Asset Portfolio Development for Long Term Investment Programs in the Hydrocarbon Industry
The topic is available also in Hungarian
Contrary to the last decade when only the environmental legislations of the EU were pushing the hydrocarbon industry to make the fossil based fuels more “green” and introduce bio/renewable components the 2020s is starting with completely different conditions. The looming changes of the mobility sector (e.g.: HEV, PHEV and EV vehicles) accompanied with the increasing cost of energy either it is electric power or natural gas are putting more and more pressure on the average European citizen to move towards the cheaper and energy efficient solutions. The EU energy supply security issues that have been lurking in the shadows have also been abruptly put in the spotlight by the Ukrainian war situation and consequent Russian crude oil embargo. The definite proof of the climate change experienced by European countries as well during the last decade put significant ammunition into the pocket of the EU Green Deal. Having such conditions the Hydrocarbon Industry is facing substantial structural changes for the upcoming years. The major directions are moving towards renewable businesses in the fuel and energy sector, putting more efforts on the Petrochemical product supply still on fossil basis and moving towards more knowledge intensive technological sectors in the long term (2050 and after).
In order to find the way forward for MOL Group amongst the above described conditions expected for the upcoming decades an innovative approach is needed. This new approach shall be based on industrial technological solutions and future product or energy supply demands embedded in a mathematical environment can optimize the operation of different business elements to provide the solution for multi-year profit expectations. The resultant tool needed to be developed shall be able to optimize the operation of different business sectors such as crude oil refining, petrochemicals production, renewable energy production and specialty businesses.
The aim is to develop and prove the capabilities of such a mathematical model environment on a simplified sample system that can be used for testing of main functionalities. The model is intended to be graph based. The nodes of the graph are the business elements / refinery unit (e.g., crude distillation unit, naphtha reformer unit, gas oil hydrotreater). The relations of the graph are the material streams (e.g., pipelines, road transportation, train transportation). The graph can be cyclic, as some materials should be recirculated due to technological reasons. A cost function is to be applied to the graph (including also relations) that should model the production costs (e.g. OPEX), revenue streams and transportation costs, etc. The parameters to be tuned can be, e.g., the amount of materials to be produced at each production unit. Some of the nodes of the graph should represent future business elements. In this case, the CAPEX should also be involved in the cost structure. Having a model defined, the next step is to optimize the production of a relatively small production site. If the pilot is successful, the model should be applied on a bigger scale.
The student can work on the following tasks:
- Definition of the model described above.
- Summarize, evaluate and rank the mathematical optimum searching methodologies available on the relevant knowledge domain.
- Apply optimization algorithms on the model.