Integration of an object formalism within a hybrid dynamic simulation environment

PrODHyS is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of systems engineering. Its major characteristic is its ability to simulate processes described by a hybrid model. In this framework, this paper focuses on the "Object Differential Petri Net" (ODPN) formalism integrated within PrODHyS. The use of this formalism is illustrated through a didactic example relating to the field of Chemical Process System Engineering (PSE)

Dynamic hybrid simulation of batch processes driven by a scheduling module

Simulation is now a CAPE tool widely used by practicing engineers for process design and control. In particular, it allows various offline analyses to improve system performance such as productivity, energy efficiency, waste reduction, etc. In this framework, we have developed the dynamic hybrid simulation environment PrODHyS whose particularity is to provide general and reusable object-oriented components dedicated to the modeling of devices and operations found in chemical processes. Unlike continuous processes, the dynamic simulation of batch processes requires the execution of control recipes to achieve a set of production orders. For these reasons, PrODHyS is coupled to a scheduling module (ProSched) based on a MILP mathematical model in order to initialize various operational parameters and to ensure a proper completion of the simulation. This paper focuses on the procedure used to generate the simulation model corresponding to the realization of a scenario described through a particular scheduling

Scheduling of heat integrated multipurpose batch Processes

A systematic mathematical framework for scheduling the operation of multipurpose batch plants involving heat-integrated unit operations is presented. The approach advocated takes direct account of the trade-offs between maximal exploitation of heat-integration and others scheduling objectives and constraints. In this paper, heat transfer takes place directly between the fluids undergoing processing in the heat integrated unit operations, and therefore a degree of time overlap of these operations must be ensured. The modelling is based on the ERTN formalism and a discrete time MILP formulation

The energy Extended Resource Task Network, a general formalism for the modeling of production systems:Application to waste heat valorization

While real-time control of process plays an important role, it is now increasingly necessary to forecast and plan production systems in order to be energy efficient and to ensure a balance between energy demand and production. In this context, a short-term planning approach of energy supply chain is presented in this paper. Because of the presence of enthalpy balance in the optimization model, the core of this system is based on the formulation and the resolution of a Mixed-Integer Non Linear Programming (MINLP) model. To facilitate the instantiation of this optimization model and its adaptation to different kinds of value chain, a specific graphical formalism named Energy Extended Resource Task Network (EERTN) is exploited. This generic framework makes it possible to model in an unambiguous way the material and energy flows passing through any type of production system. In addition, it takes into account the influence of temperature on the physicochemical phenomena involved in the process. To illustrate the potentiality of this modeling framework, it is applied to a case study aimed at carrying out the operational planning and performance evaluation of a waste heat recovery chain. This system consists, on the one hand of an industrial unit whose heat requirements are provided by a steam utility plant, and on the other hand, of a district heating network (DHN). In this study, the problem consists to optimally plan the energy use of the district heating network by recovering the flus gas (the waste heat) from the industrial site’s power plant. The planning system leads to a significant reduction in the primary fuel consumption of the overall system and an efficient exploitation of the waste heat generated by the industrial site

The extended resource task network: a framework for the combined scheduling of batch processes and CHP plants

The issue of energy has emerged as one of the greatest challenges facing mankind. In an industrial perspective, the development of site utility systems (generally combined heat and power (CHP) systems) for the generation and management of utilities provides a great potential source for energy savings. However, in most industrial sites, a master–slave relationship usually governs this kind of system and limits the potential operating capacity of CHP. To improve the decision-making process, Agha et al. (2010. Integrated production and utility system approach for optimising industrial unit operation. Energy, 35, 611–627) have proposed an integrated approach that carries out simultaneous and consistent scheduling of batch production plants and site utility systems. The modelling of the problem relies on a mixed integer linear programming (MILP) formulation. Nevertheless, although it is a powerful mathematical tool, it still remains difficult to use for non-expert engineers. In this framework, a graphical formalism based on existing representations (STN, RTN) has been developed: the extended resource task network (ERTN). Combined with an efficient and generic MILP formulation, it permits various kinds of industrial problems, including production and consumption of utility flows to be modelled homogenously. This paper focuses on the semantic elements of the ERTN formalism and illustrates their use through representative example

Model based fault diagnosis for hybrid systems : application on chemical processes

The complexity and the size of the industrial chemical processes induce the monitoring of a growing number of process variables. Their knowledge is generally based on the measurements of system variables and on the physico-chemical models of the process. Nevertheless, this information is imprecise because of process and measurement noise. So the research ways aim at developing new and more powerful techniques for the detection of process fault. In this work, we present a method for the fault detection based on the comparison between the real system and the reference model evolution generated by the extended Kalman filter. The reference model is simulated by the dynamic hybrid simulator, PrODHyS. It is a general object-oriented environment which provides common and reusable components designed for the development and the management of dynamic simulation of industrial systems. The use of this method is illustrated through a didactic example relating to the field of Chemical Process System Engineering

Definition of a Robustness Indicator for Assessment of Heat Exchanger Network Performances

Due to process variabilities and operational modifications, operation parameters of the HEN may alter its output temperatures. Flexibility of HEN refers to the ability of a system to operate for a finite number of points. The first level of flexibility concerns the robustness (ability of the system to absorb disturbances without changing utility flowrates). Assuming that some parameters p vary with a normal distribution characterized by its mean value pmean and standard deviation psd, a linear system is solved where the left-hand term involves matrices representing the HEN (fluctuations of the HEN characteristics, except topology) and right-hand side involves fluctuations of input temperatures of the HEN. Due to this linear formulation, the normally distributed inputs also propagate along a normal distribution output temperatures. A robustness criterion is then defined evaluating the probability of a selected critical value output distribution to fall within a predefined interval. This robustness criterion can only be significant when a thorough data analysis is carried out to identify the relevant perturbations and their frequency of occurrence

Formalisme hybride orienté objet pour la simulation dynamique des procédés chimiques

PrODHyS est un environnement orienté objet pour la simulation dynamique hybride des procédés chimiques. Il fournit des composants généraux et réutilisables permettant la construction d’éléments plus spécifiques. Le formalisme développé pour modéliser les systèmes hybrides s’appuie sur le modèle « Réseau de Petri Différentiel à Objets » (RdPDO)

Flexibility Assessment of Heat Exchanger Networks: From a Thorough Data Extraction to Robustness Evaluation

Due to process variabilities and operational modifications, operating parameters of Heat Exchanger Network (HEN) may alter its output temperatures. Nevertheless, the impact of these disturbances depends largely on the topology of the HEN. As a consequence, it can be relevant to evaluate the flexibility of a HEN after its synthesis. Flexibility of a HEN refers to the ability of a system to operate at a finite number of set points. In this framework, the implementation of this property is broken down into several aspects. In this contribution, the first level of flexibility concerning the robustness (ability of the system to absorb disturbances without changing utility flowrates) is addressed and compared to other contribution, this criterion is not formulated as a generic one but as a criterion that strongly depends on the studied process. As a consequence, to evaluate its value, the first step is to perform an enhanced data collection by identifying the most frequent disturbances and by pointing out the critical streams i.e. the streams whose output temperature absolutely needs to be kept into a strict interval; then, given this information, a robustness criterion can be formulated for a given HEN. In this paper, a methodology relying on several models is developed to address this issue: a Mass Equilibrium Summation enthalpy non-linear model (MESH) dedicated to the enhanced data collection, a Mixed Integer Linear Programming (MILP) model used for the HEN synthesis and finally a linear model developed for the modeling of the HEN response to disturbances. This methodology is first illustrated through a basic academic example and finally applied to an industrial case study

Planification hiérarchisée de la production

Moteurs des entreprises et du marché, les systèmes de production transforment les matériaux en biens, les ingrédients en produits. Ils mettent en pratique non seulement nos connaissances techniques et notre savoir-faire, mais aussi notre mode de vie, nos goûts et notre culture. Ils sont au cœur de la société actuelle, et leur complexité croissante est le fruit de leur histoire et de nos exigences. Leur efficacité doit sans cesse être évaluée et améliorée pour rivaliser dans la compétition mondiale, mais leur mode de fonctionnement joue aussi un rôle essentiel de structuration de l’organisation sociale. Les deux impératifs d’efficacité économique et de réalisme organisationnel animent cet ouvrage, en particulier à travers les dualités : optimisation-aide à la décision, planification-réactivité, cohérence-autonomie. Dans ce contexte, l’aide à la décision est apparue aux chercheurs du groupe LAAS-SP comme l’idée maîtresse de leur démarche scientifique et constitue le ciment des contributions qu’ils présentent dans cet ouvrage. Les concepts et outils proposés dans ce livre portent principalement sur la gestion et la commande des systèmes de production. L’ouvrage est à destination des étudiants de troisième cycle en Automatique, Informatique Industrielle, Productique, et des élèves-ingénieurs. Mais il peut aussi intéresser des ingénieurs, des enseignants, des chercheurs et tout public à formation de base scientifique cherchant à mieux comprendre et maîtriser les systèmes de production et plus particulièrement les ateliers manufacturiers. Les principaux objectifs sont : - de proposer des approches d’aide à la décision pour différents niveaux d’organisation d’une entreprise,- de décrire des méthodes de gestion, de supervision et de commande des systèmes de production, - d’expliciter les interactions entre les différents niveaux de décision, à travers des outils de coopération homme-homme et de communication homme-machin