Exploring multi-objective trade-offs in the design space of a waste heat recovery system

Mokhtar, Maizura; Burns, Stephen; Ross, Dave; Hunt, Ian

Abstract

A waste heat recovery system (WHRS) is used to capture waste heat released from an industrial process, and transform the heat into reusable energy. In practice, it can be difficult to identify the optimal form of a WHRS for a particular installation, since this can depend on various design objectives, which are often mutually exclusive. More so when the number of objectives is large. To address this problem, a multi-objective evolutionary algorithm (MOEA) was used to explore and characterise the trade-off surface within the design space of a particular WHRS. A combination of clustering algorithm and parallel coordinates plots was proposed for use in analysing the results. The trade-off surface is first segmented using a clustering
algorithm and parallel coordinates plots are then used to both visualise and understand the resulting set of Pareto-optimal designs. As a case study, a simulation of a WHRS commonly found in the food
and drinks process industries was developed, comprising of a desuperheater coupled to a hot water reservoir. The system was parameterised, considering typical objectives, and the MOEA used to build a library of alternative Pareto-optimal designs that can be used by installers. The resulting visualisation are used to better understand the sensitivity of the system’s parameters and their trade-offs, providing another source of information for prospective installations.

Citation

Mokhtar, M., Burns, S., Ross, D., & Hunt, I. (2017). Exploring multi-objective trade-offs in the design space of a waste heat recovery system. Applied Energy, 195, 114-124. https://doi.org/10.1016/j.apenergy.2017.03.030

• Journal Article Type: Article
• Acceptance Date: Mar 8, 2017
• Online Publication Date: Mar 17, 2017
• Publication Date: Jun 1, 2017
• Deposit Date: Apr 25, 2017
• Publicly Available Date: Mar 18, 2018
• Journal: Applied Energy
• Print ISSN: 0306-2619
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 195
• Pages: 114-124
• DOI: https://doi.org/10.1016/j.apenergy.2017.03.030
• Keywords: Waste heat recovery; Optimisation; Multi-objective evolutionary algorithm; Mutually exclusive objective functions
• Public URL: http://researchrepository.napier.ac.uk/Output/832526
• Contract Date: Apr 27, 2017