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Stochastic Risk-Constrained Optimal Sizing for Hybrid Power System of Merchant Marine Vessels
- Source :
- IEEE Transactions on Industrial Informatics. 14:5509-5517
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- This paper presents a risk-based stochastic model to sizing a photovoltaic (PV) /diesel/storage hybrid power system of a merchant marine vessel. Integrating renewable, in particular PV, energy resources offer significant advantages to bulk transportation by reducing the greenhouse gas emissions, improving the energy efficiency, and increasing the energy security. To this end, the sizing problem of PV/diesel/storage merchant marine vessel hybrid power system would optimally determine appropriate configuration of the PV system and energy storage system to design hybrid power system of a merchant marine vessel in an optimal and reliable manner. The uncertainty related to the hourly global solar radiation and its effect on the output power of the PV system is taken into account and modeled using proper scenario generation methods. Additionally, the scenario reduction technique is applied for the domination of dimensionality. Furthermore, an appropriate risk measurement, the conditional value-at-risk methodology, is incorporated with the proposed stochastic model to quantify the potential risk of sizing the problem. Finally, the proposed model is applied to a comprehensive test case to illustrate the efficiency and the applicability of the proposed approach.
- Subjects :
- business.industry
Computer science
Stochastic modelling
020209 energy
Energy resources
Photovoltaic system
02 engineering and technology
Energy security
Sizing
Automotive engineering
Energy storage
Computer Science Applications
Power (physics)
Renewable energy
Global solar radiation
Diesel fuel
Control and Systems Engineering
Greenhouse gas
0202 electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Hybrid power
business
Information Systems
Efficient energy use
Subjects
Details
- ISSN :
- 19410050 and 15513203
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Industrial Informatics
- Accession number :
- edsair.doi...........d64532e51d0e4d655e331e52ccfaa8ee
- Full Text :
- https://doi.org/10.1109/tii.2018.2824811