Supply chains can be energy intensive and present significant challenges towards their improvement in efficiency across multiple stages. The present work presents a modelling framework for identifying the stages and processes along supply chains which can offer the greatest potential in achieving savings in energy consumption. The identified stages in the present study are: production, transportation and storage/retail. To quantify and assess the potential for improvement in each of these three stages/processes, modelling frameworks are developed, tested and showcased.
The modelling framework developed for the production stage shows the importance of glasshouses’ thermal envelope properties, operational parameters, as well as the impact of location and temporal variability on their energy performance. The transport stage is analysed while optimising the allocation and distribution of products in multi-echelon multi-period supply chains. Modelling frameworks employing deterministic and heuristic approaches are developed for this purpose. The addition of processing stages to these modelling frameworks show their ability to contribute towards better performance, particularly at higher vehicle capacities and for small stores. The retail/storage stage is found to be dominated by electricity consumption, particularly in the case of refrigerated products. The novel approach of electricity storage technologies as solutions towards savings is considered through the thermo-economic modelling of newly proposed thermo-mechanical systems. Their potential as energy solutions is found to be affected by both internal (e.g. roundtrip efficiency, capital costs) and external (e.g. renewable technologies present, electricity prices) factors.
The ability to quantify and assess supply chains using standardised approaches can be a way towards mapping energy consumption, carbon emissions and energy costs. Analyses of outputs from such investigations can offer pathways for improvement as well as contribute to the development of strategies for setting and meeting environmental targets. Findings from this work present potential opportunities through the utilisation of the modelling frameworks developed.