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International shipping, like every industry, is driven by economics. The revenue and cost implications are a factor in every decision taken. Regulatory compliance and market demands are also essential factors. Since revenue is under stress, and more so in these difficult times, the global economy is going through, the cost and its reduction is a significant focus. The fuel cost contributes to 50-70% of OPEX[1] for a ship. In recent years many solutions have emerged that claims savings on fuel consumption like trim optimisation, route optimisation, PBCF[2] installation, Higher efficient propeller, Bow modification, and low friction coating. An investment in any of these solutions needs a clear ROI[3] for a proper business decision. The emergence of ISO 19030 as an accepted standard has paved the way for using the same standard to arrive at ROI computation.

# Understanding Ship performance

If one takes the ship as a whole, the input for generating mechanical energy is the fuel. If we separate propulsion needs, then the fuel consumption by the main engine is the input. The output is speed on the water the ship can move against all the adverse effects like the weight of the vessel, wind, wave, hull, propeller, and engine condition. We can find the engine efficiency in these steps. One way to separate the engine condition is to take engine shaft power as input instead of fuel. By doing this as well as removing the effect of vessel weight, wind, wave, current, depth, temperature, density, we can track the change in performance as a measure of achieving speed by keeping power as constant.

# ISO 19030

Once we agree to the ship performance metric, there were several methods to do data filtering, corrections for various effects, as well as interpretation of results. This range of options also meant that there was a need for an industry standard. ISO 19030 fills that need. Here we monitor the change in speed attained for the same power compared to sea trials condition after made necessary corrections for wind, current, and filter for data quality, water temperature, depth.

ISO 19030 clearly defines how to calculate speed loss for vessels using frequently collected data (automatic data). It also gives provision to estimate speed loss using noon data (reported once daily) with some exceptions by compromising the accuracy of results. Since the methodology is standardised, both owners and vendors (of energy-saving devices (ESD) and paint) are at an agreement to measure the performance. Shipowners can verify the claim raised by the vendors, and this brings transparency in the performance measurement.

# Limitations of ISO 19030

But still, ISO 19030 gives results in terms of speed loss or gain, which will not help owners to know whether the investment justifies the cost. They need to understand what reduction it caused in the vessel’s fuel consumption. Only if get the savings they can verify the payback period or ROI. Speed loss can be converted to the factor of time saved to reach a cargo, but not a good measure when vessels are slow steaming.

Vendors convert the speed gain to the fuel gain using some coefficients. But the method followed is approximate, and there exists a problem in an accurate fuel savings estimation.

# Current Methods and Issues

Vendors generally use three as a multiplier for fuel savings estimation – i.e., assuming power is proportional to speed^3. Hence if the speed gain from the ISO analysis method is 2%, then the fuel savings are estimated at 6%. But this relation is merely theoretical. See the below sea trial.

This sea trial is for ballast condition shows the following relationship, Power = Const x (Speed)^^{4.664}. For this vessel, we are underestimating the fuel savings by 55% if we multiply the speed gain by 3. For this example of 3% speed gain (assume this gain is in ballast draft), actual fuel savings is 14% where we estimated only 9%.

Another problem is when coefficients for the ballast curve and scantling curve are different. Here model test-based prediction shows for ballast draft, Power = Const x (Speed)^^{3.57} and for scantling draft, Power = Const x (Speed)^^{2.87}. Here, speed gain multiplied by three gives an average value, not accurate. We are overestimating the fuel savings for the loaded voyage and underestimating for a ballast voyage. So, fuel savings will change depending on the voyage drafts.

Similarly, the curve nature is different for different trims also. These examples show that we can underestimate or overestimate the fuel savings if we ignore the vessel’s behavior at different speeds, drafts, and trims.

# Our Solution

One thing is evident now that we should have a database at sea trials – for different speeds, drafts, and trim. This database has to be created from the vessel model/lines plan or sea trial if available. The model can predict how the vessel behaviour changes when the draft or trim is changed. Hence the change in fuel consumption due to the change in operational and environmental conditions can be accurately estimated. In other words, we can normalise the fuel consumption for draft, trim, and weather.

It is easy to compare if we normalise the fuel consumption to a particular draft and trim, say scantling draft and even keel, at calm weather. We can compare the normalised consumption before and after ESD installation or Dry Docking and painting to know the fuel gain. The below images show how normalisation can simplify the problem.

*Figure 3: Speed Power plot for reported raw data*

*Figure 4: Speed Power plot after filtering and correcting for weather*

*Figure 5: Speed Power plot after normalising to design draft*

*Figure 6: Fuel savings after drydock*

By this method, we will get real fuel savings by comparing the normalised consumptions between two periods. The below image shows the fuel estimation of a vessel after drydock.

# Conclusion

ISO 19030 provides a proper methodology to estimate speed loss/gain. This methodology standardises the performance estimation methods across the industry and helps shipowners to get on the same page with vendors.

But the standard does not focus on estimating fuel loss/gain nor establishes a method to convert it from speed loss/gain. Hence it leaves a gap behind which needs the application of smart technology to overcome it. Normalising fuel consumption is an effective method to estimate fuel gain due to any retrofit activities or ESD installations. Hence shipowners require additional technology along with implementing ISO 19030 to calculate the consumptions and ROI accurately. XShip Performance provides normalised fuel consumption for all its vessels.

[1] Operating Expenses

[2] Propeller Boss Cap Fin

[3] Return on Investment

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