Environomic multi-objective optimization of an eco-industrial park

A circular economy refers to an industrial economy with a cradle to cradle vision, shifting from the use of fossil fuels towards renewable energy, minimizing the use of toxic chemicals and reducing waste by recycling through careful system design. The concept of a circular economy is based on the study of non-linear, in particular living systems, with a major outcome being the optimisation of systems rather than of the individual components which make up each system. Industrial symbiosis (IS) is the exchange of energy, waste and by-products among industries in order to add value, while reducing costs and environmental impacts. This is consistent with the principles of a circular economy, and is a stepping stone towards the design of sustainable economies and policies. In the scope of this study, the use of local and renewable resources and the development of industrial ecology can contribute to the decrease of environmental impacts of a living, interactive system, on a given territory. A process system design framework is developped to model a superstructure that contains the list of possible options for the system. The LCA is used to calculate the environmental impacts of a product or a service. The method requires certain adjustments in order to assess the impacts of a spatially delimited system. The design of such system can be done by combining Life Cycle Assessment (LCA) that can provide a clear and structured framework to assess the environmental impacts of the system and process system design methods that applies mathematical programing techniques to systematically design territorial configurations using costs and thermo-chemical or physical models. The new method allows to generate the most attractive scenarios for the systems using a systematic modeling framework and using an optimisation approach that allows to generate a limited set of pareto optimal configurations that can then be evaluated to identify the most attractive solution. The method has been successsfully applied on a case study of a city with 100,000 inhabitants.

A Data-Driven Frequency-Domain Approach for Robust Controller Design via Convex Optimization

Achille Nicoletti

The objective of this dissertation is to develop data-driven frequency-domain methods for designing robust controllers through the use of convex optimization algorithms. Many of today's industrial processes are becoming more complex, and modeling accurate physical models for these plants using first principles may be impossible. With the increased developments in the computing world, large amounts of measured data can be easily collected and stored for processing purposes. Data can also be collected and used in an on-line fashion. Thus it would be very sensible to make full use of this data for controller design, performance evaluation, and stability analysis. The design methods imposed in this work ensure that the dynamics of a system are captured in an experiment and avoids the problem of unmodeled dynamics associated with parametric models. The devised methods consider robust designs for both linear-time-invariant (LTI) single-input-single-output (SISO) systems and certain classes of nonlinear systems. In this dissertation, a data-driven approach using the frequency response function of a system is proposed for designing robust controllers with H∞ performance. Necessary and sufficient conditions are derived for obtaining H∞ performance while guaranteeing the closed-loop stability of a system. A convex optimization algorithm is implemented to obtain the controller parameters which ensure system robustness; the controller is robust with respect to the frequency-dependent uncertainties of the frequency response function. For a certain class of nonlinearities, the proposed method can be used to obtain a best-linear-approximation with an associated frequency dependent uncertainty to guarantee the stability and performance for the underlying linear system that is subject to nonlinear distortions. The concepts behind these design methods are then used to devise necessary and sufficient conditions for ensuring the closed-loop stability of systems with sector-bounded nonlinearities. The conditions are simple convex feasibility constraints which can be used to stabilize systems with multi-model uncertainty. Additionally, a method is proposed for obtaining H∞ performance for an approximate model (i.e., describing function) of a sector-bounded nonlinearity. This work also proposes several data-driven methods for designing robust fixed-structure controllers with H∞ performance. One method considers the solution to a non-convex problem, while another method convexifies the problem and implements an iterative algorithm to obtain the local solution (which can also consider H2 performance). The effectiveness of the proposed method(s) is illustrated by considering several case studies that require robust controllers for achieving the desired performance. The main applicative work in this dissertation is with respect to a power converter control system at the European Organization for Nuclear Research (CERN) (which is used to control the current in a magnet to produce the desired field in controlling particle trajectories in accelerators). The proposed design methods are implemented in order to satisfy the challenging performance specifications set by the application while guaranteeing the system stability and robustness using data-driven design strategies.

EPFL2018

Decentralized production in urban systems, the vision of the Institute of Energy Sciences of EPFL

François Maréchal

In 1998, the Board of the Swiss Federal Institute of Technology established the challenging vision of the 2000 W society. The goal is to reach, for Switzerland by the year 2050, an energy intensity target of 2000 Wyear/year/cap. Referring to a present intensity of 5000 W year/year/cap, this means an expected factor 4 reduction of the intensity. For the Swiss Federal Institute of Technology, the challenge is to contribute to this target by its Research and Development activities. In the Ecole Polytechnique Fédérale de Lausanne (EPFL), the Institute of Energy Sciences (ISE) of the School of Engineering (STI) is a group of research laboratories that has committed to contribute to this target in the field of efficient conversion and distribution of energy. Decentralised production of electricity in urban areas is one of the multidisciplinary headlight projects that has been selected to reach the 2000 W target. Decentralised production is considered as a way of producing the energy services required by a community in an integrated approach allowing for polygeneration of heating, cooling, refrigeration and electricity services. This new systemic approach requires a new vision where several networks that have to be operated simultaneously. Electricity has to be distributed through microgrids connected with the major grids. In this field, the laboratories from electrical engineering are developing new tools for the design and the operation of such grids as well as new equipments that guarantee the safe operation of the system and its power quality. The design of district heating networks and their integration with the energy services requirements is a complex task since the demands vary with the seasons, the hours of the day and are by nature stochastic due to the behavior of the inhabitants and the weather conditions. Furthermore, the profitability and the conversion efficiency of such systems mainly rely on the appropriate system design, i.e. the size of the piping and the equipments, as well as on its optimal management. Applying techniques such as thermo-economic modeling, process integration , exergy analysis and multi-objective optimisation, the Laboratory for Industrial Energy Systems (LENI) develops computer aided design methods for helping the different stakeholders (energy services companies, technology developers, final users, policy makers) in defining the most appropriate investments both from the side of the infrastructure and the energy conversion equipments and also from the optimal operation management side in order to place the technologies in the energy market context. The Laboratories of the Energy Sciences Institute also work on the development of new equipments for advanced energy conversion, such as high speed turbocompressors for heat pumping, solid oxide fuel cells (SOFC) and cogeneration concepts combining SOFC and gas turbines. Within the Institute, this advanced R&D effort is performed in a multidisciplinary approach combining experimental work with multi-scale multi-physics computer aided design tools like CFD and optimisation.

2005

Méthodologie de conception et optimisation d'actionneurs intégrés sans fer

Igor Stefanini

The growing demand for new technologies in several fields : recreation, medicine, transport, telecommunications and the space industry, etc. is increasingly related to the field of the management, transformation and use of electric power. In this domain, the development of no-ferromagnetic integrated electromechanical actuators finds wide application and thus implies an usefulness over a large diversity of geometries. The absence of ferromagnetic materials does not allow for quick determination of an equivalent electromagnetic circuit for this type of actuator. The interaction of the magnetic induction fields produces phenomenas like the skin effect and the proximity effect which degrade its performance. In such circumstances, there is a compromise to be made between the analytical model's complexity and the precision of the results. Often, a modeling based on numerical approaches, which uses finite element methods, is the best adapted approach. Nevertheless, this type of analysis requires much experience and in particular, the parameterization of the actuator specifications and the exploitation of such a model in the optimized design is not very practical and requires considerable computing time. The use of discretized analytical models constitutes a good compromise between the degree of complexity and the model's correspondence to reality. Accordingly, in this thesis, we propose a suite of discretized analytical models allowing for the design and the optimization of this type of actuator. The development of a general rule to determine the optimal discretization step allows an arbitration between computing time, degree of complexity, and the precision of the results. The identification and the validation of the analytical models describing the skin and proximity effects have made it possible to improve the computation of self-inductance and winding resistance. The development of a design and optimization methodology for this type of actuator permits each application to be optimized in a systematic and efficient way, by proposing one or more possible solutions with their advantages and their disadvantages. Two distinct applications were conceived and optimized adopting this design methodology : the Montrac® system and the Iglus® system. In the Montrac® project, it was a question of modifying the power system of a modular assembly line. This system is composed of a fixed track with motorized shuttles for use in a clean room environment. The replacement of the electrical contacts by a contactless energy transmission system was dimensioned and optimized in order to guarantee an operation compatible with the requirements of the above mentioned environment. In the Iglus® project, a subcutaneous biomedical actuator for glycemic level detection, with the aim of measuring the glucose level of diabetes patients was optimized. The measurements and results from these two applications, made it possible to confirm the validity of the models expounded in this thesis.

EPFL2006