Pinch analysis

Summary

Pinch analysis is a methodology for minimising energy consumption of chemical processes by calculating thermodynamically feasible energy targets (or minimum energy consumption) and achieving them by optimising heat recovery systems, energy supply methods and process operating conditions. It is also known as process integration, heat integration, energy integration or pinch technology. The process data is represented as a set of energy flows, or streams, as a function of heat load (product of specific enthalpy and mass flow rate; SI unit W) against temperature (SI unit K). These data are combined for all the streams in the plant to give composite curves, one for all hot streams (releasing heat) and one for all cold streams (requiring heat). The point of closest approach between the hot and cold composite curves is the pinch point (or just pinch) with a hot stream pinch temperature and a cold stream pinch temperature. This is where the design is most constrained. Hence, by finding

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https://en.wikipedia.org/wiki/Pinch_analysis

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A comparative study has demonstrated that the formerly developed Pinch Analysis (PA) based targeting and design methods outperform (in both heat recovery and cost-effectiveness) the simplified combinatorial design methods proposed by other authors (namely the Omnium Verfahren and the Permutation Method). The PA based methods provide valuable insight in the problem, but aren’t suitable for automated design and optimization. PinchBATCH results therefore in the following advances: 1) a strategy (including guidelines and quantitative criterias) is proposed to restrict the analysis of batch processes to meaningful time slices. Likely variations of the schedule are taken into account; 2) practical constrains limiting the repipe and resequence of heat exchangers are identified and formalized under a matrix format. The formalization of all these constraints is needed for automated design methods to actually focus on feasible solutions; 3) a strategy based on genetic algorithms (GAs) is proposed for the synthesis of direct batch heat exchangers networks (i.e. without heat storage). The strategy features a decomposition into an upper level, which optimizes the overall network, and a lower level which search for the best use of the heat exchangers across time slices; 4) for indirect heat recovery using heat storage, a heuristic, PA inspired approach for targeting and simplified design is proposed and demonstrated. It uses TAM composites and includes a method to identify the minimum number of heat storage units (HSUs) as function of the heat recovery. Most generally, local minimums are to be found just before a storage pinch appears, and the search strategy systematically removes one bottleneck at a time, taking advantage of the available degrees of freedom. A simple graphical tool to assess opportunities to decrease the required capacity of HSUs by rescheduling of streams is proposed. A model suitable for a GA based optimization is also proposed, featuring a decomposition into two levels; 5) detailed specifications of the organization and of the features to be implemented in a software tool to address the heat integration of batch processes have been produced. The very next steps will be concerned with the implementation and the validation of the GA based synthesis approaches.

1999

This project inserts itself in improving the understanding of the sensitivity of the dTmin against the parameters that influence it. It is also aimed at helping to improve OSMOSE, a platform designed for the study of energy conversions systems. Three economic criteria have been taken to achieve the heat integration optimization: the net present value, the yearly total cost and the payback period. This paper explores briefly several heat exchanger types and cost estimation models and presents then the program developed on Matlab and Octave for the optimization. The results are discussed, highlighting the fact that the payback period is not relevant for the evaluation of a project, and that the NPV, used by economists, should be considered. Two case studies are presented and compared, when we consider – for a varying heat load – the cold stream with an infinite mcp or the same mcp as the hot stream.

2010

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Lignocellulosic biorefineries are the best non-petroleum alternatives for a sustainable development. In the biorefinery process design, it is important to implement an algorithm that allows the systematic generation and the evaluation of energy conversion chains and making comparison of different pathways, ranking them according to different performance criteria. To achieve these goals, a methodology has been proposed to systematically define an ordered set of solutions using mixed integer linear programming models with integer cut constraints. In this study, we apply a systematic approach which adopts thermo-environomic optimization together with heat integration to assess the economic performance, environmental impact and energy requirement of several process options. Both sugars and syngas platforms are compared considering multiple products (energy services, valuable chemicals, fuels). A hybrid superstructure of different processes is developed and the heat recovery in the systems is represented using pinch analysis. Different pathways are evaluated and ranked according to different objective functions to understand the best combination of products and the synergies between them. The results of this work provide a set of candidate solutions considering benefit of heat integration between different pathways to obtain energy efficient biorefinery systems with improved process economics and reduced environmental impacts.

2017

1999