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Subject = Energy modelling;
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Displaying Results 1 - 11 of 11 on page 1 of 1
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A data science solution for measurement and verification 2.0 in industrial buildings
(2019)
Gallagher, Colm V.
A data science solution for measurement and verification 2.0 in industrial buildings
(2019)
Gallagher, Colm V.
Abstract:
The advent of advanced metering infrastructure has led to vast quantities of energy data becoming available. Despite this, the typical methods employed for the performance verification of energy efficiency improvements have not progressed, as they continue to rely on expert knowledge and simplistic statistical modelling techniques. This leads to uncertainty in the quantity of savings arrived at, with this uncertainty acting as a barrier to investment in energy efficiency. In response to this, the industry is evolving towards more advanced and automated methods known as M&V 2.0. This however presents the challenge of keeping the resources required to perform M&V at a minimum level, while also improving the accuracy, reliability and trust in the process. The research presented in this thesis can be largely classified into two prominent tasks. These are the development of a machine learning-based methodology for the construction of accurate baseline energy models and the establ...
http://hdl.handle.net/10468/7862
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A generalization approach for reduced order modelling of commercial buildings
(2019)
Shamsi, Mohammad Haris; Ali, Usman; O'Donnell, James
A generalization approach for reduced order modelling of commercial buildings
(2019)
Shamsi, Mohammad Haris; Ali, Usman; O'Donnell, James
Abstract:
Energy-efficient retrofits have become crucial in building sector as approximately 80% of buildings in developed countries are over 10 years old. Building simulation tools are now being used to provide estimates of energy consumption and implement various models which differ on the basis of enclosed details. Not all of these models are effective in terms of computation and the associated computational costs. This work devises a novel and generalized reduced-order grey-box modelling approach to predict the thermal behaviour of commercial buildings. The generalization approach reduces the order/complexity of model and lays out a general structure to obtain reduced-order models based on easily identifiable building metrics. We also implemented a forward-selection procedure to compare results obtained using a metrics-based approach. The network order obtained using metrics-based approach matches with the network order predicted by the forward selection procedure. The generalized structu...
http://hdl.handle.net/10197/10996
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Mark
Bottom-up modelling of energy demand and technical energy savings potential in the Irish residential sector
(2014)
Dineen, Denis
Bottom-up modelling of energy demand and technical energy savings potential in the Irish residential sector
(2014)
Dineen, Denis
Abstract:
The International Energy Agency has repeatedly identified increased end-use energy efficiency as the quickest, least costly method of green house gas mitigation, most recently in the 2012 World Energy Outlook, and urges all governing bodies to increase efforts to promote energy efficiency policies and technologies. The residential sector is recognised as a major potential source of cost effective energy efficiency gains. Within the EU this relative importance can be seen from a review of the National Energy Efficiency Action Plans (NEEAP) submitted by member states, which in all cases place a large emphasis on the residential sector. This is particularly true for Ireland whose residential sector has historically had higher energy consumption and CO2 emissions than the EU average and whose first NEEAP targeted 44% of the energy savings to be achieved in 2020 from this sector. This thesis develops a bottom-up engineering archetype modelling approach to analyse the Irish residential se...
http://hdl.handle.net/10468/1762
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GIS-Based Residential Building Energy Modeling at District Scale
(2019)
Ali, Usman; Shamsi, Mohammad Haris; Hoare, Cathal; O'Donnell, James
GIS-Based Residential Building Energy Modeling at District Scale
(2019)
Ali, Usman; Shamsi, Mohammad Haris; Hoare, Cathal; O'Donnell, James
Abstract:
BSO 2018: 4th IBPSA-England Conference on Building Simulation and Optimization, Cambridge, United Kingdom, 11-12 September 2018
Urban planners often develop strategic sustainable energy planning processes that aim to minimize the overall energy consumption and CO2 emissions of buildings. Planning at such scales could be informed by the use of building energy modeling approaches. However, due to inconsistencies in available urban energy data and a lack of scalable building modeling approaches, a gap persists between building energy modeling and traditional planning practices. This paper develops a methodology based on bottom-up approach for GIS-based residential building energy modeling at a district scale. The methodology is applied to districts in Dublin and modeling results indicate where and what type of buildings have the greatest potential for energy savings throughout the city.
Science Foundation Ireland
ESIPP UCD
http://hdl.handle.net/10197/10545
Marked
Mark
Including Embodied Energy Considerations at the Conceptual Stage of Building Design
(2006)
Yohanis, Y.; Norton, Brian
Including Embodied Energy Considerations at the Conceptual Stage of Building Design
(2006)
Yohanis, Y.; Norton, Brian
Abstract:
Elevated operating temperatures reduce the solar to electrical conversion efficiency of building integrated photovoltaic devices (BIPV). Phase change materials (PCM) can be used to passively limit this temperature rise although their effectiveness is limited by their low thermal conductivities and by crystallization segregation during solidification. This paper presents an experimental evaluation of the effects of convection and crystalline segregation in a PCM as a function of efficiency of heat transfer within the finned PV/PCM system. The thermal performances of bulk PCM with crystallization segregation for different internal fin arrangements are presented. It is noted that the addition of internal fins improves the temperature control of the PV in a PV/PCM system.
https://arrow.dit.ie/dubenart/31
Marked
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Innovative approaches to developing deep decarbonisation strategies
(2019)
Pye, Steve
Innovative approaches to developing deep decarbonisation strategies
(2019)
Pye, Steve
Abstract:
After years of discussion by the international community as to how best to tackle the challenge of climate change, the Paris Agreement in 2015 both refocused attention on the necessary climate mitigation goals and saw a shift towards a more bottom-up, country-led approach to delivering on this agreed ambition. It is in this context that the research presented in this thesis on Innovative approaches to developing deep decarbonisation strategies has been undertaken. Recognising that the energy system is the largest source of CO2 emissions contributing to climate change, analytical approaches such as those using energy models, are needed to help decision makers navigate the different options to drive the energy system towards being low carbon and net-zero emitting in future years. However, there is a question as to whether energy modelling, notably energy systems modelling, is fit-for-purpose or needs to further adapt and innovate. This concerns not only the functionality and credibili...
http://hdl.handle.net/10468/9495
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Modelling sustainable energy and the implications for policy
(2018)
Clancy, John Matthew
Modelling sustainable energy and the implications for policy
(2018)
Clancy, John Matthew
Abstract:
The Paris Agreement sets out the collective ambition of the world’s nations to prevent dangerous climate change. However, at national level across the world, there is a gap between action and the required rate of effort. Long-term models show technology pathways but governments must act to realise them. Long-term pathways are often based on a single aim – achieving a level of CO2 reduction at least cost. Yet governments have wider objectives beyond climate mitigation. Economic competitiveness, wellbeing of citizens and employment also feature. This thesis approaches the modelling of sustainable energy from a policymaker’s perspective. The aim is to improve the evidence base and inform policy development. Showing citizens the impact of current policy helps governments to bring forth further support. These assessments can be difficult to implement. The first part of this thesis examines the emissions impact of existing renewable electricity policy. Several methods have been used to ex...
http://hdl.handle.net/10468/7331
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Techno-economic and socio-economic modelling of energy in road transport to inform climate policy
(2017)
Mulholland, Eamonn
Techno-economic and socio-economic modelling of energy in road transport to inform climate policy
(2017)
Mulholland, Eamonn
Abstract:
The release of increasing amounts of anthropogenic greenhouse gas emissions and the corresponding global temperature rise has prompted a growing political consensus on a decarbonised future to prevent any sustained economic or environmental harm. Many countries are using modelling tools to develop strategies and policy measures to deliver timely and effective reductions of harmful greenhouse gas emissions across all energy related sectors. Techno-economic models have a track record in developing low carbon pathways from a technical standpoint, though they have generally failed to adequately account for the underlying socio-economic behaviour which drives consumers in their choices. This thesis highlights and addresses this failing in two parts with a focus on road transport, one of the most difficult sectors to decarbonise. The first part of this thesis reviews the functionality of techno-economic road transportation models and identifies the limitations associated with their operat...
http://hdl.handle.net/10468/5536
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Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector
(2017)
Mulholland, Eamonn; Rogan, Fionn; Ó Gallachóir, Brian P.
Techno-economic data for a multi-model approach to decarbonisation of the Irish private car sector
(2017)
Mulholland, Eamonn; Rogan, Fionn; Ó Gallachóir, Brian P.
Abstract:
These data and analyses support the research article “From technology pathways to policy roadmaps to enabling measures – A multi-model approach” Mulholland et al. (2017) [1]. This article uses 3 models – an optimization model of the Irish energy system (Irish TIMES), a simulation model of the Irish private transport sector (CarSTOCK), and a market share algorithm used to provide a behavior rich representation into the multi-modelling process. Each of these models are linked to provide a technology pathway, policy roadmap, and finally identify the enabling measures of the private transport sector in a low-carbon Ireland moving toward 2050. The article is organized in the same order, firstly providing the key modelling assumptions and operability of Irish TIMES, secondly for CarSTOCK, and finally for the market share algorithm. All data is supplied within this article.
http://hdl.handle.net/10468/5134
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The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings
(2017)
Gallagher, Colm V.; Bruton, Ken; Leahy, Kevin; O'Sullivan, Dominic T. J.
The suitability of machine learning to minimise uncertainty in the measurement and verification of energy savings
(2017)
Gallagher, Colm V.; Bruton, Ken; Leahy, Kevin; O'Sullivan, Dominic T. J.
Abstract:
Accurate energy modelling is a critical step in the measurement and verification (M&V) of energy savings, as a model for consumption in the baseline period is required. Machine learning (ML) algorithms offer an alternative approach to train these models with data-driven techniques. Industrial buildings offer the most challenging environment for the completion of M&V due to their complex energy systems. This paper investigates the novel use of ML algorithms for M&V of energy savings in industrial buildings. This approach enables the extension of the traditional project boundary also. The ML techniques applied consist of bi-variable and multi-variable ordinary least squares regression, decision trees, k-nearest neighbours, artificial neural networks and support vector machines. The prediction performances of the models are validated in the context of a biomedical manufacturing facility to find the optimal model parameters. Results show that models constructed using ML algo...
http://hdl.handle.net/10468/5887
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Thermal energy modelling, benchmarking and mapping for university campus buildings
(2017)
Vaisi, Salahadin
Thermal energy modelling, benchmarking and mapping for university campus buildings
(2017)
Vaisi, Salahadin
Abstract:
According to the Chartered Institution of Building Services Engineering, CIBSE TM46:2008 University Campus benchmark, a college building needs 240 kWh/m2 of thermal energy and proportionally produces 45.6kg CO2 per annum. As heat consumption largely depends on the ambient temperature, this fixed-annual benchmark is not suitable because it does not deliver any difference between summer and winter. Firstly, the current research analysed the accuracy of the CIBSE TM46 ?University Campus? benchmark against the thermal consumption values presented in Display Energy Certificates (DECs). The DECs of 52 college buildings belonging to four universities in Dublin were assessed and based on the 46% discrepancy between the median of analysed samples and the CIBSE UC (University Campus) benchmark, a new benchmark of 130 kWh/m2/yr was recommended. This new benchmark is 110 kWh/m2/yr lower than the current benchmark which is a substantial improvement. The UC revised benchmark (UCrb, 130 kWh/m2/yr)...
http://hdl.handle.net/2262/81742
Displaying Results 1 - 11 of 11 on page 1 of 1
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Institution
Dublin Institute of Technology (1)
Trinity College Dublin (1)
University College Cork (7)
University College Dublin (2)
Item Type
Doctoral thesis (6)
Journal article (4)
Other (1)
Peer Review Status
Peer-reviewed (3)
Non-peer-reviewed (5)
Unknown (3)
Year
2019 (4)
2018 (1)
2017 (4)
2014 (1)
2006 (1)
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