Sequential Methodology for Scheduling of Heat-Integrated Batch Plants

Production of lignocellulosic ethanol still suffers the drawback of high production cost. Methods for making the process more cost efficient are therefore of high importance for commercialising large-scale production. One way of improving the process economics is to ensure efficient heat integration within the process, thereby reducing process energy costs. Another opportunity to improve production costs is to design the process for high solids loading in the bioreactors. By operating the process with higher solids concentrations (so-called high-gravity), water flows through the process will be reduced, which would enable smaller equipment and lower energy demand for downstream separation and purification of the ethanol product. However, problems with pumping and mixing are also likely to occur due to higher viscosities. Furthermore, the yield will be lower due to increased concentration of inhibitors. In addition, the opportunities for heat integration within the process will be affected. In this paper, the effect on heat integration opportunities of the high gravity concept is investigated for ethanol production in a stand-alone process in which fractionation of the softwood raw material is assumed to be achieved with steam explosion. Estimations of how the process economics will be affected are also provided.

A typical heat-integrated water network (HIWN) synthesis problem aims to minimise freshwater and utility consumption while establishing trade-offs between operating and investment costs by exploring different water and heat integration opportunities. Heat integration between hot and cold water streams is performed to save external heating and cooling utilities required to achieve the target temperatures of these streams. This paper proposes a mathematical programming approach to integrate water-to-water heat pumps into the HIWNs. A simple cascade heat pump system with isobutane as a natural working fluid enables a larger temperature lift between the heat pump source and the sink. The objective function of the proposed mixed-integer nonlinear programming (MINLP) model is to minimise the total annualised cost (TAC). The TAC includes operating costs for freshwater, heating/cooling utilities, electricity, and investment in heat exchangers and heat pumps. A sensitivity analysis is performed to evaluate the economic feasibility of the system by varying the heating/electricity cost ratio and depreciation period for the capital investment. The results show that additional utility savings can be obtained by integrating heat pumps into the HIWNs. For threshold problems, a heat pump is feasible for heating/electricity price ratios from 1.175, and heating utility is replaced by electricity for a 1:1 ratio. However, for pinched problems, the feasibility of the heat pump is shifted to lower heating/electricity price ratios, from 0.3 to 0.5, depending on the annualisation factor for the investment.

Optimal scheduling of cyclic batch processes for heat integration—I. Basic formulation

Optimal scheduling of batch plants satisfying multiple product orders with different due-dates

Batch processes have been extensively used in the process industries due to their appropriateness for small volume scale productions, high value-added products, as well as their adjustability to rapid market changes. Heat integration in a batch process can be carried out in two ways directly or indirectly. Direct heat integration is straight transfer of heat from hot to cold stream through heat exchanger, while for indirect heat integration, an intermediate fluid is involved which carries heat from hot to cold stream. In batch process, transfer of heat from one interval to another interval requires intermediate fluid. The usage of intermediate fluid needs pumping, piping, capital investment, and space. These are important aspects for any process while considering space limitation and capital investment. Minimizing intermediate fluid provides reduction in all these important fronts. In this paper, a graphical algorithm is developed to determine minimum requirement of intermediate fluid flow among time intervals while satisfying the minimum utility targets. The proposed algorithm is proved to be optimum rigorously and illustrated via examples.

The integration of energy and mass processes is one of the most powerful tools for creating sustainable and energy efficient production systems. Process integration covers a wide range of system-oriented methods and approaches that are used in the design and reconstruction of industrial processes to obtain optimal use of resources. Traditionally, methods have focused on energy efficiency, but more recently they have also covered other areas, such as the integration of mass processes for the efficient use of water and other resources.In production systems with batch processes, the task of energy integration is significantly more complex due to the presence of predominantly low-potential heat, which until recently was considered not to be recoverable. In addition, the periodic and discrete nature of heat sources and recipients imposes additional constraints that require process coordination. Two main approaches for thermal integration of periodic processes are defined, direct and indirect: Direct heat integration determines the existence of heat exchange between technological flows that occur simultaneously over time. This approach to heat recovery requires adherence to a strict production schedule to ensure energy efficiency and product quality. In the chapter different variants for direct heat integration are considered, with recirculation of the main fluids, or with the use of intermediate heating and cooling agents. The corresponding mathematical models are derived. Indirect heat integration determines the existence of heat exchange between flows that do not occur simultaneously in the system. This approach uses intermediate fluids and a heat storage system (heat tanks) so that the heat can be stored, transferred, and utilized in a future period of time. It allows the heat exchange process to be less limited and less sensitive than schedules and provides some operational flexibility. The possibilities for heat integration with the use of one common cold/hot heat tank and two separate ones, but with a common heating/cooling agent are considered. The respective mathematical models are also presented. Key wordsDirect heat integrationRecirculation main fluidsIntermediate heating and cooling agentsIndirect heat integrationTwo heat storageOne heat storage

The methanol-to-olefins (MTO) process offers a viable alternative to traditional naphtha cracking for producing light olefins, providing flexibility in feedstock sources and the potential for reduced energy consumption. This study presents a detailed plant-wide design of an MTO process, developed and optimized to increase ethylene and propylene yields while reducing energy consumption. The methodology includes comprehensive reactor modeling of a fast fluidized-bed reactor–regenerator system, accounting for coke formation kinetics, along with rigorous process simulation for the subsequent separation and purification of products. A six-column distillation train has been designed and optimized for the recovery of polymer-grade ethylene and propylene, while dual-stage CO2 absorption units ensure complete removal of carbon dioxide. Pinch analysis is used to identify opportunities for heat integration, resulting in an optimized heat-exchanger network that significantly reduces the need for external heating and cooling utilities. The results show that the optimized MTO design achieves a methanol conversion rate of over 99.9% and produces a propylene-rich product stream with a propylene-to-ethylene ratio of approximately 1.8, while maintaining a high purity level exceeding 99.5%. By implementing heat integration and recycling by-products, including using off-gas methane as furnace fuel and repurposing waste heat for steam generation, the plant reduces utility requirements by more than 85%, significantly improving energy efficiency. An economic evaluation shows a favorable payback period of approximately 5.4 years and an internal rate of return of 15–16%, confirming the viability and industrial potential of the integrated MTO process for sustainable olefin production.

Modeling and Optimization for Short-term Scheduling of Multipurpose Batch Plants

This work addresses the indirect heat integration (i.e. resorting to intermediate heat storage) and the direct heat integration (i.e. heat exchanges between coexisting process streams) of batch processes. Tools and methods for the targeting of these two limiting cases of heat integration are proposed, and completed by the development and the application of an automatic design & optimization methodology using the Struggle genetic algorithm (GA). A brewery process is used to demonstrate the feasibility and the practical relevance of the proposed indirect heat integration models. The fluctuations of the process schedule and their effects on the optimal solutions are not modelled (the indirect heat integration is known to feature an inherently low sensitivity). The rescheduling opportunities are not searched for. For the indirect heat integration, fixed temperature/variable mass inventory heat storage units (HSUs) are applied. Two models of indirect heat recovery schemes (IHRSs) are proposed : one based on a closed heat storage system, another built around an open storage system suitable e.g. for food and beverages industries. The inequality constraints of the IHRS models are automatically met owing to an appropriate definition of the decision variables managed by the GA. A rough preadjustment of the mass balance equality constraints on HSUs is achieved by a preliminary stage of heat recovery (HR) maximization before actually minimizing the total batch costs (TBCs). Optimization runs and theoretical considerations on the generation & replacement strategy of Struggle demonstrate that the structural and the parametric variables cannot be efficiently optimized within a single level, resulting in a two-levels optimization scheme. The automatically designed closed storage IHRS solutions for the brewing process are as good as the solutions obtained by another author using a combinatorial method followed by a post-optimization stage. The open storage IHRS is 13 % cheaper while the HR increases by 12 %. Optimizing the IHRS on a one-week period (including the non-periodic start-up & shut-down phases) results in an even more realistic solution, featuring a significantly different trade-off between energy, HSU capacities and HEX areas. A GA based, two-levels optimization scheme is proposed for the design of direct batch heat exchanger networks (HENs). The HEN structures, managed by the upper-level GA, do not include stream splitting. The re-use of HEX units across time slices is a key issue and a methodology to specify the actually possible structural changes by repipe or resequence is proposed, accounting for the thermo-physical compatibility, chemical compatibility, and process schedule constraints. The optimum operation of an existing HEN during each time slice has been analysed and a sound solution procedure is proposed.

The scheduling of batch process is a kind of NP-complete problem and has been the interest of research for many years. Various methods have been applied to solve such problems and simulated annealing (SA) is the most efficient algorithm. But SA is very slow when the problem size is large. In this work, particle swarm optimization (PSO) was applied to solve the scheduling problem of multiproduct batch process. The results show that PSO is a powerful method for solving the batch process scheduling problems and is superior to the widely used simulated annealing.

Intelligent scheduling and monitoring for multi-product networked batch processes

Effective scheduling of a large-scale paint production system

The scheduling of batch processes is a widely researched field of chemical engineering. Over the last few decades, a great number of tools have been developed for industrial examples and literature problems. These methods vary not only in their applied model, but in their representation of the problem inputs as well. The most well-known representations are the State-Task Network, the Resource-Task Network, the State Sequence Network, and the S-graph. While the latter also serves as the mathematical model for the related optimization approaches, the others only act as an intermediate model between the raw problem data and the model used for optimization, e.g., a mixed-integer linear programming model. The eS-graph model is a generalization of the S-graph, where the one-to-one relation between nodes and tasks has been relaxed, allowing a much wider range of scheduling problems to be tackled. Processes may simultaneously occupy several units, and release them at different stages of execution, and certain stages of separate processes can be forced to overlap in time. As in the case of the S-graph, the eS-graph models can be solved to optimality by specially designed combinatorial algorithms or serve as a basis for precedence based linear programming formulations. In this work, the modelling capacities of the eS-graph framework are illustrated via a Polymer production case study, where complex timing constraints are present.

Adsorption thermal energy storage for cogeneration in industrial batch processes: Experiment, dynamic modeling and system analysis

Gas-to-liquid (GTL) products have increasingly become a promising energy resources over the past two decades. Qatar possesses the third largest proven reserve of natural gas in the world, with a net capacity approaching 900 tcf (trillion cubic foot). This has motivated Qatar to develop a long term vision, involving the investment of huge expenditures into world-class commercial plants that convert natural gas into value-added liquid hydrocarbon products. This vision was translated into the Oryx GTL plant in late 2006 and the Shell Pearl GTL plant reported to be the largest in the world, which began operations officially at the end of 2011, leading Qatar to be described as the world capital of GTL. The substantial usage of energy in Fischer-Tropsch (FT) GTL processes and the complexity of energy distribution throughout the process offer opportunities for heat integration and waste heat recovery. The objective of this paper is to carry out an energy integration analysis for a typical GTL process. The approach was started with process simulation to develop the base-case data for the process. Next, energy integration tools were used to optimize energy distribution, heat exchange, and waste heat recovery. Finally, simulation and techno-economic analysis were utilized to assess the performance of the proposed design changes and their economic viability. The resultant pinch diagram showed that a single pinch case was faced with a fixed driving force of 10 oC, in which both external cooling and heating utilities were required to satisfy energy needs. Meanwhile, the Grand Composite Curve (GCC) showed that flue gases cover most of the heating utility while cooling water covers all the required cooling utility. Moreover, the waste heat recovery study supported by HYSYS software illustrated considerable recoveries in steam qualities from discharged flue gases within the FT reactor section. In conclusion, energy integration on a GTL process was realized to be a promising one as the targets for net energy savings were found to be close to 40%. Additionally, generation of various qualities of steam can be obtained in a cost-effective manner. At the top of it, most of the recommended projects have attractive payback periods, below six years.