IEEE Transactions on Industry Applications · 2023 · 24 citations · 29 references
EngineeringElectrical EngineeringMarine EngineeringMarine Power SystemsNaval ArchitectureShip ResistanceMarine Energy Control SystemsMarine Energy EconomicsMarine Energy OperationsMarine Power GenerationMarine Power System ReliabilityShipboard Electrical Power GenerationMaritime Energy ManagementNavigationNavigation RegulationOptimal Energy SchedulingResilience OptimizationShipboard Electrical Power SystemsShipboard Power SystemsVoyage Scheduling
Marine power systems are isolated from external grids, making them more vulnerable than land-based power systems. When ships are sailing on the ocean, complicated maritime environment and electrical component failure pose a crucial challenge to a safe and resilient shipboard power system. Different from fixed terrestrial microgrids, all-electric ships (AES) are mobile transportation vessels, complying with the navigation regulation of safe return to port. Thus, the economic and resilient operation needs to be considered from both energy and transportation aspects. In this regard, this study proposes a two-stage coordinated optimization framework for an AES, taking into account the impact of navigation. In the first stage, the normal operation mode follows the pre-voyage plan, which jointly optimizes voyage and energy management to reduce the whole voyage operation costs and greenhouse gas emissions simultaneously. In the second stage, a resilience-oriented optimization is developed to defend against emergencies by rescheduling navigation speed and generation. Furthermore, resistance during the whole AES navigation is also considered. Numerical results demonstrate the necessity of resistance impact on the voyage and the efficiency of the proposed operation scheme in economic and resilient operation for AESs.
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Sepp Hochreiter, Jürgen Schmidhuber · Neural Computation · 1997 · 98.1K citations
Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine
Can Wan, Zhao Xu, Pierre Pinson et al. · IEEE Transactions on Power Systems · 2013 · 750 citations
Computing, Data Science, Forecasting +15