Narrator: Welcome to the forefront
of the energy transition.
Integrated energy technologies are gaining traction,
enabling lower carbon energy systems at a lower cost.
However, only 4% of integrated energy projects
reach the final investment decision
due to major challenges such as technology
and infrastructure uncertainty, nascent markets
and offtake, complex business cases,
emerging and ambiguous regulations,
and a lack of required expertise.
Energy Transition Optimizer by BCG X is a cutting edge AI
and advanced analytics solution
designed to revolutionize large-scale energy projects.
The solution explores a variety of designs
considering different technologies, asset sizes,
weather patterns, and market conditions
to optimize each design on an hourly
and minute-by-minute basis.
Finally, the solution shares full lifetime asset operations
and the associated pro forma profit and loss,
which can be used to assess financial
and operational KPIs such as IRR
or percentage of off-take contract fulfilled.
Let's take a closer look at
how Energy Transition Optimizer supports a pre-feasibility
study of a green methanol project for decarbonized shipping.
The client's initial pre-feasibility study
yielded a baseline design with a set of technologies
and asset-sizing choices.
Leveraging the Energy Transition Optimizer user interface,
the business analyst can build the methanol project layout
and configure the optimization, starting with parameters
such as the project's lifetime, the optimization criteria,
and the income statement options.
Next, by clicking on an asset or a market,
they can define the exploration space,
including the range of possible capacities, technologies,
costs, and contract types.
Once ready, they can launch the simulations.
During and after the optimization,
the business analyst can explore the results page
and download the simulated financial reports
and operational metrics.
They can also draw rapid insights
from the visualization page.
Here the analyst selects CapEx
and levelized cost of methanol as KPIs to compare designs.
The plot quickly reveals an optimal design
with lower methanol costs for the same CapEx.
When choosing to shrink the electrolyzer
and increase renewables, the business analyst can cut costs
by 25% and increase production by 13%
compared to the baseline design.
The identified design reduces the project's overall risk
of producing negative returns by 20%.
The ability to rapidly test many designs
with technical confidence saves thousands
of billable engineering hours.
Energy Transition Optimizer has been deployed
to aid the investment decisions of leading energy companies
and auction authorities worldwide.
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Are you ready to transition with confidence
to a greener tomorrow
with Energy Transition Optimizer?
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