Time-dependent Thermoeconomic Modeling and Optimization of the Synthesis, Design and Operation of a Waste Incineration Cogeneration Power Plant.

Valorisation of resources with the cogeneration of electricity and heat from the incineration of wastes is an important issue in modern societies. Present decision models aiming with minimizing the total costs associated with the optimum choice of configuration (synthesis), component design (dimensioning), and operation of waste incineration/cogeneration units. In fact, the time factor which greatly affects certain key decision parameters such as the amount of wastes to eliminate and the electrical and heating demands places on the system (to name just two) renders the problem of synthesis design and operation very complex. The thermoeconomic methodology presented below is a general approach which can be used to respond to the questions: when to invest and reinvest and which technology, configuration, component capacity and performance and modes of operation to adopt. The problem consists of developing the thermoeconomic models (typically very non-linear, continuous and/or non-contiguous) which can be used to minimize the time integral of total costs, optimizing simultaneously the configuration, design and operation of the installation over its entire economic lifetime. The system considered in the paper consists of a waste incineration cogeneration power plant which may include several incinerators, one condensing steam turbine, one extraction steam turbine and one auxiliary boiler.

An Approach for the Time–Dependent Thermoeconomic Modeling and Optimization of Energy System Synthesis, Design and Operation.

Daniel Favrat

From the standpoint of waste elimination and the design and operation of the systems installed, the cogeneration of electricity and heat from the incineration of wastes has become today an important issue in Switzerland. Decision models developed to minimize the total costs associated with such systems respond only partially to the problems associated with the choice of configuration (synthesis), component design, and the operation of the waste incineration/cogeneration unit. In fact, the time factor which greatly affects certain key parameters such as the amount of wastes and the electrical and heating demands placed on the system (to name just two) renders the problem of synthesis, design and operation very complex. The thermoeconomic methodology presented in this article is a general approach which can be used to respond to the questions: when to invest and reinvest and which technology, configuration, component capacity and performance and modes of operation to adopt. The problem consists of developing the thermoeconomic models (typically very non-linear, continuous and/or non- contiguous) which can be used to minimize the time integral of total costs, optimizing simulateously the configuration, design and operation of the installation over its entire economic lifetime.

1997

An Approach for the Time-Dependent Thermoeconomic Modeling and Optimization of Energy System Synthesis, Design and Operation (Part I : Methodology and Results)

Daniel Favrat

From the standpoint of an energetically and economically efficient waste elimination, the design and operation of optimized incineration power plants with the cogeneration of electricity and heat has become today an important issue. Decision models developed to minimize the total costs associated with such systems only partially respond to the problems associated with the choice of configuration (synthesis), component design, and the operation of the waste incineration / cogeneration unit. In fact, the time factor which greatly affects certain key parameters such as the amount of wastes and the electrical and heating demands placed on the system (to name just two) renders the problem of synthesis, design and operation very complex. A thermoeconomic methodology and the results of an application of it to a waste incineration system with cogeneration and a gas turbine topping cycle are presented here as Part I of a series of two articles. The second article (Part II; Olsommer et al., 1999) presents details of the approach used to incorporate reliability and availability considerations into the methodology.

1999

Actor neural networks for the robust control of partially measured nonlinear systems showcased for image propagation through diffuse media

Navid Borhani, Eirini Kakkava, Damien Claude-Marie Loterie, Christophe Moser, Demetri Psaltis, Babak Rahmani, Ugur Tegin

The output of physical systems, such as the scrambled pattern formed by shining the spot of a laser pointer through fog, is often easily accessible by direct measurements. However, selection of the input of such a system to obtain a desired output is difficult, because it is an ill-posed problem; that is, there are multiple inputs yielding the same output. Information transmission through scattering media is an example of this problem. Machine learning approaches for imaging have been implemented very successfully in photonics to recover the original input phase and amplitude objects of the scattering system from the distorted intensity diffraction pattern outputs. However, controlling the output of such a system, without having examples of inputs that can produce outputs in the class of the output objects the user wants to produce, is a challenging problem. Here, we propose an online learning approach for the projection of arbitrary shapes through a multimode fibre when a sample of intensity-only measurements is taken at the output. This projection system is nonlinear, because the intensity, not the complex amplitude, is detected. We show an image projection fidelity as high as similar to 90%, which is on par with the gold-standard methods that characterize the system fully by phase and amplitude measurements. The generality and simplicity of the proposed approach could potentially provide a new way of target-oriented control in real-world applications when only partial measurements are available.

SPRINGERNATURE2020