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Synchronous generators are the most widely used machines in power generation. Identifying their parameters in a non invasive way is very challenging due to the inherent nonlinearity of power plant performance. This thesis proposes a parameter identification method using particle swarm optimisation (PSO) for the identification of synchronous machine, excitation system and turbine parameters. The PSO allows a generator model output to be used as the objective function to give a new, more efficient method of parameter identification. This thesis highlights the effectiveness of the proposed method for the identification of power plant parameters, using both simulation and real recorded transient data. The thesis also considers the effectiveness of the method as the number of parameters to be identified is increased, and the effect of using differing forms of disturbances on parameter identification.

This research focuses on the design and control of a new class of brushless machine known as the flux switching machine for high speed and high power application. This machine is a hybrid of the inductor alternator and the switched reluctance machine. The characteristic of this machine determined from an experimental generator shows that the power delivery capability of the machine is limited by the synchronous inductance of the machine especially at high speeds. Various power factor control techniques are proposed and evaluated as possible solutions to the attendant problems with the uncontrolled flux switching generator. This involves the use of series compensation and shunt compensation techniques. For the series compensator technique, a new class of series line compensation delivering controlled power factor using pulse width modulation is identified and tested on an experimental flux switching generator system. The shunt compensation technique for the flux switching generator system is a controlled rectifier, which uses phase angle pulse width modulation to deliver controlled power factor. The power factor control of the flux switching generator system shows that significant improvement in power delivery for the flux switching generator system can be achieved. Matlab/Simulink models are developed for each of the proposed technique and the results compared with experimental data shows reasonable agreement. These Matlab/Simulink models can now be effectively used for rapid design and prototyping of the flux switching generator system. Closed loop control of the output voltage of the flux switching generator system can be achieved. This is done using field current control and/or armature current control. The increased controllability of the FSG compared to other reluctance machines makes it a viable alternative for high speed, high power applications especially in mechanically harsh environment.

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In the past distribution networks are passive as there are no generation sources connected to them. The direction of power flow is normally from the high voltage network down to the distribution network. More and more distributed generations (DG) are now connected to distribution networks and this has changed them to become active. As a result the pricing of the use of distribution system has become more complex and it is a major issue of current interest. The issue concerns the way the cost of distribution services should satisfactorily be allocated among the involved parties due to multi-directional power flow.

This thesis proposes a method to establish the accurate parameters of stabilisers in the context of power systems with increasing penetration of Doubly Fed Induction Generators (DFIGs), Solid Oxide Fuel Cells (SOFCs) and Photovoltaic (PVs) using a hierarchical coordinated strategy and localised design. The performance of the tuned stabilisers is verified using modal analysis results and non-linear simulation. This thesis proposes that by using regulated stabilisers, the dynamic stability of a power system with large-scale Distributed Generation (DG) integration can be maintained. SmartParks have been proposed in published literature to support emergent electric vehicle charging. In practice, a SmartPark can be configured as an adjustable load, in charging mode, or a regulated generator, in a discharging mode using a voltage control strategy. In this thesis, damping torque analysis (DTA) has been used to investigate the impact on dynamic stability of the joint operation of SmartParks in power systems with conventional synchronous machines. The analysis reveals that in terms of the local damping ratio, optimal charging and local capacity is best considered during SmartPark design. According to a Phillips-Heffron model developed for a multi-machine system with SmartPark, active and reactive power stabiliser can be incorporated into the SmartPark control loops to improve the damping of the system. Finally, this thesis considers the economic operation of micro-grids by proposing a combined EV charging/discharging model which incorporates stochastic uncertainties in vehicle travel patterns and initial battery state of charge (SOC). The model includes provision of energy storage and renewable generation infeed is used to establish an economic basis for micro-grid operation based on market revenues.

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The development of power generation technologies and the deregulation of the power market has led to an increasing interest in distributed power generation, mainly the simultaneous exploitation of electricity and heat from the same energy source, known as combined heat and power (CHP) systems. As a consequence of the high competitiveness of power markets and increasing environmental concerns, distributed power generators have to make reasonable choices at multiple levels of complexity. A key issue to successfully approaching these problems is the development of decision making support tools that rely on service life prediction, intelligent economic dispatch optimisation techniques and condition monitoring. This research introduces the concept and development of a decision making support tool for a mini-pool nerve centre based on distributed gas turbine generation units operating in a competitive market. The nerve centre framework leads naturally to a multi-criteria optimisation problem which is solved in this research with a hybrid genetic algorithm adapted priority list and creep life assessment. The proposed hybrid approach can result in a significant saving to generators as it efficiently optimises mini- pool profits and service hours between failures in an acceptable computation time and accurately. Life cycle assessment combined with generation schedule optimisation can enhance the maintenance strategy activities and the competitiveness of gas turbine distributed generation plants, particularly for generators trading energy in a highly competitive market. Gas turbine combined heat and power distributed generators are unlikely to succeed in competing individually with centralised generation technologies within the present market framework, but they can be more competitive in an information technology based mini-pool. Additionally, results show that the development of a low carbon emission power industry can result in an outstanding opportunity for combined heat and power mainly in power markets currently highly dependent on coal and oil powered stations.

This PhD thesis is a demand led study taking into account changes in ambient conditions and power settings of a tri-generation power plant. Includes an evaluation tool for combined heat, cooling and power generation plant. The thesis is based on an overall technical-economic analysis of the tri-generation system, including: 1. Energy demand analysis and evaluation of actual tri-generation case studies. 2. Modelling of the prime mover (Gas Turbine, GT) 3. Modelling of the absorption cooling system, (LiBr/Water). 4. Economic analysis and evaluation of the entire tri-generation plant. Initially, the main effort is to carry out research concerning the energy demands of different actual cases. The research includes sourcing, collecting, classification and evaluation of the available information. The cases cover a wide range of economic life and the resulting data specifies the energy needs which the purposed tri-generation power plant needs to cover. The second part deals with the prime mover (namely the Gas Turbine, GT) modelling and simulation. The technical part of the assessment includes the Design Point (DP) and Off Design (OD) analysis of the GT. In other words, the performance analysis simulates different thermodynamic cycles (Simple, or with Heat Exchanger), and different configurations (one or two shafts). Also, the computer programming code is capable of simulating the effects of the use of different types of fuel, ambient conditions, part load conditions, degradation, or the extraction of power for district heating or for absorption cooling. The third part includes the simulation of the absorption cooling system alone and/or in co-operation with the prime mover. The simulation is based upon the premise that the original prime mover is replaceable. Finally, an evaluation methodology of tri-generation plants, is introduced taking into account, both technical facts and economic data -based on certain cases from Greek reality- helping the potential users to decide whether it is profitable to use such technology or not. The economic scene will include the basic economic facts such as initial cost, handling and operational cost (fuel prices, maintenance etc), using methodology based on Net Present Value (NPV). This thesis suggests several tri-generation technology modes. The more economic favourable than the conventional technology is the 2-shaft simple cycle mode for the cases of international airport (12MW total power demand) and the isolated island (120MW), while the 1-shaft simple cycle mode is the more economic favourable for the case of hotel (1MW). The main contribution of the thesis is that it provides an intergraded realistic tool, which simulates the future operation (technical and economic) of a trigeneration plant, capable of helping the potential investor decide if it is profitable to proceed with the investment.