Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions
A hybrid ship uses integrated generators, an energy storage system (ESS), and photovoltaics (PV) to match its propulsion and service loads, and together with optimal power and voyage scheduling, this can lead to a substantial improvement in ship operation cost, ensuring compliance with the environme...
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| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/12/11/2087 |
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| author | Fang Lu Yubin Tian Hongda Liu Chuyuan Ling |
| author_facet | Fang Lu Yubin Tian Hongda Liu Chuyuan Ling |
| author_sort | Fang Lu |
| collection | DOAJ |
| description | A hybrid ship uses integrated generators, an energy storage system (ESS), and photovoltaics (PV) to match its propulsion and service loads, and together with optimal power and voyage scheduling, this can lead to a substantial improvement in ship operation cost, ensuring compliance with the environmental constraints and enhancing ship sustainability. During the operation, significant uncertainties such as waves, wind, and PV result in considerable speed loss, which may lead to voyage delays and operation cost increases. To address this issue, a distributionally robust optimization (DRO) model is proposed to schedule power generation and voyage. The problem is decoupled into a bi-level optimization model, the slave level can be solved directly by commercial solvers, the master level is further formulated as a two-stage DRO model, and linear decision rules and column and constraint generation algorithms are adopted to solve the model. The algorithm aims at minimizing the operation cost, limiting greenhouse gas (GHG) emissions, and satisfying the technical and operational constraints considering the uncertainty. Extensive simulations demonstrate that the expected total cost under the worst-case distribution is minimized, and compared with the conventional robust optimization methods, some distribution information can be incorporated into the ambiguity sets to generate fewer conservative results. This method can fully ensure the on-time arrival of hybrid ships in various uncertain scenarios while achieving expected operation cost minimization and limiting greenhouse gas (GHG) emissions. |
| format | Article |
| id | doaj-art-6c65ddcdfb4e42c4b465708580ebc5f3 |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-6c65ddcdfb4e42c4b465708580ebc5f32024-11-26T18:08:34ZengMDPI AGJournal of Marine Science and Engineering2077-13122024-11-011211208710.3390/jmse12112087Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave ConditionsFang Lu0Yubin Tian1Hongda Liu2Chuyuan Ling3College of Intelligent System Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaXi’an Aerospace Precision Electromechanical Research Institute, Xi’an 710118, ChinaYantai Research Institute, Harbin Engineering University, Yantai 264000, ChinaCollege of Intelligent System Science and Engineering, Harbin Engineering University, Harbin 150001, ChinaA hybrid ship uses integrated generators, an energy storage system (ESS), and photovoltaics (PV) to match its propulsion and service loads, and together with optimal power and voyage scheduling, this can lead to a substantial improvement in ship operation cost, ensuring compliance with the environmental constraints and enhancing ship sustainability. During the operation, significant uncertainties such as waves, wind, and PV result in considerable speed loss, which may lead to voyage delays and operation cost increases. To address this issue, a distributionally robust optimization (DRO) model is proposed to schedule power generation and voyage. The problem is decoupled into a bi-level optimization model, the slave level can be solved directly by commercial solvers, the master level is further formulated as a two-stage DRO model, and linear decision rules and column and constraint generation algorithms are adopted to solve the model. The algorithm aims at minimizing the operation cost, limiting greenhouse gas (GHG) emissions, and satisfying the technical and operational constraints considering the uncertainty. Extensive simulations demonstrate that the expected total cost under the worst-case distribution is minimized, and compared with the conventional robust optimization methods, some distribution information can be incorporated into the ambiguity sets to generate fewer conservative results. This method can fully ensure the on-time arrival of hybrid ships in various uncertain scenarios while achieving expected operation cost minimization and limiting greenhouse gas (GHG) emissions.https://www.mdpi.com/2077-1312/12/11/2087hybrid shipdistributionally robust optimizationuncertain wind and wave conditionsGHGenergy management |
| spellingShingle | Fang Lu Yubin Tian Hongda Liu Chuyuan Ling Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions Journal of Marine Science and Engineering hybrid ship distributionally robust optimization uncertain wind and wave conditions GHG energy management |
| title | Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions |
| title_full | Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions |
| title_fullStr | Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions |
| title_full_unstemmed | Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions |
| title_short | Distributionally Robust Optimal Scheduling of Hybrid Ship Microgrids Considering Uncertain Wind and Wave Conditions |
| title_sort | distributionally robust optimal scheduling of hybrid ship microgrids considering uncertain wind and wave conditions |
| topic | hybrid ship distributionally robust optimization uncertain wind and wave conditions GHG energy management |
| url | https://www.mdpi.com/2077-1312/12/11/2087 |
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