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 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.

Automated summary

This paper proposes an optimal coordination method for energy dispatch and voyage scheduling for a renewable-energy-integrated hybrid AC/DC multi-energy ship microgrid under continuous ship swinging. Various uncertainties are managed by an adaptive risk-averse stochastic programming approach to minimize voyage cost and conditional value-at-risk, while chance constraints are introduced to improve thermal service quality. The original nonlinear/nonconvex operation constraints are reformulated for efficient solution using commercial solvers.