Abstract
Plug-in photovoltaics (PV)/battery power systems attract increasing interest due to their merits in zero fuel consumption and zero local emission. However, current optimization for the plug-in PV/battery power system only considers a single objective of minimizing lifecycle cost, which may result in increased lifecycle greenhouse gas (GHG) emission due to electricity generation from coal in some areas. The paper therefore proposes a bi-objective optimization methodology to find out an optimal trade-off between lifecycle cost and GHG emission. Non-dominated sorting genetic algorithm II is developed to explore the Pareto solution sets. An unmanned patrol boat is considered as a study case. Simulation results show that the optimal design from the bi-objective optimization gains a 12.6% reduction in lifecycle cost and a 53.8% reduction in GHG emission when compared with the conventional power system consisting of diesel engines and generators. Moreover, the optimal design achieves a 46.3% reduction in GHG emission compared with the single-objective one aimed at minimum lifecycle cost, which at the same time increases the lifecycle cost by just 0.6%. Besides, two variables (the number of PV array and the number of battery modules) are found to be the most sensitive to the contradiction between lifecycle cost and GHG emission.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
