The recent decade has witnessed the rapid growth of data traffic driven by various bandwidth-rich applications. Accordingly, both short-reach and long-haul fiber based optical networks are in great demand. For the long-haul transports, coherent detection is dominant due to its superior performance. Although the hardware structure of coherent systems possesses large footprint and the corresponding DSP algorithms are complicated, the cost is amortised by the high capacity and long transmission distance. While for short- to medium-reach transports such as intra- and inter- data center connections and metropolitan networks, cost is one primary concern. As such, direct detection has attracted extensive research interests due to its simple structure and low cost. To support short- and medium-reach optical transports in a cost-effective manner, field recovery is a promising solution since it enables the chromatic dispersion (CD) compensation. Given the cost of the transmission link, direct detection with the recovery of optical field has attracted extensive attention. For direct detection systems, the signal-signal beat interference (SSBI) induced by the square-law detection is a major limiting factor of obtaining the replica of information-bearing signal. As such, various algorithms dealing with SSBI have been proposed in the recent years. In this thesis, the optical field recovery of directly detected single sideband (SSB) and double sideband (DSB) signals has been studied and proposed. For SSB signals, without inserting a frequency gap to accommodate SSBI, Kramers-Kronig (KK) and iterative cancellation (IC) receivers enable the high spectral efficiency. The appropriate modulation formats fitting for both KK and IC receivers have been analysed. As KK and IC receivers are designed for the transmission links consisting of several spans of fiber, CD impacts on the performance of KK and IC receivers are investigated. Results show that the single-carrier modulation format is the better fit for KK receivers, while OFDM signals outperform single-carrier signals for IC receivers. Due to accumulated CD impacts after transmission, the peak-to-average power ratio (PAPR) of the single-carrier signals increases, which is more likely to violate the minimum phase condition of KK receivers compared to the back-to-back (btb) condition. Accordingly, the KK receiver requires a higher CSPR after transmission, while the optimal CSPR for the IC receiver remains the same as the btb case. The first-order polarization mode dispersion (PMD) impacts are also investigated, and it is demonstrated that PMD is not a major limiting factor for the KK receiver. For the field recovery of DSB signals, the direct detection scheme called carrier-assisted differential detection (CADD) has been theoretically analysed and experimentally demonstrated. The algorithm of recovering DSB signal field using CADD receiver has been elaborated, and the design guideline of CADD receiver including the joint optimization of several key parameters is given via simulations. Besides, the first-time experimental demonstration of the CADD receiver has been conducted. Experimental results show that the required receiver bandwidth is reduced by 41% compared with SSB based direct detection schemes. From the perspective of practical implementation, the IQ imbalance impacts of the CADD scheme have been analysed, and the tolerance of amplitude and phase mismatch is given. Lastly, to alleviate the requirement of high CSPR, several DSP algorithms have been proposed. For the SSB direct detection scheme, both enhanced SSBI mitigation and virtual CSPR enhancement schemes can effectively reduce the CSPR by 2 to 3 dB. For the DSB signal based CADD receiver, a simple but effective power loading scheme is proposed to enhance the performance of low-frequency subcarriers, and hence predominantly reduce the required high CSPR.

Wireless communication systems with low-resolution quantization are envisioned to be a major part in future wireless communication networks because of their potential to improve the energy efficiency of the network. In this thesis, we present a comprehensive and rigorous analytical investigation on the performance impact of using low-resolution phase quantization at the receiver of a wireless communication system, when compared to traditional high-resolution systems. To that end, we consider three different system setups; a point-to-point wireless communication system with coherent detection, a point-to-point wireless communication system with non-coherent detection and a multi-antenna system with coherent detection. We study the optimum detectors and draw fundamental insights on the error probability performance of low-resolution quantization systems in the presence of fading and noise. Firstly, we focus on coherent detection with M-ary phase shift keying (M-PSK) modulation and, derive the optimum maximum likelihood (ML) detector for a single-input single-output (SISO) system. Utilizing the structure of the derived detector, a general average symbol error probability (SEP) expression for M-PSK modulation with n-bit quantization is obtained when the wireless channel is subject to Nakagami-m fading. We show that a transceiver architecture with n-bit quantization is asymptotically optimum in terms of communication reliability if n is greater than or equal to log_2(M +1). The coherent detection techniques discussed above require channel state information (CSI) to be available at the receiver. Due to the non-linear nature of quantization, channel estimation has been one of the major challenges associated with low-resolution quantization based systems. Taking these into account, next we focus on non-coherent detection by adopting the differential quadrature phase shift keying (DQPSK) modulation scheme to differentially encode the transmit data. At the receiver side, we employ non-coherent detection that does not require instantaneous CSI. With DQPSK modulation, the ML detector is derived using which, a general average SEP expression with n-bit quantization is obtained when the wireless channel is subject to Rayleigh fading. It is shown that a transceiver architecture with n-bit quantization is asymptotically optimum in terms of communication reliability if n is greater than or equal to 4. That is, the decay exponent for the average SEP is the same and equal to 1 with infinite-bit and n-bit quantizers for n is greater than or equal to 4. Therefore, when the channel knowledge is not available at the receiver, the quantizer has to use one additional bit to achieve optimum communication robustness. Finally, we extend our investigation to low-resolution quantization based multi-antenna wireless communication systems equipped with one transmit antenna and N receive antennas. We derive the ML detector and then propose three sub-optimum detection rules based on selection combining which have less computational complexity compared to the ML detector. We also note that the simple sub-optimum detector that selects the path with the channel that locates the rotated constellation point furthest away from the decision boundary is asymptotically optimum in terms of communication reliability if n is greater than or equal to 3. An extensive simulation study is performed to illustrate the accuracy of the derived results.

The thesis addresses several critical challenges in the implementation of Model Predictive Control (MPC) for online settings, with a focus on the numerical strategies employed in solving the inherent optimisation problem at the centre of MPC. First, an MPC-specific early termination condition is considered for the family of interior-point solvers. The proposed condition allows the computational efforts associated with solving a class of MPC problems to be reduced without compromising the stability properties of the closed-loop system. Second, it is assumed that an optimisation algorithm has already been selected, and the design of a suboptimal MPC algorithm without terminal conditions is required. The proposed design approach considers the MPC problem horizon length and an acceptable suboptimality degree to minimise the algorithmic complexity associated with finding a solution. To this end, the stabilising properties of the feasible suboptimal solutions (with an appropriately defined measure of suboptimality with direct links with the closed-loop performance of the system) are utilised, along with the ability to estimate the algorithmic complexity of the process of obtaining such solutions. Through numerical simulations, it is shown that the smallest stabilising prediction horizon is not necessarily the optimal choice, and the complexity can be further reduced using a larger horizon length. This is shown to be consistent with the predictions obtained from the developed framework. Third, the case where the constraint-respecting stabilising control law is to be constructed using a set of precomputed (sub)optimal control laws. A framework for approximating the optimal control law with a special family of barycentric functions and the corresponding stability certification method is proposed. The proposed stability certificate is less conservative than the state-of-the-art approaches, which results in the method to require fewer precomputed control laws. The proposed methodology demonstrates sub-exponential growth of the number of approximation sub-regions, and potentially allows for Approximate Explicit MPC to be applied to a broader range of systems. Finally, a novel family of algorithms for solving finite-time optimal control problems with state and input constraints is proposed. The aforementioned family, termed interior-point DDP algorithms (IPDDP), are a product of combining the interior-point and differential dynamic programming (DDP) ideas. The interior-point DDP algorithms are of linear complexity in the problem's size and can either handle infeasible solution guesses or preserve the feasibility at all times. The IPDDP method is shown to have a local quadratic convergence without appealing to any convexity properties of the associated problem. Once these three main contributions of the thesis are completed, further potential research directions and extensions are outlined as avenues for future work.

In recent years, the evolution of mobile communication has projected a tremendous growth in the capacity demand of the cellular communication network. Hence, telecommunication service operators have been researching different methods to accommodate such enormous demand growth of data communications. One such approach was to deploy additional macrocells with advanced wireless technology to cater to the bandwidth demand. This approach was not a cost-optimal one due to limited signal spectrum, inter-site distances among cells, risk of higher electromagnetic radiation propagation. Hence, a heterogeneous network deployment is to encounter the increased capacity need would be a more robust solution. Such systems deploy small-cell Base Transceiver Station (BTS) with a smaller coverage radius, alongside the traditional macrocell BTSs, to counter the capacity need and related issues. The planning of such a Small-cell Network (SCN) requires extensive forms of studies, and the purpose would be to focus on specific aspects of network planning to influence the outcome of such tasks directly. These cellular wireless networks connect with a backhaul infrastructure to offer a cost-effective, high capacity, robust, energy-efficient and future-proof connectivity between these “small cells” and the core network. This thesis presents relevant research studies performed to optimise the deployment of wireless small-cell networks. Firstly, using a novel network planning algorithm, a network of small-cells is planned for different 4G carrier frequencies. This framework also maintained the Maximum Allowable Path Loss (MAPL) level for the transmitted signal from SC. The framework incorporated geographical terrain factors of ground elevation and slope values, locations and fixed coverage area formation for the selected small-cells. An energy and cost-effective optimised backhaul architecture, based on the Gigabit Passive Optical Network (GPON) technology, leveraging an existing optical fibre network resources is separately planned and dimensioned to connect with the planned small-cell network approach mentioned above. Next, the two different SCN and GPON planning methods are combined under one optimisation framework to construct a simplified network planning method applied to any cellular technology or GPON type utilised. Finally, a network capacity analysis is done, concerning the data consumption by devices, based on the population density over the case study area and the assigned 5G Small-cell (SC) carrier frequency data rate. Based on that information and other known constraints and parameters, a corresponding optimisation framework will be developed. This framework would utilise the concept of cellular frequency spectrum refarming to share the frequency spectrum of wireless signals. In turn, this allowed various types of cellular networks from different generations to function in the same wireless frequency spectrum. In summary, the technical research contribution presented in this thesis describes multiple approaches to plan a wireless small-cell network. The research also dimensions an appropriate optical backhaul network, for different cellular and optical network characteristics, within the premises of a heterogeneous telecommunications network. Additionally, we discussed some future research directions evolving from our work, alongside concluding remarks.

The increasing penetration of residential photovoltaic (PV) systems is reducing net demand leading to displacement of synchronous generation, with serious implications on the provision of Primary Frequency Response (PFR) following a contingency. Furthermore, distribution networks require management of excessive reverse power flows caused by residential PV system to avoid voltage or asset utilisation violations. To prevent distribution network problems exports limit are often imposed, but at the sacrifice of total power exported. Through pre-curtailment of maximum generation, or re-distribution of power through dynamic optimal export limits, it is possible for residential PV systems to create a power reserve for PFR. Furthermore, time-varying net demand from residential PV will lead to many changing operating states, with implications on the oscillatory performance of synchronous generators still online. In this context, this thesis investigates and proposes methodologies to determine the role of residential PV systems in the provision of PFR and the effect of a time-varying net demand on small signal stability. To achieve this, however, several of the corresponding challenges need to be understood. Firstly, the effects at the system-level from an increase in PV penetration need to be understood. It is required to model how synchronous generators change power output to in response to a change in net demand. The dispatch of PFR for the synchronous generators must also be considered. Secondly, any pre-curtailment of a PV system for PFR, will alter the net demand and potential PFR requirements. Thirdly, residential PV systems are connected to the power system through distribution networks. Distribution networks require management to prevent network issues related to high penetrations of residential PV systems, which influences net demand. This requires modelling and understanding how distribution networks operate and are restricted by their physical limitations, along with how they are managed. This all has an impact on the net demand at the system level which needs to be considered. Finally, the time-varying nature of a power system with high penetrations of PV (and the displacement it causes) presents a challenge in assessing small signal stability, whilst also being unable to relate the performance of specific constant remaining modes of oscillation throughout the day. This thesis addresses the aforementioned challenges as follows: A unit commitment (UC) is utilised to model the behaviour of generators in time, enabling modelling of changes in power output in response to residential PV, determining which generators are forced offline, as well as the distribution of PFR among the synchronous generators. The UC is modified to pre-curtail power of residential PV systems for PFR, accounting for the change in net demand from pre-curtailment in the supply of PFR. Using a modified IEEE-9 bus system, the findings highlight that residential PV systems providing PFR can prevent the inefficient and costly operation of synchronous generators (providing PFR) at low power outputs. The need for representing distribution networks to assess the role of residential PV systems providing PFR is demonstrated using a realistic Australian MV-LV residential feeder (from the primary substation to individual customers). Export limits are imposed to prevent steady-state distribution problems. The findings highlight that if distribution network constraints are not considered, the level of synchronous generator displacement may be significantly over-estimated, with corresponding knock on affects for PFR requirements. The application of optimal dynamic export limits beyond managing steady-state issues in distribution networks are applied for providing PFR. A method to translate these optimal dynamic export limits to enable a reserve via droop settings for PFR is proposed. It was found that there is a significant PFR reserve available across a power system if optimal dynamic export limits are used. This PFR reserve from residential PV systems can help reduce system costs with synchronous generators no longer operating at low power just to provide PFR. The small signal stability of the system is assessed considering a time-varying net demand and corresponding response of synchronous generators, by integrating a UC with a small signal stability study. Furthermore, a method is presented whereby oscillatory modes that remain despite displacement can be tracked. Results showed that oscillatory modes can change their damping behaviour significantly in time, with oscillatory modes changing criticality (which are the least damped). This is significant given that an approach not considering a time-varying net demand may miss these findings which may lead to improper damping.

Wireless local area networks (WLANs) have continually evolved during the last few decades to meet the ever-growing user demands. However, popular radio frequency technologies such as Wi-Fi are now experiencing a spectrum crunch due to a multitude of bandwidth hungry applications and limited bandwidth available in the sub-6 GHz bands. Therefore, a number of complementary technologies such as 60 GHz Wi-Fi, visible light communication and optical wireless communication have emerged to build high capacity WLANs in indoor spaces. Amongst these emerging WLAN technologies, optical wireless communication, operating in the infrared range, is becoming popular as it has access to virtually unlimited bandwidth compared to radio frequency technologies. With this huge spectrum resources, it is quite straightforward to establish wireless links over 10 Gbps with optical wireless communication. In addition to that, optical wireless communication has several advantages like not causing interference to existing WLANs, high security, and simple transceiver designs. Though the physical layer of optical wireless communication is being developed fast and brings unprecedented capabilities to WLAN landscape, upper layer protocols and architectures that are essential in harnessing the benefits of physical layer to provide multi-gigabit communication have received minimal attention so far. Therefore, this thesis explores the upper layer protocols, algorithms and architectures for optical wireless networks in homogeneous and heterogeneous settings. To this end, we first evaluate the suitability of the contention-based MAC protocol of Wi-Fi standard for optical wireless networks. The inefficiencies of the contention-based MAC protocol are highly pronounced at the higher data rates of optical wireless networks. Therefore, we introduce an improved version of the Wi-Fi MAC protocol with novel dynamic contention window tuning mechanism that can operate at multi-gigabit data rates. Second, due to the lack of availability of a simulation platform to evaluate the performance of optical wireless communication networks, we develop a simulation module for optical wireless networks in the Network Simulator-3 (ns-3) project. The proposed module can deploy optical wireless networks of different architectures and layouts, apply different scheduling algorithms, and channel models. To the best of our knowledge, this is the first multi-gigabit optical wireless network simulation module. Third, we explored novel network architectures for optical wireless networks considering the massive capacity, increased number of access points and smaller cells. Subsequently, we proposed the FLOWN (full-duplex split-plane optical wireless network) architecture for optical wireless networks. The FLOWN architecture is later generalised to all the upcoming WLANs such as Wi-Fi 6, 60 GHz Wi-Fi, and visible light communication to support homogeneous or heterogeneous WLAN deployments. It features a centralised pool of hardware and software resources, a high-capacity distribution network and advanced capabilities like full-duplex and split-plane operation. Further, delay-sensitive users can only receive guaranteed quality-of-service under contention-free MAC protocols. Therefore, most of the upcoming WLAN MAC protocols deploy hybrid versions of contention-based and contention-free MAC protocols to reap the advantages of both types. Hence, we finally introduce a contention-free MAC protocol for optical wireless networks with adaptable parameters that can be tuned to the traffic requirements of the current users. Overall, our work reported in this thesis provide simulation platform for optical wireless networks and also insight into design strategies that can be used to realise centralised multi-gigabit network architectures and MAC protocols.

Multi-access edge computing (MEC) is the next paradigm to support the enormous growth of diverse mobile applications that require high computational power, ultra-low latency, and high bandwidth. The user experience can be enhanced beyond the constrained resources limited by the mobile devices by offloading computation-intensive tasks to the MEC hosts. Since MEC hosts are deployed proximity to the end-users, mobility of users leads to multiple handovers in the mobile network, which leads to application migrations in the MEC network. Hence, there is a critical challenge in MEC to maintain the service continuity between the offloaded user application that is running on the MEC host and the mobile device when a user is moving from radio node to radio node. On the other hand, since a larger number of MEC hosts are going to be deployed within the radio access network, the energy efficiency of these hosts is another challenge for MEC service providers. In this thesis, we design an energy-efficient MEC network through optimizing the resource allocation and MEC hosts selection problems by considering user movements. Our findings could help mobile operators in developing a real-time network resource orchestration system to reduce network costs while increasing the number of users based on users’ mobility patterns. This thesis advances the state-of-the-art by making the following contributions: 1. Correlated user mobility model to produce user trajectories during the morning commute. 2. A utilitarian resource distribution algorithm to select suitable locations to deploy hosts and the right amount of resources for each MEC host iv 3. Energy-efficient server selection methodologies and energy-efficient virtual machine placement and migration processes to maximize the energy efficiency of the MEC hosts 4. An extended Balas-Geoffrion additive algorithm to select a suitable host based on cost minimization for MEC host selection problem 5. A shortest path-based methodology for host selection and user application migration problem to maximize the energy efficiency of the MEC network.

The rapid adoption of distributed energy resources (DER) in low voltage (LV) networks is driving the need for distribution companies to assess their impacts on customer voltages in any demand/generation condition (also known as what-if analyses). Although this can be done by running conventional power flow analyses, there are two main challenges. The first one is that LV line models (three-phase LV feeder lines and single-phase service lines) are needed. However, the corresponding impedances are often poorly recorded by distribution companies. In other words, the information is incomplete or not available. The second challenge is that, if such studies are needed for operational purposes (calculations in near real-time), then implementing power flows to be run for hundreds of LV feeders can be a complex task for distribution companies. Several studies have attempted to solve the challenges of impedance estimation and simplified voltage calculations, but there are still some gaps. Given the rollout of smart meters in many places, several works have exploited smart meter measurements to estimate impedances of LV line models. However, in most cases, the three-phase nature of LV feeders (i.e. the phase couplings) is not adequately considered; and thus, such approaches cannot cater for the needs of inherently unbalanced LV networks. For the voltage calculations, existing simplified methods are based on the single-phase voltage drop equations and an additional ‘unbalanced factor’. Given that the ‘unbalanced factor’ is determined either empirically or using data-driven techniques that require large amounts of data, such methods cannot be precise or practical enough for their actual implementation by distribution companies. This thesis proposes a practical approach to determine customer voltages (in what-if analyses) using smart meter-driven LV line models that adequately capture the effects among the three phases. Firstly, impedances (three-phase LV feeder lines and single-phase service lines) are estimated using linearised voltage drop equations and a regression technique. This process exploits historical time-series measurements from smart meters and at the head of the LV feeder and assumes that the customer connectivity and customer phase connection are known. Then, using the linearised voltage drop equations and the estimated impedances, simplified calculations of customer voltages can be carried out for what-if analyses (any demand/generation condition). The proposed approach is demonstrated on realistic LV networks from Australia and the UK. Impedances are estimated considering realistic weekly historical meter measurements (i.e. active power, reactive power, and voltage magnitudes) with a 15-minute resolution (672 time steps). Voltage calculations (what-if analyses) consider weekly demand and generation profiles with 1-minute resolution (10,080 time steps). Results show a very good accuracy for most of the estimated impedances. More importantly, the calculated voltages are not only highly accurate but are also obtained much faster than with a power flow engine. Consequently, the findings suggest that the proposed approach is accurate and practical enough for its use by distribution companies.

Graphene is the name given to a monolayer of carbon atoms arranged in a two-dimensional honeycomb lattice. Recently, there has been much interest concerning the use of graphene in photodetectors and biosensors due to its unique electronic and optical properties. Specifically, graphene is an attractive material for developing broadband and high-speed photodetectors because of its gapless band structure and ultrafast carrier dynamics. The high spatial confinement and electrical tunability of mid-infrared (MIR) graphene plasmon have also been used for biosensors which permit the quantification and identification of biomolecule monolayers. However, the realisation of high-performance graphene photodetectors operating in the MIR is hindered by the intrinsically low optical absorption (< 2.3 %) and short carrier lifetime (sub-picosecond) of this material. In addition, the sensitivity of graphene biosensors based on plasmons is limited by the relatively small field enhancement of graphene plasmons compared to that of conventional metal plasmons. In this thesis, we present nano-optical approaches to enhance the performance of graphene-based photodetectors and biosensors operating in the MIR by employing magnetic mirrors and/or plasmonic metasurfaces. First, we propose and experimentally demonstrate a long-wave infrared device that we termed a magnetic mirror, which consists of an array of amorphous silicon cuboids on a gold film. The device is demonstrated to reflect light with high reflectance and zero phase shift. A modified multipole analysis method is devised and employed to interpret the magnetic mirror behaviour. We investigate the use of this device in a graphene photodetector application and show that the light absorption by graphene placed on top can be boosted by more than three orders of magnitude compared to the absorption that would occur were the graphene instead placed on a gold mirror. This is achieved by producing a field distribution with enhanced intensity at the device surface. Second, we design and experimentally demonstrate a mid-wave infrared polarization-independent graphene photodetector via the integration of plasmonic nanoantennas that we term Jerusalem-cross antennas (JC-antennas). The JC-antennas serve to concentrate the incident light onto graphene for strongly enhanced optical absorption, as well as to collect the photocarriers. We demonstrate mid-wave infrared detection both at room temperature and at cryogenic temperatures. Our device also shows a fast and broadband photoresponse that extends to visible and near-infrared wavelengths, thanks to the carrier collection by the JC-antennas. Last, we propose and investigate a biosensor device that combines the strong field confinement and electrical tunability of graphene plasmons with the large field enhancement of metallic nanoantennas. The device consists of an array of plasmonic nanoantennas and graphene nanoslits on a resonant substrate. Systematic electromagnetic simulations are performed to quantify the sensing performance of the proposed device. Our simulations show that the proposed device outperforms designs in which only plasmons from metallic nanoantennas or plasmons from graphene are utilized.

A multispectral image camera system captures image data within specific wavelength ranges in narrow spectral bands across the electromagnetic spectrum. In the recent years, image sensors integrated with multiple optical filters with narrow spectral width have been widely used for most of the multispectral imaging across multiple applications, such as area imaging, medical detection, object identification, remote sensing and so on. There were two kinds of multispectral imaging system reported before. The first one is multispectral image cameras that combines multiple cameras mounted with optical bandpass filters and optics with different peak wavelengths and their spectral width depends on applications. The second imaging system is a single sensor based multispectral camera that integrates multiple filters (called filter mosaic) on a single image sensor. The existing filter mosaic fabrication technology disclosed so far is using multilayer coating technique and requires highly accurate alignment with micro-lithography facility. Based on this manufacturing process, each filter has to be fabricated separately with multiple steps, such as baking, exposure, development which significantly increases the fabrication complication and cost. This limits the wide use of this promising multispectral imaging in many applications. This thesis investigates the development of new low-cost single sensor based multispectral cameras using different filter mosaic technologies exploring plasmonics, multilayer coating based on heterostructured dielectrics or hybrid metal-dielectric structures. The thesis starts with an introduction, Chapter 1 presenting the filter technologies, simulation techniques and fabrication technologies. This is followed by presenting a novel technique to enhance the transmission efficiency of plasmonic colour filters based on the coaxial hole array in Chapter 2. Chapter 3 demonstrates CMY camera (cyan, magenta and yellow) using subtractive colour mixing. A colour filter mosaic made of metal-dielectric-metal nanorods is developed and then integrated on a MT9P031 CMOS image sensor to demonstrate its performance. In Chapter 4, the multispectral image camera based on a single sensor is developed using a hybrid filter mosaic integrated onto a Sony monochrome image sensor. Moreover, the multispectral imaging algorithm is used to reconstruct a colour image of a 24 - patch Macbeth Chart. Later, this image sensor was integrated with a DJI drone for the area imaging application. Chapter 5 presents new multispectral filter technologies which is polarization and incident angle independent. Lastly, Chapter 6 presents conclusions and discusses the future research directions. Appendix presents an optical bandpass filter mosaic and multispectral camera based on a mass producible filter technology with spectral width of only 17nm in the near IR wavelength and this technology is confidential and licensed as a trade secret to the University of Melbourne. Therefore, only parts of the technology is disclosed in the appendix due to a company formation (PIXsensor).

The rapid growth of renewable distributed generation (DG) has introduced unconventional challenges for distribution companies (e.g., dealing with voltage rise). To enable future DG growth, a promising alternative (to the otherwise capital-intensive and time-consuming network reinforcements) is the real-time orchestration of DG and existing network assets using advanced schemes. In this context, the operational usage of Optimal Power Flow (OPF)—an optimisation-based technique traditionally found in transmission network applications, albeit using simplified formulations—as a decision-making engine has gained tremendous interest in recent literature. Nonetheless, before such schemes can be readily integrated in the control room of distribution networks, there are several practical challenges that must be addressed. Firstly, the operational usage of OPF requires a fast and scalable formulation that can handle the size (thousands of nodes) and complexity (phase unbalances, discrete devices) of typical distribution networks. Furthermore, since the differences in device-specific characteristics in the sub-minute scale (delays, ramp rates and deadbands) may lead to coordination issues when multiple devices are being controlled simultaneously, additional adaptations are necessary to ensure OPF-based setpoints can be implemented in real-world applications. Finally, while active power curtailment is inevitable at times, since such actions has a direct impact on the return on investment for DG owners, the implications from different fairness objectives (e.g., removing disparity in renewable energy harvesting or financial benefits) as well as the trade-offs between fairness (reducing disparity) and efficiency (aggregated performance) need to be first understood. In this PhD project, the following research is carried out to address the aforementioned challenges: - A linearised, three-phase AC OPF is developed to cater for multi-voltage level distribution feeders and integer variables. Its performance is demonstrated using a realistic MV-LV residential feeder (from the primary substation down to individual connection points of 4,626 single-phase consumers) with over 4,900 nodes. - The necessary adaptations in existing device controllers and the OPF formulation are proposed, allowing network participants and assets to be successfully controlled using OPF-based schemes in an operational setting with minute-scale control actions. Particularly, the importance of the proposed adaptations in preventing short-term voltage spikes are demonstrated using a rural distribution feeder with multiple actively managed on-load tap changers and wind farms. - The implications and trade-offs from different fairness considerations are investigated using several OPF-based schemes, each considering a unique and contrasting fairness objective. The findings highlight the multi-facet nature of curtailment fairness and the importance of identifying the most appropriate objective for a given application. Furthermore, it can help operators/policymakers to make informed decisions when a portfolio of DG is to be managed. - A hardware-in-the-loop demonstration platform is built using commercially available software and hardware at the Smart Grid Lab of The University of Melbourne. This implementation extends beyond static plots and tables by introducing a rich and interactive user interface, and thus enabling a more realistic and engaging way of showcasing advanced schemes to industry.

In recent years, we have witnessed a shift from traditional internet networks interconnecting computers based on well-established standards, towards a pervasive network of networks that provides internet connectivity even to the smallest physical objects. This Internet of Things (IoT) network is an enabling technology to the next industrial revolution (aka Industry 4.0) where the operational technology meets the information technology or computer-based world. The creation of new IoT applications across special context such as smart cities, smart homes, smart agriculture, etc., are realised upon sensors and actuators. The networking of sensors and actuators has extended the scope of networked sensing technologies such as Wireless Sensor Networks (WSNs). However, the networking of wireless sensor devices, or sensor nodes, imposes several challenges due to their inherent resource limitations such as computational capabilities, energy, memory, and communication bandwidth. The management of the limited resources of WSNs becomes challenging and its complexity increases as the network size grows. Thus, the current state of WSNs would not be able to meet the IoT requirements unless appropriate solutions to the aforementioned challenges are found. The focus of this thesis is to investigate the challenges and benefits of Software- Defined Wireless Sensor Networks (SDWSNs) as a solution to flexible resource management and reconfiguration of WSNs. In short, the contributions of this thesis are as follows. (i) the feasibility and practicability, of SDWSNs, to perform network and resource management was demonstrated. This research work shows the ease of managing: the network topology and the transmission power of sensor nodes, using a centralized controller without any firmware modification. (ii) The previous research work is extended to an SDN-based management system for IP sensor networks and compare it with the Routing Protocol for Low-Power and Lossy Networks (RPL) to show the advantages of removing energy- and processing-intensive functions from sensor nodes. This contribution also presents, for the first time, the control overhead metric of an SDWSN, and compare it against a WSN running RPL. (iii) Next, the effects in network performance when making the WSN reprogrammable were examined by, proposing a model-based characterisation of energy consumption to calculate the energy consumed and control overhead introduced for small, large and ‘pseudo-dynamic’ SDWSNs. (iv) Last, the benefit of SDWSNs to augment the network lifetime, whilst keeping the control overhead low, was demonstrated by, proposing an energy-aware routing protocol for software-defined multihop wireless sensor networks, that seeks to prolong the overall network lifetime of the sensor network while also maintaining a high packet delivery ratio. Extensive simulation and experimental results were carried out, to validate the benefits and impacts in network performance, for all aforesaid research works. This thesis also puts forth SDWSN as a potential pathway to overcome the rigidity in management that currently exists in WSNs.