Research to date has highlighted a number of conditions where dropwise condensation may offer heat transfer enhancements over filmwise condensation. Previous studies have shown at pressures above or around atmospheric, dropwise condensation offers significant benefit over filmwise. However, some of this research suggests that as the system pressure is reduced below atmospheric, the benefits of dropwise condensation diminish rapidly, to the extent that, at pressures around 50mbar the benefits of dropwise over filmwise are minimal. This thesis details a series of experiments which were conducted to investigate the heat transfer and pressure drop distributions in tube bundles during both dropwise and filmwise condensation of steam. The primary objective of the work was to determine the design implications associated with switching the mode of condensation of a electricity generating steam turbine condenser from the current filmwise mode, to dropwise. Experimental data were obtained from a new purpose build apparatus containing seventy-five, 150mm long titanium tubes, arranged in an in line configuration of five columns and fifteen rows. Dropwise and filmwise data were recorded from each row at test cell inlet pressures down to 50mbar using both pure steam and steam air mixtures. Filmwise heat transfer data indicated that, under most conditions, heat transfer coefficients were generally in agreement with those obtained by previous workers. Heat transfer data obtained during dropwise condensation suggested that the benefits of dropwise condensation are not significantly diminished at low pressure, and that, unlike filmwise condensation, inundation has little or no effect in a fifteen row bundle. The data also indicated that the pressure drop characteristics and effects of air are, within experimental error, identical during both modes of condensation and in line with models and theories proposed by previous workers.

Many communities around the world have no access to an electricity grid. To supply power to these people, stand-alone power systems are often used, the majority of which are based on diesel generators. Rising fuel costs and environmental concerns make the use of renewable energy in stand-alone systems increasingly attractive. The research reported in this thesis was to demonstrate a stand-alone power system based exclusively on renewable energy sources. To achieve this, a DC electrical backbone is used. Power electronic converters are used to interconnect the loads and generators and hydrogen is used as an inter-seasonal energy store. The design and control of the DC based stand-alone power system forms the primary focus of this research. A demonstration system has been implemented at West Beacon Farm in the UK. Substantial data has been collected that confirms the successful operation of the system.

Voltage is one of the most important parameters for electrical power networks. The Distribution Network Operators (DNOs) have the responsibility to maintain the voltage supplied to consumers within statutory limits. On-Load Tap Changer (OLTC) transformer equipped with Automatic Voltage Control (AVC) relay is the most widely used and effective voltage control device. Due to a variety of advantages of adding Distributed Generation (DG), more and more distributed resources are connected to local distribution networks to solve constraints of networks, reduce the losses from power supply station to consumers. When DG is connected, the direction of power flow can be reversed when the DG output power exceeds the local load. This means that the bidirectional power flow can either be from power grid towards loads, or vice versa. The connection point of DG may suffer overvoltage when the DG is producing a large amount of apparent power. The intermittent nature of renewable energy resources which are most frequently used in DG technology results in uncertainty of distribution network operation. Overall, conventional OLTC voltage control methods need to be changed when DG is connected to distribution networks. The required voltage control needs to address challenges outlined above and new control method need to be formulated to reduce the limitations of DG output restricted by current operational policies by DNOs. The thesis presents an analysis of voltage control using OLTC transformer with DG in distribution networks. The thesis reviews conventional OLTC voltage control schemes and existing policies of DNOs in the UK. An overview of DG technologies is also presented with their operation characteristics based on power output. The impact of DG on OLTC voltage control schemes in distribution networks is simulated and discussed. The effects of different X/R ratio of overhead line and underground cable are also considered. These impacts need to be critically assessed before any new method implementation. The thesis also introduces the new concepts of Smart Grid and Smart Meter in terms of the transition from passive to active distribution networks. The role of Smart Meter and an overview of communication technologies that could be used for voltage control are investigated. The thesis analyses the high latency of an example solution of which cost and availability are considered to demonstrate the real-time voltage control using Smart Metering with existing communication infrastructures cannot be achieved cost-effectively. The thesis provides an advanced compensation-based OLTC voltage control algorithm using Automatic Compensation Voltage Control (ACVC) technique to improve the voltage control performance with DG penetration without communication. The proposed algorithm is simulated under varying load and DG conditions based on Simulink MATLAB to show the robustness of the proposed method. A generic 11kV network in the UK is modelled to evaluate the correct control performance of the advanced voltage control algorithm while increasing the DG capacity.

Today’s power systems are based on a centralised system and distribution networks that are considered as passive terminations of transmission networks. The high penetration of Distributed Generation (DG) at the distribution network level has created many challenges for this structure. New tools and simulation approaches are required to address the subject and to quantify the dynamic characteristics of the system. A distribution network or part of it with DG, Active Distribution Network Cell (ADNC), can no longer be considered as passive. An equivalent dynamic model of ADNC is therefore extremely important, as it enables power system operators to quickly estimate the impact of disturbances on the power system’s dynamic behaviour. A dynamic equivalent model works by reducing both the complexity of the distribution network and the computation time required to run a full dynamic simulation. It offers a simple and low-order representation of the system without compromising distribution network dynamic characteristics and behaviour as seen by the external grid. This research aims to develop a dynamic equivalent model for ADNC. It focuses on the development of an equivalent model by exploiting system identification theory, i.e. the grey-box approach. The first part of the thesis gives a comprehensive overview and background of the dynamic equivalent techniques for power systems. The research was inspired by previous work on system identification theory. It further demonstrates the theoretical concept of system identification, system load modelling and the modelling of major types of DG. An equivalent model is developed, guided by the assumed structure of the system. The problem of equivalent model development is then formulated under a system identification framework, and the parameter estimation methodology is proposed. The validation results of the effectiveness and accuracy of the developed model are presented. This includes the estimation of the parameter model using a clustering algorithm to improve the computational performance and the analysis of transformer impedance effects on the ADNC responses. The evaluation of probability density function, eigenvalue analysis and parameter sensitivity analysis for the model parameters are also presented. Typical model parameters for different network topologies and configurations are identified. Finally, the developed equivalent model is used for a large power system application. The accuracy and robustness of the developed equivalent model are demonstrated under small and large disturbance studies for various types of fault and different fault locations.

Flexibility describes the system ability to cope with events that may cause imbalance between electricity supply and demand while maintaining the system reliability in a cost-effective manner. Flexibility has always been present in the power system to cater for unplanned generator outages and demand uncertainty and variability. The arrival of wind generation with its variable and hard to predict nature increases the overall needs for system flexibility. This thesis provides a systematic approach for investigating the role of flexibility in different power system activities including generation scheduling, generation planning and market operation, and furthermore proposes two 'offline' indices for flexibility evaluation. Using the tools and metrics presented in this thesis, it is possible to perform the following tasks: • Conduct generation scheduling simulation to evaluate the impacts of wind on the flexibility requirement of power systems; • Use the unit construction and commitment algorithm to 1) estimate the maximum allowable wind capacity for an existing system; 2) find the optimal investment of new flexible units for accommodating more wind generation; and 3) decide an optimal generation mix for integrating a given wind penetration; • Use the market model to reveal the value and profitability of flexibility and evaluate the corresponding effects of alternative market design; • Use the two proposed flexibility indices to quantitatively assess the flexibility of individual generators and power systems without undertaking complex and time consuming simulations.

Today the modern power system is more dynamic and its operation is a subject to a number of constraints that are reflected in various management and planning tools used by system operators. In the case of hourly generation planning, Economic Dispatch (ED) allocates the outputs of all committed generating units, which are previously identified by the solution of the Unit Commitment (UC) problem. Thus, the accurate solutions of the ED and UC problems are essential in order to operate the power system in an economic and efficient manner. A number of computation techniques have progressively been proposed to solve these critical issues. One of them is a Particle Swarm Optimisation (PSO), which belongs to the evolutionary computation techniques, and it has attracted a great attention of the research community since it has been found to be extremely effective in solving a wide range of engineering problems. The attractive characteristics of PSO include: ease of implementation, fast convergence compared with the traditional evolutionary computation techniques and stable convergence characteristic. Although the PSO algorithms can converge very quickly towards the optimal solutions for many optimisation problems, it has been observed that in problems with a large number of suboptimal areas (i.e. multi-modal problems), PSO could get trapped in those local minima, including ED and UC problems. Aiming at enhancing the diversity of the traditional PSO algorithms, this thesis proposes a method of combining the PSO algorithms with a real-valued natural mutation (RVM) operator to enhance the global search capability and investigate the performance of the proposed algorithm compared with the standard PSO algorithms and other algorithms. Prior to applying to ED and UC problems, the proposed method is tested with some selected mathematical functions where the results show that it can avoid being trapped in local minima. The proposed methodology is then applied to ED and UC problems, and the obtained results show that it can provide solutions with good accuracy and stable convergence characteristic with simple implementation and satisfactory calculation time. Furthermore, the sensitivity analysis of PSO parameters has been studied so as to investigate the response of the proposed method to the parameter variations, especially in both ED and UC problems. The outcome of this research shows that the proposed method succeeds in dealing with the PSO' s drawbacks and also shows the superiority over the traditional PSO algorithms and other methods in terms of high quality solutions, stable convergence characteristic, and robustness.

M. Tech. (Department of Chemistry, Faculty of Applied and Computer Sciences), Vaal University of Technology, 2016 / Natural organic matter if not removed from water used for electricity generation has dire consequences that affect the long term plant health. The main problem is that organic matter at higher temperature and pressure disintegrate into smaller organic acids and carbon dioxide. This causes the cycle water and steam to be acidic and this can result in corrosion of the plant. The raw water from the Komati (Arnot power station) and Usutu (Kriel power station) scheme were analysed to determine the organic profile and seasonal variation. There was a noticeable variation in the quality of the water with an increase in DOC during rainy season. The water was found to be containing hydrophobic as well as hydrophilic molecules that could be quantified with a liquid chromatography organic detector (LC-OCD). Current water treatment processes employed at the two stations, Arnot and Kriel, has demonstrated the capability of removing organics to just over 50 percent at the pre-treatment section. The water treatment plant includes demineralisation plant that was able to produce water that met Eskom’s target specifications of less than 250 ppb DOC values. Qualitative and quantitative analysis of the steam-condensate water was done by use of an ion chromatography method. The determined organic anions were found to be acetates, formats and lactates.

Diversification of the energy mix is one of the main challenges in the energy agenda of governments worldwide. Technology advances together with environmental concerns have paved the way for the increasing integration of Distributed Generation (DG) seen over recent years. Combined heat and power and renewable technologies are being encouraged and their penetration in distribution networks is increasing. This scenario presents Distribution Network Operators (DNOs) with several technical challenges in order to properly accommodate DG developments. However, depending on various factors, such as location, size, technology and robustness of the network, DG might also be beneficial to DNOs. In this thesis, the impact of DG on network planning is analysed and the implications for DNOs in incorporating DG within the network planning process are identified. In the first part, various impacts of DG to the network, such as network thermal capacity release, security of supply and on voltage, are quantified through network planning by using a modified successive elimination method and voltage sensitivity analysis. The results would potentially assist DNOs in assessing the possibilities and effort required to utilise privately-owned DG to improve network efficiency and save investment. The quantified values would also act as a fundamental element in deriving effective distribution network charging schemes. In the second part, a novel balanced genetic algorithm is introduced as an efficient means of tackling the problem of optimum network planning considering future uncertainties. The approach is used to analyse the possibilities, potential benefits and challenges to strategic network planning by considering the presence of DG in the future when the characteristics of DG are uncertain.