A Risk-Averse Adaptively Stochastic Optimization Method for Multi-Energy Ship Operation Under Diverse Uncertainties

In this paper, an optimal coordination method for energy dispatch and voyage scheduling is proposed for a renewable-energy-integrated hybrid AC/DC multi-energy ship (MES) microgrid under the continuous ship swinging. In the MES microgrid, all the onboard units are dispatched coordinately with higher...

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Veröffentlicht in:IEEE transactions on power systems Jg. 36; H. 3; S. 2149 - 2161
Hauptverfasser: Li, Zhengmao, Xu, Yan, Wu, Lei, Zheng, Xiaodong
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.05.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
adaptively stochastic programming
chance-constraints
Constraints
Distributed generation
Energy
Immunization
Marine vehicles
Microgrids
Mixed integer
Multi-energy ship (MES)
Operating costs
Optimization
Programming
Propulsion
quadratically constrained
Risk management
risk-averse
Scheduling
Seaports
Thermal loading
Uncertainty
voyage scheduling
ISSN:0885-8950, 1558-0679
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Zusammenfassung:In this paper, an optimal coordination method for energy dispatch and voyage scheduling is proposed for a renewable-energy-integrated hybrid AC/DC multi-energy ship (MES) microgrid under the continuous ship swinging. In the MES microgrid, all the onboard units are dispatched coordinately with higher flexibility for providing multiple energies. To guarantee the reliable ship operation, diverse uncertainties from solar irradiation, ship swinging angle, and onboard multi-energy demands are managed by an adaptive risk-averse stochastic programming approach to minimize the voyage cost and conditional value-at-risk. Besides, chance constraints are introduced to leverage the quality of thermal service given the thermal inertia. To speed up the solution process, the original nonlinear/nonconvex operation constraints are reformulated to a mixed-integer quadratically constrained programming form by linearization/convexification and scenario generation/reduction methods. Then the problem can be efficiently solved by commercial solvers. Finally, case studies are conducted on a test MES microgrid. The simulation results verify that the proposed method is effective in coordinating multi-energy dispatch and voyage scheduling, minimizing operating cost/risk, and immunizing against diverse uncertainties.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2020.3039538