New developments in Energy Management – battery lifetime incorporation and power consumption forecasting

In the context of a continuously developing electrical world where the systems are becoming more complex, the demands on fuel consumption and greenhouse gases reduction are also becoming stricter. Additionally, more vessels are looking into using various energy sources – batteries, variable speed generators, etc. – to improve their operation. For such systems, an energy management system (EMS) becomes a vital component. The task of an EMS is to optimize the operation based on a specific goal or goals. Mostly it is the optimization of fuel consumption, and thus also the exhaust pollution reduction, that the EMS is striving to achieve. After implementing the EMS on seagoing ferries (predictable load cycle) and a super yacht (non-predictable load cycle), RH Marine has analysed the measured data and has seen a considerable reduction of fuel consumption, of even up to 38%. With the initial goals achieved, the EMS operation can now be expanded to include more tasks.

A further development of the EMS is to incorporate lifetime, wear and tear, and maintenance requirements of equipment into it.  Doing so makes it possible to optimise on total cost of ownership (TCO). As a proof of concept the battery lifetime has been incorporated. Extensive simulations demonstrate that the battery lifetime can be extended, or better: a required lifetime can be reached. This can be realised by carefully observing lifetime determining quantities, like state of charge (SOC), magnitude of charging and discharging currents. This is achieved with a minimal impact on the previously obtained reduction in fuel consumption. The same is valid for other energy sources, such as diesel-generator sets (DGs). By incorporating effects of start-stop cycles on wear and tear, the use of these can be optimised regarding TCO as well.

The better the load can be predicted, the better the EMS will perform. The self-learning function of the EMS will make use of all available data, both from past and future, like a planned combat mode. The paper describes how the above has been integrated into the EMS. The simulations that were performed to prove the concept as described are presented and further developments in the near future will be announced.