Given the urgency to transition to low carbon future, oil refineries need to identify feasible strategies for decarbonisation. One way to address this is by integrating renewable energy systems. However, the high initial costs and intermittency appeared to be the key barriers for the adoption of renewable energy technologies. Hence, a multi-period optimisation model is developed via mixed integer linear programming in this work to determine the optimal renewable energy system in terms of cost and its optimal energy storage technology to enhance its flexibility for oil refinery operations. This model aims to minimise the costs of the renewable energy system while considering its ability to accommodate the varying energy demands across the time periods. An oil refinery case study is used to demonstrate the effectiveness of the developed model. The developed model is expected to propose an optimal renewable energy system that meets the energy demands and, at the same time, achieves the decarbonisation goal. Based on the results, the optimal renewable energy system comprises cost-effective technologies to generate various energy outputs including electricity, hydrogen, high-pressure and medium-pressure steam to meet energy demands. Additionally, the result of the case study shows that the integration of renewable energy systems achieves a reduction of 5,353 tonnes of carbon dioxide. Apart from that, the incorporation of energy-efficient energy storage results in a 10% reduction in the total cost of the optimal renewable energy system. Compressed hydrogen gas storage and battery were used to store excess hydrogen and electricity during periods with low demands and subsequently consumed during peak demand periods. This can, therefore, reduce the technological capacity required. With the aid of storage facilities, the flexibility of the renewable energy system is elevated in meeting varied demands, which otherwise would incur additional expenses.
