Sizing hybrid green hydrogen energy generation and storage systems (HGHES) to enable an increase in renewable penetration for stabilising the grid.

A problem that has become apparently growing in the deployment of renewable energy systems is the power grids inability to accept the forecasted growth in renewable energy generation integration. To support forecasted growth in renewable generation integration, it is now recognised that Energy Storage Technologies (EST) must be utilised. Recent advances in Hydrogen Energy Storage Technologies (HEST) have unlocked their potential for use with constrained renewable generation. HEST combines Hydrogen production, storage and end use technologies with renewable generation in either a directly connected configuration, or indirectly via existing power networks. A levelised cost (LC) model has been developed within this thesis to identify the financial competitiveness of the different HEST application scenarios when used with grid constrained renewable energy. Five HEST scenarios have been investigated to demonstrate the most financially competitive configuration and the benefit that the by-product oxygen from renewable electrolysis can have on financial competitiveness. Furthermore, to address the lack in commercial software tools available to size an energy system incorporating HEST with limited data, a deterministic modelling approach has been developed to enable the initial automatic sizing of a hybrid renewable hydrogen energy system (HRHES) for a specified consumer demand. Within this approach, a worst-case scenario from the financial competitiveness analysis has been used to demonstrate that initial sizing of a HRHES can be achieved with only two input data, namely “ the available renewable resource and the load profile. The effect of the electrolyser thermal transients at start-up on the overall quantity of hydrogen produced (and accordingly the energy stored), when operated in conjunction with an intermittent renewable generation source, has also been modelled. Finally, a mass-transfer simulation model has been developed to investigate the suitability of constrained renewable generation in creating hydrogen for a hydrogen refuelling station

A review of sensorless control in induction machines using HF injection, test vectors and PWM harmonics

This paper gives a review of sensorless methods developed for ac drives’ operation at very low and zero speed. The sensorless drives presented in this paper use reluctance spatial anisotropy to track the mechanical rotor position, allowing the use of vector control. To extract the position information additional test signals in form of active vector pulses or continuous high frequency signals are injected into the machine. This paper also presents a technique which does not make use of additional test signals, but only components resulting from the inverter PWM pattern. Practical results show that with all reviewed methods sensorless vector control at very low and zero speed is possible. However, disturbances (eg. coming from the inverter or magnetic saturation) affect the position signal significantly and require appropriate compensation.peer-reviewe

ALTERNATIVE ENERGY SOURCES - INTEGRATION OF POWER GENERATION SYSTEMS INTO A MICROGRID AT CLEMSON UNIVERSITY AND AN ATMOSPHERIC THERMODYNAMIC DRIVEN MECHANICAL CLOCK

Non-renewable energy sources such as coal, crude oil, and natural gas are being consumed at a brisk pace which is promoting a worldwide energy crisis. The burning of fossil fuels produces greenhouse gases such as carbon dioxide and nitrous oxides as well as soot which contribute to atmospheric pollution. Although fossil fuels will continue to be available for many decades, the amount of petroleum remaining in the earth and its associated cost remains an open issue. The utilization of green energy such as solar and wind offer renewable and pollution free sources. A worldwide shift is slowly underway towards the inclusion of renewable energy sources to generate electrical and mechanical power. To meet this emerging societal demand, research into alternative energy sources such as solar, wind, and thermodynamic power generation is underway at Clemson University. This research encompasses two renewable energy strategies: a solar-based electrical microgrid, and an atmospheric thermodynamic driven mechanical clock. The concept of an electrical microgrid at Clemson University has been investigated as it promotes a renewable energy source to help realize a \u27net zero\u27 campus. For this case study, solar energy is harvested from the photovoltaic panels atop the Fluor Daniel Engineering Innovation Building which are capable of producing 15 kW of DC power at the full solar insolation rating. The electrical power produced varies throughout the day depending on the available solar irradiation and seasons. Next, compressed air energy storage has been evaluated using the generated electric power to operate an electric motor driven piston compressor. The compressed air is then stored under pressure and supplied to a natural gas driven Capstone C30 microturbine with attached electric power generator. In this approach, the compressed air facilitates the turbine\u27s rotor-blade operated compression stage resulting in direct energy savings. The compressed air energy storage mitigates the intermittency of solar power and provides a continuous energy input to the microturbine over selected time periods. In this thesis, a series of mathematical models have been developed for the solar panels, an air compressor, the pneumatic storage tank, and the microturbine as they represent the key microgrid system components. An illustrative numerical analysis was then performed to evaluate the feasibility and energy efficiency improvements. The experimental and simulation results indicated that 127.75 watts of peak power were delivered at 17.5 volts and 7.3 amps from each solar panel. The average DC power generation over a 24-hour time period from 115 panels was 75 kW which is equivalent to 30 kW of AC power from the inverter which could run a 5.2 kW reciprocating compressor for approximately 5 hours storing 1,108 kg of air at a 1.2 MPa pressure. The operation of the Capstone C30 microturbine was then simulated using a 0.31 kg/s mass flow rate with 100 air/fuel ratio. A case study indicated that the microturbine, when operated without compressed air storage, consumed 11.16 kg of gaseous propane for 30 kW∙hr of energy generation. In contrast, the microturbine operated in conjunction with solar supplied air storage could generate 50.84 kW∙hr of electrical energy for similar amount of fuel consumption. The study indicated an 8.1% of efficiency improvement in energy generated for the system which utilized compressed air energy storage over the traditional approach. An atmospheric driven mechanical Atmos clock manufactured by Jaeger LeCoultre has been investigated due to its capability to harvest energy based on climatic temperature and/or pressure changes to power the clock\u27s mechanisms. The clock\u27s bellows is the power unit which winds the on-board mainspring. The unwinding of this mainspring provides torque to run the gear train, the escapement, and the torsional pendulum. A detailed analysis of the Atmos 540 clock dynamics has been performed using a library of derived mathematical models which describe the bellows\u27 power generation, potential energy of the mainspring, gear train, escapement, and torsional pendulum. Experimental data has been collected using multiple sensors synchronized within the LabVIEW environment from National Instruments. For this thesis, the mathematical models have been simulated using Matlab/Simulink and validated with the gathered experimental results. The linear motion of the bellows was nearly 6 mm which winds the mainspring over a temperature range of 290-292K. The maximum potential energy of the mainspring was 57e-03J, or 0.67e-06 watts over a 24-hour time period. The minute hand rotation was observed to be 6 degrees/min. The captured crutch motion indicated a `hold\u27 position for a significant portion of the time (22 sec) and `impulse\u27 motion for a small portion of the time (8 sec) every 30 seconds in opposite directions. The findings indicated miniscule torque requirement to run the clock. In terms of green energy, the bellows motion is thermo-mechanical energy harvesting

Wind Turbine Generator Condition Monitoring via the Generator Control Loop

This thesis focuses on the development of condition monitoring techniques for application in wind turbines, particularly for offshore wind turbine driven doubly fed induction generators. The work describes the significant development of a physical condition monitoring Test Rig and its MATLAB Simulink model to represent modern variable speed wind turbine and the innovation and application of the rotor side control signals for the generator fault detection. Work has been carried out to develop a physical condition monitoring Test Rig from open loop control, with a wound rotor induction generator, into closed loop control with a doubly fed induction generator. This included designing and building the rotor side converter, installing the back-to-back converter and other new instrumentation. Moreover, the MATLAB Simulink model of the Test Rig has been developed to represent the closed loop control, with more detailed information on the Rig components and instrumentation and has been validated against the physical system in the time and frequency domains. A fault detection technique has been proposed by the author based on frequency analysis of the rotor-side control signals, namely; d-rotor current error, q-rotor current error and q-rotor current, for wind turbine generator fault detection. This technique has been investigated for rotor electrical asymmetry on the physical Test Rig and its MATLAB Simulink model at different fixed and variable speed conditions. The sensitivity of the each proposed signal has been studied under different operating conditions. Measured and simulated results are presented, a comparison with the results from using stator current and total power has been addressed and the improvement in condition monitoring detection performance has been demonstrated in comparison with previous methods, looking at current, power and vibration analysis

Modeling and analysis of power processing systems: Feasibility investigation and formulation of a methodology

A review is given of future power processing systems planned for the next 20 years, and the state-of-the-art of power processing design modeling and analysis techniques used to optimize power processing systems. A methodology of modeling and analysis of power processing equipment and systems has been formulated to fulfill future tradeoff studies and optimization requirements. Computer techniques were applied to simulate power processor performance and to optimize the design of power processing equipment. A program plan to systematically develop and apply the tools for power processing systems modeling and analysis is presented so that meaningful results can be obtained each year to aid the power processing system engineer and power processing equipment circuit designers in their conceptual and detail design and analysis tasks

Architecture de convertisseur statique tolérante aux pannes pour générateur pile à combustible modulaire de puissance-traction 30kW

Dans l objectif d une augmentation en puissance des piles à combustible pour satisfaire les besoins énergétiques des applications embarquées, une solution consiste à augmenter la taille des assemblages. Dès lors, des problèmes de disparités fluidique, thermique et électrique peuvent survenir dans le cœur des piles et conduire ainsi à l apparition de défaut. La pile à combustible, de par sa nature de source électrique basse tension fort courant, requiert d être couplée au réseau électrique embarqué par l intermédiaire d un convertisseur statique. Ce dernier peut alors être employé pour agir de façon corrective sur la pile et aussi de corriger les défaillances qui en sont liées. Dans cette perspective, le convertisseur doit avoir en permanence un retour sur l état de santé de la pile. Pour cela, une méthode de détection et d'identification de défaut de type noyage et d assèchement pour une pile du type PEMFC a été approfondie. Cette méthode simple, économique en capteurs, se base sur la mesure de 3 tensions de cellule judicieusement sélectionnées et localisées sur la pile. Ainsi, l utilisation de l information spatiale , qui correspond à la position de la mesure de tension dans la pile permet d identifier les défauts. Le principe de la détection localisée nous amène alors à considérer le concept de pile segmentée qui consiste à séparer électriquement la pile en 3 parties de façon à ce que des convertisseurs associés puissent agir électriquement sur chaque segment. L action peut être du type tout ou rien, ou contrôlée. Cette dernière offre davantage de degrés de liberté, et est moins contraignante pour la pile d un point de vue électrique. Pour choisir comment réaliser cette action, une étude comparative de plusieurs topologies de convertisseur est effectuée. Les structures alimentées en courant répondent au mieux aux contraintes électriques d une PEMFC et sont donc privilégiées, de même que la nécessité d une isolation galvanique imposée par la segmentation de la pile. Au final, une topologie de BOOST isolé résonant est apparue comme étant la topologie répondant au mieux à l ensemble des critères (plage de fonctionnement, performances énergétiques, nombre de composants). L ensemble convertisseur global intègre ainsi trois structures unitaires qui permettent d'offrir une modularité, une action indépendante sur chaque segment et de garantir une disponibilité du système grâce à un fonctionnement dégradé. Pour cela, la stratégie de commande de l ensemble convertisseur intègre les informations issues de la méthode de détection. La thèse se termine avec le dimensionnement complet d un pré-prototype du convertisseur avec le choix des composants actif et passifs, et du système de refroidissement associé.In the objective of fuel cell power increase in order to satisfy energetic requirements for embedded applications, a solution consists in increasing the size of fuel cell stack assemblies. As possible consequence, fluidic or thermal disparity problems may occur in the fuel cell core and lead to the appearance of faults. The fuel cell, which is a low voltage-high current electrical source, needs to be connected to the on-board electrical network thanks to a static converter. This latter can be used in order to perform a corrective action in the aim of reducing disparities in the stack and also correcting resulting faults. In this perspective, the converter should permanently get information about fuel cell state of health. Hence, a fault detection and identification method for PEMFC has been explored. This method which is simple and requires only few sensors is based on 3 voltage measurements judiciously selected and localized over the stack. Using spatial information which corresponds to the position of the sensors, allows to identify some characteristic faults. The principle of the localized fault detection leads to consider the segmentation concept for the fuel cell, which in our case is electrically split into three parts and allows an independent control of each segment by the power converter. Electrical action can be all or nothing or moderated ones. The latter offers more degree of freedom, and is less constraining from an electrical point of view. In order to execute the action, study of multiple power converter topologies have been done. Among the candidate topologies, current structures are preferred, as well as the necessity of a galvanic isolation required by the segmentation concept. The resonant isolated boost is the adopted structure; as it meets at best the whole criteria. Thus the global converter assembly is composed of three single structures which offer modularity, independent action on each segment, and continuity of service thanks to degraded modes. The detection method is hence implemented in the converter control strategy. This Ph.D. thesis ends with the complete sizing of a power converter pre-prototype together with technological choices for the active, passive and associated cooling components.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Optimisation of stand-alone hydrogen-based renewable energy systems using intelligent techniques

Wind and solar irradiance are promising renewable alternatives to fossil fuels due to their availability and topological advantages for local power generation. However, their intermittent and unpredictable nature limits their integration into energy markets. Fortunately, these disadvantages can be partially overcome by using them in combination with energy storage and back-up units. However, the increased complexity of such systems relative to single energy systems makes an optimal sizing method and appropriate Power Management Strategy (PMS) research priorities. This thesis contributes to the design and integration of stand-alone hybrid renewable energy systems by proposing methodologies to optimise the sizing and operation of hydrogen-based systems. These include using intelligent techniques such as Genetic Algorithm (GA), Particle Swarm Optimisation (PSO) and Neural Networks (NNs). Three design aspects: component sizing, renewables forecasting, and operation coordination, have been investigated. The thesis includes a series of four journal articles. The first article introduced a multi-objective sizing methodology to optimise standalone, hydrogen-based systems using GA. The sizing method was developed to calculate the optimum capacities of system components that underpin appropriate compromise between investment, renewables penetration and environmental footprint. The system reliability was assessed using the Loss of Power Supply Probability (LPSP) for which a novel modification was introduced to account for load losses during transient start-up times for the back-ups. The second article investigated the factors that may influence the accuracy of NNs when applied to forecasting short-term renewable energy. That study involved two NNs: Feedforward, and Radial Basis Function in an investigation of the effect of the type, span and resolution of training data, and the length of training pattern, on shortterm wind speed prediction accuracy. The impact of forecasting error on estimating the available wind power was also evaluated for a commercially available wind turbine. The third article experimentally validated the concept of a NN-based (predictive) PMS. A lab-scale (stand-alone) hybrid energy system, which consisted of: an emulated renewable power source, battery bank, and hydrogen fuel cell coupled with metal hydride storage, satisfied the dynamic load demand. The overall power flow of the constructed system was controlled by a NN-based PMS which was implemented using MATLAB and LabVIEW software. The effects of several control parameters, which are either hardware dependent or affect the predictive algorithm, on system performance was investigated under the predictive PMS, this was benchmarked against a rulebased (non-intelligent) strategy. The fourth article investigated the potential impact of NN-based PMS on the economic and operational characteristics of such hybrid systems. That study benchmarked a rule-based PMS to its (predictive) counterpart. In addition, the effect of real-time fuel cell optimisation using PSO, when applied in the context of predictive PMS was also investigated. The comparative analysis was based on deriving the cost of energy, life cycle emissions, renewables penetration, and duty cycles of fuel cell and electrolyser units. The effects of other parameters such the LPSP level, prediction accuracy were also investigated. The developed techniques outperformed traditional approaches by drawing upon complex artificial intelligence models. The research could underpin cost-effective, reliable power supplies to remote communities as well as reducing the dependence on fossil fuels and the associated environmental footprint

Investigation of Modular Multilevel Converter Performance under Non-Ideal Distribution System Conditions

The Modular Multilevel Converter (MMC) is an emerging power converter technology that has caught widespread attention mainly because of several technical and economic benefits such as modular realization, easy scalability, low total harmonic distortion, fail-safe operations etc. The MMC is comprised of a series connection of sub-modules (SM). A sub-module is made by either a half-bridge or a full-bridge IGBT device and a capacitor as a source of energy connected across the bridge. This modular structure allows for the possibility to design high-voltage converters handling hundreds of kilo-volts without direct series connection of the power semiconductor devices. Due to its modular and safe-fail structure, ability to work at low switching frequency (few hundreds of Hz) and reduced filtering requirements the MMCs are suitable for utility applications. One of the main challenges of a utility MMC is operation under non-ideal grid supply conditions. This includes phase to phase faults, phase to ground faults, non-sinusoidal grid supply etc. This dissertation presents a novel control strategy for MMC based on frequency domain decomposition of the converter currents. The converter supply voltage is also decomposed into symmetrical components. By using the positive sequence grid voltage component as a reference voltage the control system can produce symmetric sinusoidal phase currents under any type of grid unbalance condition. A novel circulating current controller based on frequency domain decomposition of arm currents is also presented which minimizes DC bus current ripples during unbalance grid supply A novel and simple method for estimating operating region of certain MMC parameters as a function of input variables (grid voltages and power references) is developed. The function of the operating region with respect to key system parameters ensures that the operating region can be maximized Finally, a new simplified loss modeling technique and a power reference computation algorithm is developed in order to extend its operating limit under certain unbalance conditions. The presented control architecture with a simplified real-time loss modeling method assures the best possible performance of a MMC during non-ideal supply conditions