FSRU operators optimise LNG demand amid the energy crisis

Download the full article, "Expansion for the Future," featured in LNG Industry magazine

Authors: Briain O'Dowd and Praveen Lawrence 

Business logistics predictive simulation software is increasingly being used to help operators address the complexities and interdependencies in their planning and processes. Recently, Praveen Lawrence and I were featured in LNG Industry magazine to share our expertise on how predictive simulation can aid decision-makers with managing LNG terminal demand.

The IEA has called it ‘the first truly global crisis in history,’ and it's hitting Europe disproportionately. Russian gas represents 30-45% of European gas demand and almost €100 million of spend, so reducing reliance has a life-saving potential.

LNG has emerged as one of the best alternatives to Russian gas – and FSRUs have a key role to play

It has an established global market and readily available gas infrastructure across Europe. Plus, there are environmental benefits. It’s an acknowledged transition fuel as we move towards a greener future, typically producing 40%-45% less carbon dioxide (CO2) than coal and 30-35% less than oil, making it the low-carbon fossil fuel.

Amid this rush for LNG across Europe, Floating Storage Regasification Units (FRSU) can be quicker to deploy than landside infrastructure, which is particularly appealing amid this geopolitical and economic backdrop. But understanding the feasibility of deployment is only the first step.

The true challenges emerge when considering how to balance the constraint storage, variable offtake and variability in vessel call and parcel size – and in how to optimise annual demand planning. Many of these challenges can be identified an mitigated before the FRSU is operational.

FSRU demand planning is particularly complex right now

Managing and scaling FSRUs in this dynamic and uncertain environment involves major challenges. Besides fundamentals around ship scheduling and vessel/parcel size, operators need to account for variables like:

• Equipment reliability
• Planned and unplanned maintenance
• Seasonal fluctuations, daylight restrictions and weather/tide patterns
• Port and channel operations
• Regasification rates
• Supply contracts and gas send-out rates

There’s significant expense involved in getting it wrong. For example, if a vessel can’t offload its parcel, demurrage can escalate quickly, costing operators many hundreds of thousands of dollars per day.

Predictive simulation simplifies annual demand plan optimisation

No spreadsheet can deal with this level of complexity, and that’s where predictive simulation adds real value. It models assets and dynamic processes, allowing you to analyse ‘what-if’ scenarios involving complicated variables – and in a risk-free way.

Twinn LNG Logistics Simulator (formerly under the Lanner brand) makes this easy with an out-of-the-box solution. It’s based on 30 years’ experience working in the LNG industry, and the in-built algorithms help you optimise the annual demand plan for a given profile – considering all the variables and systems involved in operations.

Let’s look at an example.

Capacity planning, satisfied suppliers and targeted investments

These are 3 ways a major European LNG operator benefited from predictive simulation as it looked to attract new shippers.

They used the LNG Logistics Simulator to prove to suppliers that they could provide the required capacity. In fact, the modelling even demonstrated that there would be capacity above initial projections, allowing them to set contracts for 6% more.

Additionally, using the simulator, the team ran scenarios for different capacity expansion opportunities to determine which would deliver the best ROI. This helped them direct €165 million of capital investment in the most effective way.

Predictive simulation can help you plan, scale and de-risk at this critical moment in the energy industry’s history.