摘要
为保证船舶能源系统的安全可靠运行,减少航行中污染物的排放,综合考虑船舶混合能源系统的供电特点,本文提出了一种基于粒子群优化的混合能源系统能源管理策略。建立了船舶混合能源系统中光伏发电、风力发电、柴油机和储能模块的数学模型。同时计及运行成本和污染物排放量为能量管理优化目标,建立能源管理的目标函数。采用粒子群优化算法对目标函数进行求解,从而实现船舶混合能源系统能量优化管理。模拟船舶航行实验验证了该策略的有效性和实时性,结果表明:该策略能够有效地降低系统的运行成本和污染物排放量。
Considering the characteristics of hybrid power supply for ships,an energy management strategy for a hybrid energy system based on particle swarm optimization is proposed to ensure safe and reliable operations of the ship energy system and reduce the emission of pollutants during a voyage.At first,mathematical models of photovoltaic power generation,wind power generation,diesel engines,and energy storage modules in a hybrid energy system were developed.Then,the energy management objective function was established,with optimization objectives to lower operating costs and pollutant emissions.Finally,the particle swarm optimization algorithm optimized the objective function,resulting in optimal energy dispatch for the ship hybrid energy system.Simulated ship navigation experiments confirmed the effectiveness and real-time performance of the strategy,and the simulation results showed that this strategy could effectively reduce operating costs and pollutant emissions of the system.
作者
司玉鹏
王荣杰
张世奇
周文婷
林安辉
曾广淼
SI Yupeng;WANG Rongjie;ZHANG Shiqi;ZHOU Wenting;LIN Anhui;ZENG Guangmiao(School of Marine Engineering,Jimei University,Xiamen 361021,China;Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering,Xiamen 361021,China)
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2022年第7期1051-1058,共8页
Journal of Harbin Engineering University
基金
国家自然科学基金项目(51879118)
交通运输行业高层次人才培养项目(2019-014)
福建省科技拥军项目(B19101)
福建省自然科学基金项目(2020J01688,2020J01687)
农业部渔业装备与工程技术重点实验室基金项目(2016002,2018001)
人工智能四川省重点实验室基金项目(2017RJY02)
江苏省输配电装备技术重点实验室项目(2017JSSPD01)。
关键词
混合能源船舶
能量管理
优化调度
储能模块
清洁能源
粒子群算法
多目标优化
排放最小化
hybrid energy ship
energy management
optimization dispatch
electric energy storage
clean energy
particle swarm optimization
multi-objective optimization
emission minimization
作者简介
司玉鹏,男,硕士研究生;通信作者:王荣杰,男,教授,博士生导师.E-mail:roger811207@163.com.
