Energy optimal dispatching of ship's integrated power system based on deep reinforcement learning

Shang, Chengya; Fu, Lijun; Bao, Xianqiang; Xu, Xinghua; Zhang, Yan; Xiao, Hang

doi:10.1016/j.epsr.2022.107885

Cited by 17 publications

(3 citation statements)

References 24 publications

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“…speed optimization [12], alternative fuels [13], electrical power optimization [14][15][16] and other improvements have been recommended in the literature [7,17]. The use of methodologies like SEEMP and EEOI to measure energy efficiency in ships was developed by studies on the relationship between speed and main engine shaft power [18,19].…”

Section: Introduction 1backgroundmentioning

confidence: 99%

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

et al. 2022

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In recent years, shipborne emissions have become a growing environmental threat. The International Maritime Organization has implemented various rules and regulations to resolve this concern. The Ship Energy Efficiency Management Plan, Energy Efficiency Design Index, and Energy Efficiency Operational Indicator are examples of guidelines that increase energy efficiency and reduce shipborne emissions. The main engine shaft power (MESP) and fuel consumption (FC) are the critical components used in ship energy efficiency calculations. Errors in ship energy efficiency calculation methodologies are also caused by misinterpretation of these values. This study aims to predict the MESP and FC of a container ship with the help of data-driven methodologies utilizing actual voyage data to assist in the calculation process of the ship’s energy efficiency indexes appropriately. The algorithms’ prediction success was measured using the RMSE, MAE, and R2 error metrics. When the simulation results were analyzed, the Deep Neural Network and Bayes algorithms predicted MESP best with 0.000001 and 0.000002 RMSE, 0.000987 and 0.000991 MAE, and 0.999999 R2, respectively, while the Multiple-Linear Regression and Kernel Ridge algorithms estimated FC best with 0.000208 and 0.000216 RMSE, 0.001375 and 0.001471 MAE, and 0.999999 R2, respectively.

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Section: Introduction 1backgroundmentioning

confidence: 99%

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

et al. 2022

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“…Zhang et al [6][7][8] proposed a new intelligent and effective method based on an improved Ant Colony Optimization (ACO) to solve the optimization problem of the path of multiobjective ships [6]. Shang et al [9] proposed a DL-based energy optimization scheduling method for ship power systems, and through simulation experiments, the effectiveness and superiority of the optimal scheduling method were verified [9]. Peng et al [10] studied the coordination and dispatch of emergency materials according to the characteristics of emergencies at sea, constructing a maritime emergency material dispatching architecture including three layers of onshore supply layer, assembly layer, and accident layer and two processes of onshore transportation and maritime maneuver rescue [10].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Transportation Network Scheduling of Maritime Silk Road and International Digital Trade Potential Based on Improved Genetic Algorithm under Digital Trade Barriers

Zhang

Pan

2022

Wireless Communications and Mobile Computing

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The purpose is to improve the ship scheduling capability of the Maritime Silk Road transportation network and advance the international digital trade capabilities along China’s Maritime Silk Road. The optimization process of ship network scheduling based on a simulated annealing- (SA-) improved genetic algorithm (GA) is studied. Then, according to the time-varying stochastic frontier gravity model, the potential of international digital trade between China and the countries on the western route of the Maritime Silk Road is analyzed. The model is simulated and verified. The results reveal that the improved GA has obvious advantages over other algorithms in the message delivery rate of the high-speed and low-speed TT Controller Area Network (TTCAN) protocol for ship control. Regardless of the external environment and the number of message nodes, the message delivery rate is above 95%, showing a high delivery rate and the best network scheduling effect. The total volume and proportion of trade between China and the countries along the western route of the Maritime Silk Road can represent a good growth trend over time, and the proportion of digital trade exports has increased from 9.75% in 2009 to 45.12% in 2020. China has great potential for the development of the countries along the Silk Road as a whole. The main contribution of the research is to construct the ship network scheduling optimization process of the GA improved by the SA and use the time-varying stochastic frontier gravity model to study the digital trade potential between China and the countries along the Maritime Silk Road. The data information management system for network dispatching of marine ships has been improved, and the optimal dispatching efficiency has been enhanced.

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“…Referring to finding the optimal decisions based on large numbers of observations and the reward signals. Researching targets include the optimal power splitting [84,86], sizing optimization of onboard energy resources [87], suppressing the power fluctuations [35], etc.. By adopting learning-based methods instead of the traditional methods, great robustness and the optimality of results can be expected even under highly dynamic, complex, and unknown situations. However, the big historical statistics and the time-consuming data training process put greater pressure on the computational resources, which may cause problems for the real-time applications.…”

Section: Decision Makingmentioning

confidence: 99%

Power Management Systems for Shipboard Microgrids

Xie¹

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Energy optimal dispatching of ship's integrated power system based on deep reinforcement learning

Cited by 17 publications

References 24 publications

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

Data-Driven Approach for Estimating Power and Fuel Consumption of Ship: A Case of Container Vessel

Analysis of Transportation Network Scheduling of Maritime Silk Road and International Digital Trade Potential Based on Improved Genetic Algorithm under Digital Trade Barriers

Power Management Systems for Shipboard Microgrids

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