Optimization of wind farm layout is an expensive and complex task involving several engineering challenges. The layout of any wind farm directly impacts profitability and return of investment. Several software optimization modules in line with wind farm design tools in industry is currently attempting to place the turbines in locations with good wind resources while adhering to the constraints of a defined objective function. Assessment of these software tools needs to be performed clearly for assessing different tools in wind farm layout design process. However, there is still not a clear demonstration of benchmarking and comparison of these software tools even for simple test cases. This work compares two different optimization software namely openWind and WindPRO commercial software tools mutually.

abstract: Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed. / Dissertation/Thesis / Ph.D. Mechanical Engineering 2013

Climate Change and Energy Security have been dominating the global energy agenda. In response the United Kingdom (UK) set a target of reducing emissions by 80% by 2050, and have accepted the European Directive to produce 15% of energy by renewable resources by 2020. Despite doubts in the last few years, the UK are on track to not only meet but exceed the target placed upon them, which sets them in good light for the long term 2050 emission reduction. This research investigated the barriers in the industry such as the planning process delays and public perception. Findings suggested that negative public perceptions still remain, with onshore projects gaining more attention than offshore projects. The planning system whilst showing an improvement in overall decision time still showed signs of delays in the pre-examination process. The research also highlighted signs of a predicted development plateau in onshore schemes, with approved capacity rates slowing in the year 2014. Furthermore, the political structure surrounding wind energy has become fragile, following recent comments from the Conservative party, suggesting they will see an end to onshore wind should they gain election in 2015. Therefore despite positive steps taken by the UK towards renewable energy targets, the future of wind energy is not certain.

The threatening impacts of climate change are driving a global revolution towards cleaner sources of energy. In South Africa, strategies for energy security and emissions reduction are focusing on renewables, wind energy being one of the most promising ones. The construction of wind energy projects has attached limitations in the identification of suitable areas that respect the environment and are technically feasible. Herein, site selection criteria has been grouped into the Site Identification group (SIG), and the Resource & Energy Generation group (R&E). The SIG incorporates technical, environmental and restricted criteria within a spatial frame; while R&E accounts for the wind resource, estimated energy generation and fitting to energy demand profiles under a spatial-temporal frame. The average wind resource is usually found to be analysed together within the technical factors to determine the feasibility of a site; however for this study, a different and independent treatment of the wind resource and its energy generation profile was undertaken. It consists of evaluating the unique hourly wind power profile of each site against the energy consumption profile for the same period. The need is for selecting places with the smallest variation between the electricity produced and the electricity demanded. The Production to Demand Difference (PDD) has been chosen as the indicator of such variations. Therefore, the new purpose is to identify spots where the combination of the PDD and the results from the SIG become smaller with time. The Mean Difference (MD) is also taken into account to obtain further information regarding the trends of the differences. Geoprocessing, overlays and mathematical combinations of datasets are all performed under a GIS environment. / Dissertation (MEng)--University of Pretoria, 2015. / tm2015 / Chemical Engineering / MEng / Unrestricted

Much research has been done on the effects of distributed generation on network characteristics. However, little research has been done on the effects of this distributed generation on current network protection schemes. An IPP has approached a South African municipality regarding the connection of a wind farm that would be connected to the municipality’s existing grid. This presented a unique opportunity to simulate and study the impact and effect that this wind farm would have on a real-life network in terms of network operation and protection schemes. This also presents the possibility of connecting the wind farm in a different configuration, possibly resulting in better network operation at a lower cost. The network optimisation in this research was done using the probability-based incremental learning (PBIL) and differential evolution (DE) optimisation techniques. These algorithms were programmed and modelled according to the desired IPP wind farm requirements using the MATLAB and MATPOWER simulation packages. The networks used in these algorithms were modelled in the text-based MATPOWER format. This research goes on to study a modified 14-bus IEEE test network in terms of network characteristics and protection performance so that an idea of the performance of the optimisation algorithms can be obtained. Protection data for the IEEE network was not available. The network was thus graded for use in this study. The research then continues to model the existing and proposed network configuration, and proposes various other points of connection to the municipal network using the PBIL and DE algorithms. These studies were conducted using the DIgSILENT PowerFactory simulation package, with the networks and protection data being modelled in this package. Network and protection performance results were recorded for each case in both networks under study. The results show that in the case of the modified IEEE network, the DE algorithm provides a better solution in terms of improving power losses while the PBIL algorithm provides a better solution in terms of improving the voltage profile. In the case of the municipality network, the DE algorithm provides the best performance, with the DE result managing to reduce power losses by 83.89% compared to the current and proposed network configurations. The overall voltage profile was also seen to improve by over 23%. The research also found that the change in fault level for the various cases are minimal. This is due to the limitation in fault current contribution imposed by the use of an inverter system connecting the wind farm to the grid. This means that, as the results shows, network grading is not very much affected by the addition of the wind farm connections. However, it is seen that the municipal network is not optimally graded in the base case. Finally, it is also seen that, though not often used in research, the MATPOWER package works well as a network simulation tool. A costing analysis was also conducted and shows that the DE solution is the most cost-effective solution, in addition to being the best-performing solution. The study recommends that the results produced by the DE algorithm be implemented instead of the proposed implementation. The municipal network should also be regraded and new protection settings should be implemented.

Wind farm layout optimization can greatly improve wind farm performance. However, past wind farm design has been limited in several ways. Wind farm design usually assumes that all the turbines throughout the farm should be exactly the same. Oftentimes, the location of every turbine is optimized individually, which is computationally expensive. Furthermore, designers fail to consider turbine loads during layout optimization. This dissertation presents four studies which provide partial solutions to these limitations and greatly improve wind farm layout optimization. Two studies explore differing turbine designs in wind farms. In these studies, Wind farm layouts are optimized simultaneously with turbine design. We found that for small rotor diameters and closely spaced wind turbines, wind farms with different heights have a 5–10% reduction in cost of energy compared to farms with all the same turbine height. Coupled optimization of turbine layout and full turbine design results in an 2–5% reduction in cost of energy compared to optimizing sequentially for wind farms with turbine spacings of 8.5–11 rotor diameters. Wind farms with tighter spacing benefit even more from coupled optimization. Furthermore, we found that heterogeneous turbine design can produce up to an additional 10% cost of energy reduction compared to wind farms with identical turbines throughout the farm, especially when the wind turbines are closely spaced. The third study presents the boundary-grid parameterization method to reduce the computational expense of optimizing wind farms. This parameterization uses only five variables to define the layout of a wind farm with any number of turbines. For a 100 turbine wind farm, we show that optimizing the five variables of the boundary-grid method produces wind farms that perform just as well as farms where the location of each turbine is optimized individually, which requires 200 design variables. The presented method facilitates the study for both gradient-free and gradient-based optimization of large wind farms. The final study presents a model to calculate fatigue damage caused by partial waking on a wind turbine which is computationally efficient and can be included in wind farm layout optimization. Compared to high fidelity simulation data, the model accurately predicts the damage trends of various waking conditions. We also perform a wind farm layout optimization with the presented model in which we maximize the annual energy production of a wind farm while constraining the damage of each turbine. The results of the optimization show that the turbine damage can be constrained with only a very small sacrifice of less than 1% to the annual energy production.

With the growing demand for electricity, renewable sources of energy have garnered a lot of support from all quarters. The problem with depending on these renewable sources is that the output from them is independent of the demand. Storage of electricity gives us an opportunity to effectively manage and balance the supply and demand of electricity. Fuel cells are a fast developing and market capturing technology that presents efficient means of storing electricity in the form of hydrogen. The aim of this research is to study the impact of integrating hydrogen fuel cell storage system with a wind farm to improve the reliability of the grid for allowing higher penetration of renewable energy sources in the power system. The installation of energy storage systems strongly depends on the economic viability of the storage system. We identified four types of fuel cells that could be used in a hydrogen fuel cell storage system. We bring together a range of estimates for each of the fuel cell systems for the economic analysis that is targeted towards the total capital costs and the total annualized costs for the storage system for individual applications like rapid reserve and load shifting. We performed sensitivity analysis to determine the effect of varying the rate of interest and cost of fuel cell on the total annualized cost of the storage system. Finally, we compared the costs of hydrogen based storage system with other storage technologies like flywheel, pumped hydro, CAES and batteries for the individual application cases.

Modern power systems are characterized by an increasing penetration of renewable energy generating units. These aim to reduce the carbon emissions in the environment by replacing conventional energy generating units which rely on fossil fuels. In this new power systems composition, wind generators (WGs) dominate, being one of the largest and fastest-growing sources of renewable energy production. Nevertheless, their unpredictable and highly volatile power output hinders their efficient and secure large-scale deployment, and poses challenges for the transient stability of power systems. Given that, we identify two challenges in the operation of modern power systems: rendering WGs capable of reguating their power output while securing transient stabilization of conventional synchronous generators (SGs). This dissertation makes several contributions for effectively dealing with these major challenges by introducing new distributed control techniques for SGs, storage devices and state-of-the-art (SoA) WGs. Initially, this dissertation introduces a novel nonlinear control design which is able to coordinate a storage device and a SG to attain transient stabilization and concurrent voltage regulation on their terminal bus. Thereafter, it proposes control designs that SoA WGs can adopt to effectively regulate their power out- put to meet local or group objectives. In this context, the rst control design is a decentralized nonlinear energy-based control design, that can be employed by a wind double-fed induction generator (DFIG) with an incorporated energy storage device (namely a SoA WG) to regulate its power output by harnessing stored energy, with guaranteed performance for a wide-range of operating conditions. Recognizing that, today, albeit wind farms (WFs) are comprised of numerous WGs which are sparsely located in large geographical areas, they are required to respond rapidly and provide services to the grid in an efficient, reliable and timely fashion. To this end, this dissertation proposes distributed control methods for power output regulation of WFs comprised of SoA WGs. In particular, a novel distributed control design is proposed, which can be adopted by SoA WGs to continuously, dynamically and distributively self-organize and control their power outputs by leveraging limited peer-to-peer communication. By employing the proposed control design, WGs can exploit their storage devices in a fair load-sharing manner so that their total power output tracks a total power reference under highly dynamical conditions. Finally, this dissertation proposes a distributed control design for wind DFIGs without a storage device, the most common type of WGs deployed today. With this control design, wind DFIGs can dynamically, distributively and fairly self-dispatch and adjust the power they extract from the wind for the purpose of their total power tracking a dynamic reference. The effectiveness of the control designs proposed in this dissertation is illustrated through several case studies on a 3-bus power system and the IEEE 24-bus Reliability Test System.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Anil Pahwa / Shelli K. Starrett / Analysis of power system voltage stability has practical value in increasing wind penetration levels. As wind penetration levels increase in power systems, voltage stability challenges arise due to locating wind resources far away from load centers. This dissertation presents several different voltage stability methods for sizing new wind farms. Power system wind penetration levels depend on the available voltage stability margins (VSMs) of the existing power system and system load characteristics. Three new iterative methods have been developed to maximize wind penetration level in weak power systems based on systems’ VSMs. The first two methods use an iterative approach for increasing the size of each wind farm until reaching the collapse point. Wind farms with less negative impact on system VSMs are sized larger than others. A third wind farm sizing method has been developed using modal analysis in conjunction with the traditional voltage stability method (Q-V method). Wind farms are placed at buses in the power system which have the lowest negative impact on voltage instability modes (strong wind injection buses). By placing the wind farms at the strongest wind injection buses, higher amounts of wind power can be injected into the power system. To further increase wind penetration in weak power systems, two additional techniques are introduced and applied to the western Kansas power system. The first technique uses modes of voltage instability to place voltage support equipment like static var compensators at locations in the power system where they provide the needed reactive power support for increasing levels of wind penetration. The second technique uses the fact that wind patterns at a wind farm site may rarely allow the wind farm to produce its maximum capacity during the peak loading hours. Wind farm maximum sizes can be increased above their maximum voltage stable size limit without driving the power system into becoming voltage unstable. Preventing voltage collapse for the additional increases in wind farm sizes is accomplished by disconnecting some wind turbines inside the wind farm during critical times to reduce its power output to a voltage stable level.

The offshore wind potential of the Caribbean Sea has barely been exploited. Currently, the offshore wind power industry in Latin America and the Caribbean region is still at very early stages, leaving aside an important resource that otherwise could contribute to satisfy the growing energy demand of the zone. In this study the possibilities arising from a massive exploitation of the wind resource in the Caribbean Sea are assessed. The objective is to investigate if the resources contained in it would be sufficient to satisfy the energy demand of Latin America and the Caribbean, which is foreseen to be about 1900 TWh/year by 2020. To address this question, the “Infinite wind farm” concept is used as a simple way to model the meteorological behaviour and the wind speed in the area. The model is utilized in combination with the bathymetric data of the Caribbean Sea and with a simple economic analysis, to evaluate what the requirements to satisfy the energy demand would be in terms of area, number of turbines, and levelized cost of energy (LCoE). The assessment is performed utilizing different turbine sizes, and inter-turbine separations to find the combination that minimizes the LCoE. It is found that the energy demand of Latin America and the Caribbean could be satisfied using only 125000 km2 (4.5% of the total Caribbean Sea area) of waters shallower than 25m at a cost of 69 €/MWh, if the turbines were separated 6.5D from one another and if they had a rotor diameter of 250m. In that case, 47760 turbines should be installed using only conventional monopile foundations.