Publications
This page lists publications using CEA as the urban building energy modeling engine in their methods. We aim to include all such publications. If yours is missing here, please fill in the form below to inform us about your work.
2023
Shi, Z., Silvennoinen, H., Chadzynski, A., von Richthofen, A., Kraft, M., Cairns, S., & Hertogs, H. (2023) Defining archetypes of mixed-use developments using Google Maps API data. Environment and Planning B: Urban Analytics and City Science 50 (6), 1607-1623.
This publication answered the question - what mixed-use really mean? - in urban building energy modelling using a machine-learning technique. It output archetypes of mixed-use profiles for Singapore’s mixed-use land parcels.
2022
This publication conducted energy demand analysis using CEA in representative urban, suburban, rural swiss communities. It showed that Swiss suburban communities exhibit the largest uncertainty in energy demand predictions.
Argyris, O., Hsieh, S., and Schlueter, A (2022) Energy Futures of Representative Swiss Communities under the Influence of Urban Development, Building Retrofit, and Climate Change. Sustainable Cities and Society 91 : 104437.
Popova, A., Hsieh, S., and Schlueter, S. (2022) Methodology for Scenario-Based Analysis of Future Energy Performance of Swiss Settlements at Urban, Sub-Urban, and Rural Scale. 36th PLEA Conference for Sustainable Architecture and Urban Design (PLEA STGO 2022), Santiago, Chile, November 22-25, 2022
This publication explored possible future urban development scenarios and assessed them using CEA.
2021
Mosteiro-Romero, M. and Schlueter, S. (2021) Effects of Occupants and Local Air Temperatures as Sources of Stochastic Uncertainty in District Energy System Modeling
This paper was to quantify the effects of two of the main sources of stochastic uncertainty, namely building occupants and urban microclimate, on electrical and thermal supply system sizing at the district scale.
Bello Acosta, J. A. (2021). Neural network model for building electric energy consumption forecasting in densely populated tropical areas. Master Thesis. Universidad de Bogotá Jorge Tadeo Lozano, Colombia.
This thesis proposes a hybrid model, based on CEA simulation results and metered data, to provide reliable energy demand forecasts by using regression models. Three regression methods, SARIMA, NARX, and RNN were evaluated.
2020
Happle, G. (2020) Data-driven Occupant Presence Models for Urban Building Energy Simulation. Doctoral Thesis. ETH Zürich, Zürich, Switzerland.
This thesis presents various data-driven methods to derive occupant presence in buildings and applies them in CEA simulations.
Mosteiro-Romero, M. (2020) Stochastic sources of uncertainty in urban energy systems: occupancy and microclimate. Doctoral Thesis. ETH Zürich, Zürich, Switzerland.
This thesis presents methods to analyze the effects of uncertainty in urban energy demand and supply systems using CEA.
Shi, Z. (2020) Energy-driven urban design at the district scale for tropical high-density cities. Doctoral Thesis. ETH Zürich, Zürich, Switzerland.
This thesis defines the concept of energy-driven urban design and presents a five-step approach using CEA applied to Singapore.
This report presents a model that can represent household energy consumption pre-intervention using observed and synthetic data. CEA is used to provide the synthetic data of 101 households in Singapore.
Fonseca, J. A. (2020). BSTS-SG: An ensemble timeseries model for the evaluation of energy conservation strategies in households. In Deliverable Technical Report: Vol. D1.2.2.6 [Report]. ETH Zurich.
This study addresses the economic and environmental viability of district cooling for different district types in Singapore. The 41 sample districts are simulated using CEA.
This publication connects CEA to ENVI-met for analysis of micro-climate. The results are presented for a case study in Zurich-CH.
Riegelbauer, E., Santos, L. G. R., Singh, V. K., & Nevat, I. (2020). Potential of District Cooling in Singapore: From Micro to Mesoscale [Report]. ETH Zurich.
Mosteiro-Romero, M., Maiullari, D., Pijpers-van Esch, M., & Schlueter, A. (2020) An Integrated Microclimate-Energy Demand Simulation Method for the Assessment of Urban Districts. Frontiers in Built Environment 6:553946.
In this publication data-driven urban occupant presence models are developed and applied in CEA to analyze a case study in Singapore.
Happle, G., Fonseca, J. A., & Schlueter, A. (2020) Impacts of diversity in commercial building occupancy profiles on district energy demand and supply. Applied Energy 277: 115594.
This publication describes the detailed thermal network model in CEA and tests it on a planned free cooling in Zurich-CH.
Mosteiro-Romero, M., Riegelbauer, E., Hsieh, S., & Schlueter, A. (2020) District-scale lake water free cooling for a case study in Zurich, Switzerland: System performance simulation and techno-economic feasibility. ECOS 2020, 29 June–3 July 2020, Osaka, Japan.
This publication presents an occupancy modeling approach and implements it on CEA to analyze a case study in Zurich-CH.
Mosteiro-Romero, M., Hischier, I., Fonseca, J. A., & Schlueter, A. (2020) A novel population-based occupancy modeling approach for district-scale simulations compared to standard-based methods. Building and Environment 181: 107084.
This thesis explores the interdependence and quantifies the tradeoffs between district energy performance and urban design parameters. CEA is used to assess the energy performance of 10’000 district designs in Singapore.
Popova (Bosova), A. (2020) Heuristics for the design of low-carbon districts in the tropics. Master Thesis. ETH Zürich, Zürich, Switzerland.
The publication studies the interdependency between street grids and the efficiency of district cooling systems in Singapore.
Shi, Z., Hsieh, S., Fonseca, J. A., & Schlueter, A. (2020) Street grids for efficient district cooling systems in high-density cities. Sustainable Cities and Society 60: 102224.
2019
This report presents a toolset including CEA for the development of energy-efficient urban areas and tests it in case studies in Zurich-CH, Almere-NL, and Bergen-NO.
Maiullari, D., Mosteiro Romero, M., de Koning, R., Van Timmeren, A., Van Nes, A., & Schlueter, A. (2019) SPACERGY: Space-Energy Patterns for Smart Energy Infrastructures, Community Reciprocities and Related Governance. BK Books, Delft, Netherlands.
This publication proposes a hybrid model based on computer simulation results from CEA and metered environmental and energy consumption data in Singapore.
Bello, J. A., Franco, H., & Fonseca, J.A. (2020) Hybrid Model for Energy Consumption Forecasting in Buildings Stocks at Tropical Regions. IBPSA 2019, September 2019, Rome, Italy.
This paper presents an agent-based model to analyze the dynamic levels of adoption of individual and community PV systems. CEA is used to generate energy demand data for 2000 building blocks in Zurich-CH.
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Mehta, P., Griego, D., Núñez-Jiménez, A., & Schlueter, A. (2020) The Impact of self-consumption regulation on individual and community solar PV adoption in Switzerland: an agent-based model. Journal of Physics: Conference Series 1343: 012143.
This publication uses LCA, urban building energy simulations and urban form generation to compare the operational emissions of buildings with BIPV in Southeast Asia.
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Happle, G., Shi, Z., Hsieh, S., Ong, B. L., Fonseca, J. A., & Schlueter, A. (2019) Identifying carbon emission reduction potentials of BIPV in high-density cities in Southeast Asia. Journal of Physics: Conference Series 1343: 012077.
This paper presents an analysis of the effects of microclimate on building energy demand in a residential district in Almere-NL.
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Mosteiro-Romero, M., Maiullari, D., Collins, F., Schlueter, A. and Van Timmeren, A. (2019) District-scale energy demand modeling and urban microclimate: A case study in The Netherlands. Journal of Physics: Conference Series 1343:012003
This publication creates a database for the lifecycle assessment of BIPV for CEA. The results are presented in a case study in Singapore.
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Ong, B. L. (2019). Life Cycle Assessment of Building Integrated Photovoltaic (BIPV) system in urban high-rise buildings in Singapore. Master thesis. Technical University of Berlin.
This publication assesses the economic and environmental feasibility of a planned district cooling network in Zürich-CH for different scenarios. CEA is used both for energy demand estimation as well as thermal network modeling.
Riegelbauer, E. (2019). Should lake water cool the HGZZ? A feasibility study using the City Energy Analyst. Semester project. ETH Zürich.
This publication creates a database for the energy demand modeling of buildings in the Netherlands. The results are presented in a case study in Almere.
Collins, F. (2019). District-scale energy demand modelling of a residential area in Almere, Netherlands. Semester project. ETH Zürich.
This publication applies the CEA network layout and simulation tools to compare a planned district cooling network in Zurich-CH to a network using the minimum Steiner tree.
Motie, M. (2019). District heating and cooling network layout analysis and optimization. Semester project. ETH Zürich.
2018
This publication highlights CEA as one of the key tools for Cooling Singapore.
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Pignatta, G. (2018). Tools for Cooling Singapore. A Guide of 20+ Simulation Tools to Assess Urban Heat Island and Outdoor Thermal Comfort. Singapore.
This publication connects CEA to ENVI-met for analysis of micro-climate. The results are presented for a case study in Zurich-CH.
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Maiullari, D., Mosteiro-Romero, M., and Pijpers-van Esch, M. (2018) Urban Microclimate and Energy Performance: An Integrated Simulation Method. PLEA 2018, 10-12 December 2018, Hong Kong
This publication showcases a new thermal-hydraulic model in CEA. The method is exemplified in a case study in Singapore.
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Rogenhofer, L., (2018). Thermal and hydraulic modelling and optimization of thermal networks in districts in the CEA framework. Master thesis. ETH Zurich.
In this publication CEA is used to estimate demand profiles for the optimisation of BIPV. The results are presented in a case study in Zurich-CH.
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Szczesniak, J. (2018). Optimal Integration of BIPV at the Community and Building Scale. Semester project. ETH Zurich.
In this publication the advantages and limitations of CEA are described in the context of integration of PV.
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Python, S., (2018). Modelling approach of a large scale district for the final objective to analyse the self-consumption of PV-produced electrical energy. Semester project. ETH Zurich.
2017
In this publication CEA is used to estimate the potential of PV. The results are presented in a case study in Zurich-CH.
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Mehta, P. (2017). Evaluation of Community Scale PV based on Spatio-temporal Energy Demand & Supply Profiles. Semester project. ETH Zurich.
In this publication CEA is used to model stochastic and deterministic models of air infiltration. The results are presented in a case study in Singapore.
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Happle, G., Fonseca, J. A., & Schlueter, A. (2017). Effects of air infiltration modeling approaches in urban building energy demand forecasts. Energy Procedia, 6.
This publication compares the sensitivity of input parameters in CEA and a case study in the city of Zurich- CH.
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Mosteiro-Romero, M., Fonseca, J. A., & Schlueter, A. (2017). Seasonal effects of input parameters in urban-scale building energy simulation. Energy Procedia, 6.
This publication showcases a new time-series clustering method implemented in CEA. The method is exemplified in a case study in Singapore.
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Fonseca, J. A., Miller, C., & Schlueter, A. (2017). Unsupervised load shape clustering for urban building performance assessment. Energy Procedia, 6.
2016
This publication showcases the integration of Daysim into CEA.
Neitzel, P. (2016) Identification of Key Input Parameters in Space and Time and their Implications on Output Uncertainty. Master Thesis. ETH Zurich.
This publication showcases the first release of CEA.
Fonseca, J. A., Thomas D., Willmann A., Elesawy A., Schlueter A. (2016). The City Energy Analyst Toolbox V0.1 (pp. 584–589). Sustainable Built Environment (SBE) Regional Conference Zurich 2016, vdf Hochschulverlag AG an der ETH Zürich.
This publication presents the workflow of CEA, main equations of supply systems and a case study in the city of Zug-CH.
Fonseca J. A., Thuy-An N., Schlueter A., and Marechal F. (2016). “City Energy Analyst (CEA): Integrated Framework for Analysis and Optimization of Building Energy Systems in Neighborhoods and City Districts.” Energy and Buildings 113: 202–26.
This publication presents the theoretical framework of CEA.
Fonseca, J. A. (2016). Energy efficiency strategies in urban communities. Doctoral Thesis. ETH Zürich, Zürich, Switzerland.
2015
This publication presents the demand simulation model of CEA and a case study in the city of Zug-CH.
Fonseca J. A., and Schlueter A. (2015). Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts. Applied Energy, 142, 247–265.
This publication presents the optimisation algorithm (master) for CEA and a case study in the city of Zug-CH.
Nguyen, T., (2015) Optimization of district energy system in the context of urban transformation. Master Thesis. ETH Zurich
2014
This publication presents the optimisation algorithm for CEA and a case study in the village of Zernez-CH.
Vollrath, T. (2014) Microgrid modeling and optimization in the context of rural transformation. Master Thesis. ETH Zurich
This publication introduced the first databases for lifecycle analysis in CEA.
Thoma, E., Fonseca, J. A., & Schlueter, A. (2014). Estimation of base-values for Grey Energy, Primary Energy, Global Warming Potential (GWP 100A) and Umweltbelastungspunkte (UBP 2006) for Swiss constructions from before 1920 until today. In DAKAM (Ed.), Contemporary Urban Issues ’14 (p. 17). Istambul.
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