• Energy Research
• OA Publications Mandate: No close
• 2021 close

Urgent efforts are required to reduce the cost of renewable energy in order to tackle the worst effects of climate change. The fastest growing renewable energy technology is photovoltaics (PV), which will account for 30% of global power generation capacity in the coming decades. Silicon PV, which currently accounts for more than 90% of the market, is a proven technology where significant technological improvements will ensure further price reductions and increased deployment. Improvement in cell power conversion efficiency is a key driving factor in reducing the cost of solar energy, which this proposal aims to achieve by developing industrially-compatible optical enhancement, surface passivation and emitter formation techniques for silicon solar cells. The methods developed as part of this project will be applied to the leading solar cell technologies based on mono- (c-Si) and multi-crystalline silicon (mc-Si). For c-Si, this is a rear junction (RJ) architecture also known as the interdigitated back contact cell, and for mc-Si, this is a front junction (FJ) architecture. To enhance the RJ cell technology, where the p-n junction is at the back of the cell and unaffected by the front surface texturing, the approach is to use a solution-based texturing technique that leads to optically black silicon surfaces. For the case of the FJ cell architecture, where formation of the p-n junction at the front surface alongside texturing has to be considered, gas-phase processes will be investigated. Upon developing effective antireflective surfaces for RJ and FJ solar cells the challenge becomes transferring the gain in photon capture to improvements in the efficiency of the cell. For this to take place the electrical properties of the surface must be studied, and methods developed to mitigate any electrical degradation due to the texturing processes. This project is uniquely positioned to address jointly the optical and electrical properties of the cells, and by doing so, aims to produce optimally textured surfaces that can be easily integrated into the manufacture of solar cells. The project teams at Southampton and Oxford will draw on their close collaborations with the world-leading research institutes at Fraunhofer ISE, Germany, and UNSW, Australia. This will enable the demonstration of the proposed texturing technology on state-of-the-art silicon solar cells, as well as providing access to advanced techniques in characterisation and processing. These collaborations will also promote knowledge transfer to the UK research community. A core principle of this proposal is to contribute to improving industrial solar cell production. For this, two strategic industrial collaborations have been established. Firstly Tetreon Technologies, the leading UK manufacturer of industrial tools for solar cell production, will be closely involved in the project, with the aim of subsequently developing industrial equipment and processes for export to the global market. Secondly Trina Solar, one of the world's largest cell manufacturers and the industrial leader in high efficiency cells, will provide insight into the market and industry needs that this project aims to address. They will demonstrate successful processes in an industrial environment from cell to module manufacture. Through these collaborations this project will leverage cutting edge expertise in the complementary areas of surface passivation and light trapping to tackle the challenge of developing photovoltaic technology. The project will deliver substantially improved efficiencies for silicon based solar cells and modules and, through close collaboration with UK and international companies, will allow the research undertaken to be rapidly exploited in the form of new tools and processes for export to the global solar industry. Alongside the expertise within the team, its academic and industrial networks form an ideal basis for the innovative and impactful research programme.

The rapid growth of wind energy production in recent years has reached a stage where the aerodynamic noise emission from wind turbines is a critical issue to overcome in order to successfully continue increasing the scale of the turbines and reducing the cost of energy (CoE). The fundamental principle to tackle the aerodynamic noise issue is to design the turbine blades in such a way that the source of noise is alleviated without changing the aerodynamic efficiency of the blades that is critical for CoE. One of the most effective ways to achieve such a noise-noise blade design is to use "serrations" on the trailing-edge of the blades from which the noise emission is strongest (at an operating condition). Vestas (one of the largest wind-turbine manufacturers in the globe) has been successful in developing blades with serrated trailing-edges (STEs) in recent years and they are in service now. However, the research on STEs is still underdeveloped and there are various areas where STEs should be better understood and improved upon what they are at present. Vestas aims to make a major breakthrough in the development of STEs within the next a few years in order to successfully implement the technology in their next-generation wind turbines. The proposed PhD project at the University of Southampton is part of the Vestas multidisciplinary programme for the development of next-generation STEs. This particular PhD project aims to achieve detailed understandings of the physical mechanisms of the noise generation and its reduction due to the STEs, and to derive a semi-empirical engineering model that provides predictions of the noise reduction through the STEs for various geometries and flow conditions. The project will be carried out mainly based on numerical simulations (large-eddy simulations) and some mathematical derivations for the prediction model. The large-eddy simulations will be performed by using an in-house code CANARD (Compressible Aerodynamic & Aeroacoustic Research coDe) developed at the University of Southampton. The code is based on high-order finite-difference methods and is fully parallelised on an MPI platform (running on the national supercomputer ARCHER as well as the local IRIDIS-4 cluster with a supra-linear scalability with up to 10,000+ processor cores). Some more relevant information about the computational work can be found in https://doi.org/10.1017/jfm.2016.841.