Photovoltaic (PV) devices become increasingly important due to the foreseeable energy crisis, limitation in natural fossil fuel resources and associated green-house effect caused by carbon consumption. At present, silicon-based solar cells dominate the photovoltaic market owing to the well-established microelectronics industry which provides high quality Si-materials and reliable fabrication processes. However ever increased demand for photovoltaic devices with better energy conversion efficiency at low cost drives researchers round the world to search for cheaper materials, low-cost processing, and thinner or more efficient device structures. Therefore, new materials and structures are desired to improve the performance/price ratio to make it more competitive to traditional energy. Metal Oxide (MO) semiconductors are one group of the new low cost materials with great potential for PV application due to their abundance and wide selections of properties. However, the development of MO solar cells is very limited so far mostly due to the poor materials and poor understanding of the materials and devices. This research conducts a systematic numerical investigation on MO thin film solar cells. Various MO semiconductors are used to explore different structures and combinations for solar cells; and the effects of material properties and structures are optimised for the best performances. For the ideal cases, it is found that a TiO2/CuO hetero-junction solar cell shows a conversion efficiency of ~16% with the CuO film thickness only 1.5μm. When a back surface field layer, such as Cu2O, is added at the back of this device, the open circuit voltage (VOC) can be improved by 70% without sacrificing short circuit current, resulting in a conversion efficiency of ~28%, increased by ~70% as compared to the two-layered structure. This is close to the theoretical maximum efficiency of silicon single junction solar cell, which requires a 200~400μm thickness film. Modelling also shows the alternative Schottky barrier type MO semiconductor solar cells can perform well. For an ideal Metal/CuO Schottky barrier solar cell, the conversion efficiency could be as high as ~17%, better than the TiO2/CuO hetero-junction solar cell. The effects of defects and interface states are then considered for more realistic cases as there exists vast amount of defects mostly due to oxygen/metal vacancies/interstitials in the films, and vast amount of interface states due to the large lattice mismatch of the two materials used. All defects and interface states in the solar cell layers, hetero-junction interfaces and metal/semiconductor contacts are found detrimental to the cells. For example, if the defect concentration in the CuO layer in TiO2/CuO structure is compatible to the acceptor concentration of 1x1016cm-3, the cell efficiency would be reduced dramatically to 7%. With defect concentration even as low as 1x1013cm-3, the significant VOC improvements in the TiO2/CuO/Cu2O would be reduced to an ignorable value. For interface states, they capture and recombine both electrons and hols passing through the hetero-junction interface, leading to deteriorated performance. The simulation shows that the interface states have a detrimental effect on the performance if its density is higher than 1012cm-2. However it was found that by increasing the difference of doping concentration in p-n junctions, the interface state effect minimized significantly. Furthermore, it is found the optical reflection at hetero-junction interface may induce a serious conversion efficiency loss, if the n-type semiconductors and p-type semiconductors have very different refractive indices. For some MO devices such as TiO2/CuO and ZnO/Cu2O, the reflection rate is around 5%, while for other material systems such as ZnO/Si, or ITO/Ge, the interfacial optical reflection may reach 10~30%, resulting in an efficiency loss by ~10%. It is also found that the interfacial reflection should be calculated through experimental data of refractive index at each photon frequency, rather than the dielectric constant. Otherwise, huge error may be introduced to the simulation results.

The increase in popularity of the microgrid concept requires the analysis and solution of the numerous technical issues arising from the operation and integration of the microgrid into the original distribution network. The work presented in this thesis is centred on the study of the fault behaviour of inverter-only microgrids and on the development of a suitable fault detection technique. This task is approached by first understanding the behaviour of a microgrid during a fault and the factors affecting it. A complete description and analysis of the key elements in the study of microgrid fault behaviour is presented. Then, three microgrid models with different inverter control methods (i.e. Synchronous Reference Frame control, Natural Reference Frame control and droop control) and with various current limiting strategies are built in PSCAD and their fault behaviour is simulated, analyzed and compared. It is found that the control of the inverter is able to shape the response of the microgrid in the event of a fault. The constraints to this capability are the inverter’s ratings (current and voltage limits) and the characteristic changes in the network introduced by faults. Moreover, it is found that the control in the Natural Reference Frame gives better fault response, in terms of voltage control and simplicity in implementation, compared with the popular control in the Synchronous Reference Frame. The behaviour of the system is then further analyzed by developing quasi steadystate inverter models suitable for numerical fault analysis. The models are developed starting from the inverter control and analyzing how it changes in the event of a fault. By combining control gains and circuit parameters, they result in being capable of capturing the key features of inverters’ fault behaviour. Depending on the control strategy, some of these models are balanced and therefore are directly applicable in numerical fault analysis based on sequence components. Others are unbalanced and therefore require a fault analysis based on a direct phase coordinates representation of the network. Examples on how to perform numerical fault analysis calculations with balanced and unbalanced models are given and the numerical results well compare with the ones obtained from time-domain simulations using PSCAD. From the knowledge of the microgrid fault behaviour developed analyzing the responses in time-domain simulations and by using the developed inverter models to numerically calculate voltages and currents in the microgrid during different faults at various locations, a fault detection strategy based on voltage sequence components is proposed. Indeed, it is the behaviour of the inverter control during faults which makes the monitoring of voltage sequence components the best discriminator between normal operation and fault operation. The three building blocks of the fault detection strategy which are capable of a fast extraction and comparison of voltage sequence components are described and then the performance of the fault detection strategy for different faults and microgrid operating conditions is tested in PSCAD and discussed. Finally, examples are given on how this voltage detection can be used in the design of a microgrid protection system.

The aim of this thesis is to design and implement an advanced control system for a working three-phase DC to AC power converter. Compared to the traditional PI controller used widely in industry, the new voltage controller can track the reference voltage with improved accuracy and efficiency in the presence of different kind of local loads, and also works well in the single phase voltage control. This voltage controller is combined with a power controller to yield a complete controller. An important aspect of this work is the hardware implementation of the whole system. Main parts of this thesis are: 1. Review of H-infinity and repetitive control techniques and their applications in power converters. 2. Design of a new voltage controller to eliminate the DC component in the output voltages, and taking into account the practical issues such as the processing delay due to the digital signal processor (DSP) implementation. 3. Modelling and simulation of the converter system incorporating different control techniques and with different kinds of loads. 4. Hardware implementation and the two-processor controller. The parallel communication between the DSPs. 5. The main problems encountered in hardware implementation and programming. The software used to initialize DSPs, implement the discrete time voltage controller and other functions such as generations of space vector pulse width modulation (SVPWM) signals, circuit protections, analog to digital (AD) cOl)versions, data transmission, etc. 6. Experimental results under circumstances of no load connected to the converter, pure three-phase resistive loads, three-phase unbalanced resistive loads and the series resistor-inductor loads.

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The majority of power distribution networks were planned, designed and built as a passive but reliable link between the bulk power transmission point and the in- dividual customer. Enough latent capacity in cables and lines to accommodate anticipated demand growth was allowed and so the system was left unmonitored. Following the signicant development in business regulation, technology evolutions and various government policies towards low carbon renewable generation, it has become necessary to operate the distribution systems efficiently and in a controlled manner. This obviously needs state estimation for network control functions. State estimation is the core function of any energy management system in transmission networks. However little emphasis have been given to the distribution system state estimation, mainly due to the absence of adequate network measurements and also lack of rigorous methodology and tools that could be applied on restricted measure- ments. The scarcity of measured information offers formidable challenge to the state estimator to provide reasonably meaningful estimates of the system states. This introduces bottlenecks in carrying out a range of substation and feeder automa- tion tasks that rely on the quality of the state estimator and opens up many issues like modelling of demand, identification of suitable estimator and placement of new measurements etc. This thesis attempts to address these issues. Thus, the objec- tives of this research are to model the demand as pseudo measurement, identify the state estimation methodology to suite the distribution scenarios and find the effec- tive locations for placing measurements for improving the quality of the estimated quantities. The thesis discusses in detail the criterion for identifying suitable solvers for the distribution system state estimation and stochastic optimisation methods to model the demand. It also discusses a probabilistic technique for identifying effective locations for measurement placement. The robustness of the state estimation algorithm against changes in network topology has been addressed in a statistical framework. All the concepts have been demonstrated on 12-bus radial and 95-bus UKGDS network models.

In contrast with traditional approaches based either on the analysis of a small specific area or on idealistic networks, the proposed methodology determines optimal network design policies by evaluating alternative planning strategies on statistically similar networks. The position of consumers influences the amount of equipment used to serve them. Therefore, simple geometric models or randomly placed points used in previous researches are not adequate. Using an algorithm based on fractal theory, realistic consumer sets are generated in terms of their position, type and demand to allow statistical evaluation of the cost of different design policies. In order to systematically deal with the problem of determining justifiable network investments, the concept of economically adapted distribution network was investigated and applied in the context of a loss-inclusive design promoting efficient investment policies from an overall social perspective. The network’s components are optimized, after yearly load flow calculations, based on the minimum life-cycle cost methodology, balancing annuitised capital investments and maintenance costs against the cost of system operation. Evaluating the cost of each particular design over statistically similar networks allows statistically significant conclusions to be drawn. The main results include the optimal number of substations for typical urban and rural LV, HV and EHV distribution systems, network costs (investment, purchasing and maintenance) and losses as well as the sensitivity of optimal network design to future energy prices and cost of equipment. The impact of the increasing amount of microgeneration on networks has not been fully addressed to date. There have not been clustering problems in existing networks as a result of customers choosing to install microgenerators, either as a new device or as a replacement of a previous heating system. The operation of microgeneration connected to the distribution network can cause statutory voltage limits, recommended voltage unbalance levels and switchgear fault ratings to be exceeded. However, there are a range of distribution network designs and operating practices and thus the impact will vary accordingly. The operation of distribution networks is approached considering the existence of single or three-phase loads and microgeneration. This would however cause the network to be unbalanced and hence, traditional methods that consider a three-phase balanced system would provide misleading results. Every residential daily load’s behaviour shows rapid shifts from “load valleys” to high peaks due to the random and frequent “switch on/off” of appliances. Modelling each load individually will reveal problematic operating conditions which were not considered when using a smooth load profile. Thus, each and every domestic load was represented by a different load profile and the impact on losses was evaluated. Relating losses, voltages, currents and load unbalance ratio leads to conclusions about the way how to optimise the network with DG. The aim was to investigate and develop methodology for evaluation of the long-term loss-inclusive optimal network design strategies and to determine the effect of the penetration of microgeneration, such as CHP and PV, in realistic distribution networks and optimal network planning. The need for reinforcement of network components will depend on the level of generation and on the extent to which reverse power flows occurs. In most parts of the network, microgeneration exports will not be sufficient to result in any need for network investment. However, if the network was to be planned accounting with DG, capital investment scenarios are presented and compared to existing networks trying to accommodate clusters of microgeneration.

The connection of Distributed Generators (DGs) to a distribution network causes technical concerns for Distribution Network Operators (DNOs) which include power flow management, loss increase and voltage management problems. An Active Network Management System can provide monitoring and control of the distribution network as well as providing the infrastructure and technology for full integration of DGs into the distribution network. The Optimal Power Flow (OPF) method is a valuable tool in providing optimal control solutions for active network management system applications. The research presented here has concentrated on the development of a multi-objective OPF to provide power flow management, voltage control solutions and network optimisation strategies. The OPF has been shown to provide accurate solutions for variety of network topologies. It is possible to apply time-series of load and generation data to the OPF in a loop, generating optimal network solutions to maintain the network within thermal and voltage limits. The OPF incorporates not only the DG real power output maximisation, but also network loss minimisation as well as minimising the dispatch of DG reactive power. This investigation uses a direct Interior Point (IP) method as the solution methodology which is speed efficient and converges in polynomial time. Each objective function has been assigned a weighting factor, making it possible to favour one objective function and ignore the others. Contributions to enhance the performance of the IP OPF algorithm include a new generic barrier parameter formulation and a new swing bus formulation to model energy export/import in the main optimisation routine. A Terminal Voltage Regulator Mode (TVRM) and Power Factor Regulation Mode (PFRM) for DG were incorporated in the main optimisation routine. The main motivation is to compare these two decentralised DG control methods in terms of the achieving the maximum DG real power generation. The DG operation methods of TVRM and PFRM are compared with the optimisation results obtained from centralised dispatch in terms of the DG capacity achieved as it produces the optimum overall network solution. A suitable value of the droop and local voltage regulator dead-bands were determined for particular DGs. Furthermore, the effect of these decentralised DG control methods on distribution network losses are considered in a measure to assess the financial implications from a DNO's perspective.

This thesis describes a novel, single point-of-attachment, gravitational torque energy harvesting system powered from rotational motion. The primary aim of such a system is to scavenge energy from a continuously rotating host in order to power a wireless sensor node. In this thesis, a wireless tachometer was prototyped. Most published work on motion-driven energy harvesters has used ambient vibrations in the environment as the energy source. However, none of the reported devices have been designed to harvest energy directly from continuous ambient rotation. There are important applications such as tire pressure sensing and condition monitoring of machinery where the host structure experiences continuous rotation. In this work, it is shown that in many applications, a rotational energy harvester can offer significant improvements in power density over its vibration-driven counterparts. A prototype single point-of-attachment rotational energy harvester was conceived using a simple direct-current generator. The rotational source was coupled to the stator and an offset mass was anchored on the rotor to create a counteractive gravitational torque. This produces a relative angular speed between rotor and stator which causes power to be generated. Power transfer from the generator to a load was maximised by enforcing an input impedance match between the generator’s armature resistance and the input impedance of a boost converter which in this case, functioned as a resistance emulator. Energy storage and output voltage regulation were implemented using supercapacitors and a wide-input buck regulator respectively. When excess power was generated, it was stored in the supercapacitors and during low source rotation speeds, i.e. insufficient harvested power, the supercapacitors will discharge to maintain operation of the interface electronics. A detailed optimisation procedure of a boost converter was conducted in Matlab in order to minimise the power loss, resulting in a maximum voltage gain of 11.1 and measured circuit efficiency of 96 %. A state-space control model of the harvester electronics was developed in the analogue domain using classical control techniques and this showed the system to be closed-loop stable. A final prototype of the rotational energy harvesting system was built and this comprised an input impedance controller, wireless transmitter and tachometer. The entire system has a measured end-to-end efficiency which peaked at 58 % from a source rotation of 1400 RPM with the generator producing 1.45 W under matched load conditions.

Unlike the centralized network, the ad hoc network does not have any central administrations and energy is constrained, e.g. battery, so the resource allocation plays a very important role in efficiently managing the limited energy in ad hoc networks. This thesis focuses on the resource allocation in ad hoc networks and aims to develop novel techniques that will improve the network performance from different network layers, such as the physical layer, Medium Access Control (MAC) layer and network layer. This thesis examines the energy utilization in High Speed Downlink Packet Access (HSDPA) systems at the physical layer. Two resource allocation techniques, known as channel adaptive HSDPA and two-group HSDPA, are developed to improve the performance of an ad hoc radio system through reducing the residual energy, which in turn, should improve the data rate in HSDPA systems. The channel adaptive HSDPA removes the constraint on the number of channels used for transmissions. The two-group allocation minimizes the residual energy in HSDPA systems and therefore enhances the physical data rates in transmissions due to adaptive modulations. These proposed approaches provide better data rate than rates achieved with the current HSDPA type of algorithm. By considering both physical transmission power and data rates for defining the cost function of the routing scheme, an energy-aware routing scheme is proposed in order to find the routing path with the least energy consumption. By focusing on the routing paths with low energy consumption, computational complexity is significantly reduced. The data rate enhancement achieved by two-group resource allocation further reduces the required amount of energy per bit for each path. With a novel load balancing technique, the information bits can be allocated to each path in such that a way the overall amount of energy consumed is minimized. After loading bits to multiple routing paths, an end-to-end delay minimization solution along a routing path is developed through studying MAC distributed coordination function (DCF) service time. Furthermore, the overhead effect and the related throughput reduction are studied. In order to enhance the network throughput at the MAC layer, two MAC DCF-based adaptive payload allocation approaches are developed through introducing Lagrange optimization and studying equal data transmission period.

Power systems exhibit nonlinear behavior especially during disturbances, necessitating the application of appropriate nonlinear control techniques. Lack of availability of accurate and updated models for the whole power system adds to the challenge. Conventional damping control design approaches consider a single operating condition of the system, which are obviously simple but tend to lack performance robustness. Objective of this research work is to design a measurement based self-tuning controller, which does not rely on accurate models and deals with nonlinearities in system response. Designed controller is required to ensure settling of inter-area oscillations within 10−12s, following disturbance such as a line outage. The neural network (NN) model is illustrated for the representation of nonlinear power systems. An optimization based algorithm, Levenberg-Marquardt (LM), for online estimation of power system dynamic behavior is proposed in batch mode to improve the model estimation. Careful study shows that the LM algorithm yields better closed loop performance, compared to conventional recursive least square (RLS) approach with the pole-shifting controller (PSC) in linear framework. Exploiting the capability of LM, a special form of neural network compatible with feedback linearization technique, is applied. Validation of the performance of proposed algorithm is done through the modeling and simulating heavy loading of transmission lines, when the nonlinearities are pronounced. Nonlinear NN model in the Feedback Linearization (FLNN) form gives better estimation than the autoregressive with an external input (ARX) form. The proposed identifier (FLNN with LM algorithm) is then tested on a 4−machine, 2−area power system in conjunction with the feedback linearization controller (FBLC) under varying operating conditions. This case study indicates that the developed closed loop strategy performs better than the linear NN with PSC. Extension of FLNN with FBLC structure in a multi-variable setup is also done. LM algorithm is successfully employed with the multi-input multi-output FLNN structure in a sliding window batch mode, and FBLC controller generates multiple control signals for FACTS. Case studies on a large scale 16−machine, 5−area power system are reported for different power flow scenarios, to prove the superiority of proposed schemes: both MIMO and MISO against a conventional model based controller. A coefficient vector for FBLC is derived, and utilized online at each time instant, to enhance the damping performance of controller, transforming into a time varying controller.