Soft-sensor design and dynamic model development for a biomass combustion power plant

From a system theory perspective, a biomass power plant is a nonlinear, coupled multivariate system with multiple inputs (fuel feed, air supply, grate speed) and multiple outputs (gas temperature, oxygen concentration, steam generated), where the different process input-output relationships are difficult to understand due to the large disturbances acting on the combustion process, which emanate mainly from the varying calorific value of fuel delivered to the furnace. Hence, any attempt to maintain stable operating conditions and to design or improve the control strategy being employed will lead to suboptimal solutions, which may jeopardize the commercial character of the combustion site. One possible way to handle such a situation is by improving the combustion performance using advanced model-based control strategies for this aim to further ameliorate the economical aspect of the power plant, while adhering to stringent emission standards. These control techniques explicitly incorporate the available process knowledge, which is represented in terms of an available mathematical model, used by the controller to compute the best control actions to fulfill the multiple conflicting goals in the plant. Therefore, mathematical modeling will be carried out to derive a suitable dynamic model of the power plant. The model is extended by designing a soft-sensor which estimates the energy content of fuel mix.Aus systemetheoretischer Perspektive ist ein Biomassekraftwerk ein nichtlineares, verkoppeltes Mehrgr¨oßensystem mit mehreren Eing¨angen (Brennstoffzufuhr, Luftzufuhr, Rostgeschwindigkeit) und mehreren Ausg¨angen (Gastemperatur, Sauerstoffkonzentration, erzeugter Dampfmenge). Dabei werden die unterschiedlichen Beziehungen zwischen Prozesseing¨angen und -ausg¨angen von großen St¨orungen ¨uberlagert, die haupts¨achlich vom variierenden Heizwert der in den Ofen gelieferten Biomasse herr¨uhren. Deshalb wird jeder Versuch, stabile Betriebsbedingungen aufrechtzuerhalten und die eingesetzte Regelstrategie zu verbessen, zu suboptimalen L¨osungen f¨uhren, die den kommerziellen Nutzen des Kraftwerks gef¨ahrden k¨onnen. Eine L¨osungsm¨oglichkeit ist die Verbesserung der Verbrennungsleistung unter Verwendung h¨oherer modellbasierter Regelungsstrategien, um den wirtschaftlichen Aspekt des Kraftwerks unter Einhaltung strikter Emissionsnormen weiter zu verbessern. Diese Strategien integrieren explizit das verf¨ugbare Prozesswissen, das durch ein verf¨ugbares mathematisches Modell repr¨asentiert wird, das vom Regler verwendet wird, um die besten Steuerungsaktionen zu berechnen, die die vielf¨altigen konkurrierenden Ziele in der Anlage erf¨ullen. Daher wird eine mathematische Modellierung durchgef¨uhrt, um ein geeignetes dynamisches Modell des Kraftwerks abzuleiten. Das Modell wird um einen Softsensor erweitert, der den Energiegehalt des Brennstoffs sch¨atzt

Participation of the Algerian Family Members in the Decision Process of Purchasing Food Products

The study of the family has been the subject of several investigations for many years. Most of the research in this area has focused on the roles of family members in decision-making. In this case, this article proposes a quantitative study devoted to the family decision-making process for the purchase of food products. The purpose of this study is to emphasize the consideration of a family-based decision-making concept. The essential idea on which the hypotheses of the present research are based is to know the cognitive, affective, and conative attitudes of each family member, namely the father, the mother and the children. The results of this study should enable companies (agribusinesses, supermarkets, groceries, etc.) to develop an adequate positioning that can meet the needs of members of the family. Keywords:Family structure; Decision-making process; Food products; Algerian family

Myth and Reality of a Universal Lithium-Ion Battery Electrode Design Optimum: A Perspective and Case Study

The quest toward optimal electrode design for energy‐ and power‐demanding applications involves besides experimental effort also less resource‐intensive model‐based studies. The diversity of optimization objectives and benchmark systems complicates the practical utilization of available methods and gained knowledge. Despite the increasing importance of fast charging, electrode design studies commonly focus only on discharge characteristics. This paper features, besides an overview and perspective of electrode structuring concepts and optimization pathways, a model‐based full cell parameter screening of two‐layered electrodes for charge and discharge. The small fraction of cells with superior performance among the evaluated configurations underlines the importance of a joint experimental and model‐based electrode design optimization. The results further indicate that the performance of cell designs tailored for fast charge or fast discharge differs substantially; the gap widens if charging is terminated below 0 V versus Li/Li+ to prevent lithium plating. The broad parameter screening is complemented by a high‐resolution half cell parameter study. Their comparison underlines that the benefit of electrode structuring depends heavily on the study extent and the chosen benchmark. Furthermore, the importance of the parameter space surrounding an optimal electrode design for production with process tolerances is highlighted