Optimal operations and resilient investments in steam networks

Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience

Resilient decision making in steam network investments

Steam is a key energy vector for industrial sites, used for process heating, direct injection and stripping, tracing and cogeneration of mechanical power. Steam networks transport steam from producers to consumers and across different pressure levels. The steam production equipments (boilers, cogeneration units and heat exchangers) should be dimensioned to always supply key consumers as well as to deal with extreme demand caused by exceptional events such as unit startups or extreme weather. An important issue to be dealt with is that of unexpected boiler shutdowns, which can take significant amounts of time to bring back online. In cases where demand surpasses the available production of steam, load shedding is necessary in order to keep the network operable. A penalty cost can be associated to load shedding. A well dimensioned steam network is one which is resilient to such events, being able to overcome extreme demand and unexpected boiler shutdowns at minimum cost. This paper proposes a methodology for evaluating the operability of a steam network when facing unexpected boiler shutdowns. A Monte-Carlo simulation is carried out on a multi-period steam network problem, randomly shutting down boilers according to their failure properties (probability of failure and duration of failure). The aim of this method is to evaluate how resilient a steam network is to boiler shutdowns. The Monte-Carlo simulation is applied to a steam network model built using a Mixed Integer Linear Programming (MILP) formulation, whose objective function is to minimise the operational costs of the steam network and therefore also to minimise the penalty costs associated to load shedding. A case study based on anonymised industrial data is used to demonstrate the method. Two investment propositions are evaluated and compared using the proposed method

Volunteering in Palliative Care in France: “A Tough Job”; Patient, Family, Caregiver, and Volunteer Perspectives

This chapter discusses the place of volunteering in palliative care in the context of hospital services in France, and the meaning each actor gives to that presence. Its aim is to go beyond general normative discourse on the role of these volunteers in order to highlight their actions from a little-explored perspective (awkwardness, fears, reticence their activity can create) but one essential to their development. We attempt to understand how (and within what work settings) personnel and volunteers “work” together, and how that lay presence is perceived by patients and families. This research is based on a literature review and individual semi-structured interviews with patients, families, medical personnel, and volunteers in 10 hospitals. In all, 114 persons were interviewed in three work settings: palliative care units, mobile palliative care teams, and traditional services. The analysis highlighted a diversity of perceptions on volunteering, as a function of the type of actors involved and the work setting. It raises the question of the role of nonprofessional actors in hospitals, and of what form volunteering in palliative care should take in France, where volunteers explained they “are there” not “to do”, but just “to be there out of human solidarity”

Virtual sector profiles for innovation sharing in process industry : sector 01: chemicals

Production data in process industry are proprietary to a company since they are key to the process design and technology expertise. However, data confidentiality restrains industry from sharing results and advancing developments in and across process sectors. Using virtual profiles that simulate the typical operating modes of a given process industry offers an elegant solution for a company to share information with the outside world. This paper proposes a generic methodology to create sector blueprints and applies it to the chemicals industry. It details the profile of a typical chemical site based on essential units and realistic data gathered from existing refineries and chemical plants

Information Needs in Palliative Care: Patient and Family Perspectives

International audienc

Économie et santé

Très tôt attirée par la médecine et plus encore par la génétique, Martine Bungener entame, après un baccalauréat de mathématiques, des études de biologie à Paris en 1966-67. Désenchantée par le discours pessimiste de certains enseignants sur ses perspectives d’avenir, elle se retrouve finalement sur les bancs de l’université de Nanterre et soutient en 1970 un mémoire de master sur l’économie de la santé, sept ans après l’article précurseur de l’économiste américain Kenneth J. Arrow. Elle explique comment une discipline aujourd’hui phare a pu trouver sa place dans la société

Modelling of a steam network using data reconciliation as a management tool

The first step towards managing and optimising the steam network of an industrial cluster or plant is to accurately measure the production and consumption of the different levels of steam. Measurement errors as well as unmeasured contributors lead to inaccurate and open balances. Consequently, operations can be unclear to engineers and costs to managers. Furthermore, steam losses, purges and thermal losses add additional unknowns to an already underdetermined problem. In this study, a flowsheeting tool with data reconciliation techniques is used to model a refinery, closing the steam balances and simulating the steam flows throughout the network. An accurate representation of the refinery’s steam distribution network and its units’ internal steam consumers and producers was the base of the model. Hundreds of online measurements and operator observations gave rise to a redundant and coherent model able to calculate the reconciled steam flows through each node as well as unmeasured flows at each time step. Calculations of steam losses were made possible thanks to a continuous site wide survey of leaks and an algorithm for their accounting. Online and archived measurements were exploited in order to calculate key performance indicators and to verify assumptions over long periods of time. With this method the refinery is able to rigorously allocate energy costs to the steam consumption. A better understanding of the site’s steam network and improvement possibilities is also obtained through reconciled and centralised data and an analysis of key performance indicators as well as steam and thermal losses. The result of this work is also tool for the strategic management of the steam network of the refinery, allowing for the simulation of OPEX improvement scenarios and their related CAPEXs, therefore obtaining a classified list of actions to improve costs