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Decarbonizing industrial processes is crucial for achieving net-zero targets, with process heat electrification emerging as a key pathway. Heat pumps (HPs) are pivotal for this transition. This study introduces a novel methodology to construct exemplar profiles for specific energy demands, representative profiles for various production capacities, and energy demand profiles at product, subsector, or sector levels, using Swiss chocolate production as a case study. Exemplar profiles offer flexibility in generating representative profiles based on production capacities, aiding in identifying integration opportunities and sizes for HPs. Sector-wide profiles provide a broader perspective, aiding in visualizing bottom-up sector-wide potential for HPs. Based on the analysis of four representative profiles for Swiss chocolate production, two potential standard heat pump (SHP) and three high-temperature heat pump (HTHP) integration opportunities were identified. Techno-economic data from 30 commercially available HPs were collected, assessing their cost-effectiveness for Swiss chocolate manufacturing using the levelized cost of saved energy and CO 2 abatement. Factors such as company size and electricity and natural gas prices impact the cost-effectiveness of HP integration. Despite variations, HPs with real coefficients of performance above 2.6 generally prove cost-effective for average energy prices and current CO 2 levies in Swiss chocolate production. Bottom-up estimations of HP integration potentials using product-specific energy demand profiles suggest a potential reduction of CO 2 emissions by up to 56% and an improvement in energy efficiency by up to 28% in Swiss chocolate production. • Bottom-up sectorial profiles are used to identify HP integration potential. • HP integration can potentially achieve up to 56% CO 2 abatement. • HP integration can potentially achieve up to 28% reduction in energy demand. • All HPs with COP greater than 2.6 are cost-effective except for very small companies. [ABSTRACT FROM AUTHOR]

Process heat electrification, energy efficiency improvement, and renewable technology integration are the most effective ways of achieving industrial decarbonization. However, precise knowledge of thermal energy demands and excess heat sources along with the corresponding temperature levels is imperative for the most optimum integration of aforementioned process. The current study presents a novel methodology for constructing sector-wide composite curves to accurately characterize the thermal energy demands and the available excess heat sources for the Swiss industry subsectors. The sector-wide energy demand profiles derived from this methodology offer valuable insights into the quantity of heat demand and the quality of the available excess heat. Thus, enabling the implementation of energy efficiency and decarbonization technologies such as heat pumps, and renewable heating and cooling technologies. The sector-wide energy demand profiles are built using Pinch Analyses and top-down statistical approach, thus ensuring complete sectoral coverage. The application of this novel approach is demonstrated using Swiss meat and chocolate industry subsectors as case studies. Based on the sector-wide energy demand profiles developed for meat and chocolate production, heat pump integration and solar thermal integration can potentially reduce about 80% of process heat demand, for both sectors. • A method was developed to estimate thermal energy demands of industry. • The method combines Pinch Analysis and statistical analysis. • The method estimates the thermal energy demands for Swiss chocolate and meat sectors. • The method allows the estimation of energy efficiency measures potentials. [ABSTRACT FROM AUTHOR]

Abstract Circular Economy has emerged as a popular research topic that is shaping public policy in Europe, China, America and elsewhere. It complements the conceptual basis of the Industrial Ecology framework, but places more emphasis on business models to create closed-loop material systems. However, the Circular Economy concept currently lacks robust engineering design methods, leading to many researchers question its effectiveness. In contrast, Process Integration is lesser known publicly, despite being widely applied in industry to achieve substantial reductions in industrial energy, water, and utility use. These three areas have developed in parallel with minimal cross-pollination, but are in fact potentially complementary. This contribution proposes the new unified concept of Circular Integration for greater transdisciplinary research cohesiveness in the sustainable development of processes, industries, and economies. Circular Integration combines elements from Process Integration, Industrial Ecology, and Circular Economy into a multi-dimensional, multi-scale approach to the minimisation of resource and energy consumption. Circular Integration thus provides an engineering toolbox for planning a Sustainable and Circular Economy. To demonstrate its potential, the paper presents a case study on sustainable biofuel production. The possible solution leverages existing industrial resources to potentially produce enough fuel to fulfil 37% of current demand for global air and marine transport. The Circular Integration framework can also be generalised to systems other than transport and energy, aiming to catalyse greater transdisciplinary research for the analysis, design, and implementation of sustainable and circular systems. Highlights • A new Circular Integration framework is developed to support a Circular Economy. • The framework uses insights from Industrial Ecology and Process Integration. • Its implementation creates new prospects for transdisciplinary research. • Global air and marine transport is analysed to demonstrate the new framework. [ABSTRACT FROM AUTHOR]

Increase in energy efficiency and reduction in greenhouse gas (GHG) emissions in industry are important steps towards a more sustainable economy. Due to the growing share of high value-added industries multi-period operation becomes more common in process industry. Therefore, retrofit of existing multi-period production plants is a key aspect towards more sustainable production processes. Hence, in this work, an existing two-level evolutionary algorithm using a genetic algorithm and a differential evolution for multi-period heat exchanger network retrofit is extended to consider GHG emissions as a second objective to the total annual cost (TAC). The multi-objective problem is addressed by incorporating a non-dominated sorting genetic algorithm (NSGA-II) and hypervolume indicators into the algorithm. By analyzing an industrial case study of a potato chips production, the results of the multi-objective optimization shows that GHG emissions can be reduced by 50%. However, compared to the single-objective optimization, TAC is increased by 27%. By selecting capital costs and operating costs as objectives instead, similar results to the single-objective optimization are achieved showing that the results are highly dependent on the selection of the objectives. Further, changes in utility costs and caused emissions have a high impact on the results. [Display omitted] • Evolutionary two-stage optimization algorithm for heat exchanger network retrofit. • Multi-objective optimization considering costs and greenhouse gas emissions. • Using NSGA-II and hypervolume indicators to generate and evaluate Pareto fronts. • The influence of objective functions selection on the final design is emphasized. • Application of the algorithm to an industrial case study in food industry. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate the feasibility of hydrothermal liquefaction (HTL) of Radiata pine with black liquor from an existing Kraft pulp mill. The biomass into the HTL process was assumed at 2000 t/day and converted into bio-crude through the HTL process and upgraded to produce a gasoline and diesel blend. The HTL process was scaled-up based on an existing published patent. Mass and heat balance of the process was obtained through the process simulator, Aspen Plus. Process Integration was carried out to minimise the hot and cold utility of the process. The production rate of the process is 78.7 kt/y of fuel. The minimum fuel selling price (MFSP) was estimated at 0.95 USD/LGE (litre gasoline equivalent). A sensitivity analysis was carried out to determine the MFSP in 2017 and to study the changes of MFSP due to the uncertainty in the capital cost estimation. [ABSTRACT FROM AUTHOR]

This paper aims to develop a novel method to visualise and solve Total Site Mass, Heat and Power Integration problem using a combination of Process Integration and P-graph techniques. Previous methods dealing with mass, heat and power integration are based on Mathematical Programming, which has the disadvantage of lacking adequate visualisation tools during the construction and optimisation of the problem. It also can face computational issues as problems become increasingly complex. The new method incorporates three important process engineering tools: (1) process modelling of mass and energy balance, (2) Pinch Analysis of individual processes and Total Site Heat Integration of clusters of related processes, and (3) the construction of a Total Site superstructure within the P-graph framework to represent the possible mass, heat, and power interconnections between process and utility systems. To demonstrate the method, a biorefinery case study is investigated. The basis for the biorefinery is a Kraft pulp mill in combination with three potential processes, combined heat and power, and geothermal steam. The three considered new processes are gasification for dimethyl-ether production, simultaneous scarification and co-fermentation of pine for ethanol production, and hydrothermal liquefaction for bio-oil production. Results from the case study show the current optimal solution as a Kraft mill with geothermal heat achieving a profit (revenue less energy and capital costs) of NZD $283 M/y. A near-optimal solution has hydrothermal liquefaction added to the Kraft mill with geothermal heat with a profit of NZD $252 M/y. [ABSTRACT FROM AUTHOR]

• Evolutionary algorithm for multi-period heat exchanger network retrofit. • Additional constraints are implemented to ensure practical results. • Mixer configurations to ensure a flexible network are investigated in detail. • Lambert W-function is used for the explicit temperature calculation. [Display omitted] In Swiss process industry, process integration is often applied to retrofit existing plants with multi-period operation. Such periods may experience a high degree of variation in temperature or mass flow. Some process streams may not exist in every period or are soft streams. The resulting retrofitted network needs to be able to ensure feasible heat transfer in each period by the integration of mixer configurations to control the temperature. These attributes increase the complexity of the solution space. Hence, this work proposes an evolutionary two-level algorithm for heat exchanger network retrofit. Genetic algorithm is used for topology optimization and a differential evolution algorithm handles the heat loads. The algorithm is extended with practical constraints such as a maximum number of heat exchangers. Explicit mixer temperature calculations are implemented using the Lambert W-function. The algorithm was successfully applied to an industrial case study, reducing its total annual cost by approximately 66%. [ABSTRACT FROM AUTHOR]

This paper aims to establish a new standard process for heat and mass integration of hydrothermal liquefaction, co-located with an existing Kraft pulp mill, to produce bio-crude. Hydrothermal liquefaction is an energy-intensive process that operates at high temperature and pressure and produces a biocrude similar to conventional crude oil. The key advantages of installing hydrothermal liquefaction in proximity with a Kraft Mills enables the use of black liquor as a feed to hydrothermal liquefaction, asset repurposing and optimisation, as well as supply chain and logistics integration. This work follows a design process to increase the energy efficiency of the hydrothermal liquefaction process by using an iterative mass and heat integration procedure to optimise mass and energy flows and assets of the hydrothermal liquefaction process. The method uses process simulation tools, Pinch Analysis, heat exchanger network design tool, and the understanding of the process constraints to develop a heat exchanger network for the hydrothermal liquefaction process with maximum energy recovery, minimum number of units and enhanced mass integration. The number of heat exchangers in the network reduced from 14 to 7 when the proposed method was applied. Substituting bio-crude from the new integration hydrothermal liquefaction process for conventional fuels has the potential to decarbonise transport fuels by 11.3 kg CO 2 -e/GJ of fuel. • Developed an iterative procedure to optimise process mass and energy flows. • Applied the new procedure to an emerging technology, hydrothermal liquefaction. • Identified critical processing constraints to ensure practical energy recovery design. • Reduced heat exchanger units in final design by 50% and maximised energy recovery. [ABSTRACT FROM AUTHOR]

Due to the nature of non-continuous processes, heat recovery through direct heat integration is limited. Thermal energy storage (TES) is usually employed for indirect heat transfer, provided excess heat sources and sinks are available. Such processes may have brief peaks in energy demand, necessitating large TES. However, practical space constraints often limit maximal storage volumes, restricting the potential for heat recovery. This paper aims to develop a linear programming optimization model to determine the storage integration solutions which maximize heat recovery per batch for volume-limited sensible stratified storage. Indirect source and sink profiles are used to determine maximum process heat recovery and subsequently the initial TES capacity. The results produce a process-specific capacity limitation chart of batch-wise maximal heat recovery, allowing generation of optimal storage loading and unloading profiles. The optimization model was applied to two case studies. The resulting capacity limitation chart shows that a stratified storage, with a volume of total 96 m 3 is needed to achieve 100 % of the trageted direct and indirect heat recovery. Approximately 60 % heat recovery can already be achieved by using only a 4 m 3 storage. The model is extended to a fixed temperature variable mass storage with multiple VSUs. Image 1 • Developed an optimization model to maximize heat recovery for volume-limited storage. • Applied the model to stratified and fixed temperature variable mass storages. • Optimized the loading and unloading profiles for maximum heat recovery. • Identified critical volumes for storage design. [ABSTRACT FROM AUTHOR]