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

Laurent Gabriel Félix Alexandre Stéphane Bungener, François Maréchal, Greta Martha Van Eetvelde

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.

The Italian Association of Chemical Engineering2015

Intégration énergétique de procédés industriels par la méthode du pincement étendue aux procédés discontinus.

Daniel Favrat, Pierre Krummenacher

In pinch analysis, the tools and methods specifically developed for the modeling, the debottlenecking and the rescheduling of batch processes have been rewieved (time slice model, cascade analysis, overal plant bottleneck, time event model, batch cascade curves, ...). The project has been focused on the targeting and on the optimization of indirect heat recovery through storage ; these domains are particularly relevant to food industry (e.g. breweries, dairies, etc.), as well as for buildings. The targeting of batch processes has to deal with the problem of heat exchangers utilised across time slices, reducing the investments costs. To minimize these costs, one has to maximise the common exchange area; this objective is reached extending the methodology developed by other authors for the multiple base cases (MBC) problem. Some limitations of this methodology have been identified and improvements proposed. Unlike rescheduling which is often not possible, heat storage is mainly limited by cost considerations; therefore, major steps of a methodology to quickly assess its profitability have been established in this project. The batch cascade curves are used in an extended form (including some particular pockets) to select the storage parameters (type, operating temperatures), while the new concept of incremental cost determines the contribution of each time slice to the heat tranfered by each storage. The latter variables are the optimized to minimize the total yearly cost. Batch processes can now be tackled using PinchLENI, the process integration software developed at our laboratory. However, several repetitive tasks are still to be done manually. Future work shall include the automation of these tasks to cut the optimisation time, as well as further proposed refinements. In addition to the simple example problems already analysed, several industrial case studies should be used to validate the procedure and formulate improved guidelines.

1995

Design of the heat exchanger network for the SOFC-GT concept

Karel De Raeve

Within the challenge of sustainability, climate change mitigation and energy supply a promising way of more rational energy conversion is decentralized power generation and the co-production of power and heat. The combination of a solid oxide fuel cell (SOFC) with a gas turbine (GT) in an hybrid system is considered as a promising technology in this context. The process performance is highly influenced by the optimal energy integration satisfying cooling and heating requirements. Therefore, the goal of this project consists in the study of the heat exchange phenomena and of the design of the heat exchanger network.