| dc.description.abstract | In this paper the main focus has been to investigate different approaches of utilizing a hybrid offshore vessel (HOV) and evaluate the sustainability of a complete hybridization. A hybridization refers to the process, of retrofitting an alternative power source, opposed to the traditional combustion engines. The evaluated HOVs in this paper, have a power system consisting of a combination of diesel engines and a lithium-ion battery. The purposes of a hybridization are to generate cost savings for the shipowner and customer, and also to reduce the carbon footprint of the vessel.
To achieve these objectives, an energy management system (EMS) will be used to execute various control schemes, optimizing the power production. While reducing emission, running hours and number of running engines. An EMS is a software which controls and protects the hardware, required to control flow of energy to and from the lithium-ion battery.
As a foundation, a control strategy was formulated for each of the three main operating modes of an offshore vessel, namely dynamic positioning (DP), transit and port. These strategies was used to investigate the potential savings. In order to evaluate the potential savings, a cost- and savings estimate was created. These estimates are based on operation data received from personal communication with SolstadFarstad [1], for a selection of the offshore fleet, PSV fleet and the vessel Far Sun. The result of these estimates should give an indication, whether a hybridization is sustainable or not.
To be able to validate the most complicated control function, particularly the peak-shaving algorithm and the support functions, a simulator was created. The main objective of the peak-shaving algorithm is to stabilize the load seen by the engines and to provide an enhanced dynamic response. This functionality is designed for operations where the engine(s) load is varying, such as a DP operation. When peak-shaving is activated it should reduce the load peaks, averaging the engine load —which in many situations reduces the need for running several engines.
The developed simulation has the ability to import a load profile and pass it through a model of an EMS. The output of the simulator are several graphs, showing the total system load with and without the battery. Additionally, the simulator calculates the fuel consumption and simulates the current state of the battery.
After validating the peak-shaving functionality, a small-scale system was developed and tested in the lab before a prototype was created. This system was further developed and deployed onboard the vessels Far Sun, Far Searcher, Skandi Mongstad and Skandi Flora. The result from the deployment of the EMS onboard these vessels will be presented and discussed later in the paper. The main topics presented will be the achieved functionality of the system, as well as the fuel savings for the vessel Far Sun.
The overall result shows that performing a hybridization of an offshore vessel, reduces fuel consumption, emission and running hours. Although the reduction is highly dependent on the operation profile of the vessel. Additionally, a hybridization increases the dynamic response of the vessel, while acting as an uninterrupted power supply (UPS) or spinning reserve, in case of engine shutdown.
To calculate the yearly potential savings for a platform supply vessel (PSV), an average operation profile for a PSV and data form a Rolls Royce C25 33 engine [2] was considered. The result shows that it could be possible to reduce the yearly fuel consumption, of a PSV by 5.7%, based on several design criteria. Additionally, the emission of CO2 and NOx could be reduced by 356.9 tonnes and 8.2 tonnes, while the running hours could be reduced by 35.8%. This reduction of CO2 and NOx emission is equivalent to 2800.5 tonnes CO2 equivalents. Such reduction can be compared to reducing the number of running passengers cars in Norway by 1 400.
To be able to evaluate theoretical saving and actual savings, operation data from the vessel Far Sun has been collected and studied. The operation data is form the period March 1st to May 1st, 2018. This data has been compared against the same period for the year 2016 and 2017. The result shows an average reduction in fuel consumption of 5.1% for the year 2018. | nb_NO |
