Assaad Zoughaib

Methodology for preselecting heat-integrated mass allocation networks likely to be associated with cost efficient HEN

Abstract Instead of being discarded to the environment with costly treatments, process effluents can be reused and valued for their mass and heat content. This may result in substantial operating costs reduction but require important capital costs. Based on models developed by Ghazouani et al. (2015a,b), a new methodology is proposed to select mass allocation network designs that can potentially lead to an economically interesting heat exchangers network (HEN) without having to design the latter. In the new objective function, an estimation of the associated HEN capital costs is added to the operating costs (fresh sources and utilities consumption). HEN costs take into account the number of mass streams requiring heating or cooling and a rough estimation of necessary heat exchange surface. Moreover, mixer units are introduced into the initial superstructure to further reduce the number of mass streams participating in the HEN. The selection of the most cost effective units among infinite possibilities is made easier by the changes done to the model previously mentionned. Besides, the model resolution speed allows evaluating fairly quickly many possibilities and selecting the most promising ones. The methodology can be very helpful for sequential or simultaneous models designing mass allocation and heat exchangers networks. In this article, HEN design is done sequentially, using an established linear model (Barbaro and Bagajewicz (2005)). The relevance of the proposed methodology is assessed through a case study detailed in a previous work (Ghazouani et al. (2015a)).

Is Wood Waste Only for Burning? A Methodology for Best Pathway Identification of Waste Recovery

Abstract Industry has always looked for maximizing on-site synergies using energy and mass integration methods, rather independently. However, considering the component valorisation in its original form, corollary implies missing the reuse opportunities of the component in another form. The conversion brings the possibility of turning the non-usable waste into another usable energy or material through chemical processes, and allows its reinsertion in the system. Hence the inclusion of these processes enables exploring new paths for the recovery of waste streams and bridging the gap between the two integration methods. This paper introduces a methodology which couples Energy and Mass integration techniques through conversion processes, in the aim of finding the best valorisation pathway of waste streams in a local context. In this methodology, the valorisation pathways are driven by the local demand leading to the synergies maximization. Indeed modelling the local demand profile will indicate the feasible pathways through identifying the needs. The best pathway will hence be determined through detailed economic evaluation. The proposed methodology is demonstrated on a case study considering a large industrial site where waste wood valorisation is assessed. Since waste wood has multiple valorisation pathways by its conversion to energy or to another high added value material, the proposed methodology will serve as a tool for the identification of the best economic valorisation solution. Each of these conversion pathways is modelled and validated with literature results. In this case study, waste wood valorisation through heat and power generation, hydrogen or methane generation is challenged using economic criteria. For each possible waste wood conversion system, the obtained superstructure is analyzed through Energy and Mass integration methods for each set of the objectives.

An MILP model for the simultaneous design of mass and heat networks of a collaborative eco-industrial park

Abstract Process integration methodologies have greatly addressed the issue of designing optimal heat and mass recovery networks at the process scale. Lately, with the advent of the concept of industrial ecology, the interest for exploring untapped synergies between industrial sites has arisen; aiming at reducing their resources consumption and the operating costs; thus, forming an eco-industrial park (EIP). In such structure, sharing resources can be done either directly or indirectly through intermediate networks for economic or safety reasons. In this perspective, a new model has been developed to design heat and mass recovery networks between industrial sites on a territorial scale. Based on an MILP model (Ghazouani et al., 2017) optimizing recovery networks at a process scale, specific concepts are added enabling exchanges between companies (sites, clusters, and intermediate mass and heat networks). The purpose is to find a collaborative partnership defined by a global economic objective without taking into account individual economic strategies. A case study is developed based on a virtual industrial zone containing three independent processes found in the literature. In addition, potential interactions with urban water and heat networks are considered in this case study. Finally, an additional opportunity to use low grade heat locally via a thermal membrane distillation unit and to transform it into fresh water is introduced. A sequential methodology is proposed consisting of first optimizing individual cluster. Then, the remaining requirements met by external utilities as well as the wastes not recovered internally in each cluster are made available to others through the intermediate networks. Overall, despite the sharp increase in capital costs, the optimal EIP manages to be profitable in many considered scenarios. The cooling utility savings are very important in all the cases (more than 80% of the operating costs). The marginal heat and water costs for the urban networks are very competitive. This suggests that, in this case of a cooperative relationship between industrial sites, the sharing and selling of resources and wastes can be profitable.

An MILP model for simultaneous mass allocation and heat exchange networks design with regeneration units

Abstract Environmental standards impose strict specifications for waste treatments to be able to discharge them. These regulations are more and more constraining because sustainability and pollution prevention place high in political agendas. Consequently, waste management can represent a considerable and unavoidable financial burden for companies. It can require heavy investments and account significant part of annual operating costs. Therefore, it can be economically interesting to reuse waste effluents generated by industrial processes and use them as resources to supply heat and matter to the process. But, it still may be necessary to treat parts of these waste effluents to either recycle them more easily or comply with environmental standards to discharge them. In this perspective, this paper proposes a new mixed integer linear programming (MILP) model to design economically optimal mass allocation and heat exchangers networks (MAHEN) including regeneration technologies. This model allows evaluating their impact on the mass and heat integration of a process. For this purpose, a novel approach is introduced to represent any type of regeneration units with a generic formulation. This formulation is added to the MILP model presented by Ghazouani et al. (2016). A phenol production case is used to illustrate the model potentials. In this case study, the purpose is recovering wastewaters polluted with phenol. The results show that the new model of treatment units helps to generate applicable results and, in this case, to find MAHEN structure that allows being independent from any fresh water source while reducing heat requirements, and the wastes generated by the process, making it more cost-efficient. The main limitation of the linear formulation of regeneration unitsḿodel is the decoupling between the inlet and outlet streams properties. However, this type of model allows understanding the influence of regeneration technologies on the mass and heat integration of processes.

Optimal Sensor Network Design to Monitor the Energy Performances of a Process Plant

Abstract Nowadays, there’s an increased interest in industry for the energy audit, whose objective is identifying opportunities to improve energy efficiency. The analysis of the energy performances, for industrial processes, requires the knowledge of the physical quantities involved in the energy and mass balances, and therefore, the establishment of a sensor network. Many studies were conducted to solve this problem. However rare are those which helped reducing the computing time substantially for medium and large size problems. This paper introduces a methodology for finding the optimal sensor network to be installed in a process plant. Using a parallelized combinatorial search associated with a verification function, the proposed sequential methodology identifies a suboptimal set of possible sensor networks to be adopted, in ascending order of number of sensors. This methodology is tested on a starch concentrator (medium size problem), showing an effective reduction of computational time.