Shuli Wen

TL;DR: In this article, the optimal size of the photovoltaic (PV) generation system, diesel generator and the energy storage system in a stand-alone ship power system that minimizes the investment cost, fuel cost and the CO2 emissions is proposed.

TL;DR: In this paper, a hybrid multi-objective particle swarm optimization (HMOPSO) approach is proposed to minimize the power system cost and improve the system voltage profiles by searching sitting and sizing of storage units under consideration of uncertainties in wind power production.

TL;DR: In this paper, an interval uncertainty model of on-board PV generation is established, which considers the effect of the swinging of the ship, and an interval optimization method is developed to determine the optimal size of the ESS in this hybrid ship power system to reduce the fuel cost, capital cost of the energy storage system, and emissions of greenhouse gases.

TL;DR: This paper explores a deep learning approach to identify active power fluctuations in real-time, which is based on a long short-term memory recurrent neural network and provides a more accurate and faster estimation of the value of power fluctuations from the real- time measured frequency signal.

TL;DR: In this article, the authors proposed a mathematical model of a photovoltaic (PV) power generation system for a ship, taking into account the effects of ship rolling.