Advancements in Real-Time Simulation of Power and Energy Systems

Modern power and energy systems are characterized by the wide integration of distributed generation, storage and electric vehicles, adoption of ICT solutions, and interconnection of different energy carriers and consumer engagement, posing new challenges and creating new opportunities. Advanced testing and validation methods are needed to efficiently validate power equipment and controls in the contemporary complex environment and support the transition to a cleaner and sustainable energy system. Real-time hardware-in-the-loop (HIL) simulation has proven to be an effective method for validating and de-risking power system equipment in highly realistic, flexible, and repeatable conditions. Controller hardware-in-the-loop (CHIL) and power hardware-in-the-loop (PHIL) are the two main HIL simulation methods used in industry and academia that contribute to system-level testing enhancement by exploiting the flexibility of digital simulations in testing actual controllers and power equipment. This book addresses recent advances in real-time HIL simulation in several domains (also in new and promising areas), including technique improvements to promote its wider use. It is composed of 14 papers dealing with advances in HIL testing of power electronic converters, power system protection, modeling for real-time digital simulation, co-simulation, geographically distributed HIL, and multiphysics HIL, among other topics

Influence of Architecture Design on the Performance and Fuel Efficiency of Hydraulic Hybrid Transmissions

Hydraulic hybrids are a proven and effective alternative to electric hybrids for increasing the fuel efficiency of on-road vehicles. To further the state-of-the-art this work investigates how architecture design influences the performance, fuel efficiency, and controllability of hydraulic hybrid transmissions. To that end a novel neural network based power management controller was proposed and investigated for conventional hydraulic hybrids. This control scheme trained a neural network to generalize the globally optimal, though non-implementable, state trajectories generated by dynamic programming. Once trained the neural network was used for online prediction of a transmission’s optimal state trajectory during untrained cycles forming the basis of an implementable controller. During hardware-in-the-loop (HIL) testing the proposed control strategy improved fuel efficiency by up to 25.5% when compared with baseline approaches. To further improve performance and fuel efficiency a novel transmission architecture termed a Blended Hydraulic Hybrid was proposed and investigated. This novel architecture improves on existing hydraulic hybrids by partially decoupling power transmission from energy storage while simultaneously providing means to recouple the systems when advantageous. Optimal control studies showed the proposed architecture improved fuel efficiency over both baseline mechanical and conventional hydraulic hybrid transmissions. Effective system level and supervisory control schemes were also proposed for the blended hybrid. In order to investigate the concept’s feasibility a blended hybrid transmission was constructed and successfully tested on a HIL transmission dynamometer. Finally to investigate controllability and driver perception an SUV was retrofitted with a blended hybrid transmission. Successful on-road vehicle testing showcased the potential of this novel hybrid architecture as a viable alternative to more conventional electric hybrids in the transportation sector

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

Unmanned Aerial Vehicles Modelling and Control Design. A Multi-Objective Optimization Approach

[ES] Aquesta tesi presenta els resultats de la feina de recerca dut a terme sobre el modelatge i el disseny de controladors per a micro-aeronaus no tripulades mitjançant tècniques d'optimització multi-objectiu. Dos principals camps d'estudi estan presents al llarg d'ella. D'una banda, l'estudi de com modelar i controlar plataformes aèries de petita envergadura. I, de l'altra, l'estudi sobre l'ús de tècniques heurístiques d'optimització multi-objectiu per aplicar en el procés de parametrització de models i controladors en micro-aeronaus no tripulades. S'obtenen com a resultat principal una sèrie d'eines que permeten prescindir d'experiments en túnels de vent o de sensòrica d'alt cost, passant directament a la utilització de dades de vol experimental a la identificació paramètrica de models dinàmics. A més, es demostra com la utilització d'eines d'optimització multi-objectiu en diferents fases de desenvolupament de controladors ajuda a augmentar el coneixement sobre la plataforma a controlar i augmenta la fiabilitat i robustesa dels controladors desenvolupats, disminuint el risc de passar de les fases prèvies de el disseny a la validació en vol real.[CA] Esta tesis presenta los resultados del trabajo de investigación llevado a cabo sobre el modelado y el diseño de controladores para micro-aeronaves no tripuladas mediante técnicas de optimización multi-objetivo. Dos principales campos de estudio están presentes a lo largo de ella. Por un lado, el estudio de cómo modelar y controlar plataformas aéreas de pequeña envergadura. Y, por otro, el estudio sobre el empleo de técnicas heurísticas de optimización multi-objetivo para aplicar en el proceso de parametrización de modelos y controladores en micro-aeronaves no tripuladas. Se obtienen como resultado principal una serie de herramientas que permiten prescindir de experimentos en túneles de viento o de sensórica de alto coste, pasando directamente a la utilización de datos de vuelo experimental en la identificación paramétrica de modelos dinámicos. Además, se demuestra como la utilización de herramientas de optimización multi-objetivo en diferentes fases del desarrollo de controladores ayuda a aumentar el conocimiento sobre la plataforma a controlar y aumenta la fiabilidad y robustez de los controladores desarrollados, disminuyendo el riesgo de pasar de las fases previas del diseño a la validación en vuelo real.[EN] This thesis presents the results of the research work carried out on the modelling and design of controllers for micro-unmanned aerial vehicles by means of multi-objective optimization techniques. Two main fields of study are present throughout it. On one hand, the study of how to model and control small aerial platforms. And, on the other, the study on the use of heuristic multi-objective optimization techniques to apply in the process of models and controllers parameterization in micro-unmanned aerial vehicles. The main result is a series of tools that make it possible manage without wind tunnel experiments or high-cost air-data sensors, going directly to the use of experimental flight data in the parametric identification of dynamic models. In addition, a demonstration is given on how the use of multi-objective optimization tools in different phases of controller development helps to increase knowledge about the platform to be controlled and increases the reliability and robustness of the controllers developed, reducing the risk of hoping from the initial design phases to validation in real flight.Velasco Carrau, J. (2020). Unmanned Aerial Vehicles Modelling and Control Design. A Multi-Objective Optimization Approach [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/156034TESI

Modelling and control for the oscillating water column

xxii, 219 p.Renewable energies are definitely part of the equation to limit our dependence to fossil fuels. Within this sector, ocean energies, and especially wave energy, represent a huge potential but is still a growing area. And like any new field, it is synonym to a high cost of energy production. Increasing the energy production, while keeping the costs controlled, has the leverage to drop down the cost of energy produced by wave energy converters (WECs). The main objective of this thesis is to make progress on the understanding of the effect of advanced control algorithms in the improvement of the power produced by wave energy devices. For that purpose, several control strategies are designed, compared, and assessed. To support this analysis, numerical models representing the overall energy conversion chain of WECs are developed. The Basque Country in Spain is fortunate enough to host the development and operation of two devices based on the Oscillating Water Column (OWC) principle. One is the Mutriku OWC plant, and the second is the floating buoy Marmok-A from Oceantec/IDOM, both devices were made available for sea trials. Several control algorithms were then implemented to be tested in real environments. Among them was a non-linear predictive control algorithm. Its test in real conditions represent a world first in the area of control for OWC systems, and maybe for the whole WEC sector if comparing with publicly available information. An outstanding results of the thesis is undoubtedly to move forward the predictive control algorithm from TRL3 to TRL6 after successful implementation and operation in both devices under real environmental conditions

Vehicle dynamics virtual sensing and advanced motion control for highly skilled autonomous vehicles

This dissertation is aimed at elucidating the path towards the development of a future generation of highly-skilled autonomous vehicles (HSAV). In brief, it is envisaged that future HSAVs will be able to exhibit advanced driving skills to maintain the vehicle within stable limits in spite of the driving conditions (limits of handling) or environmental adversities (e.g. low manoeuvrability surfaces). Current research lines on intelligent systems indicate that such advanced driving behaviour may be realised by means of expert systems capable of monitoring the current vehicle states, learning the road friction conditions, and adapting their behaviour depending on the identified situation. Such adaptation skills are often exhibited by professional motorsport drivers, who fine-tune their driving behaviour depending on the road geometry or tyre-friction characteristics. On this basis, expert systems incorporating advanced driving functions inspired by the techniques seen on highly-skilled drivers (e.g. high body slip control) are proposed to extend the operating region of autonomous vehicles and achieve high-level automation (e.g. manoeuvrability enhancement on low-adherence surfaces). Specifically, two major research topics are covered in detail in this dissertation to conceive these expert systems: vehicle dynamics virtual sensing and advanced motion control. With regards to the former, a comprehensive research is undertaken to propose virtual sensors able to estimate the vehicle planar motion states and learn the road friction characteristics from readily available measurements. In what concerns motion control, systems to mimic advanced driving skills and achieve robust path-following ability are pursued. An optimal coordinated action of different chassis subsystems (e.g. steering and individual torque control) is sought by the adoption of a centralised multi-actuated system framework. The virtual sensors developed in this work are validated experimentally with the Vehicle-Based Objective Tyre Testing (VBOTT) research testbed of JAGUAR LAND ROVER and the advanced motion control functions with the Multi-Actuated Ground Vehicle “DevBot” of ARRIVAL and ROBORACE.Diese Dissertation soll den Weg zur Entwicklung einer zukünftigen Generation hochqualifizierter autonomer Fahrzeuge (HSAV) aufzeigen. Kurz gesagt, es ist beabsichtigt, dass zukünftige HSAVs fortgeschrittene Fahrfähigkeiten aufweisen können, um das Fahrzeug trotz der Fahrbedingungen (Grenzen des Fahrverhaltens) oder Umgebungsbedingungen (z. B. Oberflächen mit geringer Manövrierfähigkeit) in stabilen Grenzen zu halten. Aktuelle Forschungslinien zu intelligenten Systemen weisen darauf hin, dass ein solches fortschrittliches Fahrverhalten mit Hilfe von Expertensystemen realisiert werden kann, die in der Lage sind, die aktuellen Fahrzeugzustände zu überwachen, die Straßenreibungsbedingungen kennenzulernen und ihr Verhalten in Abhängigkeit von der ermittelten Situation anzupassen. Solche Anpassungsfähigkeiten werden häufig von professionellen Motorsportfahrern gezeigt, die ihr Fahrverhalten in Abhängigkeit von der Straßengeometrie oder den Reifenreibungsmerkmalen abstimmen. Auf dieser Grundlage werden Expertensysteme mit fortschrittlichen Fahrfunktionen vorgeschlagen, die auf den Techniken hochqualifizierter Fahrer basieren (z. B. hohe Schlupfregelung), um den Betriebsbereich autonomer Fahrzeuge zu erweitern und eine Automatisierung auf hohem Niveau zu erreichen (z. B. Verbesserung der Manövrierfähigkeit auf niedrigem Niveau) -haftende Oberflächen). Um diese Expertensysteme zu konzipieren, werden zwei große Forschungsthemen in dieser Dissertation ausführlich behandelt: Fahrdynamik-virtuelle Wahrnehmung und fortschrittliche Bewegungssteuerung. In Bezug auf erstere wird eine umfassende Forschung durchgeführt, um virtuelle Sensoren vorzuschlagen, die in der Lage sind, die Bewegungszustände der Fahrzeugebenen abzuschätzen und die Straßenreibungseigenschaften aus leicht verfügbaren Messungen kennenzulernen. In Bezug auf die Bewegungssteuerung werden Systeme zur Nachahmung fortgeschrittener Fahrfähigkeiten und zum Erzielen einer robusten Wegfolgefähigkeit angestrebt. Eine optimale koordinierte Wirkung verschiedener Fahrgestellsubsysteme (z. B. Lenkung und individuelle Drehmomentsteuerung) wird durch die Annahme eines zentralisierten, mehrfach betätigten Systemrahmens angestrebt. Die in dieser Arbeit entwickelten virtuellen Sensoren wurden experimentell mit dem Vehicle-Based Objective Tyre Testing (VBOTT) - Prüfstand von JAGUAR LAND ROVER und den fortschrittlichen Bewegungssteuerungsfunktionen mit dem mehrfach betätigten Bodenfahrzeug ”DevBot” von ARRIVAL und ROBORACE validiert

Modelling and control for the oscillating water column

xxii, 219 p.Renewable energies are definitely part of the equation to limit our dependence to fossil fuels. Within this sector, ocean energies, and especially wave energy, represent a huge potential but is still a growing area. And like any new field, it is synonym to a high cost of energy production. Increasing the energy production, while keeping the costs controlled, has the leverage to drop down the cost of energy produced by wave energy converters (WECs). The main objective of this thesis is to make progress on the understanding of the effect of advanced control algorithms in the improvement of the power produced by wave energy devices. For that purpose, several control strategies are designed, compared, and assessed. To support this analysis, numerical models representing the overall energy conversion chain of WECs are developed. The Basque Country in Spain is fortunate enough to host the development and operation of two devices based on the Oscillating Water Column (OWC) principle. One is the Mutriku OWC plant, and the second is the floating buoy Marmok-A from Oceantec/IDOM, both devices were made available for sea trials. Several control algorithms were then implemented to be tested in real environments. Among them was a non-linear predictive control algorithm. Its test in real conditions represent a world first in the area of control for OWC systems, and maybe for the whole WEC sector if comparing with publicly available information. An outstanding results of the thesis is undoubtedly to move forward the predictive control algorithm from TRL3 to TRL6 after successful implementation and operation in both devices under real environmental conditions

Definition and verification of a set of reusable reference architectures for hybrid vehicle development

Current concerns regarding climate change and energy security have resulted in an increasing demand for low carbon vehicles, including: more efficient internal combustion engine vehicles, alternative fuel vehicles, electric vehicles and hybrid vehicles. Unlike traditional internal combustion engine vehicles and electric vehicles, hybrid vehicles contain a minimum of two energy storage systems. These are required to deliver power through a complex powertrain which must combine these power flows electrically or mechanically (or both), before torque can be delivered to the wheel. Three distinct types of hybrid vehicles exist, series hybrids, parallel hybrids and compound hybrids. Each type of hybrid presents a unique engineering challenge. Also, within each hybrid type there exists a wide range of configurations of components, in size and type. The emergence of this new family of hybrid vehicles has necessitated a new component to vehicle development, the Vehicle Supervisory Controller (VSC). The VSC must determine and deliver driver torque demand, dividing the delivery of that demand from the multiple energy storage systems as a function of efficiencies and capacities. This control component is not commonly a standalone entity in traditional internal combustion vehicles and therefore presents an opportunity to apply a systems engineering approach to hybrid vehicle systems and VSC control system development. A key non-­‐functional requirement in systems engineering is reusability. A common method for maximising system reusability is a Reference Architecture (RA). This is an abstraction of the minimum set of shared system features (structure, functions, interactions and behaviour) that can be applied to a number of similar but distinct system deployments. It is argued that the employment of RAs in hybrid vehicle development would reduce VSC development time and cost. This Thesis expands this research to determine if one RA is extendable to all hybrid vehicle types and combines the scientific method with the scenario testing method to verify the reusability of RAs by demonstration. A set of hypotheses are posed: Can one RA represent all hybrid types? If not, can a minimum number of RAs be defined which represents all hybrid types? These hypotheses are tested by a set of scenarios. The RA is used as a template for a vehicle deployment (a scenario), which is then tested numerically, thereby verifying that the RA is valid for this type of vehicle. This Thesis determines that two RAs are required to represent the three hybrid vehicle types. One RA is needed for series hybrids, and the second RA covers parallel and compound hybrids. This is done at a level of abstraction which is high enough to avoid system specific features but low enough to incorporate detailed control functionality. One series hybrid is deployed using the series RA into simulation, hardware and onto a vehicle for testing. This verifies that the series RA is valid for this type of vehicle. The parallel RA is used to develop two sub-­‐types of parallel hybrids and one compound hybrid. This research has been conducted with industrial partners who value, and are employing, the findings of this research in their hybrid vehicle development programs

An Innovative MIMO Iterative Learning Control Approach for the Position Control of a Hydraulic Press

To improve the performance of hydraulic press position control and eliminate the need to manually define control signals, this paper proposes a multi-input-multi-output (MIMO) Iterative Learning Control (ILC) algorithm. The MIMO ILC algorithm design is based on the inversion of the known low frequency dynamics of the hydraulic press, whereas the unknown and uncertain high frequency dynamics are discarded due to their low influence in the learning transient. Moreover, for the MIMO ILC convergence condition, a graphical method is proposed, in which the ILC learning filter eigenvalues are analyzed. This method allows studying the stability and convergence rate of the algorithm intuitively. Theoretical analysis and results prove that with the MIMO ILC algorithm the position control is automated and that high precision in the position tracking is gained. A comparison with other model inverse ILC approaches is carried out and it is shown that the proposed MIMO ILC algorithm outperforms the existing algorithms, reducing the number of iterations required to converge while guaranteeing system stability. Furthermore, experimental results in a hydraulic test rig are presented and compared to those obtained with a conventional PI controllerThis work was supported in part by the Department of Development and Infrastructures of the Government of the Basque Country via Industrial Doctorate Program BIKAINTEK under Grant 20-AF-W2-2018-00015