ERIGrid Holistic Test Description for Validating Cyber-Physical Energy Systems

Smart energy solutions aim to modify and optimise the operation of existing energy infrastructure. Such cyber-physical technology must be mature before deployment to the actual infrastructure, and competitive solutions will have to be compliant to standards still under development. Achieving this technology readiness and harmonisation requires reproducible experiments and appropriately realistic testing environments. Such testbeds for multi-domain cyber-physical experiments are complex in and of themselves. This work addresses a method for the scoping and design of experiments where both testbed and solution each require detailed expertise. This empirical work first revisited present test description approaches, developed a newdescription method for cyber-physical energy systems testing, and matured it by means of user involvement. The new Holistic Test Description (HTD) method facilitates the conception, deconstruction and reproduction of complex experimental designs in the domains of cyber-physical energy systems. This work develops the background and motivation, offers a guideline and examples to the proposed approach, and summarises experience from three years of its application.This work received funding in the European Community’s Horizon 2020 Program (H2020/2014–2020) under project “ERIGrid” (Grant Agreement No. 654113)

Aeroacoustic simulation of rotorcraft propulsion systems.

Rotorcraft constitute air vehicles with unique capabilities, including vertical take- off and landing, hover and forward/backward/lateral flight. The efficiency of rotorcraft operations is expected to improve rapidly, due to the incorporation of novel technologies into current designs. Moreover, enhanced or even new capabilities are anticipated after the introduction of advanced fast rotorcraft configurations into the future fleet. The forecast growth in rotorcraft operations is essentially associated with an expected increase in adverse environmental impact. With respect to the forthcoming rotorcraft aviation advancements, regulatory and advisory bodies, as well as communities, have focused their attention on reducing pollutant emissions and acoustic impact of rotorcraft activity. Consequently, robust and computationally efficient noise modelling approaches are deemed as prerequisites towards quantifying the acoustic impact of present and future rotorcraft activity. Ultimately, these approaches need to cater for unique operational conditions encompassed by modern rotorcraft across designated flight procedures. Additionally, individual variations of key design variables need to be resolved, in the context of design or operational optimisation, targeted at noise mitigation. This work elaborates on the development and application of a robust and computationally efficient methodology for the aeroacoustic simulation of rotorcraft propulsion systems. A series of fundamental modelling methods is developed for the prediction of helicopter rotor noise at fully-integrated operational level. An extensive validation is carried out against existing experimental data with respect to prediction of challenging aeroacoustic phenomena arising from complex aerodynamic interactions. The robustness of the deployed method is confirmed through a cost-effective uncertainty analysis method focused on aerodynamic sources of uncertainty. A set of generalised modelling guidelines is devised for the case of not available input parameters to calibrate the aerodynamic models. The aspect of multi-disciplinary optimisation of rotorcraft at aircraft level in terms of maximising the potential benefits of novel technologies is also tackled within this work. A holistic schedule of optimal active rotor morphing control is derived, offering simultaneous mitigation of pollutant emissions and acoustic impact across a wide range of the helicopter flight envelope. Finally, the developed noise prediction method is incorporated into an operational-level optimisation algorithm, demonstrating the potential of active rotor morphing with respect to reduction of ground-noise impact. The contribution to knowledge arising from the successful completion of this work comprises both the development of methodologies for helicopter aeroacoustic analysis and the derivation of guidelines and best practices for morphing rotor control. Specifically, a generic operational-level simulation approach is developed which effectively advances the state-of-the-art in mission noise prediction. New insight is provided with respect to the impact of wake aerodynamic modelling uncertainty on the robustness of noise predictions. Moreover, the aeroacoustic aspects of a novel morphing rotor concept are explored and quantifications with respect to the trade-off between environmental and noise disciplines are offered. Finally, a generalised set of optimal rotor control guidelines is derived towards achieving the challenging environmental goals set for a sustainable future rotorcraft aviation.PhD in Aerospac

Proceedings of the Second FAROS Public Workshop, 30th September 2014, Espoo, Finland

FAROS is an EC FP7 funded, three year project to develop an approach to incorporate human factors into Risk-Based Design of ships. The project consortium consists of 12 members including industry, academia and research institutes. The second FAROS Public Workshop was held in Dipoli Congress Centre in Otaniemi, Espoo, Finland, on the 30th of September 2014. The workshop included keynotes from industry, papers on risk models for aspects such as collision and grounding, fire and the human element, descriptions of parametric ship models and the overall approach being adopted in the FAROS project

Roadmap to the multidisciplinary design analysis and optimisation of wind energy systems

A research agenda is described to further encourage the application of Multidisciplinary Design Analysis and Optimisation (MDAO) methodologies to wind energy systems. As a group of researchers closely collaborating within the International Energy Agency (IEA) Wind Task 37 for Wind Energy Systems Engineering: Integrated Research, Design and Development, we have identified challenges that will be encountered by users building an MDAO framework. This roadmap comprises 17 research questions and activities recognised to belong to three research directions: model fidelity, system scope and workflow architecture. It is foreseen that sensible answers to all these questions will enable to more easily apply MDAO in the wind energy domain. Beyond the agenda, this work also promotes the use of systems engineering to design, analyse and optimise wind turbines and wind farms, to complement existing compartmentalised research and design paradigms

Through a Model, Darkly: An Investigation of Modellers’ Conceptualisation of Uncertainty in Climate and Energy Systems Modelling and an Application to Epidemiology

Policy responses to climate change require the use of complex computer models to understand the physical dynamics driving change, to evaluate its impacts and to evaluate the efficacy and costs of different mitigation and adaptation options. These models are often complex and built by large teams of dedicated researchers. All modelling requires assumptions, approximations and analytic conveniences to be employed. No model is without uncertainty. Authors have attempted to understand these uncertainties over the years and have developed detailed typologies to deal with them. However, it remains unknown how modellers themselves conceptualise the uncertainty inherent in their work. The core of this thesis involves the interviews of 38 modellers from climate science, energy systems modelling and integrated assessment to understand how they conceptualise the uncertainty in their work. This study finds that there is diversity in how uncertainty is understood and that various concepts from the literature are selectively employed to organise uncertainties. Uncertainty analysis is conceived as consisting of different phases in the model development process. The interplay between the complexity of the model and the capacities of modellers to manipulate these models shapes the ways in which uncertainty can be conceptualised. How we can attempt to wrangle with uncertainty in the present is determined by the path-dependent decisions made in the past; decisions that are influenced by a variety of factors within the context of the model’s creation. Furthermore, this thesis examines the application of these concepts to another field, epidemiology, to examine their generalisability in other contexts. This thesis concludes that in a situation such as climate change, where the nature of the problem changes in a dynamic way, emphasis should be placed on reducing the grip of these path dependencies and the resource costs of adapting models to face new challenges and answer new policy questions

A review of portfolio planning: Models and systems

In this chapter, we first provide an overview of a number of portfolio planning models which have been proposed and investigated over the last forty years. We revisit the mean-variance (M-V) model of Markowitz and the construction of the risk-return efficient frontier. A piecewise linear approximation of the problem through a reformulation involving diagonalisation of the quadratic form into a variable separable function is also considered. A few other models, such as, the Mean Absolute Deviation (MAD), the Weighted Goal Programming (WGP) and the Minimax (MM) model which use alternative metrics for risk are also introduced, compared and contrasted. Recently asymmetric measures of risk have gained in importance; we consider a generic representation and a number of alternative symmetric and asymmetric measures of risk which find use in the evaluation of portfolios. There are a number of modelling and computational considerations which have been introduced into practical portfolio planning problems. These include: (a) buy-in thresholds for assets, (b) restriction on the number of assets (cardinality constraints), (c) transaction roundlot restrictions. Practical portfolio models may also include (d) dedication of cashflow streams, and, (e) immunization which involves duration matching and convexity constraints. The modelling issues in respect of these features are discussed. Many of these features lead to discrete restrictions involving zero-one and general integer variables which make the resulting model a quadratic mixed-integer programming model (QMIP). The QMIP is a NP-hard problem; the algorithms and solution methods for this class of problems are also discussed. The issues of preparing the analytic data (financial datamarts) for this family of portfolio planning problems are examined. We finally present computational results which provide some indication of the state-of-the-art in the solution of portfolio optimisation problems