000007720 001__ 7720
000007720 005__ 20241024114710.0
000007720 02470 $$2doi$$a10.24868/issn.2631-8741.2018.007
000007720 035__ $$a2536810
000007720 037__ $$aGENERAL
000007720 245__ $$aThe role of future information in control system design for shipboard power systems
000007720 269__ $$a2018-10-02
000007720 336__ $$aConference Proceedings
000007720 520__ $$aBoth naval and commercial ships are incorporating new power and energy system technologies to improve fuel economy and performance while servicing high power pulsed loads. These assets can be best utilized with load demand forecasting and/or prediction, especially when considering limits on generator ramp rates, distribution lines, and energy storage capacity. Obtaining future load demand data and designing a controller to accommodate it can be challenging, but with potentially large payoff. However, this information is not useful in all cases. This paper develops a method to quantify the potential value of future information depending on the specific power system characteristics. This quantitative approach aids designers in deciding how and when to deploy future forecasting in controller design, and provides insight into the potential benefits of these more complex controllers. To quantify this trade off, two optimization-based control methods are developed. One uses only current information, while the other has an exact forecast of the future. As examples, the method is applied to a notional naval ship and drill platform service vessel with representative power and energy system architectures under indicative operational load demands. 
000007720 542__ $$fCC-BY-NC-ND-4.0
000007720 6531_ $$aPower System Design
000007720 6531_ $$aPredictive Control
000007720 6531_ $$aEnergy Storage
000007720 6531_ $$aDynamic Loads
000007720 7001_ $$aOpila, D F$$uUnited States Naval Academy
000007720 7001_ $$aStevens, J D$$uUnited States Naval Academy
000007720 7001_ $$aCramer, A M$$uUniversity of Kentucky
000007720 773__ $$tConference Proceedings of iSCSS
000007720 773__ $$jiSCSS 2018
000007720 789__ $$whttps://zenodo.org/record/2536810$$2URL$$eIsIdenticalTo
000007720 8564_ $$9f121c2dd-dc55-476d-818e-0c11c2e8d746$$s1028527$$uhttps://library.imarest.org/record/7720/files/ISCSS%202018%20Paper%20014%20Opila%20FINAL.pdf