Enhancing Sustainable Energy Supply: a Clustering Analysis of LNG Distribution for Indonesian Power Plants Using K-Means Method

This study investigates the application of K-Means++ clustering to optimize Liquefied Natural Gas (LNG) distribution to thirty power plants in Indonesia, particularly addressing the logistical challenges of inter-island distribution in archipelagic nations. Existing research often focuses on supply and demand aspects. However, this study tackles the critical challenge of efficient distribution by strategically grouping power plants. By utilizing K-Means++ to create clusters based on geographical proximity, the proposed method aims to enhance the supply chain system, promote a sustainable energy supply for Indonesia, and potentially achieve significant cost reductions or efficiency gains in LNG distribution. The results indicate that the optimal number of clusters (k) is five. The selected clusters have been evaluated for their geographical distribution and potential for use in an LNG distribution model. Through CAPEX and OPEX calculations over project lifespans of 10 and 20 years, the economic feasibility analysis has been performed by using financial metrics, including Net Present Value and Internal Rate of Return. Sensitivity analysis has showed that a tolling fee of $6 per unit would achieve a target IRR of 12%, making the business model financially feasible.