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.

A LOFAR mini-survey for low-frequency radio emission from the nearest brown dwarfs

We have conducted a mini-survey for low-frequency radio emission from some of the closest brown dwarfs to the Sun with rapid rotation rates: SIMP J013656.5 +093347, WISEPC 150649.97+702736.0, and WISEPA J174124.26+255319.5.We have placed robust 3s upper limits on the flux density in the 111 – 169 MHz frequency range for these targets: WISE 1506: < 0:72 mJy; WISE 1741: < 0:87 mJy; SIMP 0136: < 0:66 mJy. At 8 hours of integration per target to achieve these limits, we find that systematic and detailed study of this class of object at LOFAR frequencies will require a substantial dedication of resources.

Validation of a novel assay for cardiology drug screening using hESC-derived cardiomyocyte spheroids - “mini-hearts”

This is an abstract of a presented talk at the European Biotechnology Conference held in Latvia during 05–07 May 2016