I am happy to give a talk about my research on developing large optimisation models of value chains to supply products and services in the most efficient and sustainable manner.

A value chain is a network of processes or activities required to obtain raw materials and primary resources and convert them into useful products and services, along with logistics such as distribution, transportation, storage and inventory management. Along the supply chains there are many interdependent decisions involved.  For example, for green hydrogen value chains, such decisions include how many wind turbines and solar farms to build, of each type and where, where to install electrolysers, how to transport the electricity and/or hydrogen, how much grid reinforcement is needed and how much hydrogen pipeline network needs to be built, where to store hydrogen and how to manage its inventory, and what services to use the hydrogen for: heat, transport, power, industry etc.

There are so many different combinations of these decisions, so I am developing mathematical models and computer algorithms to automatically identify the best sets of combinations, which will be useful in making decisions for example around land use, location of processing facilities, the levels of production and the most effective logistics and inventory management policies.

Below are some of my publications related to this topic. I am happy to tailor my talk to suit the interest and experience of the audience. For example, I can focus on mathematical modelling or specific applications such as for hydrogen, bioenergy, forestry, or the use of the method to help inform policy.

Samsatli, S & Samsatli, NJ (2019). The role of renewable hydrogen and inter-seasonal storage in decarbonising heat – comprehensive optimisation of future renewable energy value chains. Applied Energy, vol. 233-234, pp 854-893. DOI: 10.1016/j.apenergy.2018.09.159.

Samsatli, S & Samsatli, NJ (2018). A multi-objective MILP model for the design and operation of future integrated multi-vector energy networks capturing detailed spatio-temporal dependencies. Applied Energy, vol. 220, pp. 893-920. DOI: 10.1016/j.apenergy.2017.09.055.

Samsatli, S & Samsatli, NJ (2018), A general mixed integer linear programming model for the design and operation of integrated urban energy systems. Journal of Cleaner Production, vol. 191, pp. 458-479. DOI: 10.1016/j.jclepro.2018.04.198.

Suckling, ID, de Miguel Mercader, F, Monge, JJ, Wakelin, SJ, Hall, PW, Bennett, PJ, Hock, B, Samsatli, NJ, Samsatli, S & Fahmy, M (2022). Best options for large-scale production of liquid biofuels by value chain modelling: A New Zealand case study. Applied Energy, 323, 119534. DOI: 10.1016/j.apenergy.2022.119534.

Samsatli, S, Samsatli, NJ & Shah, N (2015). BVCM: a comprehensive and flexible toolkit for whole-system biomass value chain analysis and optimisation – mathematical formulation. Applied Energy, vol. 147, pp. 131-160. DOI: 10.1016/j.apenergy.2015.01.078.

Samsatli, S & Samsatli, NJ (2015). A general spatio-temporal model of energy systems with a detailed account of transport and storage. Computers and Chemical Engineering, vol. 80, pp. 155-176. DOI: 10.1016/j.compchemeng.2015.05.019.