A detailed study of the on-site consumption of domestic solar PV generated electricity has been u... more A detailed study of the on-site consumption of domestic solar PV generated electricity has been undertaken in order to gain an insight in to the relationships between annual consumption, generation and grid injection and to explore the effect of factors such as orientation and occupant behaviour on self-consumption (SC). Both empirical and simulated generation and export time series data for a large number of PV systems were analysed, and the degree to which SC is predicted by absolute generation and consumption and its variability have been quantified. SC is seen to be generally less than 50%, and the results illustrate the value of probabilistic models for predicting the socioeconomic impacts of domestic PV. As such, the results are significant for evaluating both socioeconomic impacts and distribution network loadflow implications.
For the purpose of the sustainability assessment of distributed renewable energy resources it is ... more For the purpose of the sustainability assessment of distributed renewable energy resources it is desirable to better understand the social, economic and environmental impacts (SEE) resulting from their deployment. Often only one, or at most two, of these knowledge domains is considered, partly due to the difficulty of devising an integrated assessment methodology. An approach based on probabilistic graphical models (PGM), has been developed which helps address this problem. Data for several UK urban census areas have been systematically collected and processed in order to furnish a PGM with the probabilistic data required in order to simultaneously make inferences about the SEE impacts of domestic solar PV, deployed to high penetrations. Results show that an integrated probabilistic assessment contributes to transdisciplinary knowledge, providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives.
Social, economic and environmental (SEE) impacts resulting from the adoption of solar PV have bee... more Social, economic and environmental (SEE) impacts resulting from the adoption of solar PV have been modelled at a community scale for the first time using a probabilistic graphical model in the form of a Bayesian Network (BN). Model parameters required to conceptualise this multidisciplinary problem domain are characterised by uncertainty due to stochastic variability, measurement and modelled data errors, or missing or incomplete information. A BN conveniently represents the model parameters and the associations between them and endogenises the uncertainty in probability distribution functions or mass functions. The theory and method of construction of an object-oriented BN which encapsulates a number of SEE parameters is described. This is used to model small urban areas as potential adopters of solar PV technology. The BN has been populated with modelled and empirical quantitative data from a variety of disciplines to create an inter-disciplinary knowledge representation of the problem domain. The model has been used to explore a number of scenarios whereby 'observations' are made on one or more variables of interest thus altering their prior probability distribution. The updated or posterior distributions of all the other variables are then recalculated using inference algorithms. Results are presented which show the utility of this approach in diagnostic and prognostic inference making. For example it is shown that Solar PV can have a small but significant impact on energy poverty. It is concluded that the adoption of a BN modelling approach that endogenises uncertainty, and reduces investment and policy risks associated with energy technology interventions within communities, can act as a useful due diligence and decision support tool for a number of private, public and community sector stakeholders active in this sector, in particular key decision and policy makers.
Progress in Photovoltaics: Research and Applications, 2016
Solar photovoltaic (PV) technology is now a key contributor worldwide in the transition towards l... more Solar photovoltaic (PV) technology is now a key contributor worldwide in the transition towards low-carbon electricity systems. To date, PV commonly receives subsidies in order to accelerate adoption rates by increasing investor returns. However, many aleatory and epistemic uncertainties exist with regard to these potential returns. In order to manage these uncertainties, an innovative probabilistic approach using Bayesian networks has been applied to the techno-economic analysis of domestic solar PV. Empirical datasets from over 600 domestic PV systems, together with national domestic electricity usage datasets, have been used to generate and calibrate prior probability distributions for PV yield and domestic electricity consumption, respectively, for typical urban housing stock. Subsequently, conditional dependencies of PV self-consumption with regard to PV generation and household electricity consumption have been simulated via stochastic modelling using high temporal resolution demand and PV generation data. A Bayesian network model is subsequently applied to deliver posterior probability distributions of key parameters as part of a discounted cash flow analysis. The results illustrate the sensitivity of PV investment returns to parameters such as PV self-consumption, PV degradation rates and geographical location and quantify inherent uncertainties when evaluating the impact of sector-specific PV adoption upon economic indicators. The outcomes are discussed in terms of the value and impact of this new Bayesian approach in terms of supporting robust and rigorous policy and investment decision-making, especially in post-subsidy contexts globally.
In certain applications, accelerators are added to favour a rapid evolution of mechanical propert... more In certain applications, accelerators are added to favour a rapid evolution of mechanical properties in mortar and concrete. In order to assure adequate performance, it is necessary to test the compatibility between the accelerator and other components of the mixture. The EN 934-5 establishes that such evaluation of accelerators should be performed according with the procedure established in the EN 196-1. However, this standard does not take into account the inclusion of the accelerators or the particularities of the mortar produced with these admixtures. The objective of this paper is to adapt the EN 196-1 in order to characterize the strength of mortars with accelerator. First, an experimental parametric study to evaluate the influence of the production procedure on the results was conducted. Based on the results obtained, a modified production process was proposed. Then, a wide experimental program including a total of 40 mixes of mortars with different formulations and contents of accelerators was performed. Based on a statistical analysis, a new admissible variation used to calculate the compressive strength was proposed.
The electrical power grid is a good example of an assemblage. It is a material cluster of charged... more The electrical power grid is a good example of an assemblage. It is a material cluster of charged parts that have indeed affiliated, remaining in sufficient proximity and coordination to function as a (flowing) system. The coherence of this system endures alongside energies and factions that fly out from it and disturb it from within. And, most important for my purposes here, the elements of this assemblage, while they include humans and their constructions, also include some very active and powerful nonhumans: electrons, trees, wind, electromagnetic fields (Bennett 2005: 446).
Building Simulation Conference proceedings, Aug 7, 2017
Airtightness and thermal conductance of the fabric play a key role in constructing low energy bui... more Airtightness and thermal conductance of the fabric play a key role in constructing low energy buildings. These two factors might minimise the building's heating demand in winter but contribute to its overheating in summer. This study focused on a building using Insulated Concrete Formwork (ICF), a site-based Modern Methods of Construction (MMC). ICF walls consist of cast in situ concrete poured between two layers of Expanded Polystyrene (EPS) insulation. The walls can achieve very low U-values and high levels of airtightness. The overall aim was to investigate the resilience or vulnerability of the ICF to overheating. A whole building monitoring study was used to empirically investigate the impact of the ICF fabric performance and to validate the accuracy of Building Performance Simulation (BPS) predictions provided by two tools. The results indicate that the building was able to provide a stable internal environment. In addition, both tools were able to predict indoor temperatures in a consistent way. However, the outcome of the analysis highlighted the significance of selecting appropriate data in terms of weather, internal gains and occupant behaviour when assessing overheating and the importance of developing a methodology for model calibration against indoor air temperatures for overheating assessment.
Building Services Engineering Research and Technology, Feb 25, 2020
With the help of building diagnostics, the causes and solutions to complex problems in buildings ... more With the help of building diagnostics, the causes and solutions to complex problems in buildings can be determined. In central and greater London, an increasing number of cases of chronic, year-round, overheating in buildings have been reported. We present three cases of unexpected temperatures in multistorey residential buildings. Detailed analysis and modelling of these scenarios have led to an investigation of whether the way in which infiltration is currently modelled in building performance simulation may be exerting a pronounced effect on the results of overheating studies. An EnergyPlus model, of one of the dwellings in a multi-residential building in London, was created to investigate the influence of infiltration and exfiltration pathway assumptions on the prediction of overheating. The simulation results were compared to empirical data and show that the predicted indoor temperatures are highly sensitive to how the infiltration airflow network is modelled. The findings of this study have been used to provide practical guidance for modellers and building designers on critical aspects to consider when creating building performance simulation models to ensure more reliable outcomes. Practical application: Overheating in buildings is an emerging topic of critical importance to the future of the built environment. The importance of understanding infiltration pathways in assessing and modelling overheating risks in flats and multi-residential buildings has been hitherto underestimated or simply ignored. In this paper, examples are given which highlight the need for a fuller understanding of internal air movement where accurate predictions of internal temperatures are required. At present, common building simulation practices and existing technical memorandum (TM) standards are masking the problem and do not provide a basis from which typical or worst-case scenarios can be adequately considered.
A detailed study of the on-site consumption of domestic solar PV generated electricity has been u... more A detailed study of the on-site consumption of domestic solar PV generated electricity has been undertaken in order to gain an insight in to the relationships between annual consumption, generation and grid injection and to explore the effect of factors such as orientation and occupant behaviour on self-consumption (SC). Both empirical and simulated generation and export time series data for a large number of PV systems were analysed, and the degree to which SC is predicted by absolute generation and consumption and its variability have been quantified. SC is seen to be generally less than 50%, and the results illustrate the value of probabilistic models for predicting the socioeconomic impacts of domestic PV. As such, the results are significant for evaluating both socioeconomic impacts and distribution network loadflow implications.
For the purpose of the sustainability assessment of distributed renewable energy resources it is ... more For the purpose of the sustainability assessment of distributed renewable energy resources it is desirable to better understand the social, economic and environmental impacts (SEE) resulting from their deployment. Often only one, or at most two, of these knowledge domains is considered, partly due to the difficulty of devising an integrated assessment methodology. An approach based on probabilistic graphical models (PGM), has been developed which helps address this problem. Data for several UK urban census areas have been systematically collected and processed in order to furnish a PGM with the probabilistic data required in order to simultaneously make inferences about the SEE impacts of domestic solar PV, deployed to high penetrations. Results show that an integrated probabilistic assessment contributes to transdisciplinary knowledge, providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives.
Social, economic and environmental (SEE) impacts resulting from the adoption of solar PV have bee... more Social, economic and environmental (SEE) impacts resulting from the adoption of solar PV have been modelled at a community scale for the first time using a probabilistic graphical model in the form of a Bayesian Network (BN). Model parameters required to conceptualise this multidisciplinary problem domain are characterised by uncertainty due to stochastic variability, measurement and modelled data errors, or missing or incomplete information. A BN conveniently represents the model parameters and the associations between them and endogenises the uncertainty in probability distribution functions or mass functions. The theory and method of construction of an object-oriented BN which encapsulates a number of SEE parameters is described. This is used to model small urban areas as potential adopters of solar PV technology. The BN has been populated with modelled and empirical quantitative data from a variety of disciplines to create an inter-disciplinary knowledge representation of the problem domain. The model has been used to explore a number of scenarios whereby 'observations' are made on one or more variables of interest thus altering their prior probability distribution. The updated or posterior distributions of all the other variables are then recalculated using inference algorithms. Results are presented which show the utility of this approach in diagnostic and prognostic inference making. For example it is shown that Solar PV can have a small but significant impact on energy poverty. It is concluded that the adoption of a BN modelling approach that endogenises uncertainty, and reduces investment and policy risks associated with energy technology interventions within communities, can act as a useful due diligence and decision support tool for a number of private, public and community sector stakeholders active in this sector, in particular key decision and policy makers.
Progress in Photovoltaics: Research and Applications, 2016
Solar photovoltaic (PV) technology is now a key contributor worldwide in the transition towards l... more Solar photovoltaic (PV) technology is now a key contributor worldwide in the transition towards low-carbon electricity systems. To date, PV commonly receives subsidies in order to accelerate adoption rates by increasing investor returns. However, many aleatory and epistemic uncertainties exist with regard to these potential returns. In order to manage these uncertainties, an innovative probabilistic approach using Bayesian networks has been applied to the techno-economic analysis of domestic solar PV. Empirical datasets from over 600 domestic PV systems, together with national domestic electricity usage datasets, have been used to generate and calibrate prior probability distributions for PV yield and domestic electricity consumption, respectively, for typical urban housing stock. Subsequently, conditional dependencies of PV self-consumption with regard to PV generation and household electricity consumption have been simulated via stochastic modelling using high temporal resolution demand and PV generation data. A Bayesian network model is subsequently applied to deliver posterior probability distributions of key parameters as part of a discounted cash flow analysis. The results illustrate the sensitivity of PV investment returns to parameters such as PV self-consumption, PV degradation rates and geographical location and quantify inherent uncertainties when evaluating the impact of sector-specific PV adoption upon economic indicators. The outcomes are discussed in terms of the value and impact of this new Bayesian approach in terms of supporting robust and rigorous policy and investment decision-making, especially in post-subsidy contexts globally.
In certain applications, accelerators are added to favour a rapid evolution of mechanical propert... more In certain applications, accelerators are added to favour a rapid evolution of mechanical properties in mortar and concrete. In order to assure adequate performance, it is necessary to test the compatibility between the accelerator and other components of the mixture. The EN 934-5 establishes that such evaluation of accelerators should be performed according with the procedure established in the EN 196-1. However, this standard does not take into account the inclusion of the accelerators or the particularities of the mortar produced with these admixtures. The objective of this paper is to adapt the EN 196-1 in order to characterize the strength of mortars with accelerator. First, an experimental parametric study to evaluate the influence of the production procedure on the results was conducted. Based on the results obtained, a modified production process was proposed. Then, a wide experimental program including a total of 40 mixes of mortars with different formulations and contents of accelerators was performed. Based on a statistical analysis, a new admissible variation used to calculate the compressive strength was proposed.
The electrical power grid is a good example of an assemblage. It is a material cluster of charged... more The electrical power grid is a good example of an assemblage. It is a material cluster of charged parts that have indeed affiliated, remaining in sufficient proximity and coordination to function as a (flowing) system. The coherence of this system endures alongside energies and factions that fly out from it and disturb it from within. And, most important for my purposes here, the elements of this assemblage, while they include humans and their constructions, also include some very active and powerful nonhumans: electrons, trees, wind, electromagnetic fields (Bennett 2005: 446).
Building Simulation Conference proceedings, Aug 7, 2017
Airtightness and thermal conductance of the fabric play a key role in constructing low energy bui... more Airtightness and thermal conductance of the fabric play a key role in constructing low energy buildings. These two factors might minimise the building's heating demand in winter but contribute to its overheating in summer. This study focused on a building using Insulated Concrete Formwork (ICF), a site-based Modern Methods of Construction (MMC). ICF walls consist of cast in situ concrete poured between two layers of Expanded Polystyrene (EPS) insulation. The walls can achieve very low U-values and high levels of airtightness. The overall aim was to investigate the resilience or vulnerability of the ICF to overheating. A whole building monitoring study was used to empirically investigate the impact of the ICF fabric performance and to validate the accuracy of Building Performance Simulation (BPS) predictions provided by two tools. The results indicate that the building was able to provide a stable internal environment. In addition, both tools were able to predict indoor temperatures in a consistent way. However, the outcome of the analysis highlighted the significance of selecting appropriate data in terms of weather, internal gains and occupant behaviour when assessing overheating and the importance of developing a methodology for model calibration against indoor air temperatures for overheating assessment.
Building Services Engineering Research and Technology, Feb 25, 2020
With the help of building diagnostics, the causes and solutions to complex problems in buildings ... more With the help of building diagnostics, the causes and solutions to complex problems in buildings can be determined. In central and greater London, an increasing number of cases of chronic, year-round, overheating in buildings have been reported. We present three cases of unexpected temperatures in multistorey residential buildings. Detailed analysis and modelling of these scenarios have led to an investigation of whether the way in which infiltration is currently modelled in building performance simulation may be exerting a pronounced effect on the results of overheating studies. An EnergyPlus model, of one of the dwellings in a multi-residential building in London, was created to investigate the influence of infiltration and exfiltration pathway assumptions on the prediction of overheating. The simulation results were compared to empirical data and show that the predicted indoor temperatures are highly sensitive to how the infiltration airflow network is modelled. The findings of this study have been used to provide practical guidance for modellers and building designers on critical aspects to consider when creating building performance simulation models to ensure more reliable outcomes. Practical application: Overheating in buildings is an emerging topic of critical importance to the future of the built environment. The importance of understanding infiltration pathways in assessing and modelling overheating risks in flats and multi-residential buildings has been hitherto underestimated or simply ignored. In this paper, examples are given which highlight the need for a fuller understanding of internal air movement where accurate predictions of internal temperatures are required. At present, common building simulation practices and existing technical memorandum (TM) standards are masking the problem and do not provide a basis from which typical or worst-case scenarios can be adequately considered.
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Papers by Chris Goodier