This document is intended to present the business case of a research project, more precisely of the Sub-project "The doubly-fed induction generator: Modeling and control of non-linearities”. Non-linearity affects the operation of a real doubly-fed induction generator (DFIG) and as such has to be addressed by models. In two sentences, the Scope of this Sub-project is (1) to determine the extent to which the available methods carry over to the non linear setting, and (2) to investigate different methods, including new ones. The Plan of this Sub-project includes three Stages which may be executed in sequence and may be interleaved by gates (ISO 21502:2020, FIGURE 4). Stage 1: update the literature database; Stage 2: classify articles and book chapters by the methods they propose and by the problems they solve or address; Stage 3: determine the DFIG model which accounts for most of the physical processes in the machine and those properties of the model which are mathematically tractable; if necessary, investigate new methods and suggest the corresponding control algorithms. The Project’s scope falls into the realm of mathematical and physical Methods and Models of complex systems. The interplay between different methods and models will be emphasised during Stage 2. Complexity of the system under investigation, represented by the interaction of different physical processes in the electrical network and in magnetic materials, will be addressed during Stage 3. Risk carried by each Stage can be identified and quantified, the main Risk coming from the inability of answering a research question. Strategies exist, which can mitigate such Risk: they rely on continuous comparison of known different solutions to previously addressed problems. Such comparison characterises the investigation of mathematical models of physical systems: it allows consistency of results to be verified at each stage and suggests a solution by analogy., a.k.a. "synectics" in the Project Management parlance.
Crosta, G. (2024). Sub-project: The doubly-fed induction generator. Business case: Modeling and control of non-linearities [Rapporto tecnico].
Sub-project: The doubly-fed induction generator. Business case: Modeling and control of non-linearities
Crosta Giovanni Franco
2024
Abstract
This document is intended to present the business case of a research project, more precisely of the Sub-project "The doubly-fed induction generator: Modeling and control of non-linearities”. Non-linearity affects the operation of a real doubly-fed induction generator (DFIG) and as such has to be addressed by models. In two sentences, the Scope of this Sub-project is (1) to determine the extent to which the available methods carry over to the non linear setting, and (2) to investigate different methods, including new ones. The Plan of this Sub-project includes three Stages which may be executed in sequence and may be interleaved by gates (ISO 21502:2020, FIGURE 4). Stage 1: update the literature database; Stage 2: classify articles and book chapters by the methods they propose and by the problems they solve or address; Stage 3: determine the DFIG model which accounts for most of the physical processes in the machine and those properties of the model which are mathematically tractable; if necessary, investigate new methods and suggest the corresponding control algorithms. The Project’s scope falls into the realm of mathematical and physical Methods and Models of complex systems. The interplay between different methods and models will be emphasised during Stage 2. Complexity of the system under investigation, represented by the interaction of different physical processes in the electrical network and in magnetic materials, will be addressed during Stage 3. Risk carried by each Stage can be identified and quantified, the main Risk coming from the inability of answering a research question. Strategies exist, which can mitigate such Risk: they rely on continuous comparison of known different solutions to previously addressed problems. Such comparison characterises the investigation of mathematical models of physical systems: it allows consistency of results to be verified at each stage and suggests a solution by analogy., a.k.a. "synectics" in the Project Management parlance.File | Dimensione | Formato | |
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