An extended method for work and heat integration considering practical operating constraints

Abstract

The development of methodologies for the simultaneous work and heat integration has increasingly been the focus of recent research. Approaches may vary among optimization and heuristic-based methods considering direct and indirect work exchange, in addition to, or with the development of new strategies for heat recovery. This work presents a strategy for the synthesis of work and heat exchange networks (WHEN) considering the use of single-shaft-turbine-compressor (SSTC) units. The method is based on a meta-heuristic approach and aims fundamentally at synthesizing WHEN that may operate within industrial-like conditions, which are often narrower than those considered in the literature due to simplification assumptions. Therefore, in the present work, practical temperature upper/lower-bound constraints are considered for pressure manipulation units, and the number of coupled units per shaft is limited. Evidently, these constraints yield additional difficulties for the optimization method. The method considers inlet and outlet temperatures as decision variables in the units of a block-based model, making the maintenance of solutions within feasible range more efficient during the optimization runs. Moreover, a new Simulated Annealing (SA) based strategy is developed for deciding optimal compressor/turbine couplings in a model that considers a preset number of “slots” per shaft. The method aims at minimizing total annual costs (TAC) and is tested over four case studies. The first two are used both as benchmark for TAC comparison to those reported in the literature as well as for testing the new constraints. The other two cases are investigated for TAC and energy-wise improvements to original designs. Considerable economic improvements and better use of energy are attained in all cases. For the two benchmark studies, solutions with TAC 1.5% and 4.3% lower than literature designs were found. For the industrial cases, energy requirements were overall reduced. For instance, in example 3, no external power source is required, while literature solutions present power shortage. In example 4, compression power requirements were reduced by 9.9%. The method also proved efficient in maintaining solutions within practical operating ranges.