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To achieve electricity access in developing countries, grid extension and off-grid energy solutions, such as minigrids, are employed. Recent evidence from Southeast Asia has indicated that the grid continues to expand and converges with minigrids beyond achieving electricity access. Such convergence is associated with policy, regulatory and technical challenges. For example, one of the technical challenges related to grid integration of minigrids is the lack of appropriate methods for their optimal planning. Previous research demonstrates that identifying an optimal point of grid infeed into a minigrid improves the loss reduction of the integrated network. However, the method for identifying grid infeed points requires a detailed power system analysis to be conducted for each minigrid integrating with the main grid. This paper introduces a loading index that can operate as a ‘rule of thumb’ for pre-assessing the need for a detailed grid integration study. The presented index is demonstrated for two case studies, and its accuracy on different minigrid conditions is also discussed.

The performance of Magnetized Liner Inertial Fusion (MagLIF) experiments is sensitive to the amount of laser energy coupled to the fuel during the preheat stage. 1 A significant source of energy loss in this process comes from the need to heat a laser entrance hole foil (LEH) located at the entrance to the target that is required to contain the gaseous fusion fuel. The energy lost to the LEH is a function of its thickness which can be reduced by cryogenically cooling the fuel, lowering the pressure required for a given fuel density. 2 To realize this, a cryogenically-cooled laser target platform was commissioned in the Pecos chamber that enables rapid testing of preheat configurations, 3 and a cryogenically-cooled MagLIF configuration was tested that symmetrically cools the liner from the top and bottom, minimizing temperature gradients across the target. These new capabilities were utilized to perform a cryogenically-cooled MagLIF experiment that demonstrated >2 kJ of preheat energy coupled to the fuel for the first time on Z.

Energy services social enterprises are emerging as a sustainable response to the challenges of achieving SDG 7, but detailed case study insight is lacking to inform the sector. Malawi has one of the lowest electricity access rates in the world, with a rural electrification rate of only 4%. This paper highlights lessons from an energy service social enterprise in Malawi, using a case study framework to outline key achievements and challenges faced. The learning is used to form recommendations on increasing the impact, growth and sustainability of energy service social enterprises, both for grassroots practitioners as well as policy and investment decision makers. It has been found that energy service social enterprises need to develop robust strategies for sustainability through fostering cross sectorial linkages, investing in capacity building and awareness raising, collaborating through research partnerships, budgeting and resource planning conservatively, tracking social impact to inform business strategy, seeking innovation in business planning, and utilising smart subsidies. The case study analysis presented is intended to inform other social enterprises offering energy services, and to progress the rural electrification sector to achieve Sustainable Development Goal 7.

This paper presents the findings from a study which used household surveys and expert interviews to investigate cooking practices and understand the barriers and opportunities to the growth of the modern cooking sector in Malawi. The findings from expert interviews highlight barriers to electric and LPG cooking around the weakness of existing infrastructure, lack of consumer willingness and ability to pay and resistance to the adoption of modern cooking devices. The greatest opportunity for electric cooking is in urban areas and on mini-grids, while LPG is also most viable in urban areas, however knowledge and infrastructure gaps need to be narrowed to facilitate growth. An analysis of household surveys in urban, peri-urban and rural areas, using data from “indicative cooking diaries”, demonstrates the diversity of cooking practices in Malawian households by showing what, how, and with what, dishes are cooked. It is demonstrated that there is a latent demand for modern cooking in Malawi. Targeted research is needed to test modern cooking devices’ ability to cook Malawian dishes in ways which are acceptable to Malawian people, in order to effectively accelerate a transition towards modern cooking in Malawi and address the negative health and environmental impacts of biomass cooking.

This paper proposes a multi-terminal allocation of inductive charging infrastructure for the public bus transit network using Lagos bus rapid transit as a case study. The charging model is formulated as a mathematical optimisation problem that allocates multi-terminal based inductive chargers for the transit network. The formulated optimisation problem is solved using a particle swarm optimisation algorithm. The results indicate that the allocation of the inductive chargers to transit system is more cost-efficient and reduce the battery size of the battery-electric bus when the bus terminals in a transit route are of equal distance from each other.

Considering the effort and resources dedicated towards the Sustainable Development Goal number seven (SDG7) of "ensuring energy access for all", a post-2030 sub-Saharan Africa will be filled with a range of network solutions - main grids, minigrids and nano-grids. In time, some of the smaller networks will expand while others will be abandoned for better and resilient energy sources. However, such integration will pose technical challenges as most off-grid systems are designed and sized without any consideration of the main grid or other off-grid systems. This paper proposes that the identification of grid feedin point into the minigrid network will be one of the critical decisions in integrating the main grid with once autonomous minigrids. Using power flow simulations of case study networks, results indicate that technical parameters such as losses and voltage drops on the local network vary significantly with choice of feed-in point, influencing the performance of the local network as well as its ability to accommodate more distributed energy resources in future. Based on these results, initial recommendations are made concerning the interconnection of such networks.

In the past two decades, grid extension and off-grid solutions, such as autonomous minigrids, have become main conduits for improving energy access in developing countries. Once universal energy access is mostly achieved in these countries, efficiency, reliability, quality of supply and flexibility will become increasingly prominent objectives in the planning and operation of their electricity networks. Some of these objectives, such as network efficiency, will be strongly influenced by the approach taken for the integration of the main grid and autonomous minigrids. This paper applies optimization techniques to investigate the impact of residual generation and load factor of an autonomous minigrid in the selection of an optimal point of grid connection to minimize energy losses.

This paper proposes a multi-terminal allocation of charging infrastructure for the public bus transit network that integrates both inductive and conductive priority charging to ensure energy management without disrupting the operational bus schedule. The charging model is formulated as a mathematical optimisation problem that allocates multi-priority chargers for the transit network. The formulated optimisation problem is solved using a particle swarm optimisation (PSO) algorithm. The model is validated using Lagos BRT data. The results indicate that the integration of both inductive and multi-terminal conductive priority chargers in the transit system can serve as an energy management system and eliminate charging dwell time.

Globally, three billion people still use biomass to accommodate their cooking needs, causing negative health and adverse environmental impacts. Recent research promoting the use of electric cooking devices (eCook) to reduce biomass usage includes data capture, market assessments and eCook device prototyping to give a clearer vision on how people cook and associated costs. However, when dealing with analysis of electrification in rural and remote areas, a lack of information remains for the optimum size and costs of off-grid systems to accommodate eCook loads. The techno-economic modelling software HOMER-Pro is used in this paper to simulate four different mini-grid models to evaluate optimal configurations for the Dedza mini-grid in Malawi with increased household (HH) eCook use, targeting economic and environmental objectives. The simulation results reveal that model 4 which represents the optimized photovoltaic (PV)/battery/diesel hybrid mini-grid model, provides the lowest Cost of Electricity (COE), less greenhouse emissions, a higher Renewable Fraction (RF) when accommodating eCooks, and as the eCook penetrations increase the COE reduces due to the relative increase in the total annual electric load served (E served ).

The onset of ion-induced reverse leakage current in SiC Schottky diodes is shown to depend on material properties, ion LET, and bias during irradiation, but not the voltage rating of the parts. This is demonstrated experimentally for devices from multiple manufacturers with voltage ratings from 600 V to 1700 V. Using a device with a higher breakdown voltage than required in the application does not provide increased robustness related to leakage current degradation, compared to using a device with a lower voltage rating. peerReviewed

Heavy ion data suggest that a common mechanism is responsible for single-event burnout in 1200 V power MOSFETs and junction barrier Schottky diodes. Similarly, heavy ion data suggest a common mechanism is also responsible for leakage current degradation in both devices. This mechanism, based on ion-induced, highlylocalized energy pulses, is demonstrated in simulations and shown to be capable of causing degradation and singleevent burnout for both the MOSFETs and JBS diodes. peerReviewed

The aim of the proposed research is to investigate methods to identify objects of interest and classify dicentric and normal chromosomes in slide images using suitable digital image processing techniques. Dicentric chromosomes are abnormal chromosomes with two centromeres (instead of one) created by a variety of processes, including irradiation. When a chromosome is exposed to radiation, two chromosome segments, each with a centromere may join together resulting in a dicentric chromosome. An acentric fragment, i.e. a partial chromosome with no centromere, is also formed. The first stage of the proposed system is geared towards the detection of objects of interest, i.e. isolated normal, isolated dicentric, acentric and clusters of overlapping chromosomes. The last stage of the proposed system is geared towards the classification of isolated chromosomes as either normal or dicentric. The eventual objective is to determine the number of dicentric chromosomes present in a slide image. The proposed system automatically detects objects of interest not associated with dirt. The classification of the aforementioned objects into isolated and clustered chromosomes, as well as acentric fragments, are conducted manually, while the automation of this stage is reserved for future work. The proposed system subsequently automatically categorises isolated chromosomes as either normal or dicentric. It is demonstrated that the system correctly detects and classifies a significant number of the aforementioned chromosomes within slide images provided by iThemba LABS.

This paper presents learning relevant to off-grid energy access initiatives from a case study in Malawi. Deploying solar PV Kiosks in four rural communities, the Sustainable Off-Grid Electrification of Rural Villages (SOGERV) project set out to establish sustainable, community-based energy businesses. Focussing on access to renewable electricity and economic sustainability, the project deployed a set of services and products aiming to meet local needs identified in a detailed market survey of the area. The financial results of each business (sales revenues and operating expenses) are presented and discussed. The results demonstrate that, despite operating in remote areas with some of the lowest development statistics in Malawi, the revenues that can be obtained by these businesses have the potential to meet long-term operations and maintenance costs and generate a net surplus over a 10 year trading period. However, results are varied between businesses and many risks to long term economic sustianability remain. The learning provides a platform for further development of SDG7 focussed, community energy projects in Malawi and other similar contexts.

In the last decade, many researchers and applications focused on street view systems' geo-spatial and multimedia content. However, most street view systems have high data collection costs and have out of date content in certain regions. An efficient and effective street view system reflecting real world multimedia content on a weekly basis has been an elusive goal. We present GrabView, a street view system that: • Uses a data capture during ride sharing service trips model. • Collects up-to-date geo-referenced multimedia content atlow cost. • Processes both the multimedia and geo-sensor content. • Serves a navigation and browsing user experience equivalent to that from dedicated mapping vehicles. Grab ride hailing service vehicles collect most of GrabView's geo-sensor data and multimedia content. This results in much better up-to-the-minute road network coverage at no extra cost.

When dealing with personal data, it is important to remember the implications of relaxed security. Without implementing the correct security measures, user's personal data can be vulnerable against an assortment of different malicious attacks and actions. Personal user data can come in many different forms, so it can be easy to forget what is valuable to protect and what is not when developing a complex system. When the Bioinformatics Cloud (BioCloud) project was being developed initially, security was given a lower priority in place of a working, demo-able product. Now that the project has developed far enough to work in some degree, security measures must be implemented to protect the most personal of all data, DNA. This study is to evaluate different security measures and implementations to protect against both accidental or malicious attempts at obtaining user data in a cloud platform.

The BioCloud project, a set of Bioinformatics tools being integrated into a cloud system, provides a web-based user interface to allow users to easily access these tools. However, as a cloud-based application, the BioCloud project will need the means for semi-autonomous deployment and dynamic resource usage. The purpose of this study is to document the best practices in deploying the BioCloud project to new clusters.

GlusterFS is a scalable distributed network file-system that aggregates disk storage resources from multiple servers into a single global name-space. It is an open source software, and due to its versatility it is commonly used in data-intensive tasks such as cloud storage or media streaming services. With the vast amount of applications that bioinformatics and cloud architecture provide, understanding the Gluster file-system specifically in regard to the performance is extremely important. Throughout this research document we will investigate and analyze the various facets of performance given varying scenarios.

The BioCloud project is an expansive and complex project involving platforms and tools from areas of file storage, containerization, and server hosting. Not the least complex of all of these systems are those used in the handing of the many bioinformatic scripts and tools needed to ensure BioCloud is a service worth the effort. This paper will dive into the design and methods that allow BioCloud to support a large number of tools, to simplify the process of adding additional tools and editing existing scripts, and to be flexible enough to support the bioinformatic script no matter its needs.

To address the challenges of autonomous driving applications Blackmore has focused on integrated photonics and coherent detection as the keys to realizing high performance lidar systems. Technology adoption is discussed from the perspective of range-Doppler measurement engines.

This paper outlines an approach to integrating electric vehicle (EV) charging systems to existing low voltage direct current (LVDC) public electrical transport infrastructure. Existing utility networks face challenges of accommodating a multitude of new connections associated with the adoption of EV charging infrastructure but when present, electrical light rail or tram networks represent a good opportunity to provide fast construction and less disruptive city centre charging implementation. Light rail network operation requires immediate power capacity to be available from any point on the network but if this margin were to be relaxed it opens up opportunities for sharing the available capacity with EV charging systems. This paper presents an electrical capacity assessment based on four separate charging control strategies applied to the public tram system in the City of Edinburgh, Scotland. The results of these studies, earthing and wider system protection requirements are considered and preliminary findings made.

We present a sampling-based framework for feedback motion planning of legged robots. Our framework is based on switching between limit cycles at a fixed instance of motion, the Poincare section (e.g., apex or touchdown), by finding overlaps between the regions of attraction (ROA) of two limit cycles. First, we assume a candidate orbital Lyapunov function (OLF) and define a ROA at the Poincare section. Next, we solve multiple trajectory optimization problems, one for each sampled initial condition on the ROA to minimize an energy metric and subject to the exponential convergence of the OLF between two steps. The result is a table of control actions and the corresponding initial conditions at the Poincare section. Then we develop a control policy for each control action as a function of the initial condition using deep learning neural networks. The control policy is validated by testing on initial conditions sampled on ROA of randomly chosen limit cycles. Finally, the rapidly-exploring random tree algorithm is adopted to plan transitions between the limit cycles using the ROAs. The approach is demonstrated on a hopper model to achieve velocity and height transitions between steps.

A novel adaptive control function is presented as an improvement to the classic volts per hertz (V/f) technique where high torque oscillations occur during rapid changes of the rotating speed. The proposed adaptive feature of an improved controller limits torque oscillations by injecting a pulse and imposing the pre- determined bands on a voltage reference waveform whenever the scheduled change in speed occurs. This adaptive function has been integrated with the closed-loop V/f control scheme, subsequently modelled and evaluated numerically using transient simulation studies, as well as experimentally using an induction machine drive test rig. The results have shown that the proposed adaptive element provides an improved dynamic performance for using the V/f method, which is required in compact distributed drive systems with single voltage source inverter (VSI) controlling multiple interconnected motors.