Probabilistic design optimization of horizontal axis wind turbine rotors

Considerable interest in renewable energy has increased in recent years due to the concerns raised over the environmental impact of conventional energy sources and their price volatility. In particular, wind power has enjoyed a dramatic global growth in installed capacity over the past few decades. Nowadays, the advancement of wind turbine industry represents a challenge for several engineering areas, including materials science, computer science, aerodynamics, analytical design and analysis methods, testing and monitoring, and power electronics. In particular, the technological improvement of wind turbines is currently tied to the use of advanced design methodologies, allowing the designers to develop new and more efficient design concepts. Integrating mathematical optimization techniques into the multidisciplinary design of wind turbines constitutes a promising way to enhance the profitability of these devices. In the literature, wind turbine design optimization is typically performed deterministically. Deterministic optimizations do not consider any degree of randomness affecting the inputs of the system under consideration, and result, therefore, in an unique set of outputs. However, given the stochastic nature of the wind and the uncertainties associated, for instance, with wind turbine operating conditions or geometric tolerances, deterministically optimized designs may be inefficient. Therefore, one of the ways to further improve the design of modern wind turbines is to take into account the aforementioned sources of uncertainty in the optimization process, achieving robust configurations with minimal performance sensitivity to factors causing variability. The research work presented in this thesis deals with the development of a novel integrated multidisciplinary design framework for the robust aeroservoelastic design optimization of multi-megawatt horizontal axis wind turbine (HAWT) rotors, accounting for the stochastic variability related to the input variables. The design system is based on a multidisciplinary analysis module integrating several simulations tools needed to characterize the aeroservoelastic behavior of wind turbines, and determine their economical performance by means of the levelized cost of energy (LCOE). The reported design framework is portable and modular in that any of its analysis modules can be replaced with counterparts of user-selected fidelity. The presented technology is applied to the design of a 5-MW HAWT rotor to be used at sites of wind power density class from 3 to 7, where the mean wind speed at 50 m above the ground ranges from 6.4 to 11.9 m/s. Assuming the mean wind speed to vary stochastically in such range, the rotor design is optimized by minimizing the mean and standard deviation of the LCOE. Airfoil shapes, spanwise distributions of blade chord and twist, internal structural layup and rotor speed are optimized concurrently, subject to an extensive set of structural and aeroelastic constraints. The effectiveness of the multidisciplinary and robust design framework is demonstrated by showing that the probabilistically designed turbine achieves more favorable probabilistic performance than those of the initial baseline turbine and a turbine designed deterministically.

Geothermal district heating networks: modelling novel operational strategies incorporating heat storage

The value of integrating a heat storage into a geothermal district heating system has been investigated. The behaviour of the system under a novel operational strategy has been simulated focusing on the energetic, economic and environmental effects of the new strategy of incorporation of the heat storage within the system. A typical geothermal district heating system consists of several production wells, a system of pipelines for the transportation of the hot water to end-users, one or more re-injection wells and peak-up devices (usually fossil-fuel boilers). Traditionally in these systems, the production wells change their production rate throughout the day according to heat demand, and if their maximum capacity is exceeded the peak-up devices are used to meet the balance of the heat demand. In this study, it is proposed to maintain a constant geothermal production and add heat storage into the network. Subsequently, hot water will be stored when heat demand is lower than the production and the stored hot water will be released into the system to cover the peak demands (or part of these). It is not intended to totally phase-out the peak-up devices, but to decrease their use, as these will often be installed anyway for back-up purposes. Both the integration of a heat storage in such a system as well as the novel operational strategy are the main novelties of this thesis. A robust algorithm for the sizing of these systems has been developed. The main inputs are the geothermal production data, the heat demand data throughout one year or more and the topology of the installation. The outputs are the sizing of the whole system, including the necessary number of production wells, the size of the heat storage and the dimensions of the pipelines amongst others. The results provide several useful insights into the initial design considerations for these systems, emphasizing particularly the importance of heat losses. Simulations are carried out for three different cases of sizing of the installation (small, medium and large) to examine the influence of system scale. In the second phase of work, two algorithms are developed which study in detail the operation of the installation throughout a random day and a whole year, respectively. The first algorithm can be a potentially powerful tool for the operators of the installation, who can know a priori how to operate the installation on a random day given the heat demand. The second algorithm is used to obtain the amount of electricity used by the pumps as well as the amount of fuel used by the peak-up boilers over a whole year. These comprise the main operational costs of the installation and are among the main inputs of the third part of the study. In the third part of the study, an integrated energetic, economic and environmental analysis of the studied installation is carried out together with a comparison with the traditional case. The results show that by implementing heat storage under the novel operational strategy, heat is generated more cheaply as all the financial indices improve, more geothermal energy is utilised and less fuel is used in the peak-up boilers, with subsequent environmental benefits, when compared to the traditional case. Furthermore, it is shown that the most attractive case of sizing is the large one, although the addition of the heat storage most greatly impacts the medium case of sizing. In other words, the geothermal component of the installation should be sized as large as possible. This analysis indicates that the proposed solution is beneficial from energetic, economic, and environmental perspectives. Therefore, it can be stated that the aim of this study is achieved in its full potential. Furthermore, the new models for the sizing, operation and economic/energetic/environmental analyses of these kind of systems can be used with few adaptations for real cases, making the practical applicability of this study evident. Having this study as a starting point, further work could include the integration of these systems with end-user demands, further analysis of component parts of the installation (such as the heat exchangers) and the integration of a heat pump to maximise utilisation of geothermal energy.