Heat exchanger network synthesis using genetic algorithm and differential evolution

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.

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

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

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.

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.

The synthesis of cost optimal heat exchanger networks with unconstrained topology

Optimization of heat exchanger network is attributed to improving the process industrial energy utilization ratio. Energy consumption reduction plays an important role in the low-carbon economic development. Several synthesis approaches for heat exchanger network have been proposed and extended during the last three decades. With the evolution of the computer technology, the simultaneous synthesis method via mathematic programming attracts a great deal of attention worldwide. However, some difficulties still need to be overcome, for instance, model simplification and computational complexity. In this work, the simultaneous stage-wise synthesis model without the assumption of isothermal mixing is presented and implemented using effective initialization strategies and a novel two-level algorithm. Three case studies illustrated the better performance of the initialization strategies and two-level algorithm for heat exchanger network synthesis problems, considering non-isothermal mixing.

Intelligent search strategy applied in heat exchanger network synthesis

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

Improved optimization strategies for automated heat exchanger network synthesis through physical insights

Synthesis of heat exchanger network considering pressure drop and layout of equipment exchanging heat

Targets for Heat Exchanger Network Synthesis with Different Heat Transfer Coefficients and Non-uniform Exchanger Specifications

A randomized algorithm for the efficient synthesis of heat exchanger networks

Heat exchanger network optimisation considering different shell-side flow arrangements

Multi-objective optimization of a solid oxide fuel cell-based integrated system to select the optimal closed thermodynamic cycle and heat coupling scheme simultaneously