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This paper addresses the synthesis problem of non isothermal interplant water networks by using a mathematical programming approach based on superstructure optimisation. A recently proposed compact superstructure [1] was used and the mixed integer nonlinear programming (MINLP) model modified in order to identify the existence of process water using units wastewater treatment units and hot/cold streams within different plants as well as optimal water flow and heat transfer between the plants. The superstructure includes direct and indirect heat exchange opportunities with a manageable number of hot and cold streams enabling the control of heat exchanger network (HEN) complexity. In addition a compact superstructure reduction strategy is employed in order to reduce the model size. By using those parameters having values of 1 or 0 the existence of superstructure elements of the different plants can be addressed simply without introducing additional variables. The proposed model is solved by using a two?step iterative solution strategy [1]. The first step in the proposed strategy provides initialisation and rigorous bounds on water and utilities consumption. In the second step an MINLP model is solved simultaneously minimising the total annual cost of the network. Different case scenarios were considered analysing water and heat integration within and between the plants. The solutions obtained show that the model can be successfully used for the synthesis of interplant non isothermal water networks thus minimising the total annual cost of the overall network. The results show that additional saving in total annual costs can be achieved by enabling direct water and heat integration between plants.

Surplus electricity production is anticipated to further increase during summer periods due to the inevitable high penetration of renewable energy sources in our energy system. Potential solutions for sustainable and efficient energy storage need to be explored in order to cope with the challenges of the energy transition. Biomass is a promising source of renewable energy that can not only be converted into products, but also into storable fuels. The multitude of products and processes for converting biomass into value-added materials and storable energy necessitates systematic design methods for the generation and analysis of alternative process configurations in order to provide decision support. Due to the high computational time of simulation-based optimization of biorefinery systems, the analysis is often limited to predefined process configurations and operating conditions. Once generated, the results are often only used for one single case study or application. In this work, we suggest a methodology that enables the decision maker to profit from results that are already generated and adapt them to case-tailored system configurations. For this purpose, a database containing the results of multi-objective superstructure optimisation regarding thermo-economic performance of candidate system configurations is used to design surrogate models that predict the thermodynamic performance of the conversion of biomass to SNG, heat and electricity. Furthermore, correlations between modelling inputs and the desired output parameters are revealed. It is shown that artificial neural networks are a suitable tool to predict the thermodynamic behaviour of the biomass conversion plant. Moreover, they allow the decision maker to profit from process data that is already available and to base their decision making off this rather than running computationally expensive simulations. The developed model is adaptable for changes in the input domain, flexible in predicting different key performance indicators and allows for displaying their correlations to different inputs.

Evaporation processes are used within the process industries in order to produce concentrated products by evaporating part of water from different feeds-diluted water solutions. Concentrated products can represent final products (fruit and vegetable juices) or intermediate products in cases that crystalized (salt, sugar) or dried (milk powder) final products should be produced. Large amounts of steam and cooling water are consumed in these processes. In order to reduce energy and water consumption within evaporation processes different systems can be applied, namely, multiple-effect evaporation, vapor recompression (thermal and mechanical) or their combinations. Additionally, these processes can be integrated with other process subsystems in order to achieve improved energy and water integration. To address these issues different computer-aided tools have been proposed. However, most studies have focused on analysis and simulation of evaporation processes. Some of the initial studies [1, 2] considered the synthesis of evaporation processes in order to develop tools for computing the minimum utility use for a multiple-effect evaporation system, which was heat-integrated with process hot and cold streams. These studies were based on a modified grand composite curve and heat-path diagram. Also, the focus of the recent works have been on multiple-effect evaporation systems [3] and their energy integration with the background processes in order to minimize the energy consumption within the overall system [4]. These studies have motivated us to further expand research in this direction, by applying mathematical programming approach for the analysis of existing and the design of new evaporation systems as well as their heat integration with other process subsystems or process streams. The main goal of this paper is to develop models based on mathematical programming that can be applied for the analysis, synthesis and optimization of multiple-effect evaporation systems. The proposed models will be developed in General Algebraic Modeling System (GAMS). The developed models will enable examination of different scenarios of multiple-effect evaporation in order to address the analysis of existing, retrofit and/or design new evaporation process. Within the proposed framework, a network consisting of a multiple-effect evaporation system and heat exchanger network will be investigated in order to achieve the improved heat integration within the overall system. Two strategies will be considered to achieve this task, namely, sequential and simultaneous. The developed models will be tested on several examples, and also applied to different feed streams. New results are expected to be obtained within this field. Keywords: multiple-effect evaporation, analysis, synthesis, optimization, mathematical programming. Acknowledgment The authors are grateful to the Swiss National Science Foundation (SNSF) and the Swiss Agency for Development and Cooperation (SDC) for providing financial support within the SCOPES 2013â??2016 (Scientific Co-operation between Eastern Europe and Switzerland) joint research project (CAPEâ??EWWR: IZ73Z0_152622/1). References: [1] Hillenbrand JJB, Westerberg AW. The synthesis of multiple-effect evaporator systems using minimum utility insightsâ??I. A cascaded heat representation. Computers & Chemical Engineering. 1988;12:611. [2] Westerberg AW, Hillenbrand JJB. The synthesis of multiple-effect evaporator systems using minimum utility insightsâ??II. liquid flowpattern selection. Computers & Chemical Engineering. 1988;12:625. [3] Khanam S, Mohanty B. Energy reduction schemes for multiple effect evaporator systems. Applied Energy. 2010;87:1102. [4] Sharan P, Bandyopadhyay S. Energy Integration of Multiple Effect Evaporators with Background Process and Appropriate Temperature Selection. Industrial & Engineering Chemistry Research. 2016;55:1630.

A circular economy refers to an industrial economy with a cradle to cradle vision, shifting from the use of fossil fuels towards renewable energy, minimizing the use of toxic chemicals and reducing waste by recycling through careful system design. The concept of a circular economy is based on the study of non-linear, in particular living systems, with a major outcome being the optimisation of systems rather than of the individual components which make up each system. Industrial symbiosis (IS) is the exchange of energy, waste and by-products among industries in order to add value, while reducing costs and environmental impacts. This is consistent with the principles of a circular economy, and is a stepping stone towards the design of sustainable economies and policies. In the scope of this study, the use of local and renewable resources and the development of industrial ecology can contribute to the decrease of environmental impacts of a living, interactive system, on a given territory. A process system design framework is developped to model a superstructure that contains the list of possible options for the system. The LCA is used to calculate the environmental impacts of a product or a service. The method requires certain adjustments in order to assess the impacts of a spatially delimited system. The design of such system can be done by combining Life Cycle Assessment (LCA) that can provide a clear and structured framework to assess the environmental impacts of the system and process system design methods that applies mathematical programing techniques to systematically design territorial configurations using costs and thermo-chemical or physical models. The new method allows to generate the most attractive scenarios for the systems using a systematic modeling framework and using an optimisation approach that allows to generate a limited set of pareto optimal configurations that can then be evaluated to identify the most attractive solution. The method has been successsfully applied on a case study of a city with 100,000 inhabitants.

Industrial plant data are difficult to find in academic literature for a number of reasons such as confidentiality, and thus intentional masking, or problem size reduction. These common practices limit the ability of researchers to apply novel methods to real cases and understand energy consumption of real industrial plant instances. This is especially pertinent in the field of process integration, as realistic representations of real processes form the basis for the application of novel technologies. Few efforts have been made in this area, demonstrating the added value of these profiles; thus, a clear methodology is required for constructing such energy consumption profiles. The method proposed in this work defines an approach for constructing the heat profiles of major industries in a generic way. Parameterized models of several major European industries are presented for defining specific production/plant instances based on contextual specificities to represent different production pathways. The profile construction methodology is described for several situations of data access. Confidentiality issues are addressed by different anonymization techniques such as aggregation, statistical treatment, or by using data which are already publicly available. In this work, data were gathered from real plant operations and validated at higher levels using public information. Although the potential applications and implications of these profiles are clear, two cases are presented to exhibit adaptation of the parameterized models to specific instances and profile use for process integration problems. Varying the model parameters represents different plant instances and thus yield different integration solutions for the major process industries included in this work.

Despite commonly reported potentials for emission reduction and efficiency increase, industrial heat pumps have yet to reach wide-scale employment in non-refrigeration appli- cations. The bottlenecks are identified as a general scepticism from process operator side, little incentives from politics, and lack of knowledge of optimal placement and integration techniques. This work addresses these challenges from an environmental and economic (envi- ronomic) standpoint, thereby bridging the gap between problem-specific optimization based studies and broader potential studies. Results from the former are usually too dependent on case-specific input data, to allow generalization of the conclusions, while during the latter heat pump placement is often addressed in a coarse manner. The methodology presented in this work provides guidelines for the generation of a database of optimal solutions which are independent from most volatile input data. A parallel coordinate decision making tool is presented which grants access to the publicly available database encompassing detailed utility design.

Greenhouse gas emission mitigation is one of the main motivations for increasing the use of biomass in providing environmentally friendly value-added products. The pulp and paper industry is a promising sector for the integration of biorefinery pathways. Among different technologies to produce pulp, the Kraft process accounts for 60% of the worldwide pulp production. The by-products of the Kraft process are major resources of biomass that can further be exploited. In the conventional Kraft process, black liquor is concentrated and burned in recovery boilers in order to satisfy the process heat demands and to recover the chemicals. Almost 40% of the heating demand of the process accounts for evaporators in which the black liquor is concentrated for utilization in the recovery boilers. The aim of this work is to investigate the potential of replacing conventional recovery boilers with a hydrothermal black liquor gasification unit. Hydrothermal gasification allows for having high water content black liquor (near 80%). This leads to an increase in energy efficiency of the process by reducing the overall heating demand (via eliminating the energy-intensive evaporation and concentrations stages) and simultaneously generating syngas that can be further processed into biofuels. In order to evaluate this potential, related process flow sheets are built and thermo-economic optimization of the integrated process is conducted. Furthermore, heat integration among the mill and the biorefinery is performed in order to identify the optimal operating conditions of the process. This work is a necessary preliminary step to provide incentives to further analyze the potential of the integration of the two.

This diploma project is a joint effort between Industrial Energy System Laboratory (LENI) of EPFL and CanmetENERGY-Varennes of Natural Resources Canada on the application of advanced process integration methods for the optimal water and energy integration in the context of Canadian pulping mills. The ultimate goal is bridging the researchers from LENI and CanmetENERGY to rethink the conventional methodologies used in combined water and energy optimization. In the context of finding efficient ways of water and energy consumption, the objective of this project is to improve a mathematical superstructure for simultaneous optimization of water and energy in industrial processes. This methodology, first developed by Renard (2011), is refined on several features in the present work. The superstructure is developed using linear programming techniques and is able to employ non-isothermal mixing options to reduce utility consumption. Multi-contaminant problems are also addressed with linear programming. The first part of this work concerns a literature review of the available methodologies on simultaneous optimization of water and energy. A benchmarking analysis is carried out to evaluate these methodologies with regard to different aspects such as mathematical approach and water and heat exchange network indicators. Secondly, non-isothermal Mixing(NIM) is tailored to be used in a linear programming environment by establishing several temperature levels in which NIM can occur at the inlet of water demands. Furthermore, the methodology is adapted to pulp and paper industry context by adding new concepts to the initial superstructure. These are water tanks and restricted matches. The superstructure is evaluated using different examples from the literature. Finally a case study using data obtained from CanmetENERGY validates the developed methodology and provides useful information on the application of this methodology in pulp and paper industry.

District energy systems could be used together with centralized and decentralized energy conversion technologies in order to reduce the amount of CO2 emissions. One way to transfer the produced energy from these technologies to users is to implement the conventional district system with water. However, this will result in huge energy and exergy losses and high costs. One alternative is to use CO2 for heating and cooling purposes. Here, in the first chapter the advantages and disadvantages of CO2 based district energy system compared to conventional one will be illustrated. In the next Chapter, typical energy conversion technologies which can be used in the new system will be presented. Finally, a test case will be demonstrated using and in-house energy optimization tool, OSMOSE for multi period optimization.

This paper addresses the synthesis problem of non-isothermal interplant water networks by using a mathematical programming approach based on superstructure optimisation. A recently proposed compact superstructure (Ibrić et al., 2015) was used and the mixed integer nonlinear programming (MINLP) model modified in order to identify the existence of process water using units, wastewater treatment units, and hot/cold streams within different plants, as well as optimal water flow and heat transfer between the plants. The superstructure includes direct and indirect heat exchange opportunities, with a manageable number of hot and cold streams enabling the control of heat exchanger network (HEN) complexity. In addition, a compact superstructure reduction strategy is employed in order to reduce the model size. By using those parameters having values of 1 or 0, the existence of superstructure elements of the different plants can be addressed simply, without introducing additional variables. The proposed model is solved by using a two‒step iterative solution strategy (Ibrić et al., 2015). The first step in the proposed strategy provides initialisation and rigorous bounds on water and utilities consumption. In the second step, an MINLP model is solved, simultaneously minimising the total annual cost of the network. Different case scenarios were considered, analysing water and heat integration within and between the plants. The solutions obtained show that the model can be successfully used for the synthesis of interplant non-isothermal water networks, thus minimising the total annual cost of the overall network. The results show that additional saving in total annual costs can be achieved by enabling direct water and heat integration between plants.

Efficient consumption of energy and material resources, including water, is the primary focus for process industries to reduce their environmental impact. The Conference of Parties in Paris (COP21) highlighted the prominent role of industrial energy efficiency in combatting climate change by reducing greenhouse gas (GHG) emissions. Consumption of energy and material resources, especially water, are strongly interconnected; and therefore, must be treated simultaneously using a holistic approach to identify optimal solutions for efficient processing. Such approaches must consider energy and water recovery within a comprehensive process integration framework which includes options such as organic Rankine cycles for electricity generation from low to medium temperature heat. This thesis addresses the issue of how to efficiently manage energy and water in industrial processes by presenting two systematic methodologies for the simultaneous optimization of heat and mass and combined heat and power production. A novel iterative sequential solution strategy is proposed for optimizing heat-integrated water allocation networks through decomposing the overall problem into three sub-problems using mathematical programming techniques. The approach is capable of proposing a set of potential energy and water reduction opportunities that should be further evaluated for technical, economical, physical, and environmental feasibilities. A novel and comprehensive superstructure optimization methodology is proposed for organic Rankine cycle (ORC) integration in industrial processes including architectural features, such as turbine-bleeding, reheating, and transcritical cycles. Meta-heuristic optimization (via a genetic algorithm) is combined with deterministic techniques to solve the problem: by addressing fluid selection, operating condition determination, and equipment sizing. This thesis further addresses the importance of holistic approaches by applying the proposed methodologies on a kraft pulp mill. In doing so, freshwater consumption is reduced by more than 60%, while net power output is increased by a factor of six. The results exhibit that interactions among these elements are complex and therefore underline the necessity of such methods to explore their optimal integration with industrial processes. The potential implications of this work are broad, extending from total site integration to industrial symbiosis.

In this project we are studying the design of district energy networks together with operation and investment optimization, as well as CO2 emissions, with different combination of available conversion technologies such as Biomass Gasification, Organic Rankine Cycle and Incinerators, including renewable resources like solar and biomass resources, to satisfy the energy demand in urban area. We use Energy Integrations concept for this purpose, as well as system modeling to simulate different conversion technologies.

The synthesis problems of non‒isothermal water networks have received considerable attention throughout academia and industry over the last two decades because of the importance of simultaneously minimising water and energy consumption [1]. Most papers have addressed this issue only by considering heat integration between hot and cold water streams. In this study, the scope of heat integration is expanded by enabling heat integration of process streams (such as waste gas streams and reactor effluent streams) together with the water network’s hot and cold streams. This approach integrates the non‒isothermal water network synthesis problem with the classical heat exchanger networks (HENs) synthesis problem by considering them simultaneously as a unified network. A recently proposed superstructure [2] for the synthesis of non‒isothermal process water networks is extended to enable additional heat integration options between hot/cold water streams and hot/cold process streams. Within a unified network, heat capacity flow rates and inlet and outlet temperatures are fixed for process streams, and variable for water streams. The complexity of the overall synthesis problem increases significantly when compared to the syntheses of both networks separately. Therefore, solving this types of problem is more challenging. The objective function of the proposed mixed integer nonlinear programming (MINLP) model accounts for operating costs (including fresh water and utilities) and investment costs for heat exchangers and treatment units. The results indicate that by solving a unified network, additional savings in utilities consumption and total annual cost can be obtained, compared to the sequential solution obtained by solving both sub‒networks separately. Thus, more efficient water networks can be designed.

Due to the global increase in energy consumption, greenhouse gas emissions, and the depletion of fossil energy resources, the research presented here is focused on finding economically and environmentally competitive renewable energy resources. Fuel production from biomass is an attractive solution in this regard. Competing interests between food and energy have yielded increased interest in lignocellulosic biomass (LGB) as a feedstock. Processes such as biodiesel production from palm oil generate large volumes of LGB residues. Valorization of these residues through biorefineries may bring economic and environmental benefits through substitution of fossil fuels and such options must be studied in a systematic manner. The goal of this research is to propose a methodology for economic and environmental analysis of such biorefineries. A case study of a palm-based biorefinery in Brazil is used to illustrate this. Results indicate that multi-product processes can yield significant cost and environmental benefits.