针对综合能源系统(Integrated energy system, IES)中可再生能源(Renewable energy, RE)能量耦合的复杂性和能量波动问题,提出了一种改进的混合储能系统(Hybrid energy storage system, HESS)三阶段能量优化调度。分析了IES中各种器件...针对综合能源系统(Integrated energy system, IES)中可再生能源(Renewable energy, RE)能量耦合的复杂性和能量波动问题,提出了一种改进的混合储能系统(Hybrid energy storage system, HESS)三阶段能量优化调度。分析了IES中各种器件在不同时间尺度下的功率响应特性,表明三阶段能量优化调度方法可以与包括HESS在内的IES很好地耦合。比较分析了HESS在稳定功率波动和延长储能寿命方面优于单一储能系统的优点,提出了三阶段能量优化调度下超级电容的控制方法。根据日前预测数据,一次能源消耗、运营成本、二氧化碳排放被视为日前滚动优化阶段的优化目标。在日内滚动调整阶段,该方法可以减少RE日前预测误差的影响,实现日内能源调度平衡,确保IES设备的安全运行。考虑到IES中可再生能源比例较高的背景,创新性地利用HESS的优势来改善系统的功率响应特性。仿真结果表明,所提方法在提升系统功率响应速度、延长储能电池(Lithium-ion battery,LiB)寿命和减少碳排量上具有显著提升。展开更多
It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet o...It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.展开更多
基金supported by the National Natural Science Foundations of China(No. 51875171)
文摘It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.
