lugar. El acercamiento metodológico para la evaluación de riesgos en las ciudades históricas se basa en estrategias de planificación tanto a nivel de edificio como de su entorno, combinando, de forma integral y holística, conocimientos de mitigación de desastres naturales, adaptación al cambio climático, conservación del patrimonio, gestión de la información y toma de decisión, como proceso sostenible para el desarrollo de la ciudad histórica, objetivo último de la presente investigación.Tecnalia Politecnico Milano 1863

Setting intelligent city tiling strategies for urban shading simulations

Assessing accurately the solar potential of all building surfaces in cities, including shading and multiple reflections between buildings, is essential for urban energy modelling. However, since the number of surface interactions and radiation exchanges increase exponentially with the scale of the district, innovative computational strategies are needed, some of which will be introduced in the present work. They should hold the best compromise between result accuracy and computational efficiency, i.e. computational time and memory requirements. In this study, different approaches that may be used for the computation of urban solar irradiance in large areas are presented. Two concrete urban case studies of different densities have been used to compare and evaluate three different methods: the Perez Sky model, the Simplified Radiosity Algorithm and a new scene tiling method implemented in our urban simulation platform SimStadt, used for feasible estimations on a large scale. To quantify the influence of shading, the new concept of Urban Shading Ratio has been introduced and used for this evaluation process. In high density urban areas, this index may reach 60% for facades and 25% for roofs. Tiles of 500 m width and 200 m overlap are a minimum requirement in this case to compute solar irradiance with an acceptable accuracy. In medium density areas, tiles of 300 m width and 100 m overlap meet perfectly the accuracy requirements. In addition, the solar potential for various solar energy thresholds as well as the monthly variation of the Urban Shading Ratio have been quantified for both case studies, distinguishing between roofs and facades of different orientations

Taxonomy, Semantic Data Schema, and Schema Alignment for Open Data in Urban Building Energy Modeling

Urban Building Energy Modeling (UBEM) is a critical tool to provide quantitative analysis on building decarbonization, sustainability, building-to-grid integration, and renewable energy applications on city, regional, and national scales. Researchers usually use open data as inputs to build and calibrate UBEM. However, open data are from thousands of sources covering various perspectives of weather, building characteristics, etc. Besides, a lack of semantic features of open data further increases the engineering effort to process information to be directly used for UBEM as inputs. In this paper, we first reviewed open data types used for UBEM and developed a taxonomy to categorize open data. Based on that, we further developed a semantic data schema for each open data category to maintain data consistency and improve model automation for UBEM. In a case study, we use three popular open data to show how they can be automatically processed based on the proposed schematic data structure using large language models. The accurate results generated by large language models indicate the machine-readability and human-interpretability of the developed semantic data schema