Sizing hybrid green hydrogen energy generation and storage systems (HGHES) to enable an increase in renewable penetration for stabilising the grid.

A problem that has become apparently growing in the deployment of renewable energy systems is the power grids inability to accept the forecasted growth in renewable energy generation integration. To support forecasted growth in renewable generation integration, it is now recognised that Energy Storage Technologies (EST) must be utilised. Recent advances in Hydrogen Energy Storage Technologies (HEST) have unlocked their potential for use with constrained renewable generation. HEST combines Hydrogen production, storage and end use technologies with renewable generation in either a directly connected configuration, or indirectly via existing power networks. A levelised cost (LC) model has been developed within this thesis to identify the financial competitiveness of the different HEST application scenarios when used with grid constrained renewable energy. Five HEST scenarios have been investigated to demonstrate the most financially competitive configuration and the benefit that the by-product oxygen from renewable electrolysis can have on financial competitiveness. Furthermore, to address the lack in commercial software tools available to size an energy system incorporating HEST with limited data, a deterministic modelling approach has been developed to enable the initial automatic sizing of a hybrid renewable hydrogen energy system (HRHES) for a specified consumer demand. Within this approach, a worst-case scenario from the financial competitiveness analysis has been used to demonstrate that initial sizing of a HRHES can be achieved with only two input data, namely “ the available renewable resource and the load profile. The effect of the electrolyser thermal transients at start-up on the overall quantity of hydrogen produced (and accordingly the energy stored), when operated in conjunction with an intermittent renewable generation source, has also been modelled. Finally, a mass-transfer simulation model has been developed to investigate the suitability of constrained renewable generation in creating hydrogen for a hydrogen refuelling station

Condition assessment for water distribution pipelines using inverse transient analysis and the reconstructive method of characteristics

Modern civilisations rely on water distribution systems to deliver water resources to domestic and industrial consumers. During the lifespan of pipeline assets, they naturally deteriorate due to a combination factors such as ground movement, fatigue, high stresses, and external or internal corrosion. The gradual deterioration of pipelines may lead to the failure of pipelines which may have severe consequences in terms of water resource loss, disruption to industry, traffic and the wider community, repair costs and compensation claims. Developing an efficient and reliable pipeline condition assessment approach is essential to decision-making involving inspection, rehabilitation and replacement. Many existing methods can only investigate pipeline condition over a limited range, which makes them slow and expensive. Fluid transient-based methods can cover several kilometres of pipeline using a few seconds of transient-based test data, due to the fast wave propagation speed. In addition, a transient event can be generated and measured at existing access points along pipelines (for example, air valves or fire hydrants), so cutting the pipeline open and/or draining out the water from the pipeline is not required. Overall, fluid transient-based methods are cost-effective and non-invasive, which make them a promising tool for the future. To achieve the goal of continuous condition assessment for water distribution pipelines, this research focuses on the Inverse Transient Analysis (ITA) method and the previously developed Reconstructive Method of Characteristics (RMOC). The research proposes a faster and improved ITA approach by incorporating a new Head Based Method of Characteristics (HBMOC) and a flexible grid, which enhances the computational efficiency and avoids the need for incorporation of interpolation schemes such as those used in the traditional MOC approach. This efficient ITA approach is then developed into the multi-stage parameter-constraining inverse transient analysis (ITAMP) [MP subscript] by iteratively limiting the search-space, to overcome problem of lack of identifiability when inverse problems involve hundreds of decision variables. The previously developed RMOC for pipeline condition assessment requires a dead-end boundary and an access point immediately upstream of the dead-end boundary, which is difficult to achieve in the field. The RMOC is significantly generalised in this thesis by relaxing this requirement. The new generalised RMOC utilises two pressure transducers placed at any two interior points along a pipeline to achieve pipeline condition assessment. The number and location of pressure transducers required to achieve optimum identifiability are also investigated. It has been demonstrated by the generalised RMOC that if the pipeline condition between the two pressure transducers is unknown, pressure measurements by two transducers are not able to uniquely identify the wave speed distribution along a pipeline using transient-based methods. To improve identifiability, given that the first two sensors are N reaches apart (i.e. N pipe segments in the pipeline model), the third sensor should not be placed at nodes that are separated from any of the first two sensors by an integer multiple of N reaches. The generalised RMOC also provides insight into why general ITA methods struggle to find good solutions as it illustrates that an infinite number of plausible solutions are possible for the almost same pressure trace if the wave speed values between transducers are allowed to vary and a third sensor is placed at an integer multiple location. The verification of ITAMP [MP subscript] and generalised RMOC by a field and a laboratory experiment, respectively, demonstrates that methods developed in this research can serve as a valuable screening tool for pipeline condition assessment in the real world.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201

Hydrogeological engineering approaches to investigate and characterize heterogeneous aquifers

This dissertation presents a compilation of five stand-alone manuscripts (Chapters 2 through 5 and Appendix A). Chapters 2 through 5 present hydrogeological analysis approaches, while Appendix A is utilized within the dissertation introduction as an example of a non-physically based modeling approach, albeit demonstrated on a non-hydrogeologically based application. Chapter 2 presents an inverse approach to decompose pumping influences from water-level fluctuations observed at a monitoring location. Chapter 3 presents an inferencing approach to identify effective aquifer properties at the interwell scale that can be applied to highly transient datasets. Chapter 4 introduces the use of a Markov-chain model of spatial correlation to an automated geostatistical inverse framework, demonstrating the approach on a 2-D two-stratigraphic-unit synthetic aquifer. Chapter 5 utilizes the inverse framework introduced in Chapter 4 to develop a stochastic analysis approach to identify the most plausible geostatistical model given the available data. The dissertation introduction reconciles these hydrogeological engineering approaches within the context of the current hydrogeological perspective, discussing where these approaches within the often conflicting goals of providing operational decision support based on modeling and advancing the science of hydrogeology beyond its current limitations

Nuclear Power Plants

This book covers various topics, from thermal-hydraulic analysis to the safety analysis of nuclear power plant. It does not focus only on current power plant issues. Instead, it aims to address the challenging ideas that can be implemented in and used for the development of future nuclear power plants. This book will take the readers into the world of innovative research and development of future plants. Find your interests inside this book

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

Hydrolink 2020/2. Hydraulic Transients

Topic: Hydraulic Transient

Hydroacoustic Modeling of a Cavitation Vortex Rope for a Francis Turbine

Hydraulic machines subject to off-design operation involve the presence of cavitating flow regimes in the draft tube. The cavitation vortex rope at part load conditions is described as an excitation source for the hydraulic system, and interactions between this excitation source and system eigenfrequency may result in resonance phenomena and induce a draft tube surge and electrical power swings. To accurately predict and simulate a part load resonance, proper modeling of the draft tube is critical. The presence of this cavitation vortex rope requires a numerical pipe element taking into account the complexity of the two-phase flow. Among the parameters describing the numerical model of the cavitating draft tube flow, three hydroacoustic parameters require a special attention. The first hydroacoustic parameter is called cavitation compliance. This dynamic parameter represents the variation of the cavitation volume with respect to a variation of pressure and implicitly defines the local wave speed in the draft tube. The second parameter corresponds to the bulk viscosity and is related to internal processes breaking a thermodynamic equilibrium between the cavitation volume and the surrounding liquid. The third parameter is the excitation source induced by the precessing vortex rope. The methodology to identify these hydroacoustic parameters is based on the direct link that exists between the natural frequency of the hydraulic system and the wave speed in the draft tube. First, the natural frequency is identified with the help of an external excitation system. Then, the wave speed is determined thanks to an accurate numerical model of the experimental hydraulic system. By applying this identification procedure for different values of Thoma number, it is possible to quantify the cavitation compliance and the void fraction of the cavitation vortex rope. In order to determine the energy dissipation induced by the cavitation volume, the experimental hydraulic system is excited at the natural frequency. With a Pressure-Time method, the amount of excitation energy is quantified and is injected into the numerical model. A spectral analysis of the forced harmonic response is used to identify the bulk viscosity and the pressure source induced by vortex rope precession. Thus, the identification of the hydroacoustic parameters requires the development of a new numerical draft tube model taking into account the divergent geometry and the convective terms of the momentum equation. Different numerical draft tube models are compared to determine the impact of convective and divergent geometry terms on identification of the hydroacoustic parameters. Furthermore, to predict the hydroacoustic parameters for non-studied operating conditions and to break free from the dependence upon the level setting of the Francis turbine, dimensionless numbers are proposed. They have the advantage of being independent from the selected numerical model and they define a behavior law of hydroacoustic parameters when the cavitation volume oscillates at resonance operating conditions. Finally, to investigate the stability operation of the prototype, the hydroacoustic parameters need to be transposed to the prototype conditions according to transposition laws. By assuming both Thoma similitude and Froude similitude conditions, transposition laws are developed and the hydroacoustic parameters are predicted for the prototype

Modeling and Optimal Operation of Hydraulic, Wind and Photovoltaic Power Generation Systems

The transition to 100% renewable energy in the future is one of the most important ways of achieving "carbon peaking and carbon neutrality" and of reducing the adverse effects of climate change. In this process, the safe, stable and economical operation of renewable energy generation systems, represented by hydro-, wind and solar power, is particularly important, and has naturally become a key concern for researchers and engineers. Therefore, this book focuses on the fundamental and applied research on the modeling, control, monitoring and diagnosis of renewable energy generation systems, especially hydropower energy systems, and aims to provide some theoretical reference for researchers, power generation departments or government agencies

A review of dynamic models and stability analysis for a hydro-turbine governing system

Industrial Ecolog

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