(755a) Planning and Scheduling of Supply/Delivery Operations in An LNG Regasification Terminal

Faced with the fast depletion of crude oil reserves, high oil prices in recent times, stringent environmental restrictions on CO2 emissions, trends to diversify the energy supply, barriers to development of feasible renewable energy sources, etc., countries are now moving toward NG as their major and/or alternate source of fuel to supplement energy demand and curb the over dependency on oil [1-3]. However, Most NG reserves are offshore and away from demand sites. Pipelines pose a security risk and are not always feasible or economical. They are often limited by a “ceiling” amount of NG that can be transported. Alternately, an attractive option is to liquefy NG at -163^o C at the source and then transport it as liquefied natural gas (LNG) by specially built ships or tankers that are essentially giant floating flasks. When liquefied, the volume of natural gas reduces by a factor of about 600 at room temperature, which facilitates the bulk transport of NG. In fact, LNG is the most economical means of transporting NG over distances more than 2200 miles onshore and 700 miles offshore [1].

 As an alternate fuel, the demand of LNG is doubling every 10 years. A growth rate of 6.5% per year is expected for LNG in the near future, which would be the fastest growth for any energy activity or product worldwide [3].  New open-access, multi-user LNG terminals are already been built in Asia, capable of importing and re-exporting LNG from multiple suppliers. The terminal is to cater to carriers of size 120,000 m3 to 265,000 m3 and will supply pipeline gas for purposes of power generation. A tertiary jetty is also expected to be set up for purposes for reloading LNG into ships for use as fuel via a bunkering operation. With its excellent location coupled with the upcoming IMO regulations on sulphur and price competitiveness of LNG with respect to HFO can help Singapore emerge as a global bunkering hub for LNG.

 In recent years, new market dynamics such as rapidly increasing spot transactions and the emergence of new players, third parties and customers have made the LNG market dynamic, and thus LNG terminal operations quite complex [2]. Further, LNG regasification costs have more than doubled. Soaring operations and energy costs, availability challenges, and growing demand for yield, require LNG regasification plants to achieve high throughput rates, while improving energy efficiency, safety, and reducing emissions [4-6]. This has led to the need for developing decision support systems which examine design parameters for an LNG receiving terminal – the LNG tanker docking facility, storage tanks and the regasification facility, to determine their relationships and help optimize tanker scheduling, terminal utilization, and profitability.

 In this work, we develop optimization model that involves optimal operation of LNG unloading by scheduling of LNG vessels, transfer of LNG from vessel to LNG storage tanks, inventory optimization of storage tanks and optimal operation of vaporizer and send out in natural gas grid. Apart from conventional regasification terminal, terminal also has LNG trading and bunkering facilities. We take into account, the trading of LNG from secondary terminal. There are several decisions involved in these kinds of multi-user, open access import terminal. Shipment Scheduling of incoming and outgoing ships, inventory optimization, demand fulfillment of long and short term contracts and dynamic operational decision for vaporizer has been addressed in the work. MILP Model has been developed for optimizing this downstream side of LNG supply chain.

1. Khalilpour, R., Karimi, I.A., 2011. Investment portfolio under uncertainty for utilizing natural gas resources. Computers and Chemical Engineering 35, 1827-1837.
2. Khalilpour, R., Karimi, I.A., 2011.Selection of LNG contracts for minimizing procurement costs. Ind. Eng. Chem. Res. 50, 10298–10312.
3. Faruque Hasan, M.M., Zheng, A.M., Karimi, I.A., 2009. Minimizing Boil-Off losses in Liquefied Natural Gas Transportation. Ind. Eng. Chem. Res. 48, 9571–9580.
4. D’Amboise, A., Ozelkan, E.C., Teng, S.G., 2007. Optimizing liquefied natural gas terminal design for effective supply chain operations. Int. J. Production Economics 111 (2008) 529–554.
5. Contesse, L., Ferrer, J.C., Maturana, S., 2005. A mixed-integer programming model for gas purchase and transportation. Annals of Operations Research 139, 39–63.
6. D’Ambrosio, A., Ozelkan, E.C., Teng, S.G., 2005. Impact of supply chain capabilities on liquefied natural gas terminal design. In: Proceedings of the Global Institute for Energy and Environmental Systems (GIEES) Annual Conference, July 24–30.