Off-grid hybrid renewable energy systems are known as an attractive and sustainable solution for supplying clean electricity to autonomous consumers. Typically, this applies to the communities that are located in remote or islanded areas where it is not cost-effective to extend the grid facilities to these regions. In addition, the use of diesel generators for electricity supply in these remote locations are proven to be uneconomical due to the difficult terrain which translates into high fuel transportation costs. The use of renewable energy sources, coupling with the diesel generator allows for the diesel fuel to be offset. However, to date, a common design standard for the off-grid system has yet to be found and some challenges still exist while attempting to design a reliable system. These include the sizing of hybrid systems, coordination between the operation of dissimilar power generators and the fluctuating load demands, optimal utilisation of the renewable energy resources and identifying the underlying principles which reduce the reliability of the off-grid systems. In order to address these challenges, this research has first endeavoured into developing a sizing algorithm which particularly seeks the optimal size of the batteries and the diesel generator usage. The batteries and diesel generator function in filling the gap between the power generated from the renewable energy resources and the load demand. Thus, the load requirement is also an important factor in determining the cost-effectiveness of the overall system in the long run. A sensitivity analysis is carried out to provide a better understanding of the relationship between the assessed renewable energy resources, the load demand, the storage capacity and the diesel generator fuel usage. The thesis also presents the modelling, simulation and experimental work on the proposed hybrid wind-diesel-battery system. These are being implemented with a full-scale system and they are based on the off-the-shelf components. A novel algorithm to optimise the operation of a diesel generator is also proposed. The steady-state and dynamic analysis of the proposed system are presented, from both simulation and an experimental perspective. Three single-phase grid-forming inverters and a fixed speed wind turbine are used as a platform for case studies. The grid-forming inverters adopt droop control method which allows parallel operation of several grid-forming sources. Droop control-based inverters are known as independent and autonomous due to the elimination of intercommunication links among distributed converters. Moreover, the adopted fixed speed wind turbine employs a squirrel cage induction generator which is well known for its robustness, high reliability, simple operation and low maintenance. The results show a good correlation between the modelling, the experimental measurements, and the field tested results. The final stage of this research explores the effect of tower shadow on off-grid systems. Common tower designs for small wind turbine applications, which are the tubular and the lattice configurations, are considered in this work. They generate dissimilar tower shadow profiles due to the difference in structure. In this research, they are analytically modelled for a wind turbine which is being constructed as a downwind configuration. It is proven that tower shadow indeed brings negative consequence to the system, particularly its influence on battery lifetime within an off-grid system. This detrimental effect occurs when power generation closely matches the load demand. In this situation, small frequent charging and discharging cycles or the so called microcycles, take place. The battery lifetime reduction due to these microcycles has been quantified and it is proven that they are not negligible and should be taken into consideration while designing an off-grid hybrid system.

Higher penetration of volatile renewable sources and increasing load demand are putting a strain on the current utility grid structure. Energy storage solutions are required to maintain grid stability and are vital components to future smart grid designs. Flywheel energy storage can be a strong part of the solution due to high cycle life capabilities and flexible design configurations that balance power and energy capacity. This dissertation focuses on developing design methodologies for advanced flywheel energy storage, with an emphasis on sizing flywheel energy storage and developing lumped parameter modeling techniques for low loss, high temperature superconducting. The first contribution of this dissertation presents a method for using an optimal control law to size flywheel energy storage and develops a design space for potential power and energy storage combinations. This method is a data driven technique, that utilizes power consumption and renewable generation data from a particular location where the storage may be placed. The model for this sizing technique includes the spinning losses, that are unique to flywheel energy storage systems and have limited this technology to short term storage applications, such as frequency and voltage regulation. For longer term storage solutions, the spinning losses for flywheels must be significantly reduced. One potential solution is to use high temperature superconducting bearings, that work by the stable levitation of permanent magnet materials over bulk superconductors. These advanced bearing systems can reduce losses to less than 0.1% stored energy per hour. In order to integrate high temperature superconducting bearings into flywheel system designs, accurate and reduced order models are needed, that include the losses and emulate the hysteretic, non-linear behavior of superconducting levitation. The next two contributions of this dissertation present a lumped parameter axissymmetric model and a 3-D lumped parameter transverse model, which can be used to evaluate bearing lifting capabilities and transverse stiffness for flywheel rotor designs. These models greatly reduce computational time, and were validated against high level finite element analysis, and dynamic experimental tests. The validation experiments are described in detail. / text