Optimizing dynamic electric ferry loads with intelligent power management
In recent years, there has been an increasing shift towards using environmentally friendly renewable resources in marine vessels, replacing traditional diesel generators. However, one of the main challenges faced in renewable energy-driven marine vessels is dynamic load management. The feasibility o...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
|
| Series: | Energy Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484723007709 |
| _version_ | 1797781850081460224 |
|---|---|
| author | Rajib Baran Roy Sanath Alahakoon Shantha Jayasinghe Arachchillag Saifur Rahman |
| author_facet | Rajib Baran Roy Sanath Alahakoon Shantha Jayasinghe Arachchillag Saifur Rahman |
| author_sort | Rajib Baran Roy |
| collection | DOAJ |
| description | In recent years, there has been an increasing shift towards using environmentally friendly renewable resources in marine vessels, replacing traditional diesel generators. However, one of the main challenges faced in renewable energy-driven marine vessels is dynamic load management. The feasibility of a renewable-powered electric marine vessel largely depends on the optimal utilization of renewable resources, and storage is an essential component of the marine electric vessel. This paper proposes a two-stage power management system (PMS) for an electric ferry powered by the fuel cell and battery energy storage systems (BESS). The primary objective of the proposed PMS is to ensure a balance between the generated power and the ferry load by minimizing the consumption of hydrogen (H2) fuel. The first stage of the PMS employs particle swarm optimization (PSO), bacterial foraging optimization (BFO), and a hybrid PSO-BFO algorithm to optimize the fuel cell and battery capacity. This is done so that the generated power can follow the load demand. The second stage of the PMS utilizes the Mamdani rule-based fuzzy logic system (FLS) to match the load demand with the generated power. The hybrid PSO-BFO algorithm optimizes the fuzzy control parameters to meet the dynamic load by ensuring optimal H2fuel consumption and battery state of charge (SOC). To obtain optimal values, the load profile of a conventional ferry is used for the proposed PMS. Based on the optimization results, the optimal capacities are found to be 318 kWh and 317.64 kWh for the fuel cell and BESS, respectively, which are obtained using the hybrid PSO-BFO algorithm. The optimal value of H2fuel consumption during cruising is found to be 18 kg. A simulated model-based approach validates the operation of the proposed PMS. The proposed PMS ensures optimal H2fuel consumption and battery SOC while meeting the dynamic load demands of the ferry. The results obtained demonstrate the effectiveness of the proposed PMS in optimizing the renewable energy-driven marine vessel power system. |
| first_indexed | 2024-03-13T00:02:45Z |
| format | Article |
| id | doaj.art-507ca583dfd549b68375f33cee192ac8 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-03-13T00:02:45Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-507ca583dfd549b68375f33cee192ac82023-07-13T05:30:15ZengElsevierEnergy Reports2352-48472023-12-01959525963Optimizing dynamic electric ferry loads with intelligent power managementRajib Baran Roy0Sanath Alahakoon1Shantha Jayasinghe Arachchillag2Saifur Rahman3School of Engineering and Technology, Central Queensland University, Gladstone, QLD 4680, Australia; Corresponding author.School of Engineering and Technology, Central Queensland University, Gladstone, QLD 4680, AustraliaAustralian Energy Market Operator, Melbourne, Victoria, Australia; Australian Maritime College, University of Tasmania, AustraliaVirginia Tech Advanced Research Institute, Arlington, VA 22203, USAIn recent years, there has been an increasing shift towards using environmentally friendly renewable resources in marine vessels, replacing traditional diesel generators. However, one of the main challenges faced in renewable energy-driven marine vessels is dynamic load management. The feasibility of a renewable-powered electric marine vessel largely depends on the optimal utilization of renewable resources, and storage is an essential component of the marine electric vessel. This paper proposes a two-stage power management system (PMS) for an electric ferry powered by the fuel cell and battery energy storage systems (BESS). The primary objective of the proposed PMS is to ensure a balance between the generated power and the ferry load by minimizing the consumption of hydrogen (H2) fuel. The first stage of the PMS employs particle swarm optimization (PSO), bacterial foraging optimization (BFO), and a hybrid PSO-BFO algorithm to optimize the fuel cell and battery capacity. This is done so that the generated power can follow the load demand. The second stage of the PMS utilizes the Mamdani rule-based fuzzy logic system (FLS) to match the load demand with the generated power. The hybrid PSO-BFO algorithm optimizes the fuzzy control parameters to meet the dynamic load by ensuring optimal H2fuel consumption and battery state of charge (SOC). To obtain optimal values, the load profile of a conventional ferry is used for the proposed PMS. Based on the optimization results, the optimal capacities are found to be 318 kWh and 317.64 kWh for the fuel cell and BESS, respectively, which are obtained using the hybrid PSO-BFO algorithm. The optimal value of H2fuel consumption during cruising is found to be 18 kg. A simulated model-based approach validates the operation of the proposed PMS. The proposed PMS ensures optimal H2fuel consumption and battery SOC while meeting the dynamic load demands of the ferry. The results obtained demonstrate the effectiveness of the proposed PMS in optimizing the renewable energy-driven marine vessel power system.http://www.sciencedirect.com/science/article/pii/S2352484723007709Fuel cell and battery operated electric ferryOptimal intake of H2fuelLoad managementHybrid PSO-BFO algorithmMamdani rule based fuzzy logic |
| spellingShingle | Rajib Baran Roy Sanath Alahakoon Shantha Jayasinghe Arachchillag Saifur Rahman Optimizing dynamic electric ferry loads with intelligent power management Energy Reports Fuel cell and battery operated electric ferry Optimal intake of H2fuel Load management Hybrid PSO-BFO algorithm Mamdani rule based fuzzy logic |
| title | Optimizing dynamic electric ferry loads with intelligent power management |
| title_full | Optimizing dynamic electric ferry loads with intelligent power management |
| title_fullStr | Optimizing dynamic electric ferry loads with intelligent power management |
| title_full_unstemmed | Optimizing dynamic electric ferry loads with intelligent power management |
| title_short | Optimizing dynamic electric ferry loads with intelligent power management |
| title_sort | optimizing dynamic electric ferry loads with intelligent power management |
| topic | Fuel cell and battery operated electric ferry Optimal intake of H2fuel Load management Hybrid PSO-BFO algorithm Mamdani rule based fuzzy logic |
| url | http://www.sciencedirect.com/science/article/pii/S2352484723007709 |
| work_keys_str_mv | AT rajibbaranroy optimizingdynamicelectricferryloadswithintelligentpowermanagement AT sanathalahakoon optimizingdynamicelectricferryloadswithintelligentpowermanagement AT shanthajayasinghearachchillag optimizingdynamicelectricferryloadswithintelligentpowermanagement AT saifurrahman optimizingdynamicelectricferryloadswithintelligentpowermanagement |