Article

TEASER: an open tool for urban energy modelling of building stocks

Authors:
  • Viessmann Climate Solutions
To read the full-text of this research, you can request a copy directly from the authors.

Abstract

The energy supply of buildings in urban contexts is undergoing significant changes. The increase of renewable sources for electrical and thermal energy generation will require flexible and secure supply systems. To reflect and consider these changes in energy systems and buildings, dynamic simulation is one key element. Sparse and limited access to detailed building information as well as computing time are challenges for building simulation on urban-scale. In addition, data acquisition and modelling for building performance simulation (BPS) are time-consuming and error-prone. To enable the use of BPS on urban-scale, this paper presents TEASER, an open framework for urban energy modelling of building stocks (open-source at https://github.com/RWTH-EBC/TEASER). TEASER provides an interface for multiple data sources, data enrichment and export of ready-to-run Modelica simulation models. The paper presents TEASER's methodology and package structure. Three use cases show TEASER's capabilities on the building, neighbourhood and urban scales. © 2017 International Building Performance Simulation Association (IBPSA)

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the authors.

... The library AixLib (Müller et al. 2016) is also connected to this framework and is being continuously developed further. In this publication, we present the integration of a feature for heat flow through borders between adjacent thermal zones into the so-called ReducedOrder model (ROM) of AixLib and the complimentary Python tool TEASER (Remmen et al. 2018). The motivation for this work was the possibility to enrich geometrically available data of existing buildings with typical thermal properties using TEASER, thereby enabling a workflow to create fully parameterized simulation models quickly in cases of limited (digital) data availability. ...
... For the simulation, this means that the different zones are not interconnected, which reduces calculation complexity. In practice, the TwoElement model has shown to be a good tradeoff between calculation times and accuracy (Remmen et al. 2018). Lumping to two elements is also suggested by VDI 6007-1 (2015-06), the standard on which the modelling approach of ROM is based. ...
... Generation process of Modelica models using TEASER(Remmen et al. 2018). ...
Conference Paper
Full-text available
For dynamically simulating the thermal behavior of a building, the reduced-order model (ROM) implemented in the Modelica IBPSA and AixLib libraries provides a time-efficient calculation method based on the standard VDI 6007-1. Additionally, the Python package TEASER features a possilibity to fill the model parameters with automatically generated typical and/or enriched building data. So far, both have not been capable of modelling heat flow through borders between thermal zones. In this contribution, we present the integration of this feature into the open-source software combination. Additional new features include non-constant soil temperatures and a new approach to estimate interior building elements in cases without proper knowledge. Calculation results are presented for an exemplary application and show satisfactory agreement with measured values. The respective code (including the example presented here) is in the process of being published as part of the AixLib and TEASER open-source repositiories.
... This characteristic has empowered the creation of UBEM tools like Sim-Stadt, 71 City Energy Analyst, 72 and an urban energy modeling application developed by the Georgia Institute of Technology. 73 TEASER 74 and OpenIDEAS 75 utilize Modelica libraries 76 grounded in the reduced-order calculation method, further highlighting the adaptability and advantages of this approach. ...
... Therefore, integrating and processing data into a standardized format is vital for ensuring effective interoperability among various urban energy modeling applications. Tools such as SimStadt, 82 Energy Atlas, 83 and TEASER 74 have opted for the City Geography Markup Language (CityGML) 84 to model and exchange 3D city models. On the other hand, the URBANopt analytics platform relies on GeoJSON as another standardized data format. ...
Chapter
Full-text available
Built environment is experiencing significant changes due to population growth, improved living standards, and climate change impacts. With the building sector responsible for around 40% of global energy consumption and contributing to 30% of the world's greenhouse gas emissions, it becomes crucial to scrutinize the influence of climate change on energy usage in built spaces. This chapter seeks to explore accepted methodologies and forecasts regarding shifts in building energy demand. The efforts to refine building energy estimations and consider broader contextual factors is crucial for the sustainable and adaptive development of the built environment.
... Compared to EPA and SimStadt, CEA has subsequently been adopted by researchers in different parts of the world, further improving its generalisation performance. Another open-source tool is TEASER, based on the Modelica computational engine, which provides parametric inputs for energy modelling by integrating statistical information on existing buildings and relevant standard codes, with a database covering building form, interior zoning, use functions, and envelope material properties, in addition to a simplified model for speeding up computation using the RC model (the simplified model will be discussed and reviewed in Section 4) [54]. Table 1 below lists the library parameters collected and included in the relevant regimentation tools or projects and the areas where they have gained application. ...
... The RC model is one of the most widely used grey-box models, and many packaged tools have been developed, such as TEASER [49], CitySim [101,102], OpenIDEAS [103], and the Modelica library [104], which have been demonstrated to exhibit exemplary performance in the prediction of dynamic temperatures, the calculation of cooling and heating loads for individual buildings, and other related tasks. Some of the current studies adopted TEASER or Citysim report results at the neighbourhood or city scale [54,105]. But there are still some challenges to extend the RC model from BEM to UBEM. ...
Article
Full-text available
Urban building energy modelling (UBEM) has consistently been a pivotal tool to evaluate and control a building stock’s energy consumption. There are two main approaches to build up UBEM: top-down and bottom-up. The latter is the most commonly used in engineering. The bottom-up approach includes three methods: the physical-based method, the data-driven method, and the grey-box method. The first two methods have previously received ample attention and research. The grey-box method is a modelling method that has emerged in recent years that combines the traditional physical method with the data-driven method while it aims to avoid their problems and merge their advantages. Nowadays, there are several approaches for modelling the grey-box model. However, the majority of existing reviews on grey-box methods concentrate on a specific technical approach and thus lack a comprehensive overview of modelling method perspectives. Accordingly, by conducting a comprehensive review of the literature on grey-box research in recent years, this paper classifies grey-box models into three categories from the perspective of modelling methods and provides a detailed summary of each, concluding with a synthesis of potential research opportunities in this area. The aim of this paper is to provide a foundational understanding of grey-box modelling methods for similar research, thereby removing potential barriers in the field of research methods.
... CitySim (Robinson et al., 2009) focuses on calculating heating and cooling demands; SimStadt, primarily employed for rapidly generating evaluation scenarios to assess city-scale heating requirements; City Energy Analyst (Fonseca et al., 2016), a Python-driven tool with an intuitive graphical interface, streamlines analysis of building heating and cooling loads for district energy planning. Concurrently, TEASER (Remmen et al., 2018), another Python-based application, seeks to unite UBEM and Urban System Energy Modeling, enabling a detailed representation of urban built environments and fostering an extensive understanding of city-scale energy systems; CityBES (Hong et al., 2016), a web-based platform for simulating large-scale building energy performance, aids energy benchmarking, urban planning, retrofit analysis, building management, photovoltaic potential evaluation, and urban microclimate visualization. AutoBPS , a recent UBEM tool, utilizes GeoJSON input and EnergyPlus as its engine, providing a comprehensive UBEM for residential and commercial buildings. ...
... Discussions on data source processing are prevalent in other studies as well. Remmen et al. (2018)emphasize the importance of open data in urban energy modeling, particularly in dynamic simulations and large-scale urban scenarios, through their comparative analysis of data sources. This study focuses on simplifying and optimizing a universal methodology through the fusion of multi-source data and artificial intelligence techniques, leveraging accessible open GIS information and satellite imagery to categorize buildings by type and era. ...
... The guideline, however, states that this classification may prove difficult in an accurate estimation of interior walls' embodied energy (Zertifizierungsstelle MINERGIE-ECO 2016). In the "Tool for the Energy Analysis and Simulation for Efficient Retrofit" (TEASER) (Remmen et al. 2017;Lauster 2018), the interior wall areas are estimated based on typical lengths and widths of different building usage zones stated in the Swiss Standard SIA 2024 (SIA 2006). As an extension to the TEASER framework, the software Teco employs the same estimation approach. ...
... This means that interior walls, ceilings, and floors are modeled as classes to be aggregated into a lumped thermal storage mass in the RC model. (Remmen et al. 2017). Moreover, only one thermal zone is modeled, leading to the consideration only of typical living rooms. ...
... The increasing complexity of urban energy systems has spurred the development of comprehensive frameworks for modelling and optimization. Remmen et al. [19] introduced TEASER, an open-source tool for urban energy modelling of building stocks, which integrates diverse datasets to enable scalable energy assessments. Similarly, Ferrando et al. [20] reviewed bottom-up physics-based Urban Building Energy Modelling (UBEM) tools, identifying key trends and opportunities in energy-efficient building design. ...
Preprint
Full-text available
In recent years, the approaches of living in high-rise buildings versus flat and independent buildings have their respective supporters and critics. In this article, the cooling and heating energy consumption in high-rise and flat buildings is compared, considering the comfort Fanger index. The energy consumption for heating and cooling is examined across eight different building scenarios with varying numbers of floors and three different climatic scenarios, all with consideration of the PMV comfort index. The eight scenarios include buildings ranging from a single-story flat and independent structure up to 50 floors. The three climate scenarios represent the cities of Yazd (hot), Arak (moderate), and Shahr-e Kord (cold) are modelled and compared using Design Builder software. In the results section, the details of cooling and heating load of all building and urban scenarios are presented and discussed along with the amount of Fanger comfort index and electricity and gas consumption in all days and months of the year. The results show that in terms of energy consumption, the number of common walls is more important than the number of floors, and buildings without common walls (single floors) can have 58.9% and 67.1% more load and energy consumption in heating and cooling, respectively.
... Therefore, simulation models can serve as a replacing tool to calculate heat demand profiles of buildings (e.g. [31]) and thus estimate the heat demand of the DH model. The data required to build a building simulation model can be obtained, for example, from OSM data which contains detailed geo-referenced building data and information about the building net leased area, the usage type or sometimes the year of construction, which helps to estimate the heat demand. ...
Preprint
Full-text available
District heating (DH) systems play a pivotal role in decarbonizing the building sector's heat supply. While innovative low-exergy DH and cooling systems are increasingly adopted in new developments, the transformation of existing DH systems remains critical, as many still depend on fossil-based heating plants. Achieving a sustainable heat supply necessitates integrating renewable energy and waste heat sources into current DH systems and enhancing operational efficiency through measures such as reduced supply temperatures and advanced control algorithms. These improvements can reduce costs and CO2 emissions but may require infrastructure adaptations, including pipe replacements and building-level system adjustments. This paper introduces a workflow for generating DH models using publicly available data and open-source tools. Such models enable comprehensive analyses of existing DH systems, allowing for the evaluation of sustainable heat integration, operational improvements, and the testing of analytical tools, such as simulation and optimization models. The workflow, detailed in this study, combines general structural data with computational estimations to create digital representations of DH systems. These models facilitate scenario-based analyses, tool benchmarking, and the identification of necessary infrastructure adaptations. Two example DH models generated using the proposed workflow are presented, followed by a discussion of the methodology's applicability and limitations. This study demonstrates how leveraging open data and tools can advance the transformation of DH systems, supporting the transition to a sustainable heat supply infrastructure.
... Depending on the year of construction, the building archetypes are characterized by different energy efficiency levels: younger buildings have a lower annual heating requirement, and buildings constructed after 2020 are characterized as passive houses. For each of the twelve building archetypes, an hourly heating demand time series is generated using the open-source thermal building model TEASER (Tool for Energy Analysis and Simulation for Efficient Retrofit, 27 ) and the publicly available AixLib Library 28 . The thermal building model considers the physical components of all major building elements and their thermal inertia to derive hourly heat flows inside the building and toward the ambiance (conduction, convection, and radiation). ...
Article
Full-text available
Heat pumps play a major role in decreasing fossil fuel use in heating. They increase electricity demand, but could also foster the system integration of variable renewable energy sources. We analyze three scenarios for expanding decentralized heat pumps in Germany by 2030, focusing on the role of buffer heat storage. Using an open-source power sector model, we assess costs, capacity investments, and emissions effects. We find that investments in solar photovoltaics can cost-effectively accompany the roll-out of heat pumps in case wind power expansion potentials are limited. Results further show that short-duration heat storage substantially reduces the need for firm capacity and battery storage. Larger heat storage sizes do not substantially change the results. Increasing the number of heat pumps from 1.7 to 10 million units could annually save more than half of Germany’s private and commercial natural gas consumption and around half of households’ building-related CO2 emissions.
... If the delay is not taken into consideration, errors can occur with various consequences, such as significant heat losses along the pipes due to excessively high temperatures, excessive over-sizing of the network leading to substantial investment costs, or a risk of thermal discomfort for consumers. Having an accurate understanding of the heat demand curve of buildings connected to the network is a crucial element for optimal knowledge of the network's operation, as explained by Remmen et al. (2018). Wüllhorst et al. (2022) present the various libraries available today in Modelica for modelling energy systems. ...
... This tool generates hourly demand and supply curves for each building in the neighborhood (RWTH-EBC / districtgenerator). To generate the heat demand, the TEASER tool is used (Remmen et al., 2018). Electrical loads are generated using random occupancy profiles based on the richardsonpy tool (Richardson et al., 2010). ...
Conference Paper
Energy communities can be created in neighborhoods in a geographically and structural delineated area. Local energy markets in energy communities offer a promising approach to promote local balancing of distributed power generation and consumption. These markets enable direct energy trading between prosumers and consumers, resulting in financial benefits. These benefits are dependent on local trading volumes, which can potentially be increased by shifting load profiles. Employing a price signal can enable this coordination of electricity supply and demand through the activation of operational flexibility. In this study, we develop a price signal for a local energy market utilizing price-based demand response programs. Market participants leverage the price signal for energy management to minimize their total costs. These participants can be building energy systems that feed in or purchase electricity from the grid. The price signal's determination involves a linear optimization problem that seeks to minimize the neighborhood's residual load. To estimate the potential shifts in electricity demand and supply in response to the price signal, we employ a flexibility index for the neighborhood. Given uncertainties in weather and demand forecasts, a stochastic approach is applied when optimizing the price signal. The chance constraint method is used to minimize the risk of a high residual load. We evaluate the impact of the price signal on the trading in the local energy market. Moreover, we compare the optimization-based stochastically determined price signal with a deterministically determined and a constant price signal. As a case study, we analyze a residential neighborhood in Germany with a distributed local energy market under various system technology scenarios. These scenarios result in neighborhoods with high temporal coverage or potential mismatches between generation and consumption due to generation volatility. The study analyzes firstly the influence of price signals and neighborhood characteristics on local energy market trading using selected key performance indicators. Secondly, we examine the benefits of employing a stochastically generated price signal in a system affected by uncertainties. In addition, the flexibility index and the duration of the flexibility event are further analyzed. The results indicate that implementing a price signal can lead to an increased financial benefit of up to 162 % per month for all market participants. Additionally, the supply cover factor can increase by up to 5.65 pp, allowing for the purchase of more self-generated electricity in the district. However, these effects are only achievable in districts with sufficient flexibility potential, such as extra storage, and without already existing temporal coverage of supply and demand.
... To obtain a fully parameterized building model, the TEASER tool performs a data enrichment with data from the TABULA WebTool and uses statistical and normative information about the building stock (Loga et al., 2015;Remmen et al., 2018). Finally, the TEASER python package determines the geometry and material properties of the buildings. ...
... The building is modeled using the Building Energy System Modules (BE-SMod) Modelica library [236], which builds upon existing libraries like Aixlib [111], Build-ingSystems [237], IDEAS [82], IBPSA [238], and Buildings [83]. In order to meet the heat pump's thermal capacity, the building's parameters are calculated through TEASER [239]. ...
Thesis
Full-text available
Model predictive control is a promising approach to increase energy efficiency in buildings and tackle climate change. Based on a mathematical model of the controlled system, model predictive control computes the optimal control signals minimizing a defined cost function. In building energy systems, model predictive control achieves high energy and cost savings by exploiting storage effects and weather, occupancy, and energy price forecasts. However, model predictive control still lacks widescale application in the building sector. The main reason is its high individual implementation effort. In particular, the creation of the mathematical building model is time-consuming, costly, and requires expert knowledge. This thesis facilitates the application of model predictive controllers in buildings by employing data-driven process models. These models significantly reduce the modeling effort by approximating the system’s behavior based on measurements. The main goal of this thesis is to lower the engineering effort and data requirements for successfully deploying data-driven model predictive control. Thus, a methodology to automatically translate different machine learning models in optimization syntax is introduced, enabling efficient, gradient-based numerical optimization. Artificial neural networks, Gaussian process regression, and multiple linear regression models are considered as process models. High-quality training data is crucial but often unavailable when using data-driven process models. To overcome this issue, this thesis introduces advanced learning strategies, namely (sparse) online learning, safe online learning, and physics-informed learning. The methodology is applied to two simulative and three experimental use cases. The framework generates efficient data-driven controllers in all applications, which outperform the baseline controllers. Artificial neural networks and Gaussian process regression can achieve higher accuracy when comparing the different process model types. However, controllers based on linear models are easier to tune, and the feature selection process is less critical. Thus, linear models are more suited for practical application. Considering the different learning strategies, online learning proves to be especially powerful. Online learning significantly reduces the required data and adapts the controllers to changing environmental conditions by frequently retraining the models with new data.
... The overall heat transfer coefficient, namely U ε , is the heat rate transferred per unit area per unit temperature difference between two objects. For simplicity, in Table I, the values for the product of the overall heat coefficient and the area are given, which are derived using the Python toolbox Teaser [24]. The subscripts w , r , o , and g indicate the windows, roof, outer walls, and ground, respectively. ...
Article
Full-text available
The increasing adoption of heat pumps presents new challenges for power grids, including the potential overloading of transformers and cables. To address this issue, in this work, a Model Predictive Control (MPC) for a Low-Temperature District Heating (LTDH) network is proposed to prevent the overloading of transformers and cables. A comprehensive control strategy that considers various factors influencing the flexibility of heat pumps is introduced. The considered factors include integrating Distributed Energy Resources (DER) such as a photovoltaic (PV) system, a Battery Energy Storage System (BESS), and flexible indoor temperatures. The control mechanism is validated through a Hardware-in-the-Loop (HIL) co-simulation setup, ensuring practical applicability and operational feasibility. The results indicate that with the proposed control, the power consumption of the heat pumps is reduced to alleviate overloading issues. To meet the power consumption constraints imposed on the heat pumps the gas usage by the heating grid would increase up to 506% of the level in the case without power constraints. However, by integrating DERs, along with leveraging the flexibility in indoor temperature, this additional gas usage is limited to 135%.
... Any other approach for occupancy modelling can be defined as a custom function or a plugin using the tool's respective scripting language. On the other hand, tools that are presented as an open-source framework with specified packages provide the extra option to enable users to modify the source code to describe occupants with stochastic models or processed data [21,22]. Very few UBEM tools allowed for reading schedules from CSV files, however, those that did permit this functionality did not incorporate considerations for the integration of highresolution schedules into the model's complexity or the computational power required for the simulation. ...
Article
Full-text available
In the context of electrification for different sectors, demand-side management (DSM) strategies are acknowledged as primary strategies to ensure the stability and reliability of the utility grid. Urban building energy modelling (UBEM) emerges as a critical tool for utilities to assess the impact of these strategies on the building sector's energy consumption and flexibility. However, relying on the developed models for this task is applicable only when detailed occupant-related inputs are integrated into the model. To this end, this paper aims to develop a framework to integrate high-resolution occupancy schedules into UBEM and showcase the application of the developed models in evaluating DSM strategies with different scenarios. The developed framework is applied to a mixed-use district in Montreal, Canada with 112 buildings as a case study. The main objectives of this study are 1) developing an urban scale high-resolution occupancy profile generator representative of Canadian commercial buildings using mobile positioning data, 2) investigating the diversity between the generated profiles of buildings within the same type, 3) developing a method to integrate the generated profiles into the Canadian commercial archetypes, and 4) evaluating the applicability of the developed model in evaluating DSM strategies by investigating the effect of occupant-centric control and occupancy-based demand response strategies on the modelled district energy use. The results of this study serve as a preliminary investigation into the crucial role that occupancy patterns can play in maximizing building energy flexibility with an estimated reduction in district peak demand by up to 17%. This study also paves the way for future research incorporating occupant feedback and comfort requirements for a more precise exploration of the proposed strategy.
... • Energy savings • Heating and cooling load TEASER [128] TEASER offers a platform that allows users to access various data sources, enrich data, and export Modelica simulation models that are ready for execution [136]. ...
... . (Ferrando et al. 2020) (Remmen et al. 2018) . ...
Conference Paper
Buildings significantly impact energy consumption, making energy planning and Urban Building Energy Modeling (UBEM) at the urban scale essential for sustainable development. This research emphasizes the importance of understanding and enhancing energy modeling methods at the city level, crucial for tackling global challenges like climate change and increasing energy demands. The complexities involved in city-scale modeling necessitate a comprehensive understanding of each step, which previous studies have not sequentially addressed. This study aims to fill this gap by providing a holistic view of UBEM processes. It reviews various approaches, energy modeling methods, and 8 tools used in UBEM, including geometry simplification and archetype development methods. An analysis of 54 UBEM papers from 2015 to 2023 reveals that the EnergyPlus simulation engine is most commonly used, with Grasshopper and SketchUp being popular modeling environments. Residential archetypes are the primary focus in these studies. This research contributes to urban energy planning by offering a detailed analysis of UBEM approaches and methods, steering cities towards a sustainable future.
... It estimates retrofit potentials, requiring minimal input parameters by utilizing data enrichment functionalities. The tool generates dynamic building stock models, by integrating statistical data from multiple building stock related databases, and basic user input data [37]. The EU Horizon Hotmaps project [38] developed a building stock database for all EU nations, integrating statistical databases from both residential and non-residential sectors. ...
Article
Full-text available
Modelling the performance of building stocks is crucial in facilitating the renovation at the building stock level. Bottom-up building stock modelling begins by detailing individual buildings and then aggregates them into stock level. Its primary advantage lies in capturing the inherent heterogeneity among distinct buildings, which enables tailored retrofitting. Naturally, this approach requires a comprehensive dataset with detailed building information such as geometry and envelope thermal properties. However, a common challenge is the incompleteness of available data in individual datasets. To address this, previous bottom-up studies have filled the missing data with representative or statistical data. Such practice could lead to homogeneous modelling of distinct buildings within the same statistical group. This limits the utilization of key ability of bottom-up building stock modelling in capturing heterogeneity, such as tailored retrofitting to explore potential retrofitting areas and strategies. To address this challenge of homogeneous modelling, we utilize data fusion framework for bottom-up building stock modelling, employing probabilistic record linkage and inverse modelling techniques to integrate multiple incomplete building performance datasets. This framework fills the missing data in one dataset with information from another, thus capturing inherent heterogeneity in the building stock. An empirical study was conducted in Umeå, Sweden, to investigate the framework’s effectiveness by modelling building stock with various retrofitting strategies. This study contribution lies in enhancing bottom-up building stock modelling by capturing inherent heterogeneity, to provide tailored retrofitting solutions.
... It estimates retrofit potentials, requiring minimal input parameters by utilizing data enrichment functionalities. The tool generates dynamic building stock models, by integrating statistical data from multiple building stock related databases, and basic user input data [37]. The EU Horizon Hotmaps project [38] developed a building stock database for all EU nations, integrating statistical databases from both residential and non-residential sectors. ...
... A few tools encompass aspects of the social domain (e.g., intelligent community design (iCD) [59]) and mobility issues (e.g., City Energy Analyst [60]), while the majority focus on building energy demand and supply. Some tools employ simplified dynamic modeling approaches (e.g., City Energy Analyst [61], TEASER [62]) for calculating thermal loads, while most utilize physics-based dynamic simulations to assess thermal loads (e.g., EnergyPlus [63]). A comprehensive and exhaustive classification of these tools is a highly complex task, almost equivalent to a dissertation or book. ...
Article
Positive Energy Districts (PEDs) are emerging as a new symbol for sustainable urbanism and energy transition in the built environment. The pursuit of PED development is increasingly rooted in several EU policies and initiatives , sparking discourse on the interplay between governance, technological and non-technological solutions, multiple stakeholders, and the dynamics of urban and climatic contexts. As their name suggests, PEDs are characterized by surplus renewable energy generation; however, recent developments in urban environmental science emphasize the critical need for an integrated approach to achieve the key performance indicators of the UN 17 Sustainable Development Goals (SDGs). Consequently, PED designs must dynamically integrate several stakeholders. These complexities intersect with urban challenges such as urban heat islands, microclimates, nature-based solutions integration, future climatic conditions, resource availability, social vibrancy, connectiv-ity, walkability, economic activity, and more. Current tools are fragmented, severely limiting their ability to support such a multifaceted design process. This paper describes a holistic framework for tools and methods for PED design through a set of relevant questions. Drawing upon the expertise of nine researchers with complementary practical and scientific experience in various aspects of district-scale environmental performance analysis, we offer a comprehensive overview of the scopes, methods, metrics, and toolchains for PEDs, along with available tools to integrate them into different phases of the design process. This paper highlights both the challenges and opportunities ahead, emphasizing the cutting-edge methods and tools necessary to achieve robust, resilient, and data-driven processes for PED designs in a dynamic, multi-scale, and multidisciplinary urban environment.
... The City Energy Analyst 3.35.4 (CEA) [25] is an urban building simulation computation tool for the design of low-carbon and highly efficient strategies at city scale. This tool combines knowledge of urban planning and energy systems, and, thus, allows studying the effects and synergies of urban design scenarios and energy infrastructure plans. ...
Article
Full-text available
There is currently a growing interest in lowering energy demand and, consequently, greenhouse gas emissions in all sectors. Several attempts by national governments to reduce energy demand are centered on the residential sector, since it accounts for a significant amount of the final energy demand. In order to estimate its energy demand and to evaluate the techno-economic effects of adopting energy efficiency and renewable energy technologies, there are comprehensive models suited for residential applications, since energy demand characteristics of the residential sector are complicated and interrelated. Based on these models, several tools are nowadays available to support designers and policymakers. These tools are designed to be user-friendly and to include the possibility to develop simulated scenarios for energy demand, production of CO2 emissions, and economic costs. The present study aims to offer an up-to-date extended overview of the most functional and widespread tools for the assessment of the current energy demand of the European building stock for space heating and cooling demand, both regarding open source and commercial licenses. Results highlighted the tools most commonly used by examining real applications, identifying their strengths and weaknesses and pinpointing the primary deficiencies for the benefit of future developers.
... The Tool for Energy Analysis and Simulation for Efficient Retrofit (TEASER) (Remmen et al. (2017)) is an enrichment framework for the energy modelling of building stocks. It enables the generation of Modelica models for single or multiple buildings using one of the libraries Aixlib (Müller (2016)), Buildings (Wetter et al. (2014)), BuildingSystems (Nytsch-Geusen (2016)), or IDEAS (Jorissen (2018)). ...
... The effects of material choice, substation structure, and efficient waste heat utilization on LCA calculations are also explored. The open-source tool TEASER [7] is used to calculate dynamic heat demand load profiles. ...
Article
Full-text available
The growing industry of Information and Communication technology necessitates an increase in the construction of data centers and substations that supply them with electricity at high voltage levels. The increase in the construction of data centers and therefore substations on the one hand, and their high energy consumption on the other hand, makes sustainable substation design of utmost importance to prevent environmental degradation. However, current studies often consider only the operation phase of the building and neglect other life cycle stages, resulting in biased decisions that shift the environmental problems from one stage to another that were not included in the scope of these studies. This paper investigates Life Cycle Assessment (LCA) of a typical substation located in Germany, and applies three sustainable design strategies by creating scenarios, each varying in building material composition, waste heat utilization from data centers, and incorporation of green electricity from the grid. The environmental performance of these scenarios was evaluated using the One-Click LCA. Results indicate that switching to green electricity is the most impactful strategy that reduces the Global Warming Potential (GWP) to approximately 33 % compared to the base case. In the best solution which mixed all strategies, sharp reduction of GWP to 17.5 % was achieved. The highest impactful element of the building was its structure where the major building weight and a considerable amount of concrete cause the most GWP. Furthermore, the choice of materials is mainly important because of their embodied emissions, rather than their energetic values.
... Since 5th generation heating networks can hardly be planned by classical design methods, the use of a tool chain that takes into account all relevant dynamics, is particularly valuable for this application. TEASER 2 is designed for modeling the dynamic thermal energy demands of buildings on an urban scale [3]. The high level workflow is shown in figure 2. Unlike static methods of calculating energy demands, TEASER uses a dynamic simulation model under weather and user behavior scenarios. ...
Article
Full-text available
Urban energy systems are becoming more complex due to the integration of renewable energy sources and electrification of heat supply. Dynamic planning and operation strategies are necessary to optimally satisfy energy demands, especially in the 5th generation of heating and cooling networks, which efficiently address these challenges through decentralized water-water heat pumps. An end-to-end tool chain is presented which enables to analyze and evaluate such systems in early planning phases with limited data availability. It includes thermal building simulations, heating network simulations, optimization, and incorporation capabilities for model-based operation algorithms and AI-based forecasting algorithms. User acceptance of the energy system can also be considered in the design phase in future. This paper presents the interaction of the open-source tools: TEASER, which generates high-resolution time-series of heating and cooling demands of buildings; uesgraphs, which generates and simulates thermal networks from geodata; and EHDO, which optimizes energy hub designs. Future research pathways include integrating AI-based operation optimization and surveys to support user feedback integration. Work will also address substation models for the 5th generation heating networks and novel data infrastructures. The tool chain has already been successfully used in many scenarios, but open questions remain around integrating the methods into the operation phase and further developing the complex energy models the tool chain is built upon.
Article
This study presents CityDPC, a Python library for geometric computations on CityGML and CityJSON datasets, merging features from tools such as CityATB. It supports loading, analyzing, validating, and manipulating 3D city model datasets, aiming to enhance Python applications for urban building stock analyses. It introduces a shared building class to expedite new data formats integration and improve software development and interoperability among urban‐scope applications. A novel feature is the calculation of party or shared walls, showcased in a UBEM (Urban Building Energy Modeling) context through TEASER+ integration. This demonstrates the library's utility in urban energy modeling, calculating shared walls to advance existing tools’ functionality and foster innovative urban‐scale building analysis applications.
Article
Enthalpy exchangers recovering sensible and latent heat have an increasing share of use in residential ventilation. In this study, we introduce an optimization approach for membrane-based enthalpy exchanger (MEE). Therefore, we develop a system model, combine it with a genetic optimization algorithm and optimize the design regarding energy demand and comfort. The methodology proves promising as its application to a residential building system indicates less permeable (2.68 × 10−10 mol m−1 s−1 Pa–1) and thicker membranes (75 µm) are used for moderate climates compared to cold and dry climates (2.91 × 10−10 mol m−1 s−1 Pa–1, 20 µm).
Article
Full-text available
With climate change affecting buildings differently across various local climates, there's a heightened focus on local microclimates and their impact on building energy consumption. Urban microclimates change the buildings' energy dynamics by influencing local weather patterns while building operations affect these patterns and microclimates through feedback. This paper provides a comprehensive review of tools and applications used for examining the feedback interaction between building operation and energy, and urban microclimate. This study collects, analyses, and classifies tools and applications related to Urban Building Energy Modeling (UBEM) and Urban Climate Modeling (UCM) and particularly focuses on the combination of these tools through Multi-Domain Urban Scale Energy Modeling (MD-USEM), enabling efficient information exchange between urban microclimate and building energy models. The building-microclimate exchange of information may occur as either a one-way impact or a two-way interaction, a distinction that is thoroughly examined in the final section with an in-depth analysis of the relevant literature.
Article
Full-text available
Despite all the literature on building energy management, building-stock-scale models depicting its impact for energy-market-scale optimisation models are lacking. To address this shortcoming, an open-source tool called ArchetypeBuildingModel.jl has been developed for aggregating building-stock-level data into simplified lumped-capacitance thermal models compatible with existing open-source energy-system modelling frameworks. This paper aims to demonstrate the feasibility of these simplified thermal models by comparing their performance against dedicated building simulation software, as well as examining their sensitivity to key modelling and parameter assumptions. Modelling and parameter assumptions comparable to the existing literature achieved an acceptable performance according to ASHRAE Guideline 14 across all tested buildings and nodal configurations. The most robust performance was achieved with a period of variations above 13 days and interior node depth between 0.1 and 0.2 for structural thermal mass calibrations, and with external shading coefficients between 0.6 and 1.0 and solar heat gain convective fractions between 0.4 and 0.6 for solar heat gain calibrations. Furthermore, three-plus-node lumped-capacitance thermal models are recommended when modelling buildings with structures varying in terms of thermal mass. Nevertheless, the ArchetypeBuildingModel.jl performance was found to be robust against uncertain key parameter assumptions, making it plausible for energy-market-scale applications.
Article
Full-text available
In order to reach the goal of reducing emissions by at least 55% by 2030 and achieving decarbonization by 2050, the increasing emphasis on net-zero energy buildings/districts encourages the development of advanced modelling tools to better design and manage district energy systems. This paper presents a critical review of such tools, considering the different detail level of building data and analysing the reliability of obtainable results. Initially, it elaborates on the characteristics of data resources and formats, energy demand representations of individual buildings, and the interconnection between individual buildings and districts, which are subsequently used to analyse the accuracy level of case studies. Then, the most used evaluation criteria for comparing tools arerevised. Five categories are defined: (i) input data and representation of buildings, (ii) district energy system components (i.e., generation, distribution, storage), (iii) outdoor environment, (iv) user behaviour and mobility,and (v) validation and licencing. 29 tools suitable for district energy systems modelling are critically analysed with a focus on accuracy and validation, as well as on their application and future perspectives. The results highlighted the importance of data reliability in modelling approaches and results. Difficulties in achieving accurate results included robust data acquisition, interconnection among individual buildings, outdoor environment, and modelling approaches. The results also emphasized that, although no tools can cover all the possible features at the current stage, this study can support the selection of the most suitable tool for specific applications at the district scale.
Article
Full-text available
District energy management systems (DEMS) offer the capability to harness the energy potential of districts. Currently, there is a lack of research describing the necessary underlying information systems. An overview of lessons learned is presented from a series of workshops with experts from industry, research, and further roles, predominately from Germany. Seven workshops discussing challenges within digitalization, data requirements, district energy system planning, common elements in district energy systems are conducted, ensuring long‐term operation and transferability, and validation of prior findings. Based on these discussions, insights into topics such as the key data and its requirements, typical distinctions in DEMS, their infrastructure, considerations in the information modeling, as well as challenges in data availability, are offered. These findings are mapped to a data value pipeline, illustrating key resources and tools needed to plan and operate DEMS. As demonstrated in this article, the requirements for DEMS highlight their complexity. Distinct categorizations, such as the ownership or heterogeneity in building and technologies, form the landscape of DEMS. The need for standardized, interoperable systems is often a contrast to the uniqueness of individual systems and their needs. Further adoption of the described concepts necessitates sustainable business models.
Article
Full-text available
Environmental problems due to climate change, that have been affecting our planet for years, are the main issues which prompted European Union to establish the ambitious target of achieving carbon neutrality by 2050. This occurrence encouraged all Member States to undergo significant changes of their energy sectors, favouring the extensive use of renewable energy sources. In this scenario, the European Union introduced Renewable Energy Communities, innovative energy systems based on a new model of renewable energy production, consumption and sharing, guaranteeing environmental, economic, energy and social benefits. The objective of this paper is twofold: firstly, to examine the regulatory framework of Member States and, secondly, to present a standardized procedure for the implementation of a Renewable Energy Community, an aspect not yet covered in scientific literature. The roadmap includes four main phases: a feasibility study involving an energy analysis of end users’ consumption and a general assessment; the aggregation of members as producers, consumers or prosumers forming a legal entity, considering different funding opportunities; the operating phase, involving plant construction and project validation by national authorities; the technical and economic management phase. The dynamic structure of the roadmap allows for adjustments to accommodate different regulatory contexts, member typologies and project aim.
Article
To address the increased energy demands and carbon emissions caused by global urbanization, it is imperative to seek high-performance urban design solutions. Urban form generation and optimization (UFGO) is a powerful way of supporting performance-driven urban design by strategically searching for a possible design space to approach optimal solutions. Relevant areas of urban form generative design, urban energy and environment simulation, and urban form optimization have been widely studied. However, UFGO, which integrates these parts into an effective workflow, is still an emerging and meaningful research field lacking a systematic review. We examined studies that utilized UFGO techniques for urban design at different scales and outlined the general workflow. An overview of the available methods and tools, as well as their basic principles for each step, namely, urban form generation, performance simulation, and optimization, is provided. The reader will be well versed in the key problems and technical paths of UFGO. According to the review, UFGO is technically feasible; nevertheless, existing limitations necessitate further exploration. Future studies should focus on developing userfriendly UFGO software packages for urban designers, systematic and flexible generative design methods, and efficient data-driven models for urban performance evaluation. In addition, an evaluation system for UFGO techniques is also required to facilitate comparative studies and the widespread application of UFGO techniques.
Technical Report
Full-text available
Gemäß EU-Richtlinie 2002/91/EG über die „Gesamtenergieeffizienz von Gebäuden“ müssen innerhalb weniger Jahre für einen großen Teil des deutschen Wohngebäudebestands Energieausweise ausgestellt werden. Ziel des Projekts „Kurzverfahren Energieprofil“ war die Herleitung von Vereinfachungen für die Datenaufnahme. Das im Rahmen des Projekts entwickelte Verfahren ermöglicht es, den Aufwand für die energetische Bilanzierung und Klassifizierung von Gebäuden zu reduzieren. Die Vereinfachungen betreffen drei Bereiche der Datenaufnahme: I. Flächenschätzverfahren: Durch statistische Analyse einer Gebäudestichprobe von mehr als 4000 Wohngebäuden wurde ein einfaches Verfahren zur Abschätzung der Bauteilflächen (Außenwand, Fenster, Dach, Kellerdecke) entwickelt, das als Eingangsgrößen nur die die Hüllfläche wesentlich beeinflussenden Parameter benötigt. II. Pauschale U-Werte: Auf der Basis verschiedener Quellen wurden Pauschalwerte für den Wärmedurchgangskoeffizienten (U-Wert) abgeleitet, die – ausgehend von leicht zu ermittelnden Eigenschaften des Gebäudes – eine grobe Bewertung der Qualität der thermischen Hülle von Bestandsgebäuden erlauben. III. Pauschalwerte Anlagentechnik: Auf der Basis der vorliegenden Normen zur Anlagentechnik und ergänzender Quellen wurden Pauschalwerte für die Teilsysteme Übergabe, Verteilung, Speicherung und Erzeugung abgeleitet, die in Kombination mit einem einfachen Fragebogen eine grobe Bewertung der Anlagen zur Raumheizung und Warmwasserbereitung von Bestands- Wohngebäuden erlauben. Mögliche Anwendungsbereiche für dieses „Kurzverfahren Energieprofil“ sind: • kostengünstige Erstellung von Energiepässen für große Gebäudebestände (z.B. für Unternehmen der Wohnungswirtschaft); • Durchführung von Initialberatung (Verbraucherberatung, Internet, ...); • Szenarienberechnungen für den Gebäudebestand; • Plausibilitätsprüfung bei exakter Datenerhebung.
Conference Paper
Full-text available
This paper describes a simulation model to calculate thermal energy demand of air handling units (AHU) centrally installed in buildings with focus on laboratories. The model’s design gradually supports energy demand calculations of multiple buildings, e.g. on district level. The AHU is modelled in the open source, object-oriented modelling language Modelica®. The model uses particular operation modes while neglecting dynamic transitions as this reduces computational effort to allow simulations on district level. A comparison of simulation results to experimental results, gained with a test bed at the Institute for Energy Efficient Buildings and Indoor Climate, RWTH Aachen University gives insights into the model’s accuracy. The results justify using the model in district simulations, where reduced calculation efforts outweigh acceptable deviations. Moreover, this paper presents thermal demand simulations of a research site with 195 buildings and a comparison to monitoring data. The computed hourly heating power is satisfying compared to this measured data, e.g. in terms of the coefficient of determination with a value of R²=0.939.
Conference Paper
Full-text available
In addition to the design of reduced order building models, parameterization of these models is a crucial factor for using dynamic thermal building simulations on urban scale. One approach to simplify data acquisition and model parametrization is the use of statistical data about building archetypes to enrich given individual information. The presented workflow with the software tool TEASER utilizes this approach and generates reduced order building models. This paper adds eleven residential archetype buildings to TEASER, derived from urban fabric types. A use case shows the abilities of TEASER's approach regarding rapid use case generation.
Conference Paper
Full-text available
For building performance simulations of multiple buildings, varying objectives and data availability lead to different requirements for various model applications. Flexibility regarding spatial discretization, parameterization and process automation can offer an alternative to specifically tailored models for each application. We present adaptive low order thermal network models with variable discretization regarding number of zones, number of wall elements and wall discretization. These Modelica simulation models come with parameterization processes in Python that allow data enrichment using statistical data. Process automation takes care of model generation, parallel simulation and results analysis. All models and processes are open source and freely available.
Conference Paper
Full-text available
This paper describes the collaborative development of the Annex 60 Modelica library, a free, open-source library for building and community energy systems. The library is developed within the Annex 60 project that is conducted under the umbrella of the International Energy Agency's Energy in Buildings and Communities Programme (IEA EBC). Our goal is to develop and distribute a well documented, vetted and validated open-source library that serves as the core of future building simulation programs and that can be integrated with existing programs as well. The work brings together experts in Modelica for building energy applications and coordinates the previously fragmented development that led to four libraries that were incompatible, hard to combine and each itself limited in scope. The work resulted in a library that is now used as the core of these four Modelica libraries. The paper describes the agreed upon requirements, scope, current status of implementation, quality control process and structure of the library. The paper also provides illustrative examples.
Conference Paper
Full-text available
Sustainable use and management of energy resources is a challenging task for growing urban population. Especially, an urban environment in temperate continental climate consumes high energy resources for their space heating and domestic hot water demands. Assessment of thermal energy requirements for future energy demands is fundamental to sustainable urban environment. Thermal energy demand can be simulated using physical and empirical laws from building physics domain. Physical laws compute thermal energy consumption based on heterogeneous datasets from various data sources. These datasets may include information from cadastre, building registers, inhabitant census, 3D building models, ground surveys and meteorological databases. Furthermore, depending upon availability, accessibility and level of detail, specific simulation methods are usually employed for evaluation of energy consumption at different spatial scales. This paper attempts to identify input data parameters which could facilitate validation and calibration of thermal energy demand based on input data sensitivity using simulation methods.
Article
Full-text available
Over the past decades, detailed individual building energy models (BEM) on the one side and regional and country-level building stock models on the other side have become established modes of analysis for building designers and energy policy makers, respectively. More recently, these two toolsets have begun to merge into hybrid methods that are meant to analyze the energy performance of neighborhoods, i.e. several dozens to thousands of buildings. This paper reviews emerging simulation methods and implementation workflows for such bottom-up urban building energy models (UBEM). Simulation input organization, thermal model generation and execution, as well as result validation, are discussed successively and an outlook for future developments is presented.
Conference Paper
Full-text available
There are different options for modelling indoor and outdoor long-wave radiation exchange in thermal building models for simulations at urban scale. For improving these building models, a good trade-off between accuracy and simulation time is a major challenge. To evaluate different radiation models for thermal network building models, we compared four outdoor radiation and two indoor radiation models. For the comparison, we setup three test cases on a generic room and a single family dwelling and analysed surface temperatures, heat demands, and simulation times. The results favoured an outdoor radiation exchange model according to the German Guideline VDI 6007 with modified parameter calculations. It includes important simplifications that lead to short computing time while keeping a sufficient accuracy. For indoor radiation exchange modelling at constant temperatures, a linear approach significantly reduces simulation time without any major accuracy losses.
Conference Paper
Full-text available
Low Order Models (LOM) for thermal building simulations on urban scale exist in parallel to extensively used Higher Order Models (HOM) for thermal simulations of single buildings. However, a comparison of a HOM in IDA-ICE and a LOM in Dymola revealed optimization potential regarding heat conduction through windows and indoor radiation exchange for the LOM. Two test cases proved a phase shift in heat load prediction for a LOM based on the guideline VDI 6007. Therefore, we implemented further resistances which lead to slightly increased calculation time. Nevertheless, this improved model is well balanced regarding computational effort and simulation accuracy. Vereinfachte Modelle niederer Ordnung für thermische Simulationen von ganzen Stadtteilen existieren parallel zu Modellen höherer Ordnung, die vor allem auf Gebäudeebene zum Einsatz kommen. Ein Vergleich von Wärmebedarfssimulationen eines komplexen Modells in IDA-ICE und eines vereinfachten Ansatzes in Dymola offenbart Verbesserungspotential bezüglich der Wärmeleitung durch Fenster und dem Strahlungsaustausch im Innenraum. In zwei Testfällen zeigt sich unter anderem eine Phasenverschiebung für ein Modell niederer Ordnung basierend auf der VDI 6007. Diese Verschiebung kann durch die Einführung zusätzlicher thermischer Widerstände behoben werden, was allerdings zu leicht erhöhten Rechenzeiten führt. Nichtsdestotrotz stellt das entwickelte Modell eine gute Balance zwischen Rechenaufwand und Genauigkeit dar.
Conference Paper
Full-text available
Urbanization causes increasing energy demand within cites. To identify energy saving potentials on city district scale, integral planning approaches are necessary. This paper describes the development of a city information model (CIM) with focus on buildings and energy systems. It accounts for different building and energy system types plus geometry, building physics as well as occupant information. The CIM structure has been implemented on a PostgreSQL database (DB), which has been linked to a geographic information system (GIS) to enable graphical data analysis and modification. Considering data uncertainty, the CIM structure supports a simplified city district modeling. Within a case study, DB and a Python tool are used to parameterize buildings for dynamic simulations to estimate the state of retrofit.
Conference Paper
Full-text available
The current climate and environmental policy efforts require comprehensive planning regarding the upgrade of the energy supply and infrastructures in cities. Planning comprises e.g. the determination of locations for new power generating facilities like photovoltaic, geothermal and decentralized combined heat and power stations, the widespread introduction of e-mobility solutions and hence the grid development as well as large-scale energetic building refurbishments. A holistic approach integrating extensive complex information is essential for the strategic planning of the different measures. In order to establish interoperability and data exchange between the different planners, stakeholders, and tools, an open information standard is required. To answer this need, an international group of urban energy simulation developers, geo-information scientists and users from 11 European organizations is developing an Application Domain Extension (ADE) Energy for the OGC open standard CityGML. This paper presents the collaborative development of this new open urban information model, including its genesis, objectives, structure and next planned steps.
Article
Full-text available
The present climate and environmental policy efforts require comprehensive planning regarding the modification of the energy supply and infrastructures in cities. The strategic planning of the different measures requires a holistic approach and the combination of extensive and complex information. Within this paper, current developments in the context of the project Energy Atlas Berlin are presented. The Energy Atlas Berlin is based on the semantic information model of CityGML and provides an integrative data backbone for the common spatio-semantic representation of the city structure including energy related information of different themes. The virtual 3D city model of Berlin (mainly LOD2 building models) is used as data basis and has been enriched by information of different stakeholders and disciplines. In order to ensure the energy supply, the knowledge about the energy demands of buildings during the planning and optimization of measures is of great strategic importance. Therefore, this paper focuses on the city-wide estimation of the energy demands of buildings including heating, electricity and warm water energy in the city of Berlin using available official geobase and statistical data integrated within the Energy Atlas Berlin. It is explained in detail how the spatial and semantic properties of the 3D building models are being used to estimate these energy demands on an individual building level for the entire city.
Article
Full-text available
Many cities today are committed to increasing the energy efficiency of buildings and the fraction of renewables. However, quantitative data on urban energy performance are rarely available during the design stage of new towns or for rehabilitation scenarios of existing cities. Three dimensional city models based on the spatio-semantic data format CityGML offer powerful new methods for the quantitative evaluation of urban energy demand and costs, and simultaneously allow the simulation of renewable energy systems. Such a 'semantically enriched' models was used in this work for energy demand diagnostics, refurbishment forecast and renewable supply scenarios. A case study was done using this method in an existing urban quarter in Ludwigsburg/Germany. Based on its three dimensional representation, the photovoltaic potential has been calculated and compared with the electricity demand to establish the photovoltaic fraction. On the thermal side, the passive solar gains were simulated for each building in the city quarter to analyse the solar contribution for heating demand reduction. The simulations were validated with measured gas consumptions. Some rehabilitation scenarios have also been simulated. In such a moderately dense post-war district, the calculated energy savings potential reach in total 65%, equally distributed between heat savings following building envelope refurbishment, and electricity savings due to the installation of PV on the roofs.
Conference Paper
Full-text available
The housing sector has a significant energy savings potential achievable by retrofitting, however overheating might become a drawback in summer especially under the effect of climate change and urban heat island and should be properly considered in sustainable urban plans. This study aims at estimating the combined effect of retrofit measures on heating energy demand and indoor thermal comfort of housing stocks at the urban scale. A bottom-up approach was developed based on Geographical Information Systems, dynamic thermal simulation and indoor thermal comfort analysis. The study provided relevant results for Rotterdam city (Netherlands) to support sustainable urban planning.
Book
Full-text available
Effective building performance simulation can reduce the environmental impact of the built environment, improve indoor quality and productivity, and facilitate future innovation and technological progress in construction. It draws on many disciplines, including physics, mathematics, material science, biophysics, human behavioural, environmental and computational sciences. The discipline itself is continuously evolving and maturing, and improvements in model robustness and fidelity are constantly being made. This has sparked a new agenda focusing on the effectiveness of simulation in building life cycle processes. Building Performance Simulation for Design and Operation begins with an introduction to the concepts of performance indicators and targets, followed by a discussion on the role of building simulation in performance based building design and operation. This sets the ground for in-depth discussion of performance prediction for energy demand, indoor environmental quality (including thermal, visual, indoor air quality and moisture phenomena), HVAC and renewable system performance, urban level modelling, building operational optimization and automation. Produced in cooperation with the International Building Performance Simulation Association (IBPSA), this book provides a unique and comprehensive overview of building performance simulation for the complete building life-cycle from conception to demolition. It is primarily intended for advanced students in building services engineering, and in architectural, environmental or mechanical engineering; and will be useful for building and systems designers and operators.
Article
Full-text available
We propose and describe a method for the estimation of the energetic rehabilitation state of buildings. It combines a virtual 3D city model with real measured heating energy data in order to determine energetic relevant building characteristics. Among these characteristics are, e.g., the volume, the assignable area, the building type or the surface-to-volume ratio (S/V). Using these values the energy consumption characteristic, which is normally given in kWh/m 2 , can be calculated. This allows to classify a building into predefined heating classes. Additionally, an estimation of the energy consumption of buildings is calculated on the basis of building typologies and is compared to the real consumption values. Using these results, estimations of the energetic rehabilitation are derived.
Technical Report
Full-text available
Simple method for calculating the energy consumption for heating and domestic hot water for residential buildings
Conference Paper
Full-text available
This paper presents a Simulation Domain Model (SimModel) -a new interoperable XML-based data model for the building simulation domain. SimModel provides a consistent data model across all aspects of the building simulation process, thus preventing information loss. The model accounts for new simulation tool architectures, existing and future systems, components and features. In addition, it is a multi-representation model that enables integrated geometric and MEP simulation configuration data. The SimModel objects ontology moves away from tool-specific, non-standard nomenclature by implementing an industry-validated terminology aligned with Industry Foundation Classes (IFC). The first implementation of SimModel supports translations from IDD, Open Studio IDD, gbXML and IFC. In addition, the EnergyPlus Graphic User Interface (GUI) employs SimModel as its internal data model. Ultimately, SimModel will form the basis for a new IFC Model View Definition (MVD) that will enable data exchange from HVAC Design applications to Energy Analysis applications. Extensions to SimModel could easily support other data formats and simulations (e.g. Radiance, COMFEN, etc.).
Conference Paper
Full-text available
As automatic sensing and Information and Communication Technology (ICT) get cheaper, building monitoring data is easier to obtain. The abundance of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes ongoing developments and first results of data-driven grey-box modelling for buildings. A Python toolbox is developed based on a Modelica library with thermal building and Heating, Ventilation and Air-Conditioning (HVAC) models and the optimisation framework in JModelica.org. The tool chain facilitates and automates the different steps in the system identification procedure, like data handling, model selection, parameter estimation and validation. The results of a system identification and parameter estimation for a singlefamily dwelling are presented.
Article
Full-text available
There are many sophisticated building simulators capable of accurately modelling the thermal performance of buildings. Lumped Parameter Models (LPMs) are an alternative which, due to their shorter computational time, can be used where many runs are needed, for example when completing computer-based optimisation. In this paper, a new, more accurate, analytic method is presented for creating the parameters of a second order LPM, consisting of three resistors and two capacitors, that can be used to represent multi-layered constructions. The method to create this LPM is more intuitive than the alternatives in the literature and has been named the Dominant Layer Model. This new method does not require complex numerical operations, but is obtained using a simple analysis of the relative influence of the different layers within a construction on its overall dynamic behaviour. The method has been used to compare the dynamic response of four different typical constructions of varying thickness and materials as well as two more complex constructions as a proof of concept. When compared with a model that truthfully represents all layers in the construction, the new method is largely accurate and outperforms the only other model in the literature obtained with an analytical method.
Article
Full-text available
This paper presents the development of an energy and carbon model of existing dwellings and its application to urban housing. The model is used to predict the energy use and CO2 emissions of the housing stock of the city of Leicester, UK, and to estimate the effect of energy efficiency interventions. It is shown that a high level of energy efficiency interventions has the potential to reduce overall CO2 emissions by around 41%. The model methodology is discussed and potential improvements are explored.
Article
Full-text available
Many of the popular building energy simulation programs around the world are reaching maturity — some use simulation methods (and even code) that originated in the 1960s. For more than two decades, the US government supported development of two hourly building energy simulation programs, BLAST and DOE-2. Designed in the days of mainframe computers, expanding their capabilities further has become difficult, time-consuming, and expensive. At the same time, the 30 years have seen significant advances in analysis and computational methods and power — providing an opportunity for significant improvement in these tools.In 1996, a US federal agency began developing a new building energy simulation tool, EnergyPlus, building on development experience with two existing programs: DOE-2 and BLAST. EnergyPlus includes a number of innovative simulation features — such as variable time steps, user-configurable modular systems that are integrated with a heat and mass balance-based zone simulation — and input and output data structures tailored to facilitate third party module and interface development. Other planned simulation capabilities include multizone airflow, and electric power and solar thermal and photovoltaic simulation. Beta testing of EnergyPlus began in late 1999 and the first release is scheduled for early 2001.
Conference Paper
Full-text available
In this paper we describe new software “CitySim” that has been conceived to support the more sustainable planning of urban settlements. This first version focuses on simulating buildings’ energy flows, but work is also under way to model energy embodied in materials as well as the flows of water and waste and inter-relationships between these flows; likewise their dependence on the urban climate. We discuss this as well as progress that has been made to optimise urban resource flows using evolutionary algorithms. But this is only part of the picture. It is also important to take into consideration the transportation of goods and people between buildings. To this end we also discuss work that is underway to couple CitySim with a micro-simulation model of urban transportation: MATSim.
Article
Full-text available
Computer modelling at the urban scale is an increasingly vibrant area of research activity which aims to support designers to optimise the performance of new and existing urban developments. But the parameter space of an urban development is infinitely large, so that the probability of identifying an optimal configuration of urban design variables with say energy minimisation as a goal function is correspondingly small. To resolve this we have coupled a micro-simulation model of urban energy flows CitySim with a new evolutionary algorithm (EA): a hybrid of the CMA-ES and HDE algorithms. In this paper we present the means of coupling the EA and CitySim and identify a subset of urban design variables that have been parameterised. We then present results from application of this new methodology to minimise the energy demand of part of a case-study district in the city of Basel, Switzerland. The papers closes by discussing work that is planned to further increase the scope of this new methodology for optimising urban sustainability.
Article
Significant research effort has gone into developing urban building energy modeling (UBEM) tools, which allow evaluating district-wide energy demand and supply strategies. In order to characterize simulation inputs for UBEM, buildings are typically grouped into representative “archetypes”. This simplification reduces the real diversity of usage patterns, potentially leading to results that misrepresent energy demands. Unfortunately, very little research has focused on identifying the impact of such process in the effectiveness of an UBEM to reliably predict savings from retrofit measures. This paper analyzes two deterministic common approaches for the definition of building archetypes in UBEM, and proposes a probabilistic third method based on the characterization of uncertain parameters related to building occupancy using measured energy data. Frequency distributions for number of occupants, lighting power and cooling set points are generated through parametric simulation of an urban sample, later used for Monte Carlo (MC) simulation of retrofit scenarios. Measured data for the yearly energy use of one hundred and forty residential buildings in Kuwait city is used as a case study for the evaluation of the three methods. Results for the proposed probabilistic method suggest a significant improvement in the fit of the model to the measured energy use distribution.
Article
In many urban contexts, energy systems are undergoing fundamental change towards more interconnected system layouts. Appropriate planning tools are necessary to guide this transition towards more energy efficient system designs. Thus, the aim of this paper is to present workflow automation approaches to model buildings and district energy systems for dynamic simulation and integral system analyses. For data collection and management, we use a Geographic Information System coupled with a PostgreSQL database. In this paper, we present the software tools TEASER and uesmodels which use this data to automatically generate dynamic building and district energy system models in the modeling language Modelica. To demonstrate the application of these tools for workflow automation, we analyze a university campus with 39 buildings. In one scenario, an optimization led to an improved heating curve, with which yearly primary energy demand in the model was reduced by 0.9%. In a second scenario, the retrofitting of all building envelopes in the district energy system reduced primary energy demand by 16.0%. These examples showed that the presented approach is suited to evaluate options for improving district energy system, ranging from improved operation to changes in system design, and a combination of both.
Article
The increasing installation of volatile renewable energy sources like photovoltaics and wind enforces the need for flexibility options to match the renewable generation with the demand. One of these options is Demand Side Management (DSM) in the context of building energy systems combined with thermal storage systems. This paper discusses such concepts for DSM. A method for analyzing the flexibility that is needed to maintain the stability of the electrical grid is presented followed by the restrictions that are caused by meeting the heat demand and satisfying the comfort criteria of the residents. Approaches for simultaneously fulfilling these constraints as well as matching the flexibility needs of the electrical grid and the flexibility provided by the local building energy systems are discussed. To enhance the analysis options for the shown systems, a simulation platform that covers the electrical grid simulation, the building systems’ simulation and the control strategies is presented. This platform can be used to analyze different scenarios of building energy systems with different penetrations of renewable energy sources and different building types.
Article
This paper describes the methodology developed and the calculation steps used to evaluate the energy efficiency potential of office buildings. The methodology enables a detailed analysis of retrofit options for the building envelope and its energy supply system. Different simplification measures accelerate the data acquisition process for office building stock owners and allow a data handling according to the existing building information, thus enabling office building structures to be prompted to design typical building constructions. We implement solutions enabling both a time-saving accelerated data input for office buildings and the handling of incomplete data. An automated calculation of the most common refurbishment measures allows a comparison of up to 64 combinations of measures, the illustration of energy and CO2 savings, and an economic evaluation. The latter takes into account the time value of money, the uncertainty of future energy prices, and the possibility of delaying an investment. To this end, a net present value analysis and a real options analysis are implemented, enabling a comparison of retrofit alternatives with different initial and future cash flows both for buildings occupied by the investor (owner-occupier perspective) and for rented buildings (tenant perspective). Energy price scenarios as well as a Monte Carlo simulation account for the uncertainty in energy price trends. For a university building used as a test case, the simplified and time-saving data input methods were successfully tested and an automated evaluation of 64 typical retrofit combinations carried out. The results of the energy, ecological and economic efficiency evaluation shows that a generally preferred retrofit option cannot always be identified. Specifically, for the test case, the best-rated economic refurbishment possibility leads to the largest increase in final energy demand amongst all options considered, which points out the necessity of a multi-criteria evaluation.
Article
This paper describes a building model designed for an urban energy simulation tool. In this context, trade-off between computing time and result precision is particularly important. Our methodology involves physical simplifications and model order reduction. The physical simplications are achieved by using equivalent envelopes, linearization scheme and pre-processing, so that a Modelica detailed model can be derived into a linear and time-invariant system using fewer component models. Balanced realization reduction can then be applied on such systems leading finally to a 6-order model. Effects of the simplification and reduction on heating and cooling loads are evaluated using typical building envelope cases. Results show that the simplifications and reduction induce errors under 1% in annual energy consumption and a maximum of 3% in instantaneous values but are accurate enough to reproduce dynamics of the detailed model. Additionally, the final reduced model uses a simple numerical solver and runs in less than 1 s without compromising precision for hourly annual simulations being 700 times faster than the detailed model, which is promising for use in urban energy simulation.
Article
Am Lehrstuhl für Versorgungsplanung und Versorgungstechnik der UdK Berlin wird die Modelica-Modellbibliothek “BuildingSystems“ zur objektorientierten Modellierung und Simulation komplexer energietechnischer Gebäudesysteme entwickelt. Die Modelle der Bibliothek decken ein breites Spektrum aus den Bereichen Raum und Gebäude, solare Energietechnik (Solarthermie, Photovoltaik) sowie Heizungs- und Klimatechnik ab und werden um weitere Spezialmodelle zum Erzeugen geeigneter Klima- und Nutzer-Randbedingungen ergänzt. Ein besonderes Merkmal der Bibliothek besteht darin, dass eine Reihe der Modelle in unterschiedlicher räumlicher oder physikalischer Detaillierungstiefe vorliegen. So lässt sich mit der Modellbibliothek ein Nahwärmenetz mit einer Reihe stark vereinfachter Gebäudeverbraucher-Modelle, aber auch ein detailliertes hydraulisches Netz einer Heizungsanlage zusammen mit einem detaillierten Mehrzonen-Gebäudemodell abbilden. Im vorliegenden Beitrag werden die grundlegenden Eigenschaften der Modelica-Bibliothek “BuildingSystems“ beschrieben und an Hand mehrerer Anwendungsbeispiele demonstriert.
Article
Retrofit actions applied to the existent building stock aim at increasing the energy performance, considering the optimal trade-off between energy savings and costs, according to the Directive 2010/31/EU. To select effective refurbishment measures and to quantify the energy saving potentials of the existent building stock, the analysis should be performed on “reference buildings”. This article presents a methodology for the identification of reference buildings, according to the IEE-TABULA project (2009–12) aimed at creating a harmonised structure for “European Building Typologies”. Among the possible applications of the building typology, this work focuses on the potentialities of energy savings and CO2 emission reductions for the European residential building stock. In particular, the Italian approach to model the energy balance of a subset of the national building stock is described; the results show the enormous potentialities of energy savings even with basic energy retrofit actions. Cost analyses were not in the scope of the project, but the results of this study are the basis for further investigations aimed at assessing the cost effectiveness of sets of measures. In this regard, the TABULA building-types are being applied by the Italian government for calculating cost-optimal levels of energy performance, complying with the Directive 2010/31/EU objectives.