Prediction Of Real-Time Energy Efficiency And Main Engine Speed Optimization For An Operating Merchant Ship

Shipping industry provides huge transportation capacity.But it also consumes a large amount of fuel and produces a large amount of greenhouse gases.Therefore,improving the energy efficiency level of operating ships can effectively improve the energy saving and emission reduction level of the whole shipping industry,which is of great significance in coping with global climate change.The operating conditions of the ship and its diesel engine are variable under the interference of wind,wave,current and other changeable environmental conditions.So it is difficult to maintain a higher energy efficiency level all the time when the ship is sailing on the sea.With the increase of ship operation time,the performance of diesel engine and its propulsion power plant is gradually declining,and its operation parameters need to be adjusted in time to maintain the good performance.On the other hand,the energy consumption in the process of ship construction,maintenance and scraping is not included in the ship energy efficiency operation index(EEOI),so that EEOI can not fully reflect the actual energy efficiency level of ship.In order to maintain a high level of energy efficiency of operating ships under the variable navigation environment,a new research method is introduced that is different from the traditional research on reducing the EEOI value during a whole voyage.A real-time energy efficiency optimization method is presented which can adapt to the variation of the navigation environment.Based on the ship energy efficiency level which is real-time monitored,the optimization algorithm is used to directly adjust the running speed of the main engine.It can reduce the real-time EEOI value,improve the energy efficiency of the ship,and achieve the purpose of energy conservation and emission reduction.Based on the energy efficiency operation index proposed by International Maritime Organization,a equation for real time EEOI is proposed to measure the real time energy efficiency level of ships by time-cycle integration method;based on the combination of mechanism modeling and experimental data,a diesel ship propulsion system model is established,which integrates the ship’s direct motion model,the four-quadrant propeller model and the interference force model of wind and wave,providing a simulation platform for the optimization algorithm research;a calculation framework for other stages of ship life cycle(construction,maintenance,dismantling)except operation stage in ship life cycle assessment is given,and the calculation results are included in the real-time ship energy efficiency index.The relationship between life cycle assessment(LCA)and real-time ship energy efficiency is studied;the real time energy consumption prediction model of the main engine of the ship is established by using the navigation parameters of the real ship and back propagation neural network.The initial link weight of the network is set by genetic algorithm.And the real-time energy consumption prediction neural network is trained by the ship monitoring data.The neural network provides the basis for the calculation of the real-time energy efficiency of the ship;the prediction model of real-time energy efficiency of ship is established by using the neural network prediction model of energy consumption of the main engine.Two kinds of objective function of optimizing real time EEOI are derived:one is the single function of the real time EEOI;the other is the synthetic function of the ship speed and the real time EEOI.The genetic algorithm is used to optimize revolution of the main engine,and the simulation calculation of optimization method is carried out by using the model of ship propulsion system.Through the studies above,the propulsion power system model and life cycle assessment calculation framework of the training ship "Yuming" are established by using the ship and equipment parameters and the real-time navigation data.From the calculation results,the following conclusions are drawn:(1)The equation of the real time EEOI derived from the definition of IMO can accurately calculate the real-time energy efficiency of ships.The calculation results show that the real-time energy efficiency index is consistent with the original definition in the long-term trend,but the real-time energy efficiency index is sensitive to the variation of the navigation environment and provides a basis for the realization of real-time energy efficiency optimization;(2)The simulation results of the propulsion model of Yuming are in good agreement with the ship test and sea trail data.The model provides a simulation basis for the study of EEOI and optimization algorithm;(3)Life cycle assessment results will enlarge the real-time EEOI value especially at low engine speed.From the viewpoint of LCA,the lower speed limit of slow steaming should be significantly increased.Slow steaming may bring less effort for environmental protection than that expected by slow steaming;(4)The genetic algorithm back propagation neural network optimized can predict accurately ship speed and main engine fuel consumption.Combined with the fuel consumption of auxiliary engine,the neural network model has the ability to accurately predict the real-time EEOI;(5)The EEOI optimization method based on genetic algorithm can adapt to the varying navigation environment of the ship,and can get the lowest real time EEOI value or the lowest objective function value integrated by ship speed and real time EEOI by adjusting the speed of the main engine,so as to achieve the effect of energy saving and emission reduction.