KMB D2V: Design and Verification of Control Systems for Safe and Energy-efficient Vessels with Hybrid Power Plants

Transkript

1 1 KMB D2V: Design and Verification of Control Systems for Safe and Energy-efficient Vessels with Hybrid Power Plants Associated AMOS Project Partners: Kongsberg Maritime, DNV GL and NTNU

2 2 AMOS Research Areas 1. Autonomous offshore renewable energy 2. Offshore aquaculture 3. Autonomous unmanned vehicles and operations 4. Smarter, safer and greener marine vessels and operations

3 3 Project 6: Energy management and propulsion for greener operations of ships and offshore structures Project manager Prof. Tor Arne Johansen Department of Eng. Cybernetics AMOS How to develop hybrid power plants reducing energy consumption and emissions to a fraction of todays solutions?

4 4 Project 7: Autonomous Marine Operations in Extreme Seas, Violent Water-Structure Interactions, Deep Waters and Arctic Project manager Prof. Asgeir J. Sørensen Department of Marine Technology AMOS How to operate smarter, safer and greener at any weather condition and offshore site?

5 5 KMB D2V: Design and Verification of Control Systems for Safe and Energy-efficient Vessels with Hybrid Power Plants Design and verification of complex systems by system simulations Analysis of transient and stationary dynamics on fuel consumption and gas emissions Optimal and fault-tolerant control of hybrid power systems on ships and rigs o o o Diesel- and LNG-driven gensets Energy storage using battery banks, flywheels, etc AC and DC systems Partners: Kongsberg Maritime, DNV GL, and NTNU o o Prof. Asgeir Sørensen (IMT Project manager) Profs. Roger Skjetne, Ingrid B. Utne, Eilif Pedersen (IMT) and Tor Arne Johansen (ITK) 6 ph.d. students Budget: NOK 18,76 Million

6 6 Modeling for Emission Management of Marine Hybrid Power Plants Develop a power plant simulation model for transient operation focusing on diesel and gas/duel fuel engines at multiple complexity levels for emission predictions Methods and strategies for Emission Management PhD-student Kevin Koosup Yum South Korea Supervisor Associate Professor Eilif Pedersen

7 7 Control of Hybrid Power Plants PhD Candidate: Michel Rejani Miyazaki Modelling, design and control of hybrid power plants, focusing on DC grids and energy storage devices. Outcomes Marine Power Simulator, with DC grids and energy storage modules Comparison between several energy storage control strategies, with HIL tests on the Hybrid lab at NTNU Supervisor: Asgeir J. Sørensen Co-supervisors: Eduardo A. Tannuri Eilif Pedersen Roger Skjetne Tor A. Johansen

8 8 Power Management Based on Model Predictive Control PhD Candidate: Torstein Ingebrigtsen Bø The electric power plant is a safety critical component during DP. Increasing redundancy increases the safety, but increase fuel consumption and emissions. By simulation, the safety and optimality can be evaluated. Simulation based methods will be explored for: Governors Automatic start and stop of generators Outcomes: Marine Power and Vessel Simulator Scenario Based Economic Model Predictive Control Simulation Based Unit Commitment Supervisor: Tor Arne Johansen Co-supervisors: Asgeir Sørensen & Roger Skjetne You can add pictures on the slide showing what you do

9 9 Nonlinear and Fault-tolerant Control of Electric Power Production in Arctic DP Vessels PhD Candidate: Andreas Reason Dahl Increased producer diversity (diesel, LNG, batteries, fuel cells) in marine power plants calls for new control methods. Load sharing by nonlinear coordinated control Fault-tolerant control on producer and plant level Outcomes: Model producers and plants Develop concepts and algorithms: load sharing fault-tolerant control Verify through simulations and in hybrid power lab Supervisor: Professor Skjetne, Roger Co-supervisor: Professor Sørensen, Asgeir Johan

10 10 A New Approach for Handling Risk in Dynamic Position Systems for Marine Vessels PhD Candidate: Børge Rokseth The scope of this project is to develop new methods based on dynamic models for on-line handling and control of risk associated to drift-off and drive-off for dynamically positioned vessels. This does comprise On-line hazard identification techniques On-line identification of possible worst case failures On-line analysis of consequences of worst case failures Outcomes: The outcomes of this will be a general frame work for on-line risk handling for advanced dynamic systems where the causality and interconnections between subsystems and components cannot easily be perceived by the human brain. Supervisor: Professor Ingrid Bouwer Utne Co-supervisors: Associate Professor Eilif Pedersen Professor Asgeir J. Sørensen

11 11 Hybrid power simulator

12 12 Hvorfor simulere hele systemet?

13 13 Overordnede krav Sanntidssimulering eller detaljsimulering Integrasjon mellom kontrollsystemene i skipet Gjennomgående detaljgrad Feilhåndtering Modularitet Skalerbarhet Brukervennelighet Utvikling Konfigurasjon Sluttbruker

14 14

15 15

16 16 Bruksområder Feilsimulering Optimalisering av drift Optimalisering av design Power plant Komponenter

17 17 Multidomene Hydrodynamikk Kontrollsystemer Mekanikk Elektronikk Termodynamikk

18 18 DP DP: PID Observer: Passive Observer

19 19 Miljøkrefter Havstrøm: saktevarierende Vind: kast- og saktevarierende middelvind Bølger: irregulær sjø, første og andre ordens bølgekrefter

20 20 Thrustallokasjon Ulineært optimaliseringsproblem Effektbegrensninger fra power management system for bus og thrustere Allokerer effekt til thrustere Roterende thrustere Singularitet unngåelse

21 21 Thruster Turtallsregulert Motormodell, for effektbegrensninger 4-kvadranters propellmodell Ingen bølgeinnteraksjoner Glatting av refferansesignal Fluktuerende last (±1 %)

22 22 Elektriske systemet Stasjonær Frekvens og effektfordeling

23 23 Dieselmotor modell Mean value engine model Strømningsbegrensninger og oppslagstabeller for sylinderprosesser 20x real-time

24 24 Simulerings Case 1 Drilling rig 6 genset på 9.1 MW 3 tavler koblet i ring 6 thrustere på 4.2 MW Signifikant bølgehøyde: 5 m

25 25 DP: posisjon

26 26 Frekvens og power

27 27 Test av dieselmotor modeller: Mean value modell mot forenklet modell

28 28 Laststeg, uten begrenser

29 29 Test av dieselmotor modell

30 30 Laststeg, med begrenser

31 31 Case: nødbatteri ved tap av generator Fast load reduction ved tap av generator. Frekvens faller og kan gi (delvis) blackout. Kan batterier bli brukt?

32 32 Frekvens

33 33 Power

34 34 Oppsummering Hydrodynamikk Kontrollsystemer Mekanikk Elektronikk Termodynamikk