Research On Ship Energy Management Strategy Based On Improved Gravitational Search Algorithm

Under the background of global advocacy of energy conservation and emission reduction,ships,as the main means of transportation for trade and shipping,their operating costs and energy consumption emissions have become a research hotspot in related fields.Establishing a reasonable ship energy management strategy to achieve the goal of low operation cost,consumption reduction and emission reduction,which is of great value and significance to realize the energy conservation and environmental protection of the shipping industry.Firstly,aiming at the optimization of ship energy management strategy,the relevant mathematical model is established.In order to minimize the operating cost of the ship,a mathematical optimization model of energy management strategy for diesel-electric hybrid ship was established considering the performance constraints of diesel engine and generator set.Based on the technology development trend,a multi-objective mathematical optimization model for the energy management strategy of all-electric ships is established,taking into account the two objectives of reducing the ship energy efficiency operating index and operating cost.Secondly,research on solving algorithm for establishing mathematical model.Based on GSA,Improved Gravitational Search Algorithm(IGSA)is proposed to overcome the shortcomings of GSA,such as its prematurity and low convergence accuracy.The main improvements are as follows: first,a state switching learning strategy is introduced,in which individuals in the population determine their own state according to their own divergence and probability matrix,and select corresponding parameters and evolution rules according to the state;Secondly,the optimal individual guidance strategy is introduced to accelerate the convergence of the algorithm to the optimal point.At the same time,in order to strengthen the development of the algorithm near the best point,the neighborhood search based on the best point is introduced;Thirdly,the algorithm combined with reverse learning strategy can strengthen its ability to jump out of local optimum and prevent prematurity.In particular,an Improved non-dominated Sorting Gravitational Search Algorithm(INSGSA)is proposed to better solve the above multi-objective optimization model.A fast non-dominated sorting method is introduced to stratification the population,and the crowding distance attribute is given to the individual.An external archive is created to save the Pareto non-dominated solution generated in the search process,and the speed update formula is improved to improve the overall search ability of the proposed algorithm.Several classical single-objective and multi-objective function optimization problems were used to test the performance of the proposed two algorithms,and the results were compared with those given in related literatures.The feasibility and effectiveness of the proposed two algorithms were verified.Finally,based on the data given in the literature,the proposed two algorithms are used to solve the energy management strategy optimization of diesel-electric hybrid and all-electric ships respectively.The results show that,for diesel-electric hybrid ship,the optimization scheme given by IGSA can reduce the total operating cost of the ship on the premise of satisfying the relevant performance constraints.For all-electric ships,the proposed algorithm,INSGSA,can give a variety of decision schemes that satisfy constraints in different scale problems and whether to use energy storage system(ESS),and have different emphasis on each sub-objective,considering the ship’s economy and environmental protection,and can be selected according to specific working conditions in practice.At the same time,it also shows that the power system using ESS is indeed more conducive to energy saving and emission reduction of all-electric ships.The results above verify the applicability of the proposed algorithm to two kinds of ship energy management decision problems.The work of this thesis provides theoretical and technical support for the improvement of gravity search algorithm and the optimization of ship energy management strategy,and also provides a reference for other similar engineering optimization problems.