Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Currently the accepted technology for large wind turbines is the doubly-fed induction generator (DFIG). This technology is popular primarily due to the reduced cost of the partially rated power electronic converter. On the negative side is the fact that the generator requires brushes and slip rings which require regular maintainance.An alternative scheme is based on the brushless doubly-fed reluctance machine (BDFRM) which also has the cost benefit of a partially rated power converter but as its name implies does not require brushes and slip rings.The BDFRM has not been used for a wind power application. This project will experimentally examine its performance for a wind power application. There are a number of different approaches to the control of a BDFRM. The project will examine the use of Direct Power Control (DPC). This control approach will include sensorless operation and machine parameter independence. With the proliferation of wind power generation the issue of power system stabilty is of great concern. It is important to examine the fault-ride-through (FRT) capabilty of any generation system. This project will examine the FRT capability of the BDFRM and compare this to that of the DFIG. This will require that special grid fault emulation equipment is included in the laboratory test rig.

There is an urgent need to expand the use of renewable energy generation systems to meet UK government targets. The expansion of grid-connected renewable energy sources must be done in a way which does not reduce the security of the power distribution system. Integral to power distribution system security is the ability of distributed generators to reliably detect a loss of grid condition. This is important to prevent unwanted islanded sections of the system which continue to be energised after the grid connection is lost. An islanding system occurs when a part of the grid system become disconnected from the rest of the network but continues to be energised by localised distributed generation systems. Islanded systems are (i) potentially hazardous to power system workers, (ii) may operate outside voltage and frequency tolerance, (iii) may be inadequately grounded and (iv) may not re-synchronise properly leading to undesirable protection trips. The existing approaches to islanding detection either have operational regions in which they fail to work or are required to have artificial signals injected into the grid which can impact on power quality. The most difficult operational condition is when there is a power balance between a distributed generator and its local load network. During this condition many systems will not detect that the grid connection has been lost because the fundamental frequency quantities are not altered by the event. Many renewable generation systems require a grid-connected inverter to transfer power into the grid. This is necessary because the generating source itself is rarely capable of producing power at grid frequency. A grid-connected inverter must be able to detect the loss of grid event. This proposal will investigate a novel approach using pattern recognition with a high sampling rate. The pattern recognition system is required to analyse the inverter output voltages and currents to determine if a loss of grid event has taken place. The novelty in this proposal is to include the high frequency information due to PWM effects in the real-time analysis. The benefit of doing this is that information will still be available to the pattern recognition system when a power balance condition exists. There is concern that many islanded detection systems are not immune from the effects of other neighbouring equipment. This equipment may be power electronic loads or other grid-connected inverters. The basis of the proposed approach is that the pattern recognition system will be able to discriminate between the presence and absence of the grid connection despite potential interference signals from neighbouring equipment. A major advantage of the proposed scheme is that it makes use of high frequency signals generated by the PWM switching in the inverter. These signals are extracted from the output voltages and currents by using high sampling rates where a number of samples are taken during one PWM cycle. These signals will still be present when a balance load condition exits and therefore will provide valuable diagnostic information during this difficult condition. These high frequency signals will add to the signals associated with the fundamental frequency components to detect the loss of grid event. It is important that this scheme is demonstrated experimentally and therefore a test rig will be produced which contains a range of typical loads and other grid-connected generators. The rig will be used to evaluate the performance of the proposed scheme in the presence of other neighbouring power electronic equipment. If successful the research will have major impact on the integration of renewable energy generation into power distribution systems. There will be significant benefits to power distribution system security and to the manufacturers of grid-connected inverters.

The aim of this proposal is to demonstrate direct flame solid oxide fuel cells (DFFCs) to extract electricity directly from natural gas and liquid petroleum gas (LPG) flames. DFFCs can be integrated into conventional burners and cookers to generate electricity as a useful by-product. They can remove electrical power requirements for managing the system and perhaps also provide the energy required for pumping. Potentially it can be used for remote and portable applications to power the wireless world. We will demonstrate DFFC cells with large area which can be directly put in the flame of a burner/cooker to generate electricity with the application of advanced materials. The novelty of these DFFCs lies in optimising the flame positioning on the performance of the cell and the use of redox stable cathode to improve the durability on redox and thermal cycling. Sealing is not required and DFFCs are relatively safe. Due to the presence of the flame, the DFFC operating environment with frequent redox and thermo cycling, the real challenge comes from the identification and application of robust materials. So far the best anode material for DFFCs is (La0.75Sr0.25)Cr0.5Mn0.5O3-delta (LSCM) which was developed and patented by the proposers therefore the anode will be focused on LSCM. However, the reported cathode used for DFFCs are not redox stable which may affect the durability. The proposed project is a collaboration between University of Strathclyde and University of St Andrews that involves a coordinated program to screen existing materials, investigate the flame, optimise the operating condition, design and built suitable test rig and test the performance and cycling stability of both small and big cells including multi-cell stacks. These simple DFFC devices will provide an ideal entry market for application of SOFCs. The IP generated from this project will be protected before publishing.

Electricity and natural gas networks, as two major energy transport infrastructure, have traditionally been planned and operated independently from each other. Electricity generation was dominated by coal, oil and nuclear power stations prior to 1990, when the "dash for gas" brought a significant number of gas-fired power stations into the generation mix. These geographically dispersed large power stations have created a loose link between natural gas and electricity networks at the energy source. As the pace of decarbonising our electricity section accelerates, the two energy networks will progressively become more closely linked by end users, driven by the electrification of heat and major efficiency improvements. This presents critical new challenges to the traditional network modelling, operation and optimisations, in particular as they were developed independently for natural gas and electricity networks. The traditional methods do not take into account of the substantial rise in the interaction between the two networks, i.e. how a change in gas demand/resource might impact the demand/generation of the electrical system and vice versa. The vision of this research is to develop a statistical model for combined gas and electricity systems at the distribution level that can efficiently simulate the interactions across the energy vector under severe uncertainties. The developed model will then be fed to the novel optimal operation strategies to manage the two systems for encouraging increased use of renewables and infrastructure and promoting customer interaction with the systems. This fellowship will address this vision by developing highly efficient network sampling methodologies, multi-vector probabilistic energy flow and optimisation tools that will transform the modelling and analysis of highly integrated systems. These new developments will: i) enable detailed real-time analyses of energy flows and capacity bottlenecks of the highly integrated energy systems with high accuracy and in reasonable time scale, ii) assist network operators to optimise the performance of the existing energy systems to minimise the cost of integrating low carbon generation and demand, and iii) assist policy makers to design effective policies and regulations for economic and sustainable energy network development.