Multi-Objective Optimisation and Exergoeconomic Analyses of Energy-Conversion Systems using Excel

Abstract

In the past, the pressures on the world’s natural resources and the environment were not as high as they are today. Therefore, the designers of energy-conversion systems strived to satisfy two conflicting objectives of their designs; (a) maximising the performance efficiency of the systems and (b) minimising their owning costs. By assessing both objectives in terms of monetary measures, the design optimisation problem could be solved by minimising a “total annualised cost rate” that accounts for the two factors. However, design optimisation of present-day energy systems is more challenging due to the additional constraints that have to be met, including the effect on the environment, and the increasing complexity of the systems themselves. Solving optimisation problems of present-day energy-conversion systems would not have been possible without taking advantage of the recently developed computer-aided techniques for multi-objective optimisation (MOO) and exergoeconomic analyses. This book aims to give senior engineering students and young researchers in the field a gentle introduction to these two modern tools and show how they can be used to complement one another for design optimisation analyses of energy conversion systems.

MOO and exergoeconomics are two different optimisation methodologies. MOO applies iterative search methods to optimise the system with predefined objectives and provides the engineer with a small set of solutions to select from. Exergoeconomics uses thermodynamics and economics to associate costs to exergy flows and exergy destructions in the system and defines a number of exergoeconomic parameters to assess the economic performance of the system. Unlike MOO, the result of an exrgogoeconomic analysis is not an optimised system, but a set of indicators for setting-up optimisation strategies and, therefore, the optimised system depends on the engineer’s interpretation of the exergoeconomic results. To improve the accuracy of the method, an advanced exergoeconomic method has been developed that splits the rates of exergy destructions and associated costs into avoidable and unavoidable and self-generated (endogenous) and imported (exogenous) parts and redefines the exergoeconomic parameters accordingly. The application of the two methods for design optimisation may pose more questions than the answers it gives. Since the two methods are still under development, it is hoped that this book provides understandable and applicable answers to these questions if not comprehensive and conclusive ones.