Ocean currents and tidal energy are significant renewable energy resources, and new concepts to extract this untapped energy have been studied in the last decades. Tethered undersea kite (TUSK) systems are an emerging technology which can extract ocean current energy. TUSK systems consist of a rigid-winged kite, or glider, moving in an ocean current. One proposed concept uses an extendable tether between the kite and a generator spool on a fixed or floating platform. As the kite moves across the current at high speeds, hydrodynamic forces on the kite tension the tether which extends to turn the generator spool. Since the TUSK system is a new technology, the process of bringing a TUSK design to commercial deployment is long and costly, and requires understanding of the underlying flow physics. The use of computational simulation has proven to be successful in reducing development costs for other technologies. Currently, almost all computational tools for analysis of TUSK systems are based on linearized hydrodynamic equations in place of the full Navier-Stokes equations. In this dissertation, the development of a novel computational tool for simulation of TUSK systems is described. The numerical tool models the flow field in a moving three-dimensional domain near the rigid undersea kite wing. A two-step projection method along with Open Multi-Processing (OpenMP) on a regular structured grid is employed to solve the flow equations. In order to track the rigid kite, which is a rectangular planform wing with a NACA-0012 airfoil, an immersed boundary method is used. A slip boundary condition is imposed at the kite interface to decrease the computational run- time while accurately estimating the kite lift and drag forces. A PID control method is also used to adjust the kite pitch, roll and yaw angles during power (tether reel-out) and retraction (reel-in) phases to obtain desired kite trajectories. A baseline simulation study of a full-scale TUSK wing is conducted. The simulation captures the expected cross-current, figure-8 motions during a kite reel-out phase where the tether length increases and power is generated. During the following reel-in phase the kite motion is along the tether, and kite hydrodynamic forces are reduced so that net positive power is produced. Kite trajectories, hydrodynamic forces, vorticity contours near the kite, kite tether tension and output power are determined and analyzed. The performance and accuracy of the simulations are assessed through comparison to theoretical estimations for kite power systems. The effect of varying the tether (and kite) velocity during the retraction phase is studied. The optimum condition for the tether velocity is observed during reel-in phase to increase the net power of a cycle. The results match theoretical predictions for tethered wind energy systems. Moreover, the effect of the tether drag on the kite motion and resulting power output is investigated and compared with the results of the baseline simulation. The kite drag coefficient increases by 25% while the effect of the tether drag is included into the baseline simulation. It affects the trajectory and the velocity of the kite. However, it has a small effect on the power generation for the proposed concept of TUSK system.

Intermittent nature of renewable energy sources like the wind and solar energy poses new challenges to harness and supply uninterrupted power for consumer usage. Though, converting energy from these sources to useful forms of energy like electricity seems to be promising, still, significant innovations are needed in design and construction of wind turbines and PV arrays with BS systems. The main focus of this research project is mathematical modelling and control of wind turbines, solar photovoltaic (PV) arrays and battery storage (BS) systems. After careful literature review on renewable energy systems, new developments and existing modelling and controlling methods have been analysed. Wind turbine (WT) generator speed control, turbine blade pitch angle control (pitching), harnessing maximum power from the wind turbines have been investigated and presented in detail. Mathematical modelling of PV arrays and how to extract maximum power from PV systems have been analysed in detail. Application of model predictive control (MPC) to regulate the output power of the wind turbine and generator speed control with variable wind speeds have been proposed by formulating a linear model from a nonlinear mathematical model of a WT. Battery chemistry and nonlinear behaviour of battery parameters have been analysed to present a new equivalent electrical circuit model. Converting the captured solar energy into useful forms, and storing it for future use when the Sun itself is obscured is implemented by using battery storage systems presenting a new simulation model. Temperature effect on battery cells and dynamic battery pack modelling have been described with an accurate state of charge estimation method. The concise description on power converters is also addressed with special reference to state-space models. Bi-directional AC/DC converter, which could work in either rectifier or inverter modes is described with a cost effective proportional integral derivative (PID/State-feedback) controller.

<p>In recent years, the accelerated deployment of renewable electricity generation resources, especially wind and photovoltaic (PV) solar, has added challenges to the operation and planning of the power grid. One of the challenges is that the variability of solar and wind power output may increase the variation of the load that must be followed by dispatchable resources and increase the ramping capacity needs. Moreover, the decision about the configuration of a PV solar generation systems has operational and economic implications because peak solar energy production does not always precisely occur when the wholesale electricity prices of the system are highest. Therefore, as the renewable capacity levels grow, it becomes increasingly important to examine the potential impacts on the system cost and portfolio of conventional generating units to respond to the intermittent nature of some renewable generation technologies. Three related analyses explored in this dissertation address some of the challenges of integrating utility-scale PV solar and wind projects into a power system using a case study for Indiana.</p> <p>The first analysis identifies the optimal azimuth and tilt angles of solar PV installations that alternatively maximize the annual electricity generation or the economic value of the resource. The economic implications of the configuration of solar PV installations within Indiana are estimated based on wholesale prices of electricity and simulated solar output for different combinations of angles and types of array installations. The results show that solar projects across the state would need to have azimuth angles within the 177 and 182 degrees range to obtain maximum annual energy and 180 to 190.5 degrees to maximize annual value, independently of their array types. Furthermore, southern and northwestern zones showed the highest impacts from using an optimal angle configuration of the solar installations. Nevertheless, on average, the benefits in annual electricity generated or economic value from their reconfiguration across the state are minor, amounting to less than one percent. </p> <p>The second analysis explores the effects of additional solar and wind power investments on the 2035 requirements for baseload and peaking generation capacity, the amount of energy supplied by various types of generation technologies and the costs of Indiana’s electric supply system. From a capacity planning and unit commitment/dispatch perspective, the results of this analysis indicated that with a portfolio that includes more solar and/or wind power generation, there would be need to add new peaking generation units. However, the total need for additional peaking resources declines as more renewables are added to the generation mix. Because Indiana still heavily relies on coal and other baseload resources to generate electricity, no new baseload capacity is required in the future. Generally, additions of PV solar and wind capacity amplify the variation in load net of renewable generation and create greater needs for ramping services from conventional units. However, results of the analysis show that the existing portfolio of conventional generation resources in Indiana would have sufficient operational flexibility to be able to accommodate ramping requirements even with PV solar and wind capacity penetration levels as high as 30% of total electricity generation. However, at those levels of renewables capacity there are a times during the year when the optimal operational strategy is to curtail solar and wind generation. From a technical perspective, the results indicated that larger thermal generating units are used more for load following and turned on and off (cycled) more frequently with the additional renewables than without them but mainly during days with low levels of demand and high levels of generation from renewable technologies. From the cost perspective, the results of the model support the idea that it would be cheaper in the long-term to invest in a combination of solar and wind generation resources than in solar generation resources alone. Moreover, the reductions in variable costs, driven by the zero variable cost added to the system by the additional solar and wind capacity, were not sufficient to outweigh the increases in capital costs regardless of the levels of capacity additions. </p> <p>For the third analysis, the proposed capacity expansion model was used to estimate the value of capacity of PV solar and PV solar in combination with wind capacity in terms of baseload/peaking resources from a deterministic system peak load reliability perspective and for various penetration levels of these resources. The capacity values of solar, which refer to the contribution of PV solar plants to reliably meeting the system peak demand, for all the wind capacity levels analyzed, fall as the amount of solar capacity increases. This is because as solar generation increases and closely coincides with the occurrence of the system peak load, there is a shift of the peak load net of renewable generation time to later afternoon hours, when solar installations begin to reduce their production, therefore decreasing their contribution to reliably meeting system peak demand. The calculated solar capacity values are between 2.7% and 67.3% of the corresponding solar nameplate capacity considering all zones and types of PV solar arrays in Indiana, and vary with the level of solar penetration. The range of values obtained are in line with the ones found in other studies using stochastic reliability-based methods.</p> <p>This dissertation contributes to the literature on the interaction between PV solar with other generation resources and to their economic, operational and policy implications. Furthermore, it provides another decision-making tool from a planning perspective for policymakers, utility companies and project developers.</p>

Doctor of Philosophy / Department of Chemical Engineering / Bin Liu / In the course of mitigating our dependence on fossil energy, it has become an urgent issue to develop unconventional and innovative technologies based on renewable energy utilization for fuels and chemicals production. Due to the lack of fundamental understanding of catalytic behaviors of the novel chemical compounds involved, the task to design and engineer effective catalytic systems is extremely challenging and time-consuming. One central challenge is that an intricate balance among catalytic reactivity, selectivity, durability, and affordability must be achieved pertinent to any successful design. In this dissertation, density functional theory (DFT), coupled with modeling techniques derived from DFT, is employed to gain insights into molecular interactions between elusive intermediates and targeted functional catalytic materials for novel electrochemical and heterogeneous catalytic processes. Two case studies, i.e., electroreduction of furfural and step-catalysis for cyclic ammonia production, will be discussed to demonstrate the capability and utility of DFT-based theoretical modeling toolkits and strategies. Transition metal cathodes such as silver, lead, and nickel were evaluated for furfuryl alcohol and 2-methylfuran production through detailed DFT modeling. Investigation of the molecular mechanisms revealed that two intermediates, mh6 and mh7 from mono-hydrogenation of furfural, are the key intermediates that will determine the product formation activities and selectivities. Nickel breaks the trends from other metals as DFT calculations suggested the 2-methylfuran formation pathway is most likely different from other cathodes. In this work, the Brønsted–Evans–Polanyi relationship, derived from DFT energy barrier calculations, has been found to be particularly reliable and computationally efficient for C-O bond activation trend predictions. To obtain the solvation effect on the adsorptions of biomass-derived compounds (e.g., furfural and glycerol), influence of explicit solvent was probed using periodic DFT calculations. The adsorptions of glycerol and its dehydrogenation intermediates at the water-platinum surface were understood via various water–adsorbate, water–water, and water–metal interactions. Interestingly, the bond-order-based scaling relationship established in solvent-free environment is found to remain valid based on our explicit solvent models. In the second case study, step-catalysis that relies on manganese’s ability to dissociate molecular nitrogen and as a nitrogen carrier emerges as an alternative route for ammonia production to the conventional Haber-Bosch process. In this collaborative project, DFT was used as the primary tool to produce the mechanistic understanding of NH3 formation via hydrogen reduction on various manganese nitride systems (e.g., Mn4N and Mn2N). Both nickel and iron dopants have the potential to facilitate NH3 formation. A broader consideration of a wide range of nitride configurations revealed a rather complex pattern. Materials screening strategies, supported by linear scaling relationships, suggested the linear correlations between NHx (x=0, 1, 2) species must be broken in the development of optimal step catalysis materials. These fundamental findings are expected to significantly guide and accelerate the experimental material design. Overall, molecular modeling based on DFT has clearly demonstrated its remarkable value beyond just a validation tool. More importantly, its unique predictive power should be prized as an avenue for scientific advance through the fundamental knowledge in novel catalysts design.

In recent years, the actuator disc approach which employs the Reynolds-Averaged Navier-Stokes (RANS) solvers has been extensively applied in wind and tidal energy field to estimate the wake of a horizontal axis turbine. This method is simpler to administer and requires moderate computational resources in modelling a tidal turbines rotor. Nonetheless, the use of actuator disc approximation in predicting the performance of tidal devices has been limited to studies involving an extremely small disc (e.g. rotor diameter of 0.1 meter). The drawback of a small scale actuator disc model is the overestimation of essential parameters such as the mesh density and the resolution of the vertical layers, making them impractical to be replicated in a regional scale model. Hence, this study aims to explore the methodology on implementation of the Three- Dimensional (3D) actuator disc-RANS model in an ocean scale simulation. Additionally, this study also aspires to examine the sensitivity of the applied momentum source term and its validity in representing full-size tidal devices. Nonetheless, before the effectiveness of an actuator disc in a regional model can be tested, tidal flow models for the area of interest needed to be set up first. This was essential for two reasons: (a) to ensure accurate hydrodynamic flow conditions at the deployment site were replicated, (b) to give confidence in the outputs produced by the regional scale actuator disc simulations, since in-situ turbine measurement data from a real deployment site were difficult to source. This research was undertaken in two stages; in the first stage, a numerical model which can simulate the tidal flow conditions of the deployment sites was constructed, and, in the second stage, the actuator disc method which is capable of modelling an array of real scale-sized tidal turbines rotors has been implemented. In the first stage, tidal flow simulations of the Pentland Firth and Orkney Waters (PFOW) were conducted using two distinct open-source software - Telemac3D, which is a finite element based numerical model, and Delft3D, which is a finite difference based model. Detailed methodologies in developing a 3D tidal flow model for the PFOW using both numerical models were presented, where their functionality, as well as limitations were explored. In the calibration and validation processes, both models demonstrated excellent comparison against the measured data. However, Telemac3D was selected for further modelling of the actuator disc considering the model's capability to perform parallel computing, together with its flexibility to combine both structured and unstructured mesh. In the second stage, to examine the actuator disc's accuracy in modelling a full size tidal device, the momentum source term was initially applied in an idealised channel study, where the presence of a 20-meter diameter turbine was simulated for both single and array configurations. The following parameters were investigated: (i) size of the unstructured mesh utilised in the computational domain, (ii) variation in disc's thickness, (iii) resolution of the imposed structured grid to represent turbine's enclosure, (iv) variation in the vertical layers, and (v) influence of hydrostatic and non-hydrostatic formulations on the models' outputs. It is to be noted that the turbine's support structures have not been included in the modelling. The predicted velocities and computed turbulence intensities from the models were compared against laboratory measurement data sourced from literature, where excellent agreement between the model outputs and the data from literature was observed. In essence, these studies highlighted the efficiency and robustness of the applied momentum source term in replicating the wake profiles and turbulence characteristics downstream of the disc, hence providing credence in implementing the actuator disc method for a regional scale application. Subsequently, the validated actuator disc method was applied to the Inner Sound region of the Pentland Firth to simulate arrays of up to 32 tidal turbine rotors. The wake development, flow interactions with the rotor arrays, and flow recovery at the Inner Sound region have been successfully mapped. Also, this study highlighted the importance of employing optimal numerical margins, specifically for the structured grid and horizontal planes, as both parameters were relevant in defining the disc's swept area. As published materials on the implementation of actuator disc approach within a regional scale model is still scarce, it was aspired that this work could provide some evidence, guidance and examples of suggested best practice in effort to fill the research gap in modelling tidal turbine arrays using the actuator disc approach.

No description available.

Community energy has drawn interest from the general public, policy makers and researchers in the UK over the last few years. Community energy projects, such as energy saving measures and renewable energy projects, are usually organised by civil society groups rather than commercial businesses. This DPhil research approaches community energy as local grassroots innovation and compares its development in two different countries, Finland and the UK. Key research question is: Why and how do community energy projects develop and how do they contribute to niche development? The thesis uses Sustainability Transitions studies literature, especially literature on Strategic Niche Management (SNM), as a theoretical framing, and empirical in-depth analysis of four community energy projects, two in the UK and two in Finland. The research examines how community energy projects develop in ‘niches'. Research findings highlight that motivations for projects include monetary savings, energy savings and climate change. Projects are developed by pre-existing community groups or groups that have come together to develop an energy project. Local embedding of community energy projects to each project's individual circumstances helps successful project delivery. Pre-existing skills and tacit knowledge such as the ability to seek information and fill in funding applications can aid success. Engagement with key stakeholders further shapes projects' aims and objectives. Community energy projects benefit from a clear leader who works with a supportive team. There is evidence of projects networking at the local and national level in the UK, while in Finland networking remains limited to the local area and projects often develop in isolation. Furthermore, there is a clear lack of active intermediary organisations in the Finnish context. Policy discourse at the government level can aid the attractiveness of community energy, while continued funding support encourages more people to get involved in projects in their local areas.

About 50% of the solar energy absorbed at the Earth’s surface is used to drive evaporation, a powerful form of energy dissipation due to water’s large latent heat of vaporization. Evaporation powers the water cycle that affects global water resources and climate. Critically, the evaporation driven water cycle impacts various renewable energy resources, such as wind and hydropower. While recent advances in water responsive materials and devices demonstrate the possibility of converting energy from evaporation into work, we have little understanding to-date about the potential of directly harvesting energy from evaporation. Here, we develop a theory of the energy available from natural evaporation to predict the potential of this ubiquitous resource. We use meteorological data from locations across the USA to estimate the power available from natural evaporation, its intermittency on varying timescales, and the changes in evaporation rates imposed by the energy conversion process. We find that harvesting energy from natural evaporation could provide power densities up to 10 W m-2 (triple that of present US wind power) along with evaporative losses reduced by 50%. When restricted to existing lakes and reservoirs larger than 0.1 km2 in the contiguous United States (excluding the Great Lakes), we estimate the total power available to be 325 GW. Strikingly, we also find that the large heat capacity of water bodies is sufficient to control power output by storing excess energy when demand is low. Taken together, our results show how this energy resource could provide nearly continuous renewable energy at power densities comparable to current wind and solar technologies – while saving water by cutting evaporative losses. Consequently, this work provides added motivation for exploring materials and devices that harness energy from evaporation.

Demand response (DR) is one of the integral mechanisms of today's smart grids. It enables consumer energy assets such as flexible loads, standby generators and storage systems to add value to the grid by providing cost-effective flexibility. With increasing renewable generation and impending electric vehicle deployment, there is a critical need for large volumes of reliable and responsive flexibility through DR. This poses a new challenge for the electricity sector. Smart grid development has resulted in the availability of large amounts of data from different physical segments of the grid such as generation, transmission, distribution and consumption. For instance, smart meter data carrying valuable information is increasingly available from the consumers. Parallel to this, the domain of data analytics and machine learning (ML) is making immense progress. Data-driven modelling based on ML algorithms offers new opportunities to utilise the smart grid data and address the DR challenge. The thesis demonstrates the use of data-driven models for enhancing DR from large consumers such as commercial and industrial (C&I) buildings. A reliable, computationally efficient, cost-effective and deployable data-driven model is developed for large consumer building load estimation. The selection of data pre-processing and model development methods are guided by these design criteria. Based on this model, DR operational tasks such as capacity scheduling, performance evaluation and reliable operation are demonstrated for consumer energy assets such as flexible loads, standby generators and storage systems. Case studies are designed based on the frameworks of ongoing DR programs in different electricity markets. In these contexts, data-driven modelling shows substantial improvement over the conventional models and promises more automation in DR operations. The thesis also conceptualises an emissions-based DR program based on emissions intensity data and consumer load flexibility to demonstrate the use of smart grid data in encouraging renewable energy consumption. Going forward, the thesis advocates data-informed thinking for utilising smart grid data towards solving problems faced by the electricity sector.

The UK government has committed to challenging climate change and renewable energy obligations to 2020 and beyond. The renewable electricity sector remains a key focus in meeting these targets, given the critical need to decarbonise the power sector in the longer term. This has led to an ambitious renewable electricity sectoral target of 30 percent of total electricity generation from renewable sources (RES-E) by 2020, corresponding to a deployment target of 35-40GW of installed capacity. In 2011, RES-E deployment stood at 12.3GW, resulting in the UK requiring 23-28GW of additional renewable electricity technology (RET) deployment in eight years. This requires a substantial amount of new RET capacity be adopted, the majority anticipated to come from a four large-scale (>5MW) technologies (onshore and offshore wind, biomass conversion and dedicated biomass). However, large-scale renewable deployment has consistently under-performed against previous targets and other policy objectives. There are a number of failures that historically and currently act as constraints to RET deployment. This thesis categories those constraints as either internal or external failures. Internal failures are due to the design of the subsidy mechanism used to promote renewable deployment (type of mechanism, how it operates, revenue risk, investment (lender) risk, subsidy support levels and mechanism complexity). External failures are those constraints out-with the direct control of the mechanism (planning, network, public participation and engagement and policy risk). These constraints need to be addressed. This thesis has carried out an evaluation of the current UK approach to large-scale RET deployment to 2020 and beyond by adopting a systemic framework approach to determine whether or not the UK will be successful in addressing the potential constraints – the internal and external failures – to deployment. The systemic approach is based on three key criteria regarding the potential constraints: a comprehensive set of constraints, analysed in-depth and taking into account the interaction of the constraints in a systemic fashion. In contrast, the government approach to dealing with these potential constraints has typically focused on failures in isolation; also government commissioned modelling and existing research does not take into account all of the internal and external failures and/or examine them in-depth. Critically, no research has analysed the systemic interactions. With this approach, this research aims to fill the gap in extant knowledge and analysis due to the absence of existing research meeting the key criteria. This thesis was carried out by a textual analysis of key policy documents and legislation that form the basis of the UK government’s current approach to addressing the barriers to RET deployment. The method of inquiry utilised here is that of the qualitative research approach. The results show that there are significant systemic interactions between the internal and external failures (internal>internal; external>external; and internal to external and vice versa). There are also a number of feedbacks, specifically between grid>planning and public participation and engagement>planning. This creates systemic imbalances and unresolved tensions between the constraints. Importantly, the systemic interactions impact disproportionately on the key RETs, with a particular emphasis on onshore and offshore wind. By not addressing potential constraints from a systemic perspective, the current UK approach discriminates in favour of a system highly dependent on large-scale developments, of a few select RETs by a limited number of developers of a particular type (typically ex-utility, large-scale). This limits the focus on social and behavioural issues, particularly in terms of participation and engagement in ownership, decision-making and reducing the role of small-scale, independent and community group participation. In conclusion, under the current approach, decisions will be made on a separate ad-hoc basis leading to continual reform and adjustment with less clarity of where the risks lie. Increasing deployment year-by-year will only accumulate and intensify the potential constraints with limited options to address this. Effectively, government can only buy or control its way out of the constraints. In contrast, a systemic approach offers policy makers a way out of this. By providing an overview of the system and identification of systemic interactions in an early and novel way, this approach offers the opportunity for pragmatic decision-making at the systemic level leading to more predictable routes to solving problems via focused reforms, thus mitigating risks to a greater extent and redefining the system in a more optimal and resilient way. In other words, it allows government to connect the dots in addressing potential constraints to deployment.