Case study of zero energy house design in UK

Wang, Liping; Gwilliam, Julie; Jones, Paul

doi:10.1016/j.enbuild.2009.07.001

Cited by 238 publications

(89 citation statements)

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“…The greater the surface area, the higher the heat gain/loss through it. Therefore, small A/V ratios imply minimum heat gain and minimum heat loss [50].…”

Section: Area/volume (A/v) Ratio (M 2 /M 3 )mentioning

confidence: 99%

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Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation

Turhan

Kazanasmaz

Uygun

et al. 2014

Energy and Buildings

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a b s t r a c tThe several parameters affect the heat load of a building; geometry, construction, layout, climate and the users. These parameters are complex and interrelated. Comprehensive models are needed to understand relationships among the parameters that can handle non-linearities. The aim of this study is to predict heat load of existing buildings benefiting from width/length ratio, wall overall heat transfer coefficient, area/volume ratio, total external surface area, total window area/total external surface area ratio by using artificial neural networks and compare the results with a building energy simulation tool called KEP-IYTE-ESS developed by Izmir Institute of Technology. A back propagation neural network algorithm has been preferred and both simulation tools were applied to 148 residential buildings selected from 3 municipalities of Izmir-Turkey. Under the given conditions, a good coherence was observed between artificial neural network and building energy simulation tool results with a mean absolute percentage error of 5.06% and successful prediction rate of 0.977. The advantages of ANN model over the energy simulation software are observed as the simplicity, the speed of calculation and learning from the limited data sets.

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“…The greater the surface area, the higher the heat gain/loss through it. Therefore, small A/V ratios imply minimum heat gain and minimum heat loss [50].…”

Section: Area/volume (A/v) Ratio (M 2 /M 3 )mentioning

confidence: 99%

“…The relatively low insulation levels afforded by windows will have an impact on the internal thermal performance of a building during the winter, while larger windows will increase internal solar heat gains [50].…”

Section: Total Window Area/total External Surface Area (Twa/tesa) Ratmentioning

confidence: 99%

Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation

Turhan

Kazanasmaz

Uygun

et al. 2014

Energy and Buildings

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“…Wang et al [15] discussed possible solutions for ZEB design in UK. EnergyPlus and TRNSYS 16 were used in their study as a Simulation software.…”

Section: Literature Reviewmentioning

confidence: 99%

An Environmentally-Friendly Tourist Village in Egypt Based on a Hybrid Renewable Energy System––Part Two: A Net Zero Energy Tourist Village

et al. 2015

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Abstract:The main objective of this study is to discuss the economical and the environmental analysis of a net zero energy (NZE) tourist village in Alexandria, Egypt, by maximizing the renewable energy fraction and minimizing the greenhouse gases (GHG) emissions. The hybrid photovoltaics (PV)/wind/diesel/battery system is found to be the optimum hybrid renewable energy system (HRES) for the proposed tourist village under the study. The optimum HRES consists of 1600 kW of PV panels (58.09% solar energy penetration), 1000 kW of wind turbines (41.34% wind energy penetration), 1000 kW of power converters, 200 kW diesel generator (only 0.57% diesel generator penetration) in addition to 2000 batteries with the capacity of 589 Ah each. The levelized cost of energy (COE) from the optimum HRES is $0.17/kWh and the total net present cost (NPC) of this system is $15,383,360. Additionally, the maximum renewable energy fraction is 99.1% and the amount of GHG emitted from the optimum HRES is only 31,289 kg/year, which is negligible in comparison with the other system configurations, therefore the optimum HRES can be considered as a green system. In addition to this, the achieved percentage of the capacity shortage and the unmet load in the optimal HRES is only 0% for both. OPEN ACCESS

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“…EnergyPlus has been used for building design (Graça et al, 2004;Wang et al, 2009), fault detection and diagnostics (Jacob et al, 2010;Pang et al, 2012), and energy standard development (Borgeson and Brager, 2011;Thorton et al, 2011). Since the focus of EnergyPlus is whole annual building energy simulation, it is not designed to study the controls performance of HVAC systems, to perform detailed daylighting analysis, or detailed temporal distribution of indoor airflow and contaminants that are better addressed by other simulation programs.…”

Section: Introductionmentioning

confidence: 99%

Functional mock-up unit for co-simulation import in EnergyPlus

Nouidui

Wetter

Zuo

2013

Journal of Building Performance Simulation

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This article describes the development and implementation of the Functional Mock-up Unit (FMU) for cosimulation import interface in EnergyPlus. This new capability allows EnergyPlus to conduct co-simulation with various simulation programs that are packaged as FMUs. For example, one can model an innovative Heating, Ventilation, and Air Conditioning (HVAC) system and its controls in Modelica, export the HVAC system and the control algorithm as an FMU, and link it to a model of the building envelope in EnergyPlus for run-time data exchange.The formal of FMUs is specified in the Functional Mock-up Interface (FMI) standard, an open standard designed to enable links between disparate simulation programs. An FMU may contain models, model description, source code, and executable programs for multiple platforms. A master simulator-in this case, EnergyPlusimports and simulates the FMUs, controlling simulation time and coordinating the exchange of data between the different FMUs.This article describes the mathematical basis of the FMI standard, discusses its application to EnergyPlus, and describes the architecture of the EnergyPlus implementation. It then presents a typical workflow, including pre-processing and co-simulation. The article concludes by presenting two use cases in which models of a ventilation system and a shading controller are imported in EnergyPlus as an FMU.

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Case study of zero energy house design in UK

Cited by 238 publications

References 1 publication

Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation

Comparative study of a building energy performance software (KEP-IYTE-ESS) and ANN-based building heat load estimation

An Environmentally-Friendly Tourist Village in Egypt Based on a Hybrid Renewable Energy System––Part Two: A Net Zero Energy Tourist Village

Functional mock-up unit for co-simulation import in EnergyPlus

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