**Are you an EPFL student looking for a semester project?**

Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.

Person# Raffaele Bolliger

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related units

Loading

Courses taught by this person

Loading

Related research domains

Loading

Related publications

Loading

People doing similar research

Loading

Related publications (9)

Loading

Loading

Loading

Related research domains (3)

Heat exchanger

A heat exchanger is a system used to transfer heat between a source and a working fluid. Heat exchangers are used in both cooling and heating processes. The fluids may be separated by a solid wall t

Complex system

A complex system is a system composed of many components which may interact with each other. Examples of complex systems are Earth's global climate, organisms, the human brain, infrastructure such as

Mathematical optimization

Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternative

Related units (1)

People doing similar research (134)

Courses taught by this person

No results

, , ,

OSMOSE is a platform for the study and design of complex integrated energy systems. The software is developed in the Laboratory for Industrial Energy Systems (LENI) in the Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. The project is motivated by the need of a fexible and performant research tool to study and design energy systems. In this perspective, the general scope of the software is to help the user to develop and compute technology models that combine (a) thermodynamic computations, (b) power and energy integration as well as (c) economic or environomic aspects. OSMOSE , exploits the models by performing (a) sensitivity analysis, (b) optimization and (c) data analysis. The present document is a complete user guide to OSMOSE. In addition, elements of software structure and architecture are exposed. This makes therefore the document useful as an introduction for future developers in the project.

This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and energy services. The purpose of the preliminary synthesis is to define which technologies form the system, to calculate their technical characteristics, their operating conditions and their interactions, based on performance indicators such as for example the cost of the system or its environmental impact. This area is studied since a long time and many synthesis approaches are available. However, these methods have significant limitations, particularly in their ability to face the study of more and more complex systems. The main goal of the method presented in this work is to enable the study of large systems and promote the use of the experience gained from previous studies in the form of models and methodological approaches. The synthesis method of industrial energy systems is based on the overall system optimization using a model that is obtained by assembling several modules, representing each a set of physical unit operations and whose equations are formulated with the black box technique, and an integration model that can represent the possible interactions within the system. Optimization is performed using a multi-objective evolutionary algorithm, whose objective functions are defined on the basis of calculation of several performance indicators based on the model of the system. To simplify the resolution of this complex system, the optimization problem is decomposed into a master problem, responsible for calculating the characteristics of the units and their operating conditions, and an optimization slave subproblem, which selects the units being part of the system and their interconnections. To ensure its robustness, the slave subproblem is formulated as a mixed-integer linear optimization problem. The slave subproblem is formulated by using process integration techniques, which are extended in this work to allow the synthesis of multiple heat and mass transfer networks. The synthesis problem can thus be defined using an explicit superstructure or by one generated automatically, either implicit or explicit. This work also introduces a technique that greatly reduces the number of degrees of freedom of the integration model. Instead of separately optimizing each ΔTmin/2 associated with heat streams, a formula is applied to calculate their value from a reference case. The ΔTmin/2 optimization is thus reduced to the optimization of a single decision variable related to the reference case, regardless of the size of the problem. The proposed method uses a set of heterogeneous elements, including flowsheeting software for modeling physical unit operations, mathematical programming tools for the formulation of the integration problem, methods for calculating performance indicators and calculation tools such as the optimization algorithm. This work introduces new tools developed to systematically apply the proposed methodology and to automate recurring operations of data transfer and the call of the various used software. In particular, a syntax description is defined as an abstraction layer to describe and to structure the exchanged information. A computing platform has been created to support the application of the method and to ensure the data transfer between its components. Two case studies are presented to illustrate the various aspects of the synthesis method. A first case, involving the synthesis of two combined cycles, has been chosen to illustrate the different application stages of the method and to show the potential reuse of certain modules. Through the integration techniques, it has been possible to identify potential heat recovery that can increase the performance of one of the cycles beyond what had been expected by experts using conventional simulation techniques. The second case study is about the treatment of waste generated by an industrial site active in the field of fine chemicals. Waste treatment can recover different materials and energy services useful for process units, thereby reducing the quantities purchased in the market. The model of multi-network integration can easily solve the complexity of the problem of waste management in developing strategies for allocating waste to the various treatments available for different objective functions related to operating costs and environmental impact.

Helen Carla Becker, Raffaele Bolliger, François Maréchal

This paper proposes a new approach in the field of energy conversion systems analysis and synthesis. The method is based on a generic and multi-platform description syntax, that clearly separates the information concerning the physical behavior of the modeled technology (e.g. mass and energy balances and chemical reactions) from the information necessary to apply one or more system analysis methods (e.g. process integration, Life Cycle Impact Assessment, thermo-economic evaluation,. . . ). The description syntax also contains other informations about the model, namely about its history, quality, scope or documentation. The approach encourages the development of reusable models, which can be easily assembled to create large superstructures from which optimal system configurations can be extracted. By dissociating technology models from the analysis and synthesis method, the approach allows the independent development of analysis methods and the consistent data transfer between models of different scales. The study of a fine chemical industry waste incineration system is presented to demonstrate the flexibility of the approach.