Potential of operational saving measures Orka 2015 Summit Jacob W. Clausen, Head of Advisory
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1 LEADERS IN MARITIME ENERGY EFFICIENCY Potential of operational saving measures Orka 2015 Summit Jacob W. Clausen, Head of Advisory SUPERIOR DATA. ULTIMATE SAVINGS. MAXIMUM RETURNS.
2 AGENDA Introduction Potential of operational measures Use case Realizing saving potentials Key operational energy saving measures Difference in operational performance and potential savings Speed management case example Setting up for driving energy management and recent developed Advisory services
3 Section 1 INTRODUCTION
4 MARINE ENERGY MANAGEMENT Today s Status 2015 Almost all companies are Using standard SEEMP but implementation of measures or changes largely not effective. They are compliant but haven t saved any energy Many companies have Identified measures but struggle with implementation, successfully tracking and monitoring. For these reasons they achieve only minor fuel savings. Big players have Few companies have acted and implemented holistic approach, these companies see 8-15% savings, better charter rates and higher utilization!
5 ENERGY SAVING MEASURES Initiatives by 80 shipping companies studied Hull and propeller cleaning Hull coating Performance monitoring and reporting Top 10 selected initiatives Marorka products Marorka Online Hull performance drop Marorka Solution Voyage plannning optimisation Slow steaming Weather routing Marorka Voyages Speed pattern optimization Trim & draft optimisation Engine performance optimization Engine optimization Marorka Trim & Hull Marorka Machinery 0% 20% 40% 60% 80% 100% Implemented by company Planned for 2015 Source: DNV GL Energy Management Study
6 AUTO-LOGGED VS. MANUAL INPUT DATA Speed drop measuring hull and propeller performance What sensor accuracy can you expect? Speed through water: Speed log 3% GPS 5% Delivered power: Torque meter and RPM 1.1% Flow meter & est. SFOC 7% Tank dip & est. SFOC 10% Shaft Power [kw] Effects of how frequently are you measuring Vessel Speed [kn] Accuracy for each sample method 3 months 12 months Continuous monitoring Noon report torque meter, rpm and speed log 13.9% 7.0% flow meter and speed log 17.5% 8.2% torque meter, rpm and speed log 131% 69% tank dip and GPS speed 264% 136% Note: All values in table are +/- of a mean value to 95% confidence interval Source: UCL Institute, Optimising route, speed and port performance to reduce fuel cons.
7 DATA-DRIVEN ENERGY MANAGEMENT Holistic approach to realize maximum savings Efficient machinery operation Speed profile optimization Propulsion efficiency Optimized bunker control Hull and propeller performance Trim optimization Addressing all key energy saving levers 7
8 TECHNICAL VS. OPERATIONAL MEASURES Comparing large potential saving measures Payback approx. (years) >3 Y 1-3 Y Technical saving measure 1 Bulbous bow 2 Propeller retrofit (slow-steaming) 3 Becker Twisted Fin / Mewis Duct 4 Propeller Boss Cap Fin 5 Auto-tuning of main engine Operational saving measure 6 Marorka solution - Speed management - Trim optimization - ME Optimization - Hull & Propeller Performance - Diesel Generator Optimization < 1Y 14 6 Saving potential USD <0.5 M USD M Net Present value USD >1.5 M 1-2% 2-5% >5% Fuel price of 300 USD/MT NPV savings duration of 5 years and discount rate of 10%
9 Section 2 POTENTIAL OF OPERATIONAL MEASURES
10 DIFFERENCE IN SPEED VS. CONSUMPTION Large spread in vessel daily consumption 10
11 DAILY CONSUMPTION AND HOW IT VARIES Variation shows potential for improvements 11
12 DATA-DRIVEN ENERGY MANAGEMENT Potential savings based on experience from our analysis Diesel Generator Optimization Propulsion Optimization (Main Engine SFOC) Fuel savings Speed Management (Voyage execution) 2% Dynamic Trim Optimization (Reduce hull resistance) 1% 1% (Optimal load sharing) 0.5% 3% 1% 5% 6% Assumptions Upper and lower average saving potential during full operational year Upper and lower potential dependent on current practice Assuming diesel generator is 10% of total fuel consumption and 5% savings translates to 0.5% Earlier corrective maintenance based on real-time data avoiding unnecessary high SFOC Hull & Propeller Perf. (Minimize fouling resistance) 1% 5% Data based decisions for selecting of anti-fouling and measuring hull and propeller cleaning intervals. Transparency and Awareness 1% 5% Experience shows that companies start utilizing real-time data increase awareness of where is energy used Total saving potential 6.5% 25% Upper Lower Min Annual saving potential Payback: <5 months *Assumed fuel price of 300 USD/MT LR2 Tanker 156k USD* Cons. 8,000 MT/year Post-panamax 390k USD* Cons. 20,000 MT/year Ultra Large 546k USD* Cons. 28,000 MT/year
13 Section 3 USE CASE
14 SPEED MANAGEMENT Summary of potential savings tanker and container vessels 71 voyages were analyzed in this study. Optimal speed profile and potential savings were calculated for each voyage. Total potential savings was calculated by the weighted average of fuel savings. Tanker vessel Container vessel # Voyages Savings # Voyages Savings Efficient speed management 2% savings or less % % OK speed management 2-5% savings % 7 3.5% Inefficient speed management 5% saving or more 4 7.5% 8 7.0% Total / Weighted AVG (fuel) % % Annual saving potential Payback: 2-6 months Tanker 120k USD* Consumption 8,000 MT/year Container 394k USD* Consumption 28,000 MT/year *Assumed fuel price of 300 USD/MT
15 SPEED MANAGEMENT Optimizing speed profile for a given route and weather Speed management involves the following objectives: Decreasing Speed Volatility: Minimize speed volatility by staying as close as possible to target speed and thereby reducing speed fluctuations. Speed Profile Planning: Reducing speed on a given route when environmental load (wind, waves, swells and currents) is high and increased again during favourable conditions to make up for lost time. Marorka Voyages enables energy efficient voyage planning and execution based on mathematical models and forecasts for weather and sea state. Fuel consumption and harmful emissions are therefore minimized.
16 SPEED MANAGEMENT Example: Sprint-loitering Actual speed Optimal speed Potential savings MT MT 21.2 MT 58.1 MT/24h 54.5 MT/24h 3.6 MT/24h 6% Ship Container Date Feb 2015 Distance 2,271 nm Draft 8.5 m
17 Section 2 REALIZING SAVING POTENTIALS
18 REALIZING SAVING POTENTIAL Setting up for data driven energy management Marorka understands that every organization is unique with its own set of challenges. Nevertheless we at Marorka Advisory encounter the same general challenges, when considering implementation of energy management system on a fleet level. 1. Analyze and Plan Create baseline of current fleet performance level though analysis of your data. Plan for data driven energy management including identify KPIs and set targets for energy savings. 4. Evaluate and Improve 3. Monitor and Track 1. Analyze and Plan 2. Adapt and Implement 2. Adapt and Implement Establish organizational framework for implementing and using Marorka solution. Identify and prioritize energy saving initiatives and create SEEMP. 3. Monitor and Track Monitor and track fleet performance using benefits of auto-logged data. Train on-shore management to create baselines and identify excess consumption. 4. Evaluate and Improve Evaluate fleet performance, evaluate impact of energy saving initiatives and identity future initiatives. Train on-shore management to maximize benefits of auto-logged data from Marorka system. 18
19 ASSISTING CUSTOMERS IN REALIZING SAVINGS New Advisory services Implementation & training packages Marorka Advisory Data analysis & validation Fuel Tables (speed cons. + power) 19
20 THANK YOU! MARORKA Borgartun 26, 105 Reykjavik, Iceland USE SUPERIOR DATA. REALIZE ULTIMATE SAVINGS. MAXIMIZE YOUR RETURNS.
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