Optimal energy control of a grid connected solar-wind based electric power plant.

Doctor of Philosophy in Electrical Engineering. University of KwaZulu-Natal, Howard College 2016.In the present context of urge energy demand, renewable energy is considered as an alternative source of clean energy. In view of the increase in the price of fossil fuel due to its rarity and emissions, more integration of renewable sources is needed for better economic management of the grid. This research work has been done in two parts. The first part deals with the daily energy consumption variations for the low demand season and high demand season on weekdays and weekends. The intention is to correlate the corresponding fuel cost and estimate the operational efficiency of the hybrid system, which comprises the PV, PW, DG, battery system, for a period of 24 hours taken as control horizon. The latest published research literature has shown that a good deal of work has been done using a fixed load and uniform daily operational cost. The economic dispatch strategy, fuel cost, energy flows and energy sales are analysed in this study. The results show that a renewable energy system, which combines the PV/PW/diesel/battery models, achieves more fuel saving during both the high demand and low demand seasons than a model where the diesel generator satisfies the load on its own. The fuel cost during the low demand and high demand seasons for weekdays and weekends shows considerable fluctuations, which should not be neglected if accurate operational costs are to be obtained. The model shows the achievement of a more practical estimate of fuel costs, which reflects the fluctuation of power consumption behaviour for any given model. In the last part of the thesis model predictive control (MPC) is introduced in the management and control of power flow. The highlight in this thesis is the management of the energy flow from the hydro pump, wind, photovoltaic system and turbine when the system is subject to severe disturbances. The results demonstrated in the thesis prove the advantages of the approach and its robustness against uncertainties and external disturbances. When analysed with the open loop control system, MPC is more robust because of its stability of the system when external disturbances occur in the system. This thesis presents a practical solution to energy sale, control, optimization and management

Automated Control Flaw Generation Procedure: Cheakamus Dam Case Study

This thesis deals with the problem of aging hydropower infrastructure systems and system components, a problem that is very common across Canada. Flaws of common risk analysis methods are noted, and the need for new risk analysis approaches is identified. System dynamics simulation method is introduced as an implementation mechanism for the System Theoretic Process Analysis (STPA). STPA and its adaptation to complex hydropower systems are explained thoroughly. Fuzzy logic is used to model operator’s decision making. The main objectives of the research include the development of an automated generic approach that implements STPA and fuzzy logic for the investigation and identification of potentially hazardous actions and hazardous system states. The developed methodology is illustrated using a case study based on the BC Hydro’s Cheakamus Dam, British Columbia, Canada

Water Systems towards New Future Challenges

This book comprises components associated with smart water which aims at the exploitation and building of more sustainable and technological water networks towards the water–energy nexus and system efficiency. The implementation of modeling frameworks for measuring the performance based on a set of relevant indicators and data applications and model interfaces provides better support for decisions towards greater sustainability and more flexible and safer solutions. The hydraulic, management, and structural models represent the most effective and viable way to predict the behavior of the water networks under a wide range of conditions of demand and system failures. The knowledge of reliable parameters is crucial to develop approach models and, therefore, positive decisions in real time to be implemented in smart water systems. On the other hand, the models of operation in real-time optimization allow us to extend decisions to smart water systems in order to improve the efficiency of the water network and ensure more reliable and flexible operations, maximizing cost, environmental, and social savings associated with losses or failures. The data obtained in real time instantly update the network model towards digital water models, showing the characteristic parameters of pumps, valves, pressures, and flows, as well as hours of operation towards the lowest operating costs, in order to meet the requirement objectives for an efficient system

Passivity - Based Control and Stability Analysis for Hydro-Solar Power Systems

Los sistemas de energía modernos se están transformando debido a la inclusión de renovables no convencionales fuentes de energía como la generación eólica y fotovoltaica. A pesar de que estas fuentes de energía son buenas alternativas para el aprovechamiento sostenible de la energía, afectan el funcionamiento y la estabilidad del sistema de energía, debido a su naturaleza inherentemente estocástica y dependencia de las condiciones climáticas. Además, los parques solares y eólicos tienen una capacidad de inercia reducida que debe ser compensada por grandes generadores síncronos en sistemas hidro térmicos convencionales, o por almacenamiento de energía dispositivos. En este contexto, la interacción dinámica entre fuentes convencionales y renovables debe ser estudiado en detalle. Para 2030, el Gobierno de Colombia proyecta que el poder colombiano El sistema integrará en su matriz energética al menos 1,2 GW de generación solar fotovoltaica. Por esta razón, es necesario diseñar controladores robustos que mejoren la estabilidad en los sistemas de energía. Con alta penetración de generación fotovoltaica e hidroeléctrica. Esta disertación estudia nuevas alternativas para mejorar el sistema de potencia de respuesta dinámica durante y después de grandes perturbaciones usando pasividad control basado. Esto se debe a que los componentes del sistema de alimentación son inherentemente pasivos y permiten formulaciones hamiltonianas, explotando así las propiedades de pasividad de sistemas eléctricos. Las principales contribuciones de esta disertación son: una pasividad descentralizada basada control de los sistemas de control de turbinas hidráulicas para sistemas de energía de múltiples máquinas para estabilizar el rotor acelerar y regular el voltaje terminal de cada sistema de control de turbinas hidráulicas en el sistema como, así como un control basado en PI pasividad para las plantas solares fotovoltaicas

A novel method for power system stabilizer design

Power system stability is defined as the condition of a power system that enables it to remain in a state of operating equilibrium under normal operating conditions and to regain an acceptable state of equilibrium after being subjected to a finite disturbance. In the evaluation of stability, the focus is on the behavior of the power system when subjected to both large and small disturbances. Large disturbances are caused by severe changes in the power system, e.g. a short-circuit on a transmission line, loss of a large generator or load, loss of a tie-line between two systems. Small disturbances in the form of load changes take place continuously requiring the system to adjust to the changing conditions. The system should be capable of operating satisfactorily under these conditions and successfully supplying the maximum amount ofload. Power system stability is defined as the condition of a power system that enables it to remain in a state of operating equilibrium under normal operating conditions and to regain an acceptable state of equilibrium after being subjected to a finite disturbance. In the evaluation of stability, the focus is on the behavior of the power system when subjected to both large and small disturbances. Large disturbances are caused by severe changes in the power system, e.g. a short-circuit on a transmission line, loss of a large generator or load, loss of a tie-line between two systems. Small disturbances in the form of load changes take place continuously requiring the system to adjust to the changing conditions. The system should be capable of operating satisfactorily under these conditions and successfully supplying the maximum amount ofload. This dissertation deals with the use of Power System Stabilizers (PSS) to damp electromechanical oscillations arising from small disturbances. In particular, it focuses on three issues associated with the damping of these oscillations. These include ensuring robustness of PSS under changing operating conditions, maintaining or selecting the structure of the PSS and coordinating multiple PSS to ensure global power system robustness. To address the issues outlined above, a new PSS design/tuning method has been developed. The method, called sub-optimal Hoo PSS design/tuning, is based on Hoo control theory. For the implementation of the sub-optimal Hoo PSS design/tuning method, various standard optimization methods, such as Sequential Quadratic Programming (SQP), were investigated. However, power systems typically have multiple "modes" that result in the optimization problem being non-convex in nature. To overcome the issue of non-convexity, the optimization algorithm, embedded in the 111 University of Cape Town sub-optimal Hoo PSS design/tuning method, is based on Population Based Incremental Learning (PBIL). This new sub-optimal Heo design/tuning method has a number of important features. The method allows for the selection of the PSS structure i.e. the designer can select the order and structure of the PSS. The method can be applied to the full model of the power system i.e. there is no need for using a reduced-order model. The method is based on Heo control theory i.e. it uses robustness as a key objective. The method ensures adequate damping of the electromechanical oscillations of the power system. The method is suitable for optimizing existing PSS in a power system. This method improves the overall damping of the system and does not affect the observability of the system poles. To demonstrate the effectiveness of the sUb-optimal Hoo PSS design/tuning method, a number of case studies are presented in the thesis. The sub-optimal Hoo design/tuning method is extended to allow for the coordinated tuning of multiple controllers. The ability to tune multiple controllers in a coordinated manner allows the designer to focus on the overall stability and robustness of the power system, rather than focusing just on, the local stability of the system as viewed from the generator where the controllers are connected

Grid-Connected Renewable Energy Sources

The use of renewable energy sources (RESs) is a need of global society. This editorial, and its associated Special Issue “Grid-Connected Renewable Energy Sources”, offers a compilation of some of the recent advances in the analysis of current power systems that are composed after the high penetration of distributed generation (DG) with different RESs. The focus is on both new control configurations and on novel methodologies for the optimal placement and sizing of DG. The eleven accepted papers certainly provide a good contribution to control deployments and methodologies for the allocation and sizing of DG

Methods of system identification, parameter estimation and optimisation applied to problems of modelling and control in engineering and physiology

Mathematical and computer-based models provide the foundation of most methods of engineering design. They are recognised as being especially important in the development of integrated dynamic systems, such as “control-configured” aircraft or in complex robotics applications. These models usually involve combinations of linear or nonlinear ordinary differential equations or difference equations, partial differential equations and algebraic equations. In some cases models may be based on differential algebraic equations. Dynamic models are also important in many other fields of research, including physiology where the highly integrated nature of biological control systems is starting to be more fully understood. Although many models may be developed using physical, chemical, or biological principles in the initial stages, the use of experimentation is important for checking the significance of underlying assumptions or simplifications and also for estimating appropriate sets of parameters. This experimental approach to modelling is also of central importance in establishing the suitability, or otherwise, of a given model for an intended application – the so-called “model validation” problem. System identification, which is the broad term used to describe the processes of experimental modelling, is generally considered to be a mature field and classical methods of identification involve linear discrete-time models within a stochastic framework. The aspects of the research described in this thesis that relate to applications of identification, parameter estimation and optimisation techniques for model development and model validation mainly involve nonlinear continuous time models Experimentally-based models of this kind have been used very successfully in the course of the research described in this thesis very in two areas of physiological research and in a number of different engineering applications. In terms of optimisation problems, the design, experimental tuning and performance evaluation of nonlinear control systems has much in common with the use of optimisation techniques within the model development process and it is therefore helpful to consider these two areas together. The work described in the thesis is strongly applications oriented. Many similarities have been found in applying modelling and control techniques to problems arising in fields that appear very different. For example, the areas of neurophysiology, respiratory gas exchange processes, electro-optic sensor systems, helicopter flight-control, hydro-electric power generation and surface ship or underwater vehicles appear to have little in common. However, closer examination shows that they have many similarities in terms of the types of problem that are presented, both in modelling and in system design. In addition to nonlinear behaviour; most models of these systems involve significant uncertainties or require important simplifications if the model is to be used in a real-time application such as automatic control. One recurring theme, that is important both in the modelling work described and for control applications, is the additional insight that can be gained through the dual use of time-domain and frequency-domain information. One example of this is the importance of coherence information in establishing the existence of linear or nonlinear relationships between variables and this has proved to be valuable in the experimental investigation of neuromuscular systems and in the identification of helicopter models from flight test data. Frequency-domain techniques have also proved useful for the reduction of high-order multi-input multi-output models. Another important theme that has appeared both within the modelling applications and in research on nonlinear control system design methods, relates to the problems of optimisation in cases where the associated response surface has many local optima. Finding the global optimum in practical applications presents major difficulties and much emphasis has been placed on evolutionary methods of optimisation (both genetic algorithms and genetic programming) in providing usable methods for optimisation in design and in complex nonlinear modelling applications that do not involve real-time problems. Another topic, considered both in the context of system modelling and control, is parameter sensitivity analysis and it has been found that insight gained from sensitivity information can be of value not only in the development of system models (e.g. through investigation of model robustness and the design of appropriate test inputs), but also in feedback system design and in controller tuning. A technique has been developed based on sensitivity analysis for the semi-automatic tuning of cascade and feedback controllers for multi-input multi-output feedback control systems. This tuning technique has been applied successfully to several problems. Inverse systems also receive significant attention in the thesis. These systems have provided a basis for theoretical research in the control systems field over the past two decades and some significant applications have been reported, despite the inherent difficulties in the mathematical methods needed for the nonlinear case. Inverse simulation methods, developed initially by others for use in handling-qualities studies for fixed-wing aircraft and helicopters, are shown in the thesis to provide some important potential benefits in control applications compared with classical methods of inversion. New developments in terms of methodology are presented in terms of a novel sensitivity based approach to inverse simulation that has advantages in terms of numerical accuracy and a new search-based optimisation technique based on the Nelder-Mead algorithm that can handle inverse simulation problems involving hard nonlinearities. Engineering applications of inverse simulation are presented, some of which involve helicopter flight control applications while others are concerned with feed-forward controllers for ship steering systems. The methods of search-based optimisation show some important advantages over conventional gradient-based methods, especially in cases where saturation and other nonlinearities are significant. The final discussion section takes the form of a critical evaluation of results obtained using the chosen methods of system identification, parameter estimation and optimisation for the modelling and control applications considered. Areas of success are highlighted and situations are identified where currently available techniques have important limitations. The benefits of an inter-disciplinary and applications-oriented approach to problems of modelling and control are also discussed and the value in terms of cross-fertilisation of ideas resulting from involvement in a wide range of applications is emphasised. Areas for further research are discussed

Transient performance simulation of gas turbine engine integrated with fuel and control systems

Two new methods for the simulation of gas turbine fuel systems, one based on an inter-component volume (ICV) method, and the other based on the iterative Newton Raphson (NR) method, have been developed in this study. They are able to simulate the performance behaviour of each of the hydraulic components such as pumps, valves, metering unit of a fuel system, using physics-based models, which potentially offer more accurate results compared with those using transfer functions. A transient performance simulation system has been set up for gas turbine engines based on an inter-component volume (ICV). A proportional- integral (PI) control strategy is used for the simulation of engine control systems. An integrated engine and its control and hydraulic fuel systems has been set up to investigate their coupling effect during engine transient processes. The developed simulation methods and the systems have been applied to a model turbojet and a model turboshaft gas turbine engine to demonstrate the effectiveness of both two methods. The comparison between the results of engines with and without the ICV method simulated fuel system models shows that the delay of the engine transient response due to the inclusion of the fuel system components and introduced inter-component volumes is noticeable, although relatively small. The comparison of two developed methods applied to engine fuel system simulation demonstrate that both methods introduce delay effect to the engine transient response but the NR method is ahead than the ICV method due to the omission of inter-component volumes on engine fuel system simulation. The developed simulation methods are generic and can be applied to the performance simulation of any other gas turbines and their control and fuel systems. A sensitivity analysis of fuel system key parameters that may affect the engine transient behaviours has also been achieved and represented in this thesis. Three sets of fuel system key parameters have been introduced to investigate their sensitivities, which are, the volumes introduced for ICV method applied to fuel system simulation; the time constants introduced into those first order lags tosimulate the valve movements delay and fuel spray delay effect; and the fuel system key performance and structural parameters