An iterative analytical design framework for the optimal designing of an off-grid renewable energy based hybrid smart micro-grid

Creative ways of utilising renewable energy sources in electricity generation especially in remote areas and particularly in countries depending on imported energy, while increasing energy security and reducing cost of such isolated off-grid systems, is becoming an urgently needed necessity for the effective strategic planning of Energy Systems. The aim of this research project was to design and implement a new decision support framework for the optimal design of hybrid micro grids considering different types of different technologies, where the design objective is to minimize the total cost of the hybrid micro grid while at the same time satisfying the required electric demand. Results of a comprehensive literature review, of existing analytical, decision support tools and literature on HPS, has identified the gaps and the necessary conceptual parts of an analytical decision support framework. As a result this research proposes and reports an Iterative Analytical Design Framework (IADF) and its implementation for the optimal design of an Off-grid renewable energy based hybrid smart micro-grid (OGREH-SμG) with intra and inter-grid (μG2μG & μG2G) synchronization capabilities and a novel storage technique. The modelling design and simulations were based on simulations conducted using HOMER Energy and MatLab/SIMULINK, Energy Planning and Design software platforms. The design, experimental proof of concept, verification and simulation of a new storage concept incorporating Hydrogen Peroxide (H2O2) fuel cell is also reported. The implementation of the smart components consisting Raspberry Pi that is devised and programmed for the semi-smart energy management framework (a novel control strategy, including synchronization capabilities) of the OGREH-SμG are also detailed and reported. The hybrid μG was designed and implemented as a case study for the Bayir/Jordan area. This research has provided an alternative decision support tool to solve Renewable Energy Integration for the optimal number, type and size of components to configure the hybrid μG. In addition this research has formulated and reported a linear cost function to mathematically verify computer based simulations and fine tune the solutions in the iterative framework and concluded that such solutions converge to a correct optimal approximation when considering the properties of the problem. As a result of this investigation it has been demonstrated that, the implemented and reported OGREH-SμG design incorporates wind and sun powered generation complemented with batteries, two fuel cell units and a diesel generator is a unique approach to Utilizing indigenous renewable energy with a capability of being able to synchronize with other μ-grids is the most effective and optimal way of electrifying developing countries with fewer resources in a sustainable way, with minimum impact on the environment while also achieving reductions in GHG. The dissertation concludes with suggested extensions to this work in the future.

Effects of mass and body composition on fasting fuel utilisation in grey seal pups (Halichoerus grypus Fabricius): an experimental study using supplementary feeding

This study used supplementary feeding to test the hypothesis that fuel partitioning during the postweaning fast in grey seal pups is affected by size and composition of energy reserves at weaning, and by extra provisioning. Mass and body composition changes were measured during suckling and fasting to investigate the effect of natural differences in energy reserves at weaning on subsequent allocation of fat and protein to energy use. We fed seven pups for 5 days after weaning, to investigate the effect of increased fuel availability, and particularly protein, on fuel utilisation. After correcting for protein used during the moult, the proportional contribution of fat was 86–99% of total energy use. Pups with greater energy reserves, i.e. those that were heavier and fatter at weaning, had higher rates of fat and energy use. There was no significant relationship between adiposity at weaning and proportional contribution of fat to energy use, perhaps due to a limited sample size or range of body masses and adiposity. Supplemented individuals used energy, specifically fat, much faster and utilised proportionally less of their endogenous protein by departure than non-supplemented individuals. Fat metabolism contributed a similar percentage to daily energy use in both groups. These findings show that pups spare protein, even when energy use is dramatically increased. Pups that receive greater maternal provisioning and lay down more protein may have increased survival chances at sea. This study highlights the importance of protein reserves in first year survival of grey seal pups.

Evolution of emerging iPS cell-based therapies for age-related macular degeneration (AMD)

Stem cell-based regenerative medicine is poised to revolutionize the way diseases are treated. In recent years, induced pluripotent stem (iPS) cells, a newly stem cell species, has attracted significant attention. This paper seeks to understand the pathways along which emerging clinical research efforts in the field of iPS cells is evolved. In particular, the empirical case of age-related macular degeneration (AMD) is used, which is the world-pioneering clinical application of iPS cells. In line with the literature, this study explores the interrelations between three different pathways, such as biomedical scientific understanding, development of medical technologies, and learning in clinical practice. For this, a techmining approach is used including co-term, co-citation, and direct citation methods. Scientific publications indexed in the Thomson Reuters' Web of Science and Elsevier's Scopus databases form the basis of the study. This research first explores the iPS cell research landscape through the construction of a co-term map, particularly stressing the location and intensity of disease-tackling efforts; then focus on the evolution of scientific knowledge on AMD through co-citation networks and the main path algorithm on direct citations. At the researcher level, the development of four different research groups working on cell therapies for AMD is evaluated through the software CitNetExplorer. By integrating these approaches, the result shows a wider picture of the complexities inherent in the translation of knowledge into revolutionary clinical methods.