Economic Analysis of Hybrid Wind/PV/Diesel/ESS System on a Large Oil Tanker

Abstract

Due to the global concern on the increasing amount of fossil energy consumed by traditional ships, the application of renewable energy into a ship power system provides a new solution to improve the energy efficiency and to reduce the greenhouse gas emissions. This study proposes a stand-alone power system on a large oil tanker including wind generation system, photovoltaic generation system, the diesel generator, and the energy storage system (ESS). Unlike on land, the wind generation on the shipboard not only relies on the natural wind speed but also the ship's course and speed. The installation of the wind turbines on the board is optimally designed, which takes the relative speed into account. In order to mitigate the intermittence of the renewable energy generation, a lead–acid battery serves as the ESS to enhance the stability of the ship power system, and the size is optimized by the multi-objective particle swarm optimization to minimize the whole system cost and CO₂ emissions. Additionally, variations of the ship loads are considered with respect to the different operational conditions. Various cases are compared in detail to demonstrate the applicability of the proposed algorithm.

Keywords:

• wind power generation system
• photovoltaic generation system
• energy storage system
• oil tanker
• multi-objective particle swarm optimization

Additional information

Notes on contributors

Shuli Wen

Shuli Wen was born in 1987 and received his PhD degree from Harbin Engineering University, Harbin, China, in 2016. Currently, he is a lecturer at Harbin Engineering University, and his research interests mainly focus on the renewable energy, power system planning and optimization, and microgrid.

Hai Lan

Hai Lan was born in 1975. He is a professor at Harbin Engineering University, Harbin, China. Prof. Lan is a member of IEEE, and his current research interests include microgrid, ship power system analysis, control theory, etc.

Jinfeng Dai

Jinfeng Dai received his MS degree from Harbin Engineering University, Harbin, China, in 2016. His research mainly focuses on modeling and assessing of microgrid as well as probabilistic analysis of power system.

Ying-Yi Hong

Ying-Yi Hong received his BSEE degree from the Chung Yuan Christian University, Chung Li, Taiwan, in 1984, and his MSEE degree from the National Cheng Kung University, Tainan, in 1986, and his PhD degree in electrical engineering from the National Tsing-Hua University, Hsin Chu, in 1990. Sponsored by the Ministry of Education of ROC, he conducted research in the Department of Electrical Engineering, University of Washington, Seattle, WA, USA, from 1989 to 1990. He was the Chair for the IEEE Power and Engineering Society Taipei Chapter in 2001. His research interests are power system analysis and artificial intelligence (AI) applications.

David C. Yu

David C. Yu received his PhD degree in Electrical Engineering from the University of Oklahoma, Norman, in 1983. Currently, he is a full professor in the Department of Electrical Engineering and Computer Science at the University of Wisconsin, Milwaukee. His research interests include power distribution system analysis, renewable energy, and microgrid analysis.

Lijun Yu

Lijun Yu was born in 1976. He is an associate professor at Harbin Engineering University, Harbin, China. His current research interests include nonlinear system control and ship power system control.