Author
Listed:
- Luo, Miao
- Jin, Puhang
- Qi, Changxing
- Cai, Ruimou
- Xie, Gongnan
Abstract
The configuration of ship integrated energy system (SIES) is crucial for improving the reliability and economy of ship systems. This paper introduces the sine-cosine and cauchy mutation sparrow search algorithm (SCSSA) into the SIES-ORC optimization configuration model, and uses the 2022 benchmark test function set to verify the algorithm's performance in convergence speed, optimization accuracy, robustness, and ability to solve complex problems within the meta-heuristic algorithm framework. Then, a thorough technical, economic, and environmental analysis of the SIES-ORC optimization results is conducted for both systems with and without ORC. The results show that compared to PSO, SSA, HHO, GWO, and WOA algorithms, SCSSA achieved smaller RMSE and δ values in most test functions, with high solution accuracy and fast convergence speed. The SIES-ORC system has a significant economic advantage, with a slight increase in the total cost compared to the SIES system, but the initial investment cost and annual operation and maintenance costs decrease by 57.78% and 73.52%, respectively. The carbon emissions of the SIES-ORC system mainly come from Dual Fuel Engine (DFE) and Dual Fuel Generator Set (DFGS). The proportion of carbon emissions from DFGS in the SIES-ORC system is the highest during the transition season, summer, and winter typical days, at 79.05%, 80.48%, and 83.03%, respectively, while the proportion from DFE is 20.95%, 19.52%, and 16.97%, respectively. The proposed SIES-ORC optimization configuration method based on SCSSA can provide theoretical basis and technical support for the design of energy-saving ships.
Suggested Citation
Luo, Miao & Jin, Puhang & Qi, Changxing & Cai, Ruimou & Xie, Gongnan, 2026.
"Configuration optimization of ship integrated energy system with Organic Rankine Cycle based on SCSSA,"
Energy, Elsevier, vol. 348(C).
Handle:
RePEc:eee:energy:v:348:y:2026:i:c:s0360544226005001
DOI: 10.1016/j.energy.2026.140397
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