A Multi-Criteria decision making (MCDM) methodology for high temperature thermochemical storage material selection using graph theory and matrix approach.

[Display omitted] • The application of a MCDM methodology based on Graph Theory and Matrix approach leads to selection of Cao/Ca(OH) 2 for high temperature thermochemical storage. • Target based, universal and user-friendly MATLAB program based on MCDM methodology allows the simple selection of candidate materials. • The MCDM tool is tested against a real-life situation, namely the capture of waste heat from Tata Steel UK Port Talbot steelworks. • Practicality of proposed MCDM method is validated with selection of a suitable heat storage material for low-medium temperature application. • Proposed method can be applied to other scenarios such as heat storage from high and low temperature coupled with solar thermal generators. Industrial waste heat is currently underutilized due to the techno-economic challenges, inherent variability and intermittency of this source. To overcome the existing barriers, reduce the emission of greenhouse gases and protect the global environmental conditions, energy recovery is one of the most effective strategies. In the design of heat storage systems, the material selection procedure plays an important role and requires complex interrelationships between the various factors and parameters to be elucidated toachieve the best candidate material for a given application. This paper presents a Multi-Criteria Decision Making (MCDM) methodology based on Graph Theory and Matrix approach for high temperature thermochemical storage (TCS) material selection. Furthermore, the presented approach has been used to select the suitable candidate material for recovering the high temperature waste heat (over 500 °C) in Port Talbot Steelworks. [ABSTRACT FROM AUTHOR]