Smart grid-integrated vessel through a shore power system

Master thesis (2023)

Authors

T.C.J. Weenk Electrical Engineering, Mathematics and Computer Science

Contributors

P.P. Vergara Barrios Intelligent Electrical Power Grids - EEMCS (mentor)
N. Vahabzad Intelligent Electrical Power Grids - EEMCS (mentor)
J.F.J. Pruyn Ship Design, Production and Operations - Mechanical, Maritime and Materials Engineering (graduation committee member)
José L. Rueda Intelligent Electrical Power Grids - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2023 Thomas Weenk
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Published Date

23-01-2023

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Battery energy storage systems (BESS) that are integrated with the electricity grid have proven to be a suitable solution for reducing costs by providing flexible demand, but are often uneconomical when used solely for this purpose. Despite the research efforts showing the benefits of an energy-integrated harbor-area smart grid (HASG), the integration of onboard BESS in synergy with shore power connections has not been considered in the literature. Moreover, not from the financial perspective of the vessel owner.

This thesis addresses the integration of onboard BESS with a shore power system. More specifically, by presenting a cost-effective energy management system (EMS) that uses a stochastic approximation to define the charging and discharging decisions based on electricity prices. Additionally, the system takes the uncertainty of wind power production into account and reduces the power strain on the grid. Besides this, the research provides an analysis of the battery parameters that influence the cost-reducing ability of the EMS. As a result, the additional cost reduction presented while at berth may allow for previously uneconomical investments in onboard BESS for SSCV operators.

The wait-and-see (WS) approach was applied to provide an optimal energy scheduling solution with regard to uncertainty in wind power generation. Within the WS, three strategies were applied. By optimally scheduling a 5MWh BESS, the arbitrage, arbitrage + peak shaving, and peak shaving strategies respectively achieved a 1.4%, 15.7%, and 10.2% yearly reduction in electricity costs for the vessel operator during a 100-day stay in port.