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It is proposed to use advancements in Large Scale Particle Image Velocimetry (LSPIV), such as improved charge-coupled device in cameras, unmanned aerial vehicles, and faster algorithms, for a non-invasive river water surface velocity measurement to assess potential hydrokinetic turbine sites. The approach will compare results to an Acoustic Doppler Velocimeter (ADV). Being able to measure the water surface velocity using the proposed method allows the use of a low-cost and simple approach to determine hydrokinetic sites suitable for turbine deployment for electrification of remote communities. The research tests were conducted in a water tunnel and at the Canadian Hydrokinetic Turbine Testing Center located in Winnipeg River using cameras and a drone with results compared to an ADV. Two LSPIV simulation software’s PIVlab and OpenPIV were used to analyze the water surface velocity captured in a water tunnel and at the Canadian Hydrokinetic Turbine Testing Center. The results of the LSPIV software analysis with optimized average velocity data results from PIVlab are within ±0.1 m/s from the average ADV velocity results. In addition, optimized velocity data from PIVlab show vector results moved closer to the ADV measured water surface velocity and resulted with fewer fluctuations after the erroneous data was removed. Thus, a non-invasive way of analyzing water surface velocity by flying a drone overhead capturing the water surface and using LSPIV software such as PIVlab and OpenPIV to extract data from the captured images could replace conventional invasive methods of water surface velocity measurements for site assessments so long as these are done in good weather, minimal wind and water surface ripples are clear, detailed and defined.

Hydrokinetic turbines present an opportunity for generating renewable energy sustainably in support of microgrids. This research examines the performance and environmental impact of a 25-kW New Energy vertical axis hydrokinetic river turbine under freewheeling conditions, focusing on flow and turbulence behavior. Field measurements of flow velocity at the Canadian Hydrokinetic Turbine Test Center on the Winnipeg River are measured using an acoustic Doppler current profiler and an acoustic Doppler velocimeter. Measurements are taken at various distances downstream of the turbine, from 1 to 17 turbine diameters, to analyze turbulence intensity, turbulent kinetic energy, and mean velocity profiles. The results indicated that turbulence intensity was highest near the turbine, with peaks at the centerline reaching 84% in the first acoustic Doppler current profiler test and 119% in the second, while acoustic Doppler velocimeter measurements showed 41% and 55%, respectively. As expected, turbulence levels gradually decreased with increasing distance from the turbine and are documented. Additionally, the TKE values exhibited a similar trend, demonstrating significant energy dissipation and flow stabilization further downstream. The mean velocity profiles revealed the maximum velocity deficit near the turbine, which gradually recovered with distance. River in-situ values measured do not compare favorably with scaled turbine water tunnel studies. This comprehensive analysis, comparing acoustic Doppler current profiler and acoustic Doppler velocimeter data, provides valuable insights into the wake dynamics and turbulence characteristics of vertical-axis turbines, which are required for optimizing turbine efficiency and assessing environmental impacts.

Seasonal velocity variations can significantly impact total energy delivered to microgrids produced by river hydrokinetic turbines. These turbines typically use a diffuser to increase the velocity at the rotor section, adding weight and increasing deployment and retrieval costs. There is a need for practical solutions to improve the capacity factor of such turbines for remote communities. Part of the solution is addressed by developing multiple turbine rotors that can be interchanged to match seasonal velocity variations and thereby eliminate the need for shrouds to simplify the design and reduce costs. The proposed approach employs different rotor sizes to address seasonal river velocity changes, modifying the turbine power curve to increase the yearly river turbine capacity factor. A turbine design that can be surfaced using boats available in remote communities is used to allow 2 blades rotor changes. BladeGen ANSYS Workbench is used to design the three rotors of decreasing size for free stream velocities of 1.6, 2.2, and 2.8 m/s. For each hydrokinetic turbine rotor, the 3D simulation is applied to reduce aerodynamic losses and target a coefficient of performance of up to 45%, by optimizing the blade shape and rotor aerodynamic parameters. Mechanical stress analyses determine the maximum displacement and blade stress for stainless steel and composite materials. Numerical results were compared to experimental results: the pressure coefficient against the tip speed ratio demonstrated good agreement with the experimental data. Based on the simulations, the three rotor efficiencies varied from 43% to 45% at a TSR of 4, the point at which the maximum pressure coefficient was observed in numerical and experimental results, while the power output varied from 5.4 to 5.6 kW for the three velocities investigated. Results show that it is possible to significantly increase turbine capacity factors by interchanging rotors to account for seasonal velocity variations in rivers.

Drone systems are being used everyday for many applications including delivery of goods and surveillance systems, which require a reliable navigation system to allow for a safe and successful mission. Global Navigation Satellite Systems have been the main means of navigation for decades, however, regions with poor GNSS coverage, such as the Arctic or urban centers, are challenging environments to navigate. In this thesis, the design and implementation of a low-cost portable beacon system that can provide position information using an extended Kalman filter (EKF) is presented. For the beacon system, an angle beacon prototype and two range beacon prototypes, one based on the received signal strength and the other based on the signal’s time of flight, were developed. The positioning performance of the EKF and beacons system in different scenarios was evaluated using Matlab simulations. The simulation results indicate that the range beacons offered the best positioning performance compared to the angle beacons or a mixture of both. Additionally, particle swarm optimization was used to optimally place an additional range/angle beacon, improving the overall system performance. Finally, the integrated system was tested in indoor and outdoor scenarios and the system output was compared with the ground truth data. The experimental tests resulted in a minimum error of 10.1 cm and 31.8 cm for indoor and outdoor tests, respectively. The steady state error was in orders of ≈ ±25 cm for the indoor tests and ≈ ±40 cm for the outdoor tests. Overall, the custom beacon designs provided reliable performance for drone navigation. With future hardware improvements, the system could be a viable option for low-cost portable navigation systems.

Four sensors embedded in a tear-shaped buoy are investigated to measure non-instantaneous river velocity to eliminate seasonal elements that can damage velocity instruments when deployed over a long-term period for measurements at energetic sites. Velocity data is required to predict the 95% confidence interval of the power production from hydrokinetic turbines at potential river sites. This novel measurement buoy measures flow velocities inferred from the tilt angle of the buoy using an inertial measurement unit sensor, tension on the wire rope connecting the buoy to the riverbed anchor using a strain gauge sensor, vortex-induced vibration of the mooring line also using an inertial measurement unit sensor, and sound of the water flowing around the buoy using a microphone sensor. The four sensors are embedded in a prototype buoy and tested in a laboratory water tunnel at flow velocities from 0.1 to 1 m/s. The laboratory measurement data is analyzed to find the relationship of each sensor to water velocity based on a phenomenon-based approach. The data from the sensors displayed a nonlinear relationship with flow velocity. Calibration curves were developed for each sensor to measure the flow velocity. The most accurate measurement method is tilt angle method. The average percent error in accuracy for estimation of flow velocities from 0.5 to 1 m/s from tilt angle data is 0.5 %. Each of the sensors embedded in the buoy is critically assessed for its validity to estimate the long-term river velocity at energetic river sites to determine the power production from potential hydrokinetic turbine sites.

Due to excessive fossil fuels consumption, the concentration of carbon dioxide is predicted to be approximately 500 ppm by 2050, impacting global biodiversity for generations. Increasing the percentage of recent solar energy use—sun, wind, hydro, and biomass—to address our global energy needs is of fundamental importance. With buildings representing nearly 38% of global emissions, solar energy can contribute to reduce impact: increasing the productive use of solar insolation from building grounds using reflective tracking mirrors, referred to as Sunflower, is a critical component. To this effect, a Sunflower model is developed from first principles to evaluate the productive use of low-level solar magnification from building grounds and rooftops. This model predicts the solar insolation incident onto a user chosen target with many Sunflowers to contribute to net-zero buildings. The model inputs are flexible, for example, change in number of Sunflower mirrors and their target specifications, including seasonal relocation to optimally reduce energy demand in a building, are part of user inputs. The model utilizes a single ray-tracing method to evaluate the solar irradiation redirected onto the building using low-cost solar tracking mirrors. This model developed in Python is based on solar angles and weather data to calculate the redirected hourly solar flux onto a chosen target. Using NREL’s Solartrace program based on the Monti-Carlo method, model results are validated within an error of 2.35%. The Sunflower model is then applied to predict the displaced energy in an outdoor pool heating application. The pool heating approach using Sunflower bypasses second law inefficiencies as the pool is heated by the irradiations directly from sun without the use of an intermediate thermal fluid. Multiple case scenarios are established to evaluate the optimal mirror angles to increase the solar intensity for a given seasonal configuration. The Sunflower model predictions for appl

The optimization of turbine array layouts for maximized power generation is an important and challenging problem in the fields of wind and hydrokinetic energy. Since multi-turbine simulations with resolved rotor geometries are beyond the capacity of modern computers, turbine arrays are generally modelled by replacing each rotor with a permeable, zero-thickness momentum sink, known as an actuator. Although actuator models are computationally inexpensive, they do not easily replicate the wake structures observed in experiments and foil-resolved simulations. With the aim of developing an alternative approach for modelling turbine interactions, the following study explores the potential of a deep learning-based turbine modelling technique. In the proposed method, a Convolutional Neural Network (CNN) is trained to predict the solutions of a foil resolved, two-dimensional (2-D) Reynolds-Averaged Navier-Stokes (RANS) model, for a vertical-axis hydrokinetic turbine operating in free-stream velocities between 1 and 3 m/s. Based on the boundary conditions of free-stream velocity and rotor position, the flow gradients of x-velocity, y-velocity, pressure, and turbulent viscosity are predicted, in addition to the angular velocity of the rotor. Training and testing data are generated from the solutions of five RANS simulations, with free stream velocities of 1, 1.5, 2, 2.5 and 3 m/s. Three trained CNN models are produced to evaluate the effects of (1) the dimensions of the training data, and (2) the number of simulations that are used as training cases. Smaller data sizes were found to improve prediction accuracy overall, while diminishing the computational cost associated with the generation of data from RANS solutions. Dramatic improvements in prediction accuracy were achieved by increasing the number of training cases from two to three. For the best achieved CNN model, the variables of x-velocity, y-velocity, pressure, turbulent viscosity, and angular velocity were predicted w

Incorporation of renewable sources and energy storage can contribute to reduce fuel consumption in diesel generation-based remote off-grid power systems. This thesis proposes methodologies for improved management of available generating and storage resources to reduce costs and emissions and investigates the coordination of energy management with power management functions essential for stable operation of the isolated power systems. Firstly, a test system is developed considering a case of retrofitting an existing diesel power system with photovoltaic (PV) generation and battery energy storage. A sizing study conducted using HOMER software with weather and load data for Northern Canada resulted in a PV-Diesel-Battery topology with high PV penetration levels. Next, the energy management functions are developed incrementally in three steps. First, a computationally efficient energy management system (EMS) is implemented to optimize the system operation while incorporating multiple operational requirements essential to remote power systems. Then, a demand response (DR) model that requires minimal bi-directional interactions and therefore implementable without sophisticated communication infrastructure is developed and integrated with the EMS. Thirdly, a computationally efficient two-stage model predictive control process is developed to compensate for forecast uncertainties. Finally, the power management functions necessary to achieve a logical real-time operation are implemented and coordinated with the energy management functions in a hierarchical architecture. Also, an operation evaluation framework is suggested to assess the viability of the optimum operation routines under dynamic conditions. After adding PV and energy storage to an existing diesel-only system and optimizing the operation with the DR integrated EMS, over 60% cost and emission reductions are achieved for a representative summer day compared to the diesel-only operation. The cost and emission reduc

The effects of nozzle orientation on the mixing and turbulent characteristics of elliptical free triple and twin jets were studied experimentally. The experiments were conducted using modified contoured nozzles with a sharp linear contraction. The centers of the nozzle pair had a separation ratio of s/d = 5.5 for twin jets and s/d = 4.1 for triple jets. For the twin-jet system, two nozzle configurations were tested, twin nozzles oriented along the minor plane (Twin_Minor) and twin nozzles oriented along the major plane (Twin_Major) and the results were compared with single jet. For the triple-jets system, three nozzle configurations were tested. The first configuration had each nozzle oriented along the minor plane (3_Minor), the next had two nozzles oriented along the minor plane and one along the major plane (Min_Maj_Min) and the last configuration had one nozzle oriented along the minor plane and two along the major plane (Maj_Min_Maj). In each case, the Reynolds number based on the maximum jet velocity and the equivalent diameter was 10,000. A planar particle image velocimetry system was used to measure the velocity field in the jet symmetry plane. The velocity decay, jet spread, merging point, combined point and potential core length were used to characterize the effects of nozzle orientation on the mixing performance. For both twin jets and triple jets, it was observed that the velocity decay rate is not sensitive to nozzle orientation. However, the spread rate was approximately 35% higher in the minor plane for each configuration. In addition, the potential core length for 3_Minor was approximately 42% shorter than Twin_Minor. Furthermore, contour plots of swirling strength, Reynolds shear stress and turbulent intensities revealed significant differences between the minor and major plane for both twin and triple jets. One-dimensional plots revealed that jets approached self-similarity at a faster rate in the major axis.

A hydrokinetic turbine extracts energy from river currents and can enable communities worldwide to establish micro-grids to address part of their base loads. Hydrokinetic turbines offer a viable solution to produce power year-round to displace diesel generation in northern communities. However, these turbines must operate in reduced winter flows and not be impacted by ice. A passive-counter-torque and river-prototype hydrokinetic turbine integrated system is presented that offers a simpler and lower-cost approach to deploy, operate and maintain hydrokinetic turbines year-round in cold climates. A 500-W river prototype designed with a 0.48 m diameter two-blade impeller is optimized, built and tested. It produces a torque of 24.44 Nm at 200 RPM for a flow velocity of 2.0 m/s. For this in-situ prototype, shrouds, winglets, and wingtips are developed and optimized to reduce the levelized cost of electricity and micro-grid performance when flow velocities are lower than the design set point of 2.0 m/s. Such off-design conditions are mainly experienced during winter seasons. Numerical simulations confirm that the winglet design maintains the design power when experiencing up to 18% reduction in velocity. Various design combinations were tested by varying component dimensions: 2,216 combinations for shrouds and 4,103 for winglets. The optimal results were achieved using the shrouds, while the winglets were found to have the advantage to prevent stalling. Testing of the prototype turbine at the Canadian Hydrokinetic Turbine Testing Centre shows that the counter-torque design selected was stable. However, using a field vacuum pump to control the ballast in the configuration tested needs to be reconsidered.

Velocity and turbulence measurement uncertainty using acoustic methods in highly energetic river flows are quantified by performing measurements to isolate specific error terms, and by applying analytical methods and statistical analysis to recorded data. A MATLAB code is developed for motion compensation and data filtering. The methodology adopted is to perform acoustic measurements in a controlled laboratory setting and in an energetic river test site at Reynolds number from 0.05x10^7 to 3x10^7. As the performance of hydrokinetic turbines operating in highly energetic flows depends on localized velocity and turbulence parameters, uncertainty analysis contributes to improving river site characterization for the marine industry. The uncertainty analysis applies to acoustic instruments deployed from a stationary platform, a moving vessel, or alternatively, suspended in the water column via a cabling system in energetic river flows, which are typical configurations required by this industry. A methodology to conduct measurement and estimate the uncertainty is presented for these three configurations. The uncertainty analysis results are dependent on multiple inputs which are processed using algorithms made accessible online. A typical result of the error analysis at a velocity of 1.10 m/s a maximum deviation of 23% is observed between the measured and expected streamwise velocity at an instrument pitch angle of 45 degree. After implementing angle compensation the uncertainty reduces to 4%. Furthermore, by applying an IMU correction algorithm, the maximum velocity error is reduced by 29.3% and the turbulence by 77.0% after applying the motion compensation to river surface measurements. Processed flow results from an energetic river test site show the ADV overestimate streamwise mean time-averaged velocity and underestimate turbulence intensity measurements with an average of 4.6% and 27.4%, respectively.

The main objective of the research described in this thesis is to develop appropriate models and techniques for the probabilistic transient stability assessment of active distribution networks and extend the conventional well-being framework to the area of power system transient stability assessment. Transient stability assessment is one of the important aspects in power system planning and operating. The transient stability performance of power systems can be evaluated using either a deterministic method or a probabilistic approach. Deterministic methods are unable to fully recognize and reflect the actual risk associated with a given system and therefore the industry is leaning towards using probabilistic methods. This is particularly true with the introduction of non-dispatchable renewable generation in the energy supply. A probabilistic approach based on Monte Carlo simulation is, therefore, proposed in this thesis to accurately model and evaluate the risk of various uncertainties associated with active distribution networks transient stability performance. The approach utilizes the calculation accuracy of Electromagnetic Transient (EMT) simulator such as PSCAD/EMTDC and computationally-efficient algorithms such as parallel computing to facilitate the probabilistic transient stability evaluation of active distribution networks. A framework for advancing the industry knowledge in the area of power system transient stability well-being analysis is also proposed. Well-being analysis uses an acceptable deterministic criterion incorporated into probabilistic assessment to assign a comfort level to the power system in terms of healthy, marginal, and risk states probabilities. The concepts, models and methodologies are illustrated using the results obtained from studies on a practical active distribution network.

Reported are laboratory and field measurements obtained to characterize the flow structures caused by mooring anchors and rough river beds on the performance of hydrokinetic turbines. Series of flow velocity profile in-situ measurements characterize the energetic flow at the Canadian Hydrokinetic Turbine Test Centre (CHTTC) located on the Winnipeg River. Using an acoustic Doppler velocimeter, a novel method was applied to obtain the flow velocity through the water column to contribute to the design and optimization of power production from a hydrokinetic turbine. The acoustic Doppler velocimeter measures the mean and fluctuating velocity components at a frequency of 64 Hz. Tests were performed between 2.1 and 2.7 m/s upstream and downstream of turbine mooring anchors. Anchors occupy 12% of the water column height. Near-surface measurements show a 9.9% increase in turbulence intensity and 8.8% increase in free-stream velocity due to the upstream turbine mooring structures while the profile measurements show a temporal variation in the velocity and turbulence intensity profiles. In a more detailed laboratory investigation, four different scaled geometries of turbine mooring anchors were designed, fabricated and tested, including a 19.8 cm diameter horizontal axis turbine in a water tunnel. Tests are first performed at a steady velocity of 1.1 m/s and at an unobstructed Reynolds number of 217000 based on rotor diameter. During this testing, velocity measurements were taken at different locations upstream of a scaled horizontal turbine to determine the optimum operating conditions in a steady free-stream velocity. Furthermore, 25 surface roughness and four mooring anchor geometries were tested and located 2 and 3 rotor diameter upstream of the turbine in the water tunnel. Results show a 14% to 36% increase in turbine performance due to the impact of mooring anchor geometries and surface roughness. These results are useful in choosing a turbine mooring anchor design, geo

The objective of this thesis is to apply thermal analysis, coupled thermo-hydraulic analysis, and fully coupled thermo-hydro-mechanical analysis developed in this research to different engineering designs in cold regions. The applications vary from Geothermal Snow-Melting System Design to Structural and Thermal Integrity of Buried Infrastructure in cold regions. A feasibility study of geothermal energy pile based snow melting systemwas performed for six major cities in Canada. The coefficient of performance (COP) of heat pump is derived and the number of geothermal piles are determined for each city based on its specific local geological condition and heating demand.Also, the structural and thermal integrity of buried infrastructure were studied by performing an optimum design of rigid plastic foam insulations to protect buried utilities against frost damage and reduce the excavation cost. Furthermore, the effect of frost heave on the structural integrity of pavement structure and culverts are assessed.

The use of B100 biodiesel for compression ignition engines during the winter poses a challenge due to gelling and plugging of engine filters and fuel lines. The most common method to prevent this issue is blending it with petroleum diesel and many engine manufacturers limit the biodiesel in blends to 20% or less for warrantee purposes; as low as 5% may be set for winter months. In this research, an experimental analysis is performed using a scaled model of the fuel tank with canola oil as a test fluid in the tank. The tank is subjected to an ambient temperature of −20℃ in an icing tunnel facility with air velocity at 10 m/s. The results show that the time for the oil to drop from 20℃ to 5℃ was increased from 18.6 hours to 22.5 and 33 hours respectively when 4 and 12 tubes containing phase change materials (PCM) were inserted in the tank containing 33 litres of canola oil. A numerical model was further formulated to predict the transient temperature of the oil and comparison with experimental results showed excellent agreement. ANSYS Fluent was then used to conduct a visualization study of the flow for a sample scenario of a commercial tank with PCM. Finally, the developed numerical model was used to simulated different cases to investigate the effect of tank filling level, overall heat transfer coefficient, number of PCM modules and diameter of PCM modules on the tank performance. Results show that B100 can be implemented in diesel engines in cold climates.

To date, concentrated solar trough collectors have focused primarily on electricity generation in low latitudes using 400oC thermal oil temperatures. To adapt this technology to remote communities—that rely on diesel and heating oil and reach ambient temperatures of -40°C for extended periods—it is postulated that lowering the fluid temperature below 100oC is a preferred approach to reduce safety risks and operator qualification requirements. This approach mitigates higher heat losses in cold climates and still allows refrigeration and heating loads to be displaced by thermal energy; however, it significantly reduces thermal power generation efficiency. To regain electrical efficiency, the system is redesigned using concentrated photovoltaic cells secured to each receiver tube that can be cooled by glycol, an environmentally safer working fluid compared to thermal oil, operating at temperatures below 100oC. To investigate lower operating fluid temperatures and control issues related to cold climates, the methodology adopted is to design and build a 52-kW parabolic solar trough pilot plant in Winnipeg, as this location is chosen by some industries to perform cold weather testing. In addition, a transient model is developed to investigate how to integrate solar troughs in remote community applications. The model is validated using the pilot plant, predicting the fluid outlet temperature of the solar field with an average deviation of 1°C from measurements during thermal energy generation. A concentrated-photovoltaic-thermal configuration is then introduced to achieve attractive payback periods for remote communities in cold climates experiencing high energy costs and implementing renewable energy. Furthermore, to maximize revenues in these communities, a pump control strategy is implemented to reduce parasitic power by 80%; a multi-objective optimization algorithm results demonstrate the need to adjust the solar field flow rate in cold climates during operations.

In-situ testing of hydrokinetic river turbines demonstrates the feasibility of installing these turbines in cold climates and at remote communities without significant infrastructure requirements. Complete water-to-wire systems are deployed, tested in winter conditions and retrieved with major aspects of the technology investigated. A robust river-bottom anchoring system is developed and tested suitable for remote communities with minimal infrastructure. Vertical-axis 5-kW and 25-kW hydrokinetic turbines are deployed and tested in the Winnipeg River, under various climatic and flow conditions: -36ºC to 30ºC and 2.0 m/s to 2.6 m/s. Winter testing reveals that frazil ice accumulates on devices near the water surface, ice forms at the air-water interface, and ice sheets flowing with the stream can impact near-surface components. These factors lead to the conclusion that for low-maintenance and reliable year-round deployment in cold climates, systems must be fully submerged and removed if major ice floes occur. Hydrokinetic turbine generated power is delivered to a utility 12.47-kV overhead distribution line through pole-top transformers and bi-directional electricity meters, establishing a remote community water-to-wire system for the first time. Commercially available rectifier/inverters, developed for use in wind and solar energy capture, are successfully integrated into the power conversion system for the 5-kW and 25-kW units, reducing costs. A power conversion design is developed and tested. Concurrent measurement of river flow and turbulence with electrical power output from the permanent magnet generator are obtained in-situ. This data is used to investigate power production fluctuations resulting from turbulence in the flow. Turbulence is evaluated in detail, using time domain and frequency domain analysis. Calculated turbulence length scales varied from 0.7 m to 1.2 m, which are in the order of magnitude for the physical rotor elements. The results show that po

Multiple flow devices, techniques, procedures, and approaches are tested and validated to characterize the velocity, turbulence, and length-scales of high-velocity riverine sites for distributed hydrokinetic turbine applications. Measurements are performed at the Canadian Hydrokinetic Turbine Testing Center located on the Winnipeg River. Devices tested include the acoustic Doppler velocimeter (ADV), acoustic Doppler current profiler (ADCP) and the shear probe. ADV and ADCP streamwise mean time-averaged velocity measurements agree within an average of 4.38% difference. These velocity profiles are affected by upstream turbine wakes. In contrast, turbulence intensities differ to a larger degree between the ADCP, ADV, and shear probe. The average percent difference in turbulence intensity between ADV and ADCP is observed to be 30%. In the ADV results, vortex shedding suppression is suspected when the ADV is in the wake of an underwater turbine. Finally, the shear probe measured micro-turbulence scale and cannot capture macro-turbulence.

IEC 61850 is rapidly becoming the internationally recognized standard for substation automation systems making it an indispensable element in power system protection and automation education. In order to facilitate teaching this very practical subject, a laboratory setup was developed to demonstrate IEC 61850 station bus inter Intelligent Electronic Device (IED) communication. In this setup, an electrical substation was implemented in a real time digital simulator (RTDS) and protection schemes were implemented in IEC 61850 station bus compliant IEDs from different vendors. Trip signals and breaker statuses were exchanged between RTDS and IEDs using GOOSE (Generic Object Oriented Substation Event) messages. Several protection applications including a novel backup bus protection scheme were developed based on the setup to demonstrate the use of GOOSE messages in time critical applications. The developed test setup along with the designed laboratory exercises will undoubtedly enhance teaching, training and research in this important field.

Numerical simulation allows investigation into the influence of separation distance and rotation on the performance of two vertical-axis hydrokinetic turbines. Compu- tational fluid dynamics is applied to calulate the lift and drag coefficients acting upon interacting NACA 0021 turbine blades for a Reynolds number of Red = 10, 000. To understand the effect of separation distance, large-eddy simulation of the flow around side-by-side and staggered cylinders, ReD = 3,000, and airfoils, Rec = 3,000, are also performed. Based upon the simulations, a drag reduction of 11.3% and 19.8% is determined for the downstream cylinder and airfoil, respectively. A reduction in Reynolds stresses is also observed for the staggered configuration compared to the side-by-side configuration. Due to computational resources of large-eddy simulation, the Reynolds averaged Navier-Stokes method is also applied to investigate the influence of separation distance and rotation on two vertical axis hydrokinetic turbines. The numerical simulations show that a drag reduction of 15.5% occurs when the non-dimensional spanwise and streamwise separation distances, based on turbine diameter, reach 1 and 2, respectively.