Our algo-based LNG shipping and portfolio optimisation software with an integrated Hydrogen shipping model. All model elements listed in the sections Digital Fleet Management and Portfolio Optimisation are consistent and iterate with each other to maintain the solution’s optimality at all times.

Model Input

Vessel characteristics used for optimisation:
  • Charter rate
  • Volume
  • BOG rates (laden/ballast)
  • Speed variations
  • Bunker fuel consumption (laden/ballast)
Global LNG infrastructure:
  • 289 LNG terminals / trains
  • Choose from list or select on global map
  • Dynamic time windows for pick-up and delivery
  • Dynamic nomination of discharge ports for DES contracts
Shortest maritime connections based on historic ship movements:
  • Distance matrix in nautical miles
  • Second-best route alternatives in case of Suez/Panama conjunctions
  • Panama and Suez incl. transit costs
  • Northeast Passage (min. Arc7)
  • Cost premium in risk areas
  • Route alternatives in case of Suez/Panama conjunctions
Optimisation of client’s Long and Short positions:
  • LTCs are entered in ADP first
  • FOB and DES cargos included
  • Spot trades can be added to portfolio in short term horizon
  • Prices based on forward curves or client’s assumptions
  • Stochastic optimisation taking into account price fluctuations

Hydrogen Shipping Model

First global shipping model for hydrogen carriers:
  • Simulation tool for H2 carriers (LH2, ammonia/ethanol bonds, LOHC)
  • Shipping model with existing & planned tanker and terminal capacities
  • Data/estimates on carrier-specific parameters e.g. Boil-off of LH2, NOx emissions of ammonia bonding, pyrolysis cost estimates for chemical bonds
  • Full shipping costs break-down for each carrier
  • Integration of H2 cargos in contract portfolio

Digital Fleet Management

  • Optimisation of client’s Long and Short positions (incl. FOB and DES), spot cargos can also be added.

  • Temporal and geographic contract constraints can be specified closer to the nomination deadlines.

  • AI-based clustering of ports into regions and route groups also helps to downsize the number of relevant nodes – in order to reduce the optimality gap and increase computing speed.

  • Dynamic routing optimisation from fleet perspective with unlimited number of daily re-calculations.

  • Canals and bottlenecks: costs and waiting times at canals can be adjusted and certain bottlenecks (such as NEP) seasonally disabled, with instantaneous re-calculation of the optimal fleet routing.

  • Vessels: model optimises the vessels’ speed taking into account the contractual time windows, bunker costs and idle time. Bunker fuel consumption and BOG are modelled for ballast and laden journeys. Acceleration is achieved through forced BOG or HFO with a separate bunker optimisation depending on fuel prices and opportunity costs.

  • Ports: distance matrix comprises all existing LNG terminals incl. berth constraints, with contractual time windows for pick-up and delivery.

  • Computing time of a few minutes enables hundreds of model runs daily to ensure the routing optimality with changing constraints.

  • User receives full break-down of shipping costs for each vessel & route.
  • Optimisation of bunker fuel based on consumption rates, fuel prices and opportunity costs (reduced LNG volume for sale), constrained by contractual min. volume restrictions.

  • For each vessel in the fleet, consumption formulas for variable speeds are provided for gas, HFO and MDO (we have a decent vessels database, but the client can also provide his own data on vessel performance.

  • Optimisation is performed outside the main model to reduce run time.

  • In-tank management for remaining LNG on ballast journey.

  • Constant re-evaluation of cool-down feasibility depending on tank types, boil-off rates and prospective journey time.

  • Optimisation is performed outside the main model to reduce run time.

  • Portfolio Optimisation

    • Extension of the ADP planning tool to capture intrinsic and extrinsic value of client’s portfolio.

    • Model takes into account changing hub prices and contract prices to maintain the portfolio’s optimality with a dynamic information flow.

    • Forward curves based price modelling, using Monte Carlo Simulations to model price variations; Client can also feed in his own price assumptions.

    • Compute and predict complete price and cost distributions to model uncertainty. The model can determine the most profitable trading strategies and routes under this uncertainty.
  • Additional stochastic risks beyond the price variations, can also be included in the model concerning meteorological conditions, traffic jams (at Panama or Suez), piracy and security issues, etc.

  • Contract changes, spot cargos, or canal queues require permanent route adjustments – Algorithmic Tree Search mechanisms enable short-term routing adjustments without a full model recalculation.

  • Output consists of an optimal fleet deployment plan with stable routes that is maximizing the client’s portfolio value.

  • We provide commonly used risk metrics such as Value-at-Risk or Profit-at-Risk as well as the full profit and cost distributions for the proposed trading strategies.
  • While X-LNG is a model specifically developed for LNG shipping and trading, it includes a Gas market add-on to value the LNG beyond arrival at the discharge port. The model evaluates the profitability of re-gasification upon arrival, storage, or direct sales in liquid form.
  • UI & UX

    The optimisation software can be accessed through an API or through the browser dashboard.

    Integration with client’s contracts database and vessel database can be undertaken

    UI for manual input entry through typing, choice from drop down menu or selection on a map

    Visualisation of fleet routing output on map to continually track vessel movements

    Output can either be fed back into client’s trading systems, provided in excel or accessed through the UI

    Full output break-down vessel by vessel, or contract by contract is available to see and understand cost and revenue drivers

    Documentation on the API is provided by Calypso; Adaptation of the API to the customer's interfaces possible on request

    Tech Support And Model Updates

    As we are keen to offer our clients a ready-to-use product, we also commit to a four-week integration phase after the purchase. During this phase we would be available on demand to assist your team in the initialisation of all models, to troubleshoot any bugs, and to support on any issues arising with the use of the models. Beyond that, we would like to offer you two tech-support packages.

    Tech support: Beyond this initialisation phase, we also offer unlimited tech-support per mail/phone on arising questions and troubleshooting.

    Model updates: We continuously develop our models and extend their functionalities. Under the regular user licence all model updates are free or additional charge during the licence period.