Logistical Analysis for Offshore Wind │LAUTEC Consulting

logistical analysis for offshore wind

The Difference Between ESOX and ESOX Python

We have used two different tools for sequential downtime modeling:

ESOX is our user-friendly, simplified Excel-based tool available as freeware, which works only with the ERA5 data from the ESOX website. We also provide custom-built, paid versions of ESOX based on individual client requests.
ESOX Python is our advanced, flexible Python-based tool for high complexity modeling, which is run by our internal staff on a consulting basis. We do not provide the tool itself to our clients.

Compare ESOX and ESOX Python


Automated generation of a task list for cycle-based work campaigns
Manual editing of individual tasks in the auto-generated task list
Multi-variable constraints
Hs/Tp curve workability limits for floating operations
Learning curve modeling
Generate weather calendars for P6 and MS Project
Milestone completion statistics
Root cause analysis
Annual campaign simulation for each reanalysis year
Global ERA5 metocean time series data
Time step log of simulation steps for validation of results
Any number and type of time series variables
Parallel, interdependent activity streams
Shared inventory modeling
Shared resource modeling
Weather window requirements with non-constant limits
Advanced root cause analysis

Unlock the Full Potential of Your Installation Setup

ESOX PYTHON DATA EXAMPLE

Unlock the Full Potential of Your Installation Setup

Visualize the root cause for downtime, identify the bottlenecks and optimize your construction setup accordingly.

Evaluate Storage Area Size

ESOX PYTHON DATA EXAMPLE

Evaluate Storage Area Size

Dimension your storage capacity by modeling inbound and outbound logistics. Will the installation vessels run out of components in a P30 scenario? How likely is it that the storage capacity limit will be reached, stopping the inbound logistics?

(A) Risk of storage at max capacity (12 WGTs). Inbound logistics on standby until the next load-out of components.

(B) Risk of running out of WTGs at staging port. Coupling of load-out activities and storage level.

Interdependent Workability Criteria

ESOX PYTHON DATA EXAMPLE

Interdependent Workability Criteria

Model interdependent operational constraints, such as floating operations with interdependent wave periods and wave heights.

Fixed, individual limits on wave height and wave period leads to overly conservative downtime estimates. Identify all workable periods by modeling the correct Hs-Tp curves instead .

Curious about how it works? Check out the tool!

ESOX Python Implementation Case

Project: Supporting an offshore wind project in the US Atlantic Coast by analyzing the transport and installation options.

Challenges: The logistic options including several vessels feeding components from different harbours to a main installation vessel located at the offshore site. Some of the questions asked were:

How do the feeder vessels’ performance impact the construction schedule?
How many feeder vessels are needed so that the main installation vessel remains in the critical path of the installation program?
What does the port in-/outbound logistics look like?
Will the rate of inbound components be sufficient?
Will the port storage be able to accommodate all components during the installation program?

Outcome: ESOX Python helped to answer the questions by combining unparalleled modelling capabilities together with our specialists’ solid industry experience.

ESOX Python

Advanced Weather Downtime Simulations