Multi-objective optimization on total cost and carbon dioxide emission of coal supply for coal-fired power plants in Indonesia

Indonesian coal is distributed in several islands, such as Sumatra, Kalimantan, Sulawesi, and Papua. Most of them are classified as low and medium rank coal, which is very suitable for coal-fired power plants. In the future, domestic coal demand will increase, driven by the government plans to increase the electricity generation capacity and primary energy demand. In the existing scheme, only a coal mining company whose coal quality is an exact match with the coal-fired power plant specification can be selected as a supplier, without considering a blending mechanism. This condition may have some issues for long-term supply, as the coal will be exhausted in time and tends to come at a high cost. To improve the decision making for securing the long-term coal demand for electricity generation, optimization with coal blending should be considered. This research includes the consideration of the coal quality parameters; the power plant's requirement criteria; the location of the coal-blending facility; and ship types. A multi-objective optimization using mixed-integer linear programming, consisting of linear inequalities in binary and continuous variables as the constraints, is introduced to find the optimal solution, with cost and carbon dioxide emission as the objective functions. Several scenarios, which are the baseline condition, chartered ship, and environmental consciousness, will be analyzed. The results obtained by using the epsilon-constraint method show the benefits of the proposed schemes and scenarios, which are able to secure long-term demand with a more flexible solution, and reduce the total cost and carbon dioxide emission. Furthermore, considering the parameter setting and modeling, the optimization can be considered as applicable for solving similar problems related to the transportation selection and supply chain for similar commodities in the greater area.

Automated summary

This research aims to improve decision-making in the Indonesian coal supply chain by using multi-objective optimization to secure long-term coal demand and reduce total cost and carbon dioxide emission. The study considers factors such as coal quality parameters, power plant requirements, coal blending facility location, and ship types.