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

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

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)

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

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

Modelling and Assessment of Biomass-PV Tradeoff within the Framework of the Food-Energy-Water Nexus

Food, water and energy are three essential resources for human well-being, poverty reduction and sustainable development. These resources are very much linked to one another, meaning that the actions in any one particular area often can have effects in one or both of the other areas. At the same time, an economy's shift towards climate neutrality requires a massive expansion of energy production from renewable sources. Among these ground-mounted photovoltaic (PV) and biomass will be expanded massively to meet the clean energy generation goal, simultaneously influence regional water and food availability and supply security. It is crucial to understand Food-Water-Energy Nexus (FWE) nexus during the energy transition. However, current studies have limitation both methodically (qualitative assessments) and spatially (aggregated data on a national level is more available). Firstly, a consistent share input data set in geographical format was created with the resolution of building/field. An energy simulation platform (SimStadt) was then extended with new workflows on biomass potential, ground-mounted PV potential, food demand/potential, and urban water demand. Combining with existing workflows on urban building heating/electricity demand and roof PV potential, the dissertation created a complete simulation environmental covering most-relating FWE topics in energy transition with consistent input and output structures at a fine resolution. Secondly, the most representative inter-linkage between ground-mounted PV and biomass on hinterland is investigated in details with the new tools. The output data of each field from ground-mounted PV and biomass workflows are linked and ranked according to the scenarios emphasizing PV yield, feasibility, profit, or biomass. The assessment and scenarios are applied at three representative German counties with distinguished land-use structures and geometries as case studies. Results show that current policies does not guarantee the technically efficient allocation of fields. The optimal technical strategy is to follow the individual market profit drive, which is very likely, at the same time for the social good, to achieve high PV yields with limited biomass losses and more significant crop water-saving effects. The local food, water, and energy demands are also included as a metric for resource allocation on the potential side. Besides focusing on the biomass-PV tradeoff simulation and analysis, pioneer works have also been done to test the transferability of the method in cases outside Germany, and the complement of urban solid waste to agricultural biomass is explored to achieve energy autarky

Scale aware modeling and monitoring of the urban energy chain

With energy modeling at different complexity levels for smart cities and the concurrent data availability revolution from connected devices, a steady surge in demand for spatial knowledge has been observed in the energy sector. This transformation occurs in population centers focused on efficient energy use and quality of life. Energy-related services play an essential role in this mix, as they facilitate or interact with all other city services. This trend is primarily driven by the current age of the Ger.: Energiewende or energy transition, a worldwide push towards renewable energy sources, increased energy use efficiency, and local energy production that requires precise estimates of local energy demand and production. This shift in the energy market occurs as the world becomes aware of human-induced climate change, to which the building stock has a significant contribution (40% in the European Union). At the current rate of refurbishment and building replacement, of the buildings existing in 2050 in the European Union, 75% would not be classified as energy-efficient. That means that substantial structural change in the built environment and the energy chain is required to achieve EU-wide goals concerning environmental and energy policy. These objectives provide strong motivation for this thesis work and are generally made possible by energy monitoring and modeling activities that estimate the urban energy needs and quantify the impact of refurbishment measures. To this end, a modeling library called aEneAs was developed in the scope of this thesis that can perform city-wide building energy modeling. The library performs its tasks at the level of a single building and was a first in its field, using standardized spatial energy data structures that allow for portability from one city to another. For data input, extensive use was made of digital twins provided from CAD, BIM, GIS, architectural models, and a plethora of energy data sources. The library first quantifies primary thermal energy demand and then the impact of refurbishment measures. Lastly, it estimates the potential of renewable energy production from solar radiation. aEneAs also includes network modeling components that consider energy distribution in the given context, showing a path toward data modeling and simulation required for distributed energy production at the neighborhood and district level. In order to validate modeling activities in solar radiation and green façade and roof installations, six spatial models were coupled with sensor installations. These digital twins are included in three experiments that highlight this monitoring side of the energy chain and portray energy-related use cases that utilize the spatially enabled web services SOS-SES-WNS, SensorThingsAPI, and FIWARE. To this author\u27s knowledge, this is the first work that surveys the capabilities of these three solutions in a unifying context, each having its specific design mindset. The modeling and monitoring activity and their corresponding literature review indicated gaps in scientific knowledge concerning data science in urban energy modeling. First, a lack of standardization regarding the spatial scales at which data is stored and used in urban energy modeling was observed. In order to identify the appropriate spatial levels for modeling and data aggregation, scale is explored in-depth in the given context and defined as a byproduct of resolution and extent, with ranges provided for both parameters. To that end, a survey of the encountered spatial scales and actors in six different geographical and cultural settings was performed. The information from this survey was used to put forth a standardized spatial scales definition and create a scale-dependent ontology for use in urban energy modeling. The ontology also provides spatially enabled persistent identifiers that resolve issues encountered with object relationships in modeling for inheritance, dependency, and association. The same survey also reveals two significant issues with data in urban energy modeling. These are data consistency across spatial scales and urban fabric contiguity. The impact of these issues and different solutions such as data generalization are explored in the thesis. Further advancement of scientific knowledge is provided specifically with spatial standards and spatial data infrastructure in urban energy modeling. A review of use cases in the urban energy chain and a taxonomy of the standards were carried out. These provide fundamental input for another piece of this thesis: inclusive software architecture methods that promote data integration and allow for external connectivity to modern and legacy systems. In order to reduce time-costly extraction, transformation, and load processes, databases and web services to ferry data to and from separate data sources were used. As a result, the spatial models become central linking elements of the different types of energy-related data in a novel perspective that differs from the traditional one, where spatial data tends to be non-interoperable / not linked with other data types. These distinct data fusion approaches provide flexibility in an energy chain environment with inconsistent data structures and software. Furthermore, the knowledge gathered from the experiments presented in this thesis is provided as a synopsis of good practices

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

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

DEVELOPMENT OF THE CITYGML APPLICATION DOMAIN EXTENSION ENERGY FOR URBAN ENERGY SIMULATION

ABSTRACT No widely applicable open information model standard exists until now for large-scale Urban Energy Modelling. Although different data models have been developed for different urban energy tools, they do not offer possibilities of interoperability and exchange between the stakeholders, tools and expert fields. To address this issue, an international group of urban energy simulation developers and users is developing since May 2014 an Application Domain Extension (ADE) Energy for the open urban information model CityGML. This paper introduces the Energy ADE developed and tested by this international urban energy group. Goals, requirements and the modular structure of the CityGML extension are described in detail