Generalized simultaneous optimization model for synthesis of heat and work exchange networks

MINLP model for work and heat exchange networks synthesis considering unclassified streams

Heat exchanger network (HEN) synthesis has been a well-studied subject over the past decades. Many studies and methodologies were proposed to make possible the energy recovery, minimizing the utilities consumption and the number of heat transfer equipment. Most of papers published in this subject are based on Pinch Analysis and mathematical programming. Some recent papers use meta-heuristic techniques like Genetic Algorithms or Simulated Annealing to solve the HEN synthesis problem and good results are found but with large computational effort. In this paper an optimization model for the synthesis of HEN is proposed. The approach is based on the use of Particle Swarm Optimization to determine the HEN that minimizes the total annualized cost, accounting for capital costs of heat exchangers and the energy costs for utilities and pumping duties. The algorithm is based on a superstructure simultaneous optimization model for the HEN synthesis considering stream splitting. Some examples from the literature were used to show the application of the proposed algorithm, and the results confirm the achievement of the optimum HEN configuration with little computational effort.

A monogenetic algorithm for optimal design of large-scale heat exchanger networks

The primary objective of this study is to develop a simultaneous approach for the synthesis of flexible heat exchanger networks (HENs) with non-isothermal mixing assumptions. The HENs synthesis procedure presented in this study took into consideration quantified uncertainties in inlet temperatures and flow rates with an unpredictable time of shift. The proposed multi-period MINLP model was used to generate a HEN with optimized heat exchanger areas and total annualized costs attributed to utility duties. A framework for generating the flexible HEN over a specified range of variations in flow rates and stream temperature was proposed in this study. The framework was based on a two-stage strategy; a HEN design stage was first performed before the testing stage where the energy-saving potential of the synthesized HEN was established. The effectiveness of the proposed approach was tested for energy minimization using a case study in literature with variation in inlet temperature and flow rate. It was observed that the inclusion of non-isothermal parameters in the non-linear model resulted in a HEN that optimally works under fluctuating conditions without losing stream temperature targets while maintaining economically-optimal energy integration.

Comparison of reformulations of the Duran-Grossmann model for Work and Heat Exchange Network (WHEN) synthesis

The synthesis of cost optimal heat exchanger networks with unconstrained topology

Key process parameters in the synthesis of heat exchanger networks, such as process stream supply and target temperatures and process stream flowrates, may vary from time to time due to issues such as changing environmental conditions, plant start-ups/shut-downs, changes in product quality demand, etc. Also some other key design parameters which may also change from time to time include the availability of utilities as well as their costs. These changes may be due to factors such as seasonality issues, e.g. for utilities sourced from renewable energies, or government policies in form of tax, availability of utilities due to shortage of supply, etc. This implies that heat exchanger networks should not only be designed to be flexible in order to satisfy heat demand under changing process parameter scenarios, but should also be flexible in situations where utility costs as well as their availability change from time to time. Hence this paper aims to extend existing stage-wise superstructure (SWS) based multi-period heat exchanger network synthesis methods to be capable of satisfying the heat demand under scenarios where both process stream parameters and utility parameters such costs change from time to time in a pre-defined manner. The approach used entails extending the current multi-period SWS model through the inclusion of additional time index to represent future costs of utilities. The model is applied to one example so as to demonstrate its benefits.

Heat exchanger network synthesis using genetic algorithm and differential evolution

Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach

Optimization and utilities relocation approach for the improvement of heat exchanger network designs

The simultaneous heat exchanger network (HEN) synthesis problem is generally formulated as a mixed integer non-linear programming (MINLP) problem by using superstructures, which embed several possible stream matches and various alternative HEN designs. The superstructures proposed by Yee et al. [1] and by Floudas et al. [2] are used for this purpose. In the present work, the graph theoretic principles used by Shivakumar and Narasimhan [3] to develop an efficient nonlinear program (NLP) formulation for Yee superstructure has been extended to the Floudas superstructure. A comparison of the NLP formulations based on the two superstructures, in terms of efficiency, scalability, convergence and quality of solution has been carried out using several test problems available in the literature. It has been shown that the Floudas superstructure is superior in terms of these performance metrics, and appears to be the best suited for optimisation based HEN synthesis.

Incorporating Process Safety into Heat Exchanger Network Synthesis and Operation

An extended superstructure modeling method for simultaneous synthesis of direct work exchanger networks

Intelligent search strategy applied in heat exchanger network synthesis

Fouling and aging are the main causes for the degradation of heat exchanger performance from a well-behaved heat-transfer performance. They result in extra capital and energy costs for heat exchanger networks (HENs) to compensate for the gap in target temperatures. To reduce the negative effect of deposition, this paper presents a novel methodology for managing the cleaning schedule problem in the design of HENs. The method consists of three steps. First, obtain an original HEN using pseudotemperature enthalpy diagram approach. Then, simplify the structure of the original HEN through loop-breaking and small size unit eliminating strategies. Finally, optimize heat-transfer areas and cleaning schedules by considering the growth of deposits via a mixed integer nonlinear programming model. Therefore, the model is capable of weighing the capital cost for exchangers and the operation cost for both utility consumption and cleaning activities. In this study, two off-line cleaning alternatives with distinct cleaning efficiencies are provided for deposition removal; therefore, the problem of which method should be selected for each exchanger will also be investigated in the model. At the end of the study, an illustrative example is presented to demonstrate the proposed method. The results have indicated the potential for cost savings when good cleaning schedules are planned with the design of HENs.