Track: Operations Research
Abstract
Natural gas has remained the fastest growing energy resource in most regions of the world for more than two decades, driven by the low greenhouse gas emissions as well as high conversion efficiency in power generation. In the Philippines, natural gas is one of the major energy sources specifically coming from Malampaya gas field located 80 km northwest of Palawan. This study analyzed the supply chain of liquefied natural gas (LNG) by selecting the appropriate LNG suppliers through analytic hierarchy process and minimizing operational cost by applying linear programming. Using AHP, we identified important criteria that a company would consider in choosing a suitable supplier. In this model, it gives more weight on commercial criterion and price sub-criterion, as any fuel supply contracts can be considered as highly commercial transaction. Fuel supply affects power generation cost as well as electricity prices paid by consumers. Thus, consumers need to procure their fuel at the least-cost manner as possible. On the other hand, in terms of technical aspect, gas quality directly affects efficiency, soundness in operation and emission levels. For each cluster of suppliers, a mathematical model was developed to determine the optimum delivery to each cluster from variety of supply and constraints to minimize operational cost. Understanding the impacts of restrictive provisions in long-term supply contracts, such as take-or-pay agreements, on overall business operation will save the buyer from high operational cost and profit reduction. The balance between long-term and spot supply must be well managed to maximize the benefit of entire supply portfolio. As the Philippines is expected to become a new LNG importer in the near future, for the reasons of energy security, GHG emission reduction and environmental concerns in power generation sector can be further studied. Further, more comprehensive studies must be conducted to ensure that various considerations and real-life scenarios were taken into account.