An Energy-Related CityGML ADE and Its Application for Heating Demand Calculation

2019 ◽  
pp. 1306-1323
Author(s):  
Marcel Bruse ◽  
Romain Nouvel ◽  
Parag Wate ◽  
Volker Kraut ◽  
Volker Coors
Keyword(s):  
Energy Demand ◽  
Building Energy ◽  
Energy Simulation ◽  
Data Sets ◽  
Application Domain ◽  
Data Formats ◽  
Building Energy Systems ◽  
Domain Extension ◽  
Energy Simulations ◽  
Heating Energy Demand

Different associated properties of city models like building geometries, building energy systems, building end uses, and building occupant behavior are usually saved in different data formats and are obtained from different data sources. Experience has shown that the integration of these data sets for the purpose of energy simulation on city scale is often cumbersome and error prone. A new application domain extension for CityGML has been developed in order to integrate energy-related figures of buildings, thermal volumes, and facades with their geometric descriptions. These energy-related figures can be parameters or results of energy simulations. The applicability of the new application domain extension has been demonstrated for heating energy demand calculation.

An Energy-Related CityGML ADE and Its Application for Heating Demand Calculation

2015 ◽  
Vol 4 (3) ◽  
pp. 59-77 ◽  
Author(s):  
Marcel Bruse ◽  
Romain Nouvel ◽  
Parag Wate ◽  
Volker Kraut ◽  
Volker Coors
Keyword(s):  
Energy Demand ◽  
Building Energy ◽  
Data Sets ◽  
Application Domain ◽  
Data Formats ◽  
Building Energy Systems ◽  
Domain Extension ◽  
Energy Simulations ◽  
Heating Energy Demand ◽  
City Models

Different associated properties of city models like building geometries, building energy systems, building end uses, and building occupant behavior are usually saved in different data formats and are obtained from different data sources. Experience has shown that the integration of these data sets for the purpose of energy simulation on city scale is often cumbersome and error prone. A new application domain extension for CityGML has been developed in order to integrate energy-related figures of buildings, thermal volumes, and facades with their geometric descriptions. These energy-related figures can be parameters or results of energy simulations. The applicability of the new application domain extension has been demonstrated for heating energy demand calculation.

scholarly journals Updated Typical Weather Years for the Energy Simulation of Buildings in Mediterranean Climate. A Case Study for Sicily

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4115 ◽  
Author(s):  
Vincenzo Costanzo ◽  
Gianpiero Evola ◽  
Marco Infantone ◽  
Luigi Marletta
Keyword(s):  
Residential Building ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Weather Station ◽  
Simulation Tools ◽  
The Difference ◽  
Energy Simulations

Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.

scholarly journals Impact Assessment for Building Energy Models Using Observed vs. Third-Party Weather Data Sets

2020 ◽  
Vol 12 (17) ◽  
pp. 6788 ◽  
Author(s):  
Eva Lucas Segarra ◽  
Germán Ramos Ruiz ◽  
Vicente Gutiérrez González ◽  
Antonis Peppas ◽  
Carlos Fernández Bandera
Keyword(s):  
Energy Demand ◽  
Meteorological Data ◽  
Building Energy ◽  
Third Party ◽  
Weather Data ◽  
Data Sets ◽  
Weather Station ◽  
Energy Models ◽  
The Impact ◽  
Energy Strategies

The use of building energy models (BEMs) is becoming increasingly widespread for assessing the suitability of energy strategies in building environments. The accuracy of the results depends not only on the fit of the energy model used, but also on the required external files, and the weather file is one of the most important. One of the sources for obtaining meteorological data for a certain period of time is through an on-site weather station; however, this is not always available due to the high costs and maintenance. This paper shows a methodology to analyze the impact on the simulation results when using an on-site weather station and the weather data calculated by a third-party provider with the purpose of studying if the data provided by the third-party can be used instead of the measured weather data. The methodology consists of three comparison analyses: weather data, energy demand, and indoor temperature. It is applied to four actual test sites located in three different locations. The energy study is analyzed at six different temporal resolutions in order to quantify how the variation in the energy demand increases as the time resolution decreases. The results showed differences up to 38% between annual and hourly time resolutions. Thanks to a sensitivity analysis, the influence of each weather parameter on the energy demand is studied, and which sensors are worth installing in an on-site weather station are determined. In these test sites, the wind speed and outdoor temperature were the most influential weather parameters.

scholarly journals Comparison between Energy Simulation and Monitoring Data in an Office Building

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 239
Author(s):  
Koldobika Martin-Escudero ◽  
Garazi Atxalandabaso ◽  
Aitor Erkoreka ◽  
Amaia Uriarte ◽  
Matteo Porta
Keyword(s):  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Energy Simulation ◽  
Office Building ◽  
Mean Bias Error ◽  
Bias Error ◽  
Data Sets ◽  
Hourly Basis ◽  
Good Agreement

One of the most important steps in the retrofitting process of a building is to understand its pre-retrofitting stage energy performance. The best choice for carrying this out is by means of a calibrated building energy simulation (BES) model. Then, the testing of different retrofitting solutions in the validated model allows for quantifying the improvements that may be obtained, in order to choose the most suitable solution. In this work, based on the available detailed building drawings, constructive details, building operational data and the data sets obtained on a minute basis (for a whole year) from a dedicated energy monitoring system, the calibration of an in-use office building energy model has been carried out. It has been possible to construct a detailed white box model based on Design Builder software. Then, comparing the model output for indoor air temperature, lighting consumption and heating consumption against the monitored data, some of the building envelope parameters and inner building inertia of the model were fine tuned to obtain fits fulfilling the ASHRAE criteria. Problems found during this fitting process and how they are solved are explained in detail. The model calibration is firstly performed on an hourly basis for a typical winter and summer week; then, the whole year results of the simulation are compared against the monitored data. The results show a good agreement for indoor temperature, lighting and heating consumption compared with the ASHRAE criteria for the mean bias error (MBE).

Building Energy Simulation with On-Site Weather Station

2016 ◽  
Vol 859 ◽  
pp. 88-92 ◽  
Author(s):  
Radu Manescu ◽  
Ioan Valentin Sita ◽  
Petru Dobra
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Building Energy Simulation ◽  
Existing Buildings ◽  
Existing Building ◽  
Simulation Tools ◽  
Heating And Cooling

Energy consumption awareness and reducing consumption are popular topics. Building energy consumption counts for almost a third of the global energy consumption and most of that is used for building heating and cooling. Building energy simulation tools are currently gaining attention and are used for optimizing the design for new and existing buildings. For O&M phase in existing buildings, the multiannual average weather data used in the simulation tools is not suitable for evaluating the performance of the building. In this study an existing building was modeled in EnergyPlus. Real on-site weather data was used for the dynamic simulation for the heating energy demand with the aim of comparing the measured energy consumption with the simulated one. The aim is to develop an early fault detection tool for building management.

scholarly journals Hacia un modelo dinámico para la isla de calor urbana de Madrid = Towards a Dynamic Model for the Urban Heat Island of Madrid.

2016 ◽  
Vol 2 (1) ◽  
pp. 49 ◽  
Author(s):  
Miguel Núñez Peiró ◽  
Emilia Román López ◽  
Carmen Sánchez-Guevara Sánchez ◽  
Francisco Javier Neila González
Keyword(s):  
Urban Heat Island ◽  
Predictive Model ◽  
Energy Demand ◽  
Building Energy ◽  
Energy Performance ◽  
Heat Island ◽  
Urban Heat ◽  
Weather Stations ◽  
Energy Simulations ◽  
The City

Resumen Esta investigación se enmarca dentro del proyecto MODIFICA (modelo predictivo - Edificios - Isla de Calor Urbano), financiado por el Programa de I + D + i Orientada a los Retos de la sociedad 'Retos Investigación' de 2013. Está dirigido a desarrollar un modelo predictivo de eficiencia energética para viviendas, bajo el efecto de isla de calor urbano (AUS) con el fin de ponerla en práctica en la evaluación de la demanda de energía real y el consumo en las viviendas. A pesar de los grandes avances que se han logrado durante los últimos años en el rendimiento energético de edificios, los archivos de tiempo utilizados en la construcción de simulaciones de energía se derivan generalmente de estaciones meteorológicas situadas en las afueras de la ciudad. Por lo tanto, el efecto de la Isla de Calor Urbano (ICU) no se considera en estos cálculos, lo que implica una importante falta de precisión. Centrado en explorar cómo incluir los fenómenos ICU, el presente trabajo recopila y analiza la dinámica por hora de la temperatura en diferentes lugares dentro de la ciudad de Madrid. Abstract This research is framed within the project MODIFICA (Predictive model - Buildings - Urban Heat Island), funded by Programa de I+D+i orientada a los retos de la sociedad 'Retos Investigación' 2013. It is aimed at developing a predictive model for dwelling energy performance under the Urban Heat Island (UHI) effect in order to implement it in the evaluation of real energy demand and consumption in dwellings. Despite great advances on building energy performance have been achieved during the last years, weather files used in building energy simulations are usually derived from weather stations placed in the outskirts of the city. Hence, Urban Heat Island (UHI) effect is not considered in this calculations, which implies an important lack of accuracy. Focused on exploring how to include the UHI phenomena, the present paper compiles and analyses the hourly dynamics of temperature in different locations within the city of Madrid. 

scholarly journals Grid-Aware Layout of Photovoltaic Panels in Sustainable Building Energy Systems

2021 ◽  
Vol 8 ◽  
Author(s):  
Luise Middelhauve ◽  
Francesco Baldi ◽  
Paul Stadler ◽  
François Maréchal
Keyword(s):  
Energy Demand ◽  
Power Grid ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy Generation ◽  
Building Energy ◽  
Solar Irradiation ◽  
Mixed Integer ◽  
Photovoltaic Panels ◽  
Building Energy Systems

In the context of increasing concern for anthropogenic CO2 emissions, the residential building sector still represents a major contributor to energy demand. The integration of renewable energy sources, and particularly of photovoltaic (PV) panels, is becoming an increasingly widespread solution for reducing the carbon footprint of building energy systems (BES). However, the volatility of the energy generation and its mismatch with the typical demand patterns are cause for concern, particularly from the viewpoint of the management of the power grid. This paper aims to show the influence of the orientation of photovoltaic panels in designing new BES and to provide support to the decision making process of optimal PV placing. The subject is addressed with a mixed integer linear optimization problem, with costs as objectives and the installation, tilt, and azimuth of PV panels as the main decision variables. Compared with existing BES optimization approaches reported in literature, the contribution of PV panels is modeled in more detail, including a more accurate solar irradiation model and the shading effect among panels. Compared with existing studies in PV modeling, the interaction between the PV panels and the remaining units of the BES, including the effects of optimal, scheduling is considered. The study is based on data from a residential district with 40 buildings in western Switzerland. The results confirm the relevant influence of PV panels’ azimuth and tilt on the performance of BES. Whereas south-orientation remains the most preferred choice, west-orientationed panels better match the demand when compared with east-orientationed panels. Apart from the benefits for individual buildings, an appropriate choice of orientation was shown to benefit the grid: rotating the panels 20° westwards can, together with an appropriate scheduling of the BES, reduce the peak power of the exchange with the power grid by 50% while increasing total cost by only 8.3%. Including the more detailed modeling of the PV energy generation demonstrated that assuming horizontal surfaces can lead to inaccuracies of up to 20% when calculating operating expenses and electricity generated, particularly for high levels of PV penetration.

scholarly journals TESTING THE NEW 3D BAG DATASET FOR ENERGY DEMAND ESTIMATION OF RESIDENTIAL BUILDINGS

2021 ◽  
Vol XLVI-4/W1-2021 ◽  
pp. 69-76
Author(s):  
C. León-Sánchez ◽  
D. Giannelli ◽  
G. Agugiaro ◽  
J. Stoter
Keyword(s):  
The Netherlands ◽  
Energy Demand ◽  
Residential Buildings ◽  
Energy Performance ◽  
Building Envelope ◽  
Simulation Software ◽  
Energy Simulation ◽  
Building Stock ◽  
Simulation Tools ◽  
Energy Simulations

Abstract. The 3D BAG v. 2.0 dataset has been recently released: it is a country-wide dataset containing all buildings in the Netherlands, modelled in multiple LoDs (LoD1.2, LoD1.3 and LoD2.2). In particular, the LoD2.2 allows differentiating between different thematic surfaces composing the building envelope. This paper describes the first steps to test and use the 3D BAG 2.0 to perform energy simulations and characterise the energy performance of the building stock. Two well-known energy simulation software packages have been tested: SimStadt and CitySim Pro. Particular care has been paid to generate a suitable, valid CityGML test dataset, located in the municipality of Rijssen-Holten in the central-eastern part of the Netherlands, that has been then used to test the energy simulation tools. Results from the simulation tools have been then stored into the 3D City Database, additionally extended to deal with the CityGML Energy ADE. The whole workflow has been checked in order to guarantee a lossless dataflow.The paper reports on the proposed workflow, the issues encountered, some solutions implemented, and what the next steps will be.

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