Paul Rowley

Determination of coordinations and coordination-specific site occupancies by electron energy-loss spectroscopy: An investigation of boron—oxygen compounds

Abstract Electron energy-loss near-edge structure (ELNES) in B1s core-level spectra has been investigated for various compounds containing boron in planar-trigonal, tetrahedral or both coordinations to oxygen. Distinctive BO 3 and BO 4 ELNES “fingerprints” have been determined experimentally and confirmed theoretically by multiple scattering calculations. We demonstrate a quantitative method to derive the coordination-specific boron site occupancies from B1s spectra taken from complex borates containing both coordinations. This method has been applied to investigate the radiation damage of hydroxyborate minerals and to analyze the B1s ELNES taken from boron-doped Fe-Cr oxide layers formed on stainless steel in superheated steam.

The effects of boron additions on the oxidation of Fe-Cr alloys in high-temperature steam: Analytical results and mechanisms

The oxide films formed on iron-chromium alloys in superheated steam have been investigated using a variety of microanalytical techniques, most notably electron energy loss spectroscopy. The addition of boron dopants leads to the rapid formation of a microcrystalline film of composition (Cr)xB1}-x2O3,which resists further oxidation. Analysis of the near-edge structures associated with each core-loss edge after different oxidation times allows us to postulate various mechanisms for the observed behavior.

Utilizing a Risk-Based Systems Approach in the Due Diligence Process for Renewable Energy Generation

The commercial viability of a marine renewable energy technology is impacted by a range of holistic factors related not only to the performance of the generating device, but also the characteristics of the system-of-systems within which the device operates. In this work, an investment risk assessment methodology is presented that takes account of a wide range of whole-system parameters, and provides a bridge between a device-centric evidence base and the wider systems-level data that is required in order to effectively assess the case for a specific investment. Within the paper, a system modeling framework is presented, and a case study assessment is conducted to illustrate the application of the proposed approach. The results indicate that by considering a proposed scheme in terms of both its efficacy as an operating system, along with specific lifecycle factors from concept to disposal, risks and costs can be identified in a systematic and justifiable manner. In addition, technical factors can be described in terms of their effects on the primary capability of the system, namely to produce electricity at an economically feasible cost whilst maximizing return on investment.

Establishing the zero-carbon performance of compact urban dwellings

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.

Techno-economic optimization of sustainable power for telecommunications facilities using a systems approach

Telecommunications network operators face the dual challenges of powering remote equipment while controlling both operating costs and energy consumption. As a means to help meet these challenges, this paper describes the functionality and performance of an Alternative Power Analyzer tool specially made for remote base station applications which models the outputs of renewably generated power based on location and user inputs. It combines these results with economic inputs to produce a business plan for the implementation of the preferred system. An important factor affecting economic viability is the various incentives for sustainable power generation. These can vary greatly by value, duration, equipment eligibility, location, and other constraints. To manage these complex datasets, a dynamic ontological information framework has been developed which is designed to iteratively interface with the APA tool. The outputs of the work indicate that a techno-economic systems approach can be applied both to assess the viability of location-specific system configurations under current incentives frameworks and to inform policy makers in terms of future incentives optimization.

Electron energy-loss studies of Fe–Cr–Mn oxide films

Abstract Electron energy-loss spectroscopy (EELS) conducted in an electron microscope has been employed to investigate the stoichiometry of oxide films formed during the steam oxidation of an Fe–9%Cr–1%Mo alloy, containing 0·5%Mn, in the presence of boron dopants. Significant amounts of boron were detected which resulted in a large enhancement of both the chromium and manganese concentrations, the overall oxide stoichiometry being (Fe, Cr, Mn, B)2O3. Analysis and modelling of the electron loss near-edge structures provided support for the postulated stoichiometry as well as indicating that boron is in trigonal coordination to oxygen.

The effect of model and objective function mismatch in model predictive control (MPC) for a solar heating system with a heat pump

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.

Assessing the viability of electric vehicle technologies for UK fleet operators

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 CO2 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 CO2 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.

The value of electric vehicles in the context of evolving electricity markets

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.

Assessment of PV System Performance with Incomplete Monitoring Data

An analysis of PV system performance requires both meteorological and electrical data for the assessment period. However, actual in-field data acquisition is rarely 100%, often resulting in a significant amount of incomplete data sets for performance assessment. These gaps, if not taken into account, may add noticeable bias in yield assessment and thus estimations of the lacking data need to be made. An approach of back-filling the required data is given and validated here. Three different categories of data loss are identified and case-specific methods of synthesising missing data are developed. The integrity of the performance assessment process is assessed. The three cases of data loss are defined as: missing meteorological data only, missing electrical monitoring data only and missing both electrical and meteorological data. Case-specific methods are proposed and their performance against measured data is evaluated statistically by means of: root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The inferred monthly performance ratio on two of the selected cases showed accurate agreement against measured data presenting significantly low MBE values, equal or less than -0.01.