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Paul N. Rowley
Centre for Renewable Energy Systems Technology, Loughborough University, UK

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Erratum
Published: 01 December 2020 in Energy Economics
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ACS Style

Filippo Beltrami; Andrew Burlinson; Monica Giulietti; Luigi Grossi; Paul Rowley; Grant Wilson. Where did the time (series) go? Estimation of marginal emission factors with autoregressive components. Energy Economics 2020, 95, 105027 .

AMA Style

Filippo Beltrami, Andrew Burlinson, Monica Giulietti, Luigi Grossi, Paul Rowley, Grant Wilson. Where did the time (series) go? Estimation of marginal emission factors with autoregressive components. Energy Economics. 2020; 95 ():105027.

Chicago/Turabian Style

Filippo Beltrami; Andrew Burlinson; Monica Giulietti; Luigi Grossi; Paul Rowley; Grant Wilson. 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components." Energy Economics 95, no. : 105027.

Journal article
Published: 15 August 2020 in Energy Economics
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This paper offers a novel contribution to the literature on Marginal Emission Factors (MEF) by proposing a robust empirical methodology for their estimation across both time and space. Our Autoregressive Integrated Moving Average models with time-effects not only outperforms the established models in the economics literature but it also proves more reliable than variations adopted in the field of engineering. Utilising half-hourly data on carbon emissions and generation in Great Britain, the results allow us to identify a more stable path of MEFs than obtained with existing methodologies. We also estimate marginal emission effects over subsequent time periods (intra-day), rather than focussing only on individual settlement periods (inter-day). This allows us to evaluate the annual cycle of emissions as a result of changes in the economic and social activity which drives demand. Moreover, the reliability of our approach is further confirmed upon exploring the cross-country context. Indeed, our methodology proves reliable when applied to the case of Italy, which is characterised by a different data generation process. Crucially, we provide a more robust basis for valuing actual carbon emission reductions, especially in electricity systems with high penetration of intermittent renewable technologies.

ACS Style

Filippo Beltrami; Andrew Burlinson; Monica Giulietti; Luigi Grossi; Paul Rowley; Grant Wilson. Where did the time (series) go? Estimation of marginal emission factors with autoregressive components. Energy Economics 2020, 91, 104905 .

AMA Style

Filippo Beltrami, Andrew Burlinson, Monica Giulietti, Luigi Grossi, Paul Rowley, Grant Wilson. Where did the time (series) go? Estimation of marginal emission factors with autoregressive components. Energy Economics. 2020; 91 ():104905.

Chicago/Turabian Style

Filippo Beltrami; Andrew Burlinson; Monica Giulietti; Luigi Grossi; Paul Rowley; Grant Wilson. 2020. "Where did the time (series) go? Estimation of marginal emission factors with autoregressive components." Energy Economics 91, no. : 104905.

Journal article
Published: 04 May 2020 in Energies
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This paper describes the results of recent research carried out with the UK energy sector to assess low-carbon related skills gaps and training requirements at the masters-level. Via iterative engagement across the industry, the characteristics of the market for new ‘needs-driven’ industry-focussed masters-level training offerings were defined. The results, taken together with the outcomes of a gap analysis of existing masters-level training, support the creation of a new framework for masters-level energy education that will more effectively meet the growing unmet need for such skills in the UK and beyond. The outcomes of the research indicate that flexibility in both delivery mode and curriculum content across both technical and non-technical disciplines is essential, along with improved supplier agility to rapidly develop new courses in evolving engineering specialisations. Without responding effectively to such demands from industry, we conclude that the advanced skills needed across the highly dynamic UK and global energy engineering sector will be in increasingly short supply.

ACS Style

Paul Rowley; Caroline Walker. Adapt or Perish: A New Approach for Industry Needs-Driven Master’s Level Low-Carbon Energy Engineering Education in the UK. Energies 2020, 13, 2246 .

AMA Style

Paul Rowley, Caroline Walker. Adapt or Perish: A New Approach for Industry Needs-Driven Master’s Level Low-Carbon Energy Engineering Education in the UK. Energies. 2020; 13 (9):2246.

Chicago/Turabian Style

Paul Rowley; Caroline Walker. 2020. "Adapt or Perish: A New Approach for Industry Needs-Driven Master’s Level Low-Carbon Energy Engineering Education in the UK." Energies 13, no. 9: 2246.

Journal article
Published: 01 January 2019 in Renewable Energy
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The dairy industry accounts for 9-14% of East Africa’s agricultural gross development product. Due to lack of milk cooling facilities, dairy farmers in areas without access to reliable grid electricity face problems of high milk spoilage and limited access to formal markets, which limits their income and standard of living. This article examines the economic viability for a number of configurations of off-grid solar, wind, biomass and biogas based milk-cooling systems serving a community in Tanzania. Key risk factors having the greatest impact on system viability are identified and a stochastic approach, by means of a Monte Carlo simulation is employed to determine the risk-adjusted economic performance of the project. The results indicate that biogas based systems offer the most viable option, with an internal rate of return of around 25%, a net present value of around $9,000 and a projected increase in farmers’ monthly income of at least 78%. Despite specific risk factors, the 300-liter cooling system had an 82% probability of a positive net present value. However, larger system cooling capacities have a significant likelihood of a financial loss. Consequently, risk mitigation strategies designed to increase the probability of economic success are proposed.

ACS Style

June M. Lukuyu; Richard E. Blanchard; Paul N. Rowley. A risk-adjusted techno-economic analysis for renewable-based milk cooling in remote dairy farming communities in East Africa. Renewable Energy 2019, 130, 700 -713.

AMA Style

June M. Lukuyu, Richard E. Blanchard, Paul N. Rowley. A risk-adjusted techno-economic analysis for renewable-based milk cooling in remote dairy farming communities in East Africa. Renewable Energy. 2019; 130 ():700-713.

Chicago/Turabian Style

June M. Lukuyu; Richard E. Blanchard; Paul N. Rowley. 2019. "A risk-adjusted techno-economic analysis for renewable-based milk cooling in remote dairy farming communities in East Africa." Renewable Energy 130, no. : 700-713.

Conference paper
Published: 01 June 2017 in 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC)
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Complete photovoltaic monitoring data are required in order to evaluate PV system performance and to ensure confidence in project financing. Monitoring sub-system failures are common occurrences, reducing data availability in meteorological and electrical datasets. A reliable backfilling method can be applied in order to mitigate the impact of long monitoring gaps on system state and performance assessment. This paper introduces a method of inferring in-plane irradiation from remotely obtained global horizontal irradiation, by means of a neural network approach. Generation output is then calculated utilizing a simple electrical model with fitted coefficients. The proposed method is applied to a UK case study for which the mean absolute error in monthly system output was reduced significantly, to as low as 0.9%. This yielded more accurate results in backfilling the missing datasets when compared to standard approaches. The impact of missing data on monthly performance ratio is also investigated. Using backfilling to synthesize lost data increases performance ratio prediction accuracy significantly when compared to simply omitting such periods from the calculation.

ACS Style

Eleni Koubli; Diane Palmer; Tom Betts; Paul Rowley; Ralph Gottschalg. Inference of missing PV monitoring data using neural networks. 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC) 2017, 1 .

AMA Style

Eleni Koubli, Diane Palmer, Tom Betts, Paul Rowley, Ralph Gottschalg. Inference of missing PV monitoring data using neural networks. 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC). 2017; ():1.

Chicago/Turabian Style

Eleni Koubli; Diane Palmer; Tom Betts; Paul Rowley; Ralph Gottschalg. 2017. "Inference of missing PV monitoring data using neural networks." 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC) , no. : 1.

Journal article
Published: 01 April 2017 in Applied Energy
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This paper is in closed access until 9th Feb 2018.© 2017 Elsevier LtdThe potential for electric vehicles to obtain income from energy supplied to a commercial building together with revenue accruing from specific ancillary service markets in the UK is evaluated in this work. A hybrid time-series/probabilistic simulation environment using real-world data is described, which is applied in the analysis of electricity trading with vehicle-to-grid to vehicles, buildings and markets. Key parameters are found to be the electric vehicle electricity sale price, battery degradation cost and infrastructure costs. Three vehicle-to-grid scenarios are evaluated using pool vehicle trip data, market pricing index data and half-hourly electricity demand for a commercial building. Results show that provision of energy to the wholesale electricity market with additional income from the capacity market results in the greatest projected return on investment, producing an individual vehicle net present value of ∼£8400. This is over 10 years for a vehicle supplying energy three times per week to the half-hour day-ahead market and includes the cost of installing the vehicle-to-grid infrastructure. The analysis also shows that net income generation is strongly dependent upon battery degradation costs associated with vehicle-to-grid cycling

ACS Style

Rebecca Gough; Charles Dickerson; Paul Rowley; Chris Walsh. Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage. Applied Energy 2017, 192, 12 -23.

AMA Style

Rebecca Gough, Charles Dickerson, Paul Rowley, Chris Walsh. Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage. Applied Energy. 2017; 192 ():12-23.

Chicago/Turabian Style

Rebecca Gough; Charles Dickerson; Paul Rowley; Chris Walsh. 2017. "Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage." Applied Energy 192, no. : 12-23.

Conference paper
Published: 21 November 2016 in 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)
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Complete photovoltaic monitoring data are required in order to evaluate PV system performance and to ensure confidence in project financing. Monitoring sub-system failures are common occurrences, reducing data availability in meteorological and electrical datasets. A reliable backfilling method can be applied in order to mitigate the impact of long monitoring gaps on system state and performance assessment. This paper introduces a method of inferring in-plane irradiation from remotely obtained global horizontal irradiation, by means of a neural network approach. Generation output is then calculated utilizing a simple electrical model with fitted coefficients. The proposed method is applied to a UK case study for which the mean absolute error in monthly system output was reduced significantly, to as low as 0.9%. This yielded more accurate results in backfilling the missing datasets when compared to standard approaches. The impact of missing data on monthly performance ratio is also investigated. Using backfilling to synthesize lost data increases performance ratio prediction accuracy significantly when compared to simply omitting such periods from the calculation.

ACS Style

Eleni Koubli; Diane Palmer; Tom Betts; Paul Rowley; Ralph Gottschalg. Inference of missing PV monitoring data using neural networks. 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC) 2016, 3436 -3440.

AMA Style

Eleni Koubli, Diane Palmer, Tom Betts, Paul Rowley, Ralph Gottschalg. Inference of missing PV monitoring data using neural networks. 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC). 2016; ():3436-3440.

Chicago/Turabian Style

Eleni Koubli; Diane Palmer; Tom Betts; Paul Rowley; Ralph Gottschalg. 2016. "Inference of missing PV monitoring data using neural networks." 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC) , no. : 3436-3440.

Journal article
Published: 01 April 2016 in IET Renewable Power Generation
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To assess the systemic value and impacts of multiple photovoltaic (PV) systems in urban areas, detailed analysis of on-site electricity consumption and of solar PV yield at relatively high temporal resolution is required, together with an understanding of the impacts of stochastic variations in consumption and PV generation. In this study, measured and simulated time-series data for consumption and PV generation at 5 and 1 min resolution for a large number of domestic PV systems are analysed, and a statistical evaluation of self-consumption (SC) carried out. The results show a significant variability of annual PV SC across the sample population, with typical median annual SC of 31% and inter-quartile range of 22–44%. About 10% of the dwellings exceed an SC of 60% with 10% achieving 14% or less. The results have been used to construct a Bayesian network model capable of probabilistically analysing SC given consumption and PV generation. This model provides a basis for rapid detailed analysis of the techno-economic characteristics and socio-economic impacts of PV in a range of built environment contexts, from single building to district scales.

ACS Style

Philip A. Leicester; Chris I. Goodier; Paul N. Rowley. Probabilistic analysis of solar photovoltaic self‐consumption using Bayesian network models. IET Renewable Power Generation 2016, 10, 448 -455.

AMA Style

Philip A. Leicester, Chris I. Goodier, Paul N. Rowley. Probabilistic analysis of solar photovoltaic self‐consumption using Bayesian network models. IET Renewable Power Generation. 2016; 10 (4):448-455.

Chicago/Turabian Style

Philip A. Leicester; Chris I. Goodier; Paul N. Rowley. 2016. "Probabilistic analysis of solar photovoltaic self‐consumption using Bayesian network models." IET Renewable Power Generation 10, no. 4: 448-455.

Journal article
Published: 01 April 2016 in IET Renewable Power Generation
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Photovoltaic (PV) systems are frequently covered by performance guarantees, which are often based on attaining a certain performance ratio (PR). Climatic and electrical data are collected on site to verify that these guarantees are met or that the systems are working well. However, in-field data acquisition commonly suffers from data loss, sometimes for prolonged periods of time, making this assessment impossible or at the very best introducing significant uncertainties. This study presents a method to mitigate this issue based on back-filling missing data. Typical cases of data loss are considered and a method to infer this is presented and validated. Synthetic performance data is generated based on interpolated environmental data and a trained empirical electrical model. A case study is subsequently used to validate the method. Accuracy of the approach is examined by creating artificial data loss in two closely monitored PV modules. A missing month of energy readings has been replenished, reproducing PR with an average daily and monthly mean bias error of about −1 and −0.02%, respectively, for a crystalline silicon module. The PR is a key property which is required for the warranty verification, and the proposed method yields reliable results in order to achieve this.

ACS Style

Eleni Koubli; Diane Palmer; Paul Rowley; Ralph Gottschalg. Inference of missing data in photovoltaic monitoring datasets. IET Renewable Power Generation 2016, 10, 434 -439.

AMA Style

Eleni Koubli, Diane Palmer, Paul Rowley, Ralph Gottschalg. Inference of missing data in photovoltaic monitoring datasets. IET Renewable Power Generation. 2016; 10 (4):434-439.

Chicago/Turabian Style

Eleni Koubli; Diane Palmer; Paul Rowley; Ralph Gottschalg. 2016. "Inference of missing data in photovoltaic monitoring datasets." IET Renewable Power Generation 10, no. 4: 434-439.

Journal article
Published: 22 March 2016 in Progress in Photovoltaics: Research and Applications
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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. © 2016 The Authors.Progress in Photovoltaics: Research and Applications published by John Wiley & Sons Ltd.

ACS Style

Philip A. Leicester; Chris I. Goodier; Paul Rowley. Probabilistic evaluation of solar photovoltaic systems using Bayesian networks: a discounted cash flow assessment. Progress in Photovoltaics: Research and Applications 2016, 24, 1592 -1605.

AMA Style

Philip A. Leicester, Chris I. Goodier, Paul Rowley. Probabilistic evaluation of solar photovoltaic systems using Bayesian networks: a discounted cash flow assessment. Progress in Photovoltaics: Research and Applications. 2016; 24 (12):1592-1605.

Chicago/Turabian Style

Philip A. Leicester; Chris I. Goodier; Paul Rowley. 2016. "Probabilistic evaluation of solar photovoltaic systems using Bayesian networks: a discounted cash flow assessment." Progress in Photovoltaics: Research and Applications 24, no. 12: 1592-1605.

Journal article
Published: 25 February 2016 in Progress in Photovoltaics: Research and Applications
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The establishment of new photovoltaic (PV) markets in emerging economies represents a business development opportunity for expansion outside traditional energy markets. Appropriate assessment of PV market competitiveness is thus necessary in order to inform policy and regulatory development, and in order to manage risks related to investment. This paper presents an evaluation of PV energy competitiveness using a case study of the emerging residential PV market in South Africa. Competitiveness is defined in light of the risks associated with the financial performance of domestic grid-connected rooftop PV considering the current market status together with three proposed business models, namely net-metering, net-billing and an energy savings performance contract framework. Financial performance is evaluated in terms of a socket parity evaluation together with a discounted net cash flow analysis. Investment risk assessment was facilitated using a Monte Carlo simulation. The results indicate the highest potential profitability for the energy savings performance contract model, which includes PV system ownership by an energy services company. It is also shown that appropriate application of risk modelling has the potential to inform decisions by investors and policy makers alike that result in improved policy and business solutions that are able to support increased residential PV energy market competitiveness without the need for explicit subsidy frameworks. Copyright © 2016 John Wiley & Sons, Ltd.

ACS Style

Stephanie Betz; Silvia Caneva; Ingrid Weiss; Paul Rowley. Photovoltaic energy competitiveness and risk assessment for the South African residential sector. Progress in Photovoltaics: Research and Applications 2016, 24, 1577 -1591.

AMA Style

Stephanie Betz, Silvia Caneva, Ingrid Weiss, Paul Rowley. Photovoltaic energy competitiveness and risk assessment for the South African residential sector. Progress in Photovoltaics: Research and Applications. 2016; 24 (12):1577-1591.

Chicago/Turabian Style

Stephanie Betz; Silvia Caneva; Ingrid Weiss; Paul Rowley. 2016. "Photovoltaic energy competitiveness and risk assessment for the South African residential sector." Progress in Photovoltaics: Research and Applications 24, no. 12: 1577-1591.

Journal article
Published: 01 July 2015 in IET Renewable Power Generation
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Replace with: Currently, the impacts of wide-scale implementation of photovoltaic (PV) technology are evaluated in terms of such indicators as rated capacity, energy output or return on investment. However, as PV markets mature, consideration of additional impacts (such as electricity transmission and distribution infrastructure or socio-economic factors) is required to evaluate potential costs and benefits of wide-scale PV in relation to specific policy objectives. This study describes a hybrid GIS spatio-temporal modelling approach integrating probabilistic analysis via a Bayesian technique to evaluate multi-scale/multi-domain impacts of PV. First, a wide-area solar resource modelling approach utilising GIS-based dynamic interpolation is presented and the implications for improved impact analysis on electrical networks are discussed. Subsequently, a GIS-based analysis of PV deployment in an area of constrained electricity network capacity is presented, along with an impact analysis of specific policy implementation upon the spatial distribution of increasing PV penetration. Finally, a Bayesian probabilistic graphical model for assessment of socio-economic impacts of domestic PV at high penetrations is demonstrated. Taken together, the results show that integrated spatio-temporal probabilistic assessment supports multi-domain analysis of the impacts of PV, thereby providing decision makers with a tool to facilitate deliberative and systematic evidence-based policy making incorporating diverse stakeholder perspectives.

ACS Style

Paul Rowley; Philip Leicester; Diane Palmer; Paul Westacott; Chiara Candelise; Thomas Betts; Ralph Gottschalg. Multi‐domain analysis of photovoltaic impacts via integrated spatial and probabilistic modelling. IET Renewable Power Generation 2015, 9, 424 -431.

AMA Style

Paul Rowley, Philip Leicester, Diane Palmer, Paul Westacott, Chiara Candelise, Thomas Betts, Ralph Gottschalg. Multi‐domain analysis of photovoltaic impacts via integrated spatial and probabilistic modelling. IET Renewable Power Generation. 2015; 9 (5):424-431.

Chicago/Turabian Style

Paul Rowley; Philip Leicester; Diane Palmer; Paul Westacott; Chiara Candelise; Thomas Betts; Ralph Gottschalg. 2015. "Multi‐domain analysis of photovoltaic impacts via integrated spatial and probabilistic modelling." IET Renewable Power Generation 9, no. 5: 424-431.

Conference paper
Published: 01 May 2015 in 2015 12th International Conference on the European Energy Market (EEM)
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The recent introduction of a number of electricity market instruments is designed to incentivise investment in reliable peaking capacity and power quality services. In this context, the energy storage capability of plug-in electric vehicles has the potential to provide valuable services to these markets. Using the UK as a case study, this paper quantifies the current and projected value streams for specific ancillary services markets, and evaluates the criteria for participation of EVs in the form of demand response. Using analysis of empirical EV usage data, the basis for a proposed aggregator operating model based on driver and vehicle classification is presented, taking into account charge/discharge depending on the time of day, thus providing an insight into the potential revenues that can be expected for an EV V2G aggregator.

ACS Style

Becky Gough; Paul Rowley; Sarwar Khan; Chris Walsh; Gough Becky. The value of electric vehicles in the context of evolving electricity markets. 2015 12th International Conference on the European Energy Market (EEM) 2015, 1 -6.

AMA Style

Becky Gough, Paul Rowley, Sarwar Khan, Chris Walsh, Gough Becky. The value of electric vehicles in the context of evolving electricity markets. 2015 12th International Conference on the European Energy Market (EEM). 2015; ():1-6.

Chicago/Turabian Style

Becky Gough; Paul Rowley; Sarwar Khan; Chris Walsh; Gough Becky. 2015. "The value of electric vehicles in the context of evolving electricity markets." 2015 12th International Conference on the European Energy Market (EEM) , no. : 1-6.

Conference paper
Published: 01 July 2014 in 2014 UKACC International Conference on Control (CONTROL)
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This paper investigates the effect of model mismatch on the performance of model predictive control (MPC) when applied to the heating system. The controller uses a linear model and a quadratic cost function, while the actual process is non-linear in nature with a linear cost function. A genetic algorithm (NSGA II) is used to find the optimal solution to the actual problem and a number of variations, which are then compared the performance of the MPC controller. The results show that the model mismatch has a small but significant effect on the control performance, and it does prevent effective load shifting in certain situations.

ACS Style

Muhammad Waseem Ahmad; Mahroo Eftekhari; Thomas Steffen; Paul Rowley; Mahdi Eftekhari. The effect of model and objective function mismatch in model predictive control (MPC) for a solar heating system with a heat pump. 2014 UKACC International Conference on Control (CONTROL) 2014, 685 -690.

AMA Style

Muhammad Waseem Ahmad, Mahroo Eftekhari, Thomas Steffen, Paul Rowley, Mahdi Eftekhari. The effect of model and objective function mismatch in model predictive control (MPC) for a solar heating system with a heat pump. 2014 UKACC International Conference on Control (CONTROL). 2014; ():685-690.

Chicago/Turabian Style

Muhammad Waseem Ahmad; Mahroo Eftekhari; Thomas Steffen; Paul Rowley; Mahdi Eftekhari. 2014. "The effect of model and objective function mismatch in model predictive control (MPC) for a solar heating system with a heat pump." 2014 UKACC International Conference on Control (CONTROL) , no. : 685-690.

Review
Published: 07 March 2014 in Architectural Engineering and Design Management
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The performance of Pimlico District Heating Undertaking (PDHU), in London, with an annual heating load of 50,000 MWh was analysed throughout 2012. Half-hourly data for the system were investigated to determine the natural gas consumed, operation of the 2500 m3 accumulator, the two 1.6 MWe combined heat and power (CHP) engines, the three 8 MW boilers, the electricity import and export and the consumers' heat consumption. These data were used to characterise the current performance in detail, and an energy flow diagram for the system energy flows was generated. The modulating efficiencies of the boilers varied from 84% to 91%, whereas the CHP engines performed with a modulating near constant electrical efficiency of 40%, but with a thermal efficiency that decreases with higher load. The current operation of the plant is compared across 10 scenarios. These scenarios were compared while (i) using the accumulator more effectively to let the boilers operate at full load only and (ii) using the provided maintenance agreement contract of the CHP engines to guarantee their good operation. Optimising the operation of the current plant reduces the annual heating cost of £165,000 or 12% and investing in additional CHP capacity can reduce the CO2 emissions by 28%.

ACS Style

Oliver Martin-Du Pan; Philip Eames; Paul Rowley; Dino Bouchlaghem; Gideon Susman. Current and future operation scenarios for a 50,000 MWh district heating system. Architectural Engineering and Design Management 2014, 11, 280 -304.

AMA Style

Oliver Martin-Du Pan, Philip Eames, Paul Rowley, Dino Bouchlaghem, Gideon Susman. Current and future operation scenarios for a 50,000 MWh district heating system. Architectural Engineering and Design Management. 2014; 11 (4):280-304.

Chicago/Turabian Style

Oliver Martin-Du Pan; Philip Eames; Paul Rowley; Dino Bouchlaghem; Gideon Susman. 2014. "Current and future operation scenarios for a 50,000 MWh district heating system." Architectural Engineering and Design Management 11, no. 4: 280-304.

Journal article
Published: 18 September 2013 in IEEE Journal of Photovoltaics
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The aim of this investigation is to apply advanced microstructural characterization techniques to study the effect of cadmium chloride treatment on the physical properties of cadmium telluride (CdTe) solar cells deposited via close-spaced sublimation and relate these to cell performance. A range of techniques have been used to observe the microstructural changes as well as the chemical changes before and after the cadmium chloride treatment. Electrical measurements that link the device performance with the microstructural properties of the cells have also been undertaken. Transmission electron microscopy (TEM) has revealed high densities of stacking faults in the as-grown CdTe samples. Further, it has been observed that these stacking faults are removed during the cadmium chloride treatment. These observations show that the presence of chlorine plays an important role in the removal of these defects and the subsequent production of high efficiency thin-film CdTe solar cells. Elemental analysis in the TEM indicates chlorine-rich regions appearing at the CdTe/CdS interface as well as at grain boundaries after the treatment.

ACS Style

A. Abbas; G. D. West; Jake Bowers; Patrick Isherwood; P. M. Kaminski; Biancamaria Maniscalco; Paul Rowley; John Walls; K. Barricklow; W. S. Sampath; K. L. Barth. The Effect of Cadmium Chloride Treatment on Close-Spaced Sublimated Cadmium Telluride Thin-Film Solar Cells. IEEE Journal of Photovoltaics 2013, 3, 1361 -1366.

AMA Style

A. Abbas, G. D. West, Jake Bowers, Patrick Isherwood, P. M. Kaminski, Biancamaria Maniscalco, Paul Rowley, John Walls, K. Barricklow, W. S. Sampath, K. L. Barth. The Effect of Cadmium Chloride Treatment on Close-Spaced Sublimated Cadmium Telluride Thin-Film Solar Cells. IEEE Journal of Photovoltaics. 2013; 3 (4):1361-1366.

Chicago/Turabian Style

A. Abbas; G. D. West; Jake Bowers; Patrick Isherwood; P. M. Kaminski; Biancamaria Maniscalco; Paul Rowley; John Walls; K. Barricklow; W. S. Sampath; K. L. Barth. 2013. "The Effect of Cadmium Chloride Treatment on Close-Spaced Sublimated Cadmium Telluride Thin-Film Solar Cells." IEEE Journal of Photovoltaics 3, no. 4: 1361-1366.

Conference paper
Published: 01 September 2013 in 2013 48th International Universities' Power Engineering Conference (UPEC)
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UK greenhouse gas (GHG) emissions are mandated by law to be 80% lower in 2050 than in 1990. In an effort to reduce transport emissions, vehicle manufacturers have recently introduced new electric vehicle technologies to the UK market. A number of empirical studies have shown that consumer attitudinal barriers are inhibiting the adoption of new vehicle technologies. This study was established to develop software tools that could be used to minimise these barriers. Four dynamic models were developed to examine vehicle CO 2 emissions, all electric vehicle range, factors that determine vehicle energy requirements and vehicle cost of ownership. Seven vehicles representing diesel, battery only electric vehicles and range extended electric vehicle technologies were compared using the software tools. The results of the study show that relatively simple models, based on standard office spreadsheet software, can be used to demonstrate the significant CO 2 emissions reduction possible with electric vehicles and that vehicle range is largely determined by the charging infrastructure. The results also suggest that the higher purchase price for these technologies may be recovered based on the fuel cost savings, congestion charge savings and potential higher retained value at end of life. The models also have the potential to demonstrate the impact of auxiliary loads, payload and battery charger efficiency on the vehicles fuel consumption.

ACS Style

Kevin Davis; Paul Rowley; Steve Carroll. Assessing the viability of electric vehicle technologies for UK fleet operators. 2013 48th International Universities' Power Engineering Conference (UPEC) 2013, 1 -6.

AMA Style

Kevin Davis, Paul Rowley, Steve Carroll. Assessing the viability of electric vehicle technologies for UK fleet operators. 2013 48th International Universities' Power Engineering Conference (UPEC). 2013; ():1-6.

Chicago/Turabian Style

Kevin Davis; Paul Rowley; Steve Carroll. 2013. "Assessing the viability of electric vehicle technologies for UK fleet operators." 2013 48th International Universities' Power Engineering Conference (UPEC) , no. : 1-6.

Conference paper
Published: 01 June 2013 in 2012 38th IEEE Photovoltaic Specialists Conference
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The aim of this investigation is to apply advanced microstructural characterization techniques to study the effect of the cadmium chloride treatment on the physical properties of cadmium telluride solar cells deposited via close-spaced sublimation (CSS) and relate these to cell performance. A range of techniques have been used to observe the microstructural changes as well as the chemical changes before and after cadmium chloride treatment. Electrical measurements that link the device performance with the microstructural properties of the cells have also been undertaken. Transmission Electron Microscopy (TEM) has revealed high densities of stacking faults in the as-grown CdTe samples. Further, it has been observed that these stacking faults are removed during the cadmium chloride treatment. These observations show that the presence of chlorine plays an important role in the removal of these defects and the subsequent production of high efficiency thin film CdTe solar cells. Elemental analysis in the TEM indicates chlorine rich regions appearing at the CdTe/CdS interface as well as at grain boundaries after the treatment.

ACS Style

A. Abbas; G. D. West; J. W. Bowers; Patrick Isherwood; P. M. Kaminski; Biancamaria Maniscalco; Paul Rowley; J. M. Walls; K. Barricklow; W. S. Sampath; K. L. Barth. The effect of cadmium chloride treatment on close spaced sublimated cadmium telluride thin film solar cells. 2012 38th IEEE Photovoltaic Specialists Conference 2013, 1 -6.

AMA Style

A. Abbas, G. D. West, J. W. Bowers, Patrick Isherwood, P. M. Kaminski, Biancamaria Maniscalco, Paul Rowley, J. M. Walls, K. Barricklow, W. S. Sampath, K. L. Barth. The effect of cadmium chloride treatment on close spaced sublimated cadmium telluride thin film solar cells. 2012 38th IEEE Photovoltaic Specialists Conference. 2013; ():1-6.

Chicago/Turabian Style

A. Abbas; G. D. West; J. W. Bowers; Patrick Isherwood; P. M. Kaminski; Biancamaria Maniscalco; Paul Rowley; J. M. Walls; K. Barricklow; W. S. Sampath; K. L. Barth. 2013. "The effect of cadmium chloride treatment on close spaced sublimated cadmium telluride thin film solar cells." 2012 38th IEEE Photovoltaic Specialists Conference , no. : 1-6.

Journal article
Published: 28 March 2013 in Applied Sciences
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The UK Government has ambitious targets for CO2 emissions reductions, particularly for the domestic housing stock. One technology that is expected to contribute significantly is heat pumps, both air and ground source. However, recent field trial results suggest that heat pumps in the UK are not delivering to performance expectations. This paper looks at the implications of these results for the UK housing stock’s future CO2 emissions. The English Housing Condition Survey dataset is used as the basis for a Monte Carlo simulation in order to model CO2 emissions and energy consumption for the whole of English housing stock out to 2050. The results suggest that, given the current UK electricity grid CO2 emission factor, in the short term poor heat pump performance could lead to a rise in emissions where natural gas boilers are displaced. In the longer term, heat pumps can realise emissions reductions when installed at high penetration levels when combined with a grid decarbonisation strategy. Until grid decarbonisation occurs, an alternative phased strategy is proposed that includes phased replacement of resistive electric heating, first in households in fuel poverty and then the remainder of properties with this heating type. Following this phased strategy, real emissions savings are possible along with a potential reduction in fuel poverty.

ACS Style

David Braun; Paul Rowley. Modelling the Contribution of Domestic Heat Pumps to Delivering UK Energy Policy Objectives. Applied Sciences 2013, 3, 338 -354.

AMA Style

David Braun, Paul Rowley. Modelling the Contribution of Domestic Heat Pumps to Delivering UK Energy Policy Objectives. Applied Sciences. 2013; 3 (2):338-354.

Chicago/Turabian Style

David Braun; Paul Rowley. 2013. "Modelling the Contribution of Domestic Heat Pumps to Delivering UK Energy Policy Objectives." Applied Sciences 3, no. 2: 338-354.

Original articles
Published: 31 January 2013 in Journal of Building Performance Simulation
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This paper presents an analysis of the zero-carbon performance of a case-study building which is representative of a growing number of new buildings that are being built on redevelopment sites in inner-city areas in the UK. Compact urban dwellings are apartment style buildings with a floor area of ∼50 m2 per dwelling, often based over two floors. The constraints of this type of building on achieving zero-carbon performance in the context of the Code for Sustainable Homes is discussed and the shortcomings of the code are demonstrated in terms of the target heat and electricity demand targets for the design of the building systems. A graphical representation of the simulation results is used to present the findings. It has been demonstrated that in specific urban contexts, zero-carbon performance as defined within the current UK compliance framework may be very difficult to achieve in practice given the assumptions used in the simulation here. Therefore, it is very likely that zero-carbon compact urban dwellings may require a net off-site import of electrical and/or thermal energy.

ACS Style

L. A. Steijger; R. A. Buswell; V. A. Smedley; S. K. Firth; Paul Rowley. Establishing the zero-carbon performance of compact urban dwellings. Journal of Building Performance Simulation 2013, 6, 319 -334.

AMA Style

L. A. Steijger, R. A. Buswell, V. A. Smedley, S. K. Firth, Paul Rowley. Establishing the zero-carbon performance of compact urban dwellings. Journal of Building Performance Simulation. 2013; 6 (4):319-334.

Chicago/Turabian Style

L. A. Steijger; R. A. Buswell; V. A. Smedley; S. K. Firth; Paul Rowley. 2013. "Establishing the zero-carbon performance of compact urban dwellings." Journal of Building Performance Simulation 6, no. 4: 319-334.