Coupling of CityGML-based Semantic City Models with Energy Simulation Tools: some Experiences

More and more cities are creating and adopting three-dimensional virtual city models as a means for data integration, harmonisation and storage, often based on CityGML, which is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. A centralised database can thus foster the development of new integrated applications profiting from such an harmonised data source, in that detailed information is retrieved about building characteristics or any other relevant entities needed for urban planning (infrastructures, hydrography and terrain models, etc.). This paper focuses on the adoption of a CityGML-based semantic 3D virtual city model to perform energy simulations. It deals primarily with the demand side, and concentrated particularly on the spatial and temporal evaluation of the net energy demand for space heating of buildings in a city. Two approaches are presented: the first one deals with the estimation of the heating energy demand of buildings adopting a standard-based approach, which allow obtaining monthly values of heating energy demand. The second approach describes the first results as how a dynamic simulation tool can be connected to a CityGML-based city model in order to benefit from the amount of harmonised data stored therein and further refine the results, e.g. in terms of time resolution. As test area, a part of the city of Trento (Italy) was chosen

Integrating the urban planning process into energy systems models for future urban heating system planning: A participatory approach

For local governments and municipalities, both urban and energy planning are required to make the transition to more energy efficient cities with lower carbon emissions. However, energy planning and urban planning are usually under the responsibility of different departments and have their own planning processes. When dealing with energy plans, this separation could lead to a less effective impact on cities in reaching climate goals since a lack of coordination may result in different strategies set out by the two plans. In consideration of the fact that space heating dominates the energy use in buildings, this study has a focus on urban heating systems in the building sector. We propose an integrative municipal heat planning methodology investigating which features of the urban planning process that could be integrated into a spatially explicit energy systems model and how. The proposed methodology is then applied to a specific case: the heating system in the municipality of Lyngby-Taarbaek, Denmark. The inclusion of stakeholders from both the heat and urban planning departments in the case study enabled us to reflect on their preferences and expectations for the future heating system. Finally, the applicability of the methodology and the application results are discussed and compared to other methods

Visualization of Vibrant Cities and Regions – Identification, Design and Development of 3D-GIS Applications and Modules

Facing a continuous state of transition and herewith connected financial, societal and ecological challenges such as the climate or demographic change (United Nations 2013), cities try to integrate innovative information and communication technologies in order to optimize administrative processes, legitimize decision making and to involve all relevant local actors into processes of public relevance. In this context 3D-GIS-models offer various not yet exploited potentials for all named levels of interest. This paper presents an overview over existing application fields for 3D-GIS-solutions, further proposing a categorization in order to be able to develop and implement target-oriented solutions. Moreover, this paper presents the project activities of the Fraunhofer IAO, the city of Cologne and the provider of geo-information-services ESRI, designing and developing end-user oriented applications for the 3D-GIS-tool CityEngine. Therefore various city departments such as the agencies for city planning, traffic and environment were involved in an iterative process in order to identify potential application fields and their benefits within the administrative work as well as their andvantages regarding existing solutions and processes. Aditionally, the particpants decided upon a set of focus applications to be developed within the project. Therefore, this document will concentrate on the potential benefits of the identified and cooperatively designed application fields, further outlining the first steps of the deleopment phase of the citizen particpiation application

How to pinpoint energy-inefficient Buildings? An Approach based on the 3D City model of Vienna

This paper describes a methodology to assess the energy performance of residential buildings starting from the semantic 3D city model of Vienna. Space heating, domestic hot water and electricity demand are taken into account. The paper deals with aspects related to urban data modelling, with particular attention to the energy-related topics, and with issues related to interactive data exploration/visualisation and management from a plugin-free web-browser, e.g. based on Cesium, a WebGL virtual globe and map engine. While providing references to existing previous works, only some general and introductory information is given about the data collection, harmonisation and integration process necessary to create the CityGML-based 3D city model, which serves as the central information hub for the different applications developed and described more in detail in this paper. The work aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. The results obtained so far, as well as some comments about their quality and limitations, are presented, together with the discussion regarding the next steps and some planned improvements

ENABLING “ENERGY-AWARENESS” IN THE SEMANTIC 3D CITY MODEL OF VIENNA

This paper presents and discusses the first results regarding selection, analysis, preparation and eventual integration of a number of energy-related datasets, chosen in order to enrich a CityGML-based semantic 3D city model of Vienna. CityGML is an international standard conceived specifically as information and data model for semantic city models at urban and territorial scale. The still-in-development Energy Application Domain Extension (ADE) is a CityGML extension conceived to specifically model, manage and store energy-related features and attributes for buildings. <br><br> The work presented in this paper is embedded within the European Marie-Curie ITN project “CINERGY, Smart cities with sustainable energy systems”, which aims, among the rest, at developing urban decision making and operational optimisation software tools to minimise non-renewable energy use in cities. Given the scope and scale of the project, it is therefore vital to set up a common, unique and spatio-semantically coherent urban data model to be used as information hub for all applications being developed. This paper reports about the experiences done so far, it describes the test area in Vienna, Austria, and the available data sources, it shows and exemplifies the main data integration issues, the strategies developed to solve them in order to obtain the enriched 3D city model. The first results as well as some comments about their quality and limitations are presented, together with the discussion regarding the next steps and some planned improvements

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

The Energy Application Domain Extension for CityGML: enhancing interoperability for urban energy simulations

The road towards achievement of the climate protection goals requires, among the rest, a thorough rethinking of the energy planning tools (and policies) at all levels, from local to global. Nevertheless, it is in the cities where the largest part of energy is produced and consumed, and therefore it makes sense to focus the attention particularly on the cities as they yield great potentials in terms of energy consumption reduction and efficiency increase. As a direct consequence, a comprehensive knowledge of the demand and supply of energy resources, including their spatial distribution within urban areas, is therefore of utmost importance. Precise, integrated knowledge about 3D urban space, i.e. all urban (above and underground) features, infrastructures, their functional and semantic characteristics, and their mutual dependencies and interrelations play a relevant role for advanced simulation and analyses. As a matter of fact, what in the last years has proven to be an emerging and effective approach is the adoption of standard-based, integrated semantic 3D virtual city models, which represent an information hub for most of the abovementioned needs. In particular, being based on open standards (e.g. on the CityGML standard by the Open Geospatial Consortium), virtual city models firstly reduce the effort in terms of data preparation and provision. Secondly, they offer clear data structures, ontologies and semantics to facilitate data exchange between different domains and applications. However, a standardised and omni-comprehensive urban data model covering also the energy domain is still missing at the time of writing (January 2018). Even CityGML falls partially short when it comes to the definition of specific entities and attributes for energy-related applications. Nevertheless, and starting from the current version of CityGML (i.e. 2.0), this article describes the conception and the definition of an Energy Application Domain Extension (ADE) for CityGML. The Energy ADE is meant to offer a unique and standard-based data model to fill, on one hand, the above-mentioned gap, and, on the other hand, to allow for both detailed single-building energy simulation (based on sophisticated models for building physics and occupant behaviour) and city-wide, bottom-up energy assessments, with particular focus on the buildings sector. The overall goal is to tackle the existing data interoperability issues when dealing with energy-related applications at urban scale. The article presents the rationale behind the Energy ADE, it describes its main characteristics, the relation to other standards, and provides some examples of current applications and case studies already adopting it

CityGML in the Integration of BIM and the GIS: Challenges and Opportunities

CityGML (City Geography Markup Language) is the most investigated standard in the integration of building information modeling (BIM) and the geographic information system (GIS), and it is essential for digital twin and smart city applications. The new CityGML 3.0 has been released for a while, but it is still not clear whether its new features bring new challenges or opportunities to this research topic. Therefore, the aim of this study is to understand the state of the art of CityGML in BIM/GIS integration and to investigate the potential influence of CityGML3.0 on BIM/GIS integration. To achieve this aim, this study used a systematic literature review approach. In total, 136 papers from Web of Science (WoS) and Scopus were collected, reviewed, and analyzed. The main findings of this review are as follows: (1) There are several challenging problems in the IFC-to-CityGML conversion, including LoD (Level of Detail) mapping, solid-to-surface conversion, and semantic mapping. (2) The ‘space’ concept and the new LoD concept in CityGML 3.0 can bring new opportunities to LoD mapping and solid-to-surface conversion. (3) The Versioning module and the Dynamizer module can add dynamic semantics to the CityGML. (4) Graph techniques and scan-to-BIM offer new perspectives for facilitating the use of CityG

Enhancing Urban Heating Systems Planning through Spatially Explicit Participatory Modeling

Effective planning of urban heating systems is crucial for achieving net-zero emissions at the city level. In particular, the spatial dimension plays a pivotal role in shaping the design and operation of these systems. Nonetheless, the integration of urban spatial and energy planning is rarely performed. To address this deficit, the current study proposes a participatory modeling methodology that explicitly incorporates the spatial dimension to facilitate integration and decision-making in the planning of urban heating systems. The methodology is applied to a case municipality to evaluate its benefits and implications for stakeholders involved in urban heat planning. The results reveal that the participatory nature of the methodology enhances the legitimacy, transparency, and relevance of the modeling process by engaging urban stakeholders, so as to exploit their valuable knowledge, experience, and understanding of the local context and related challenges. The developed methodology provides a spatial representation of district heating expansion, heating technology transition at the district-building level, and the installed capacities in each district, thereby improving the coherence of urban heat planning integrated with other urban plans. Consequently, the incorporation of the spatial dimension adds a nuanced layer of modeling outcomes to standard city level optimization models

Neural network model for building electric energy consumption forecasting in densely populated tropical areas

Electric energy consumption forecasting is a relevant issue to design and implement public policies related to energy generation and distribution at urban scale. This problem has been addressed from different standpoints, including traditional time series analysis and machine learning techniques, focused on the prediction of future energy demand according to metered data. This work proposes a hybrid model, based on computer simulation results from the City Energy Analyst toolbox and metered environmental and energy consumption data from a representative set of buildings located in Singapore. Such model is intended to provide reliable energy demand forecasts by using regression models. Three different regression methods were evaluated: a traditional SARIMA model and both NARX and Recurrent neural network architectures. The results obtained using this approach point out that RNN models provide accurate forecasts for 1 and 24 hours, outperforming NARX based models, while the SARIMA is, in general, unable to represent the electrical demand time series patterns.#SistemasDeEnergía1 recurso en línea (archivo de texto)El pronóstico del consumo de energía eléctrica es un asunto de relevancia para diseñar e implementar políticas públicas relacionadas con la generación y distribución de energía a escala urbana. Este problema ha sido abordado desde distintos frentes, incluyendo el análisis estadístico de series temporales y los modelos basados en aprendizaje de máquina, enfocándose en la predicción de la futura demanda de energía según datos tomados mediante medición directa. Este trabajo propone un modelo híbrido, que combina resultados de simulaciones obtenidas mediante el City Energy Analyst (CEA) y variables ambientales medidas junto con los datos de consumo de energía para un conjunto representativo de edificios localizados en la ciudad de Singapur. Este propuesta pretende obtener pronósticos fiables de consumo de electricidad usando modelos de regresión. Los resultados obtenidos usando esta aproximación, muestran que la configuración de redes neuronales recurrentes (RNN) proveen un pronóstico acertado para distintas ventanas de tiempo, mejorando los resultados obtenidos al usar un modelo no lineal autoregresivo con variables exógenas (NARX), mientras que los modelos autoregresivos integrados de media móvil no son capaces de representar apropiadamente los patrones de la serie de tiempo de la demanda de electricidad