Small-scale hybrid alternative energy maximizer for wind turbines and photovoltaic panels

This thesis describes the creation of a small-scale Hybrid Power System (HPS) that maximizes energy from a wind turbine and photovoltaic array. Small-scale HPS are becoming an increasingly viable energy solution as fossil fuel prices rise and more electricity is needed in remote areas. Modern HPS typically employ wind speed sensors and three power stages to extract maximum power. Modern systems also use passive rectifiers to convert AC from the wind turbine to DC that is usable by power electronics. This passive system inefficiently wastes power and introduces damaging harmonic noise to the wind turbine. The HPS described in this thesis does not require external wind speed sensors, and has independent wind and solar Maximum Power Point Tracking (MPPT). It converts AC from the wind turbine to DC with a Vienna rectifier that can be controlled to improve efficiency, allow MPPT, and allow Power Factor Correction (PFC). PFC all but eliminates the harmonic noise that can damage the wind turbine. A prototype HPS was built and evaluated that combines the two renewable sources in such a way that only two power stages are necessary, the Vienna rectifier and a step-down converter. This thesis describes the prototype and reports the results obtained

Comparative assessment of control strategies for the biradial turbine in the Mutriku OWC plant

To be competitive against other renewable energy sources, energy converted from the ocean waves needs to reduce its associated levelised cost of energy. It has been proven that advanced control algorithms can increase power production and device reliability. They act throughout the power conversion chain, from the hydrodynamics of wave absorption to the power take-off to improve the energy yield. The present work highlights the development and test of several algorithms to control the biradial turbine which is to be installed in the Mutriku oscillating water column plant. A collection of adaptive and predictive controllers is explored and both turbine speed controllers and latching strategies are examined. A Wave-to-Wire model of one chamber of the plant is detailed and simulation results of six control laws are obtained. The controllers are then validated using an electrical test infrastructure to prepare the future deployment in the plant. Finally, the control strategies are assessed against criteria like energy production, power quality or reliability.This work has received funding from the European Union'sHorizon 2020 research and innovation programme under grantagreement No 654444 (OPERA Project). This work was financed by GV/EJ (Basque Country Government) under grants IT1324-19. The second author was partially funded by the Portuguese Foundationfor Science and Technology (FCT) through IDMEC, under LAETAPEst-OE/EME/LA0022 by FCT researcher grant No. IF/01457/2014.The authors acknowledge AZTI Tecnalia for wave resource data measured at the plant

NASA Langley's AirSTAR Testbed: A Subscale Flight Test Capability for Flight Dynamics and Control System Experiments

As part of the Airborne Subscale Transport Aircraft Research (AirSTAR) project, NASA Langley Research Center (LaRC) has developed a subscaled flying testbed in order to conduct research experiments in support of the goals of NASA s Aviation Safety Program. This research capability consists of three distinct components. The first of these is the research aircraft, of which there are several in the AirSTAR stable. These aircraft range from a dynamically-scaled, twin turbine vehicle to a propeller driven, off-the-shelf airframe. Each of these airframes carves out its own niche in the research test program. All of the airplanes have sophisticated on-board data acquisition and actuation systems, recording, telemetering, processing, and/or receiving data from research control systems. The second piece of the testbed is the ground facilities, which encompass the hardware and software infrastructure necessary to provide comprehensive support services for conducting flight research using the subscale aircraft, including: subsystem development, integrated testing, remote piloting of the subscale aircraft, telemetry processing, experimental flight control law implementation and evaluation, flight simulation, data recording/archiving, and communications. The ground facilities are comprised of two major components: (1) The Base Research Station (BRS), a LaRC laboratory facility for system development, testing and data analysis, and (2) The Mobile Operations Station (MOS), a self-contained, motorized vehicle serving as a mobile research command/operations center, functionally equivalent to the BRS, capable of deployment to remote sites for supporting flight tests. The third piece of the testbed is the test facility itself. Research flights carried out by the AirSTAR team are conducted at NASA Wallops Flight Facility (WFF) on the Eastern Shore of Virginia. The UAV Island runway is a 50 x 1500 paved runway that lies within restricted airspace at Wallops Flight Facility. The facility provides all the necessary infrastructure to conduct the research flights in a safe and efficient manner. This paper gives a comprehensive overview of the development of the AirSTAR testbed

An approach to the characterisation of the performance of a tidal stream turbine

In order to better manage and maintain deployed Tidal Stream Turbine (TST) devices their response to complicated and severe loading mechanisms must be established. To aid this process the research presented details a methodology for mapping TST operational data, taken under a variety of operating conditions, to a set of model parameters. The parameter sets were developed based on a TST rotor torque model which, as well as providing means of characterising turbine behaviour, can be used to create TST simulations with minimal computation expense. The use of the model in facilitating parameter surface mapping is demonstrated via its application to a set of rotor torque measurements made of a 1/20th scale TST during flume testing. This model is then deployed to recreate the known rotor behaviour which is compared with the original flume based measurements. This is a flexible tool that can be applied to investigate turbine performance under conditions that cannot be readily replicated using tank-based experiments. Furthermore, Computational Fluid Dynamics simulations of such conditions could be time consuming and computationally expensive. To this end, the use of the model in creating drivetrain test bed based simulations is demonstrated. The model, which can be calculated in real-time, is used to develop representative turbine simulations at high turbulence intensity levels which were not achievable during flume experimentation. The intention is to provide a test-bed for future turbine performance monitoring under more realistic, site specific conditions. The work will also support the deployment of performance surfaces in real-life turbine applications

IPCS implications for future supersonic transport aircraft

The Integrated Propulsion Control System (IPCS) demonstrates control of an entire supersonic propulsion module - inlet, engine afterburner, and nozzle - with an HDC 601 digital computer. The program encompasses the design, build, qualification, and flight testing of control modes, software, and hardware. The flight test vehicle is an F-111E airplane. The L.H. inlet and engine will be operated under control of a digital computer mounted in the weapons bay. A general description and the current status of the IPCS program are given

Hydrogen vs. Battery in the long-term operation. A comparative between energy management strategies for hybrid renewable microgrids

The growth of the world’s energy demand over recent decades in relation to energy intensity and demography is clear. At the same time, the use of renewable energy sources is pursued to address decarbonization targets, but the stochasticity of renewable energy systems produces an increasing need for management systems to supply such energy volume while guaranteeing, at the same time, the security and reliability of the microgrids. Locally distributed energy storage systems (ESS) may provide the capacity to temporarily decouple production and demand. In this sense, the most implemented ESS in local energy districts are small–medium-scale electrochemical batteries. However, hydrogen systems are viable for storing larger energy quantities thanks to its intrinsic high mass-energy density. To match generation, demand and storage, energy management systems (EMSs) become crucial. This paper compares two strategies for an energy management system based on hydrogen-priority vs. battery-priority for the operation of a hybrid renewable microgrid. The overall performance of the two mentioned strategies is compared in the long-term operation via a set of evaluation parameters defined by the unmet load, storage efficiency, operating hours and cumulative energy. The results show that the hydrogen-priority strategy allows the microgrid to be led towards island operation because it saves a higher amount of energy, while the battery-priority strategy reduces the energy efficiency in the storage round trip. The main contribution of this work lies in the demonstration that conventional EMS for microgrids’ operation based on battery-priority strategy should turn into hydrogen-priority to keep the reliability and independence of the microgrid in the long-term operation

Determining Wind Turbine Drivetrain Test Bench Capability to Replicate Dynamic Loads: Evaluation Methods and Their Validation

Wind turbine drivetrain test facilities are impressive laboratories that offer a controlled environment to test the response of drivetrains under design conditions. The stochastic nature of the wind results in highly dynamic loads and this is reflected in the design standards and certification process of wind turbines. A wide range of wind conditions and turbine operating states are prescribed as design load cases. The design process of a wind turbine yields thousands of time series of fluctuating forces, bending moments and speed to cover these design load cases. The capability of a test bench to replicate such dynamic loads has been the subject of this research at Clemson University in cooperation with GE Renewable Energy. This collaborative research project used the 7.5-MW test bench of Clemson University to test two multi-MW drivetrain designs used on GE onshore wind turbines. This testing provided the first demonstration that the design load cases that typically drive the design of wind turbine drivetrains can be replicated on a test bench with an acceptable accuracy. The acceptance threshold for the accuracy was found to vary depending on the specific loads. The yaw and nodding bending moments are most critical to replicate accurately due to being generally much large than the forces, and the measurement error of the load application unit of the test bench was demonstrated to be an appropriate threshold based on multibody simulations. The dynamic response of one of the drivetrains tested was simulated using inputs to the model with and without the measured tracking error. This is the error between the loads commanded to the test bench and the loads that are measured at the point of application. For the drivetrain displacements considered, the multibody simulations quantified the impact of the tracking error on the displacements to be within 11% of the peak displacement. Most displacements were within 2.6%-3.1% of the peak displacement on average. Multibody simulations were also used to quantify the impact of a cross-coupling effect between forces and bending moments that occurs when the load application unit of the test bench applies loads dynamically. The impact on the dynamic response of the drivetrain from the cross-coupling was found to be generally small and acceptable despite significant tracking error on the forces. The testing also served as experimental verification of a novel method for the early assessment of the capability of a test bench to replicate dynamic loads. The identification of load time series that should be replicated with an acceptable level of accuracy and those that are likely beyond the capability of the test bench was validated. A new avenue of research in the wind energy sector has been initiated, and several recommendations are proposed for growing the knowledge base and the role of test benches for design certification purposes

Hardware-In-The-Loop Assessment of Robust Fuzzy Control Solutions for Hydroelectric and Wind Turbine Models

The interest towards renewable energy resources is increasing, and in particular it concerns wind and hydro powers, where the key point regards their efficient conversion into electric energy. To this end, control techniques can be used to meet this purpose, especially the ones relying on fuzzy models, due to their capabilities to manage nonlinear dynamic processes working in different conditions, and affected by faults, measurement errors, uncertainty and disturbances. The design methods addressed in this paper were already developed and validated for wind turbine plants, and important results can be achieved from their appropriate design and application to hydroelectric plants. This is the key issue of the paper, which recalls some considerations on the proposed solutions, as well as their validation to these energy conversion systems. Note that works available in the related literature that consider both wind and hydraulic energy conversion systems investigate a limited number of common issues, thus leading to little exchange opportunities and reduced common research aspects. Another important point addressed in the paper is that the proposed control design solutions are able to take into account the different working conditions of these power plants. Moreover, faults, uncertainty, disturbance and model reality mismatch effects are also considered when analyzing the reliability and robustness features of the derived control schemes. To this end, proper hardware in the loop tools are considered to verify and validate the developed control schemes in more realistic environments. Copyright (C) 2022 The Authors