Abstract
Pinch Analysis has evolved over the past four decades from a methodology originally developed for optimising energy efficiency of industrial plants. Applications of Pinch Analysis applications are based on common principles of using stream quantity (e.g., enthalpy) and quality (e.g., temperature) to determine optimal system targets. This targeting step identifies the Pinch Point, which facilitates problem decomposition for subsequent network design.One important class of Pinch Analysis problems is energy planning with footprint constraints. This area of work began with the development of Carbon Emissions Pinch Analysis (CEPA), where energy sources and demands are characterized by carbon footprint as the quality index. This methodology has been extended by using alternative quality indexes, such as water footprint, land footprint, emergy transformity, inoperability risk, energy return on investment (EROI) and human fatalities. Despite such developments, these Pinch Analysis variants have the limitation of being able to use one quality index at a time. To date, attempts at developing multiple-index Pinch Analysis methods have only been partially successful. In this work, a multiple-index Pinch Analysis method is developed by using a composite quality index; the latter is assumed to be a weighted linear function of different quality indexes normally used in energy planning, as discussed previously. The weights used to compute the composite index are determined via the Analytic Hierarchy Process (AHP). A case study adapted from a literature example is solved to illustrate this approach.
