集装箱港口综合能源系统日前-日内两阶段滚动优化调度
Two-Stage Day-Ahead and Intra-Day Rolling Optimization Scheduling of Container Integrated Port Energy System
周思怡 1杨欢红 1黄文焘 2周泽 1焦伟 1杨镇瑜1
作者信息
- 1. 上海电力大学 电气工程学院,上海 200090
- 2. 上海交通大学 电力传输与功率变换控制教育部重点实验室,上海 200240
- 折叠
摘要
针对目前集装箱港口综合能源系统(IPES)未考虑冷藏集装箱在港口调度上时间尺度的差异性及可再生能源与负荷不确定性的影响,提出一种集装箱 IPES 日前-日内两阶段滚动优化调度方法.日前调度针对冷藏集装箱温升阶段,结合冷藏箱入港后的物流过程建立港口冷链能量需求模型,以运行成本最低为目标得到系统各机组的日前出力值;日内调度考虑港口岸电负荷与可再生能源的预测误差及冷、热、电响应速度不同,建立日内双层滚动优化模型,最终得到港口各能源设备的调整出力.算例结果表明,将冷藏集装箱与集装箱IPES进行协同优化调度可有效降低港口运行成本与碳排放量,日前-日内两阶段滚动优化调度模型提高了系统经济性与平稳运行的能力.
Abstract
In view of the fact that the current integrated port energy system(IPES)considers neither the time scale difference of refrigerated containers in port scheduling nor the impact of renewable energy and load uncertainty,this paper proposes a day-ahead and intra-day two-stage rolling optimization scheduling method for a container IPES.In day-ahead scheduling,based on the temperature rise process of refrigerated containers,a port cold chain energy demand model is established,which is combined with the logistics process after the arrival of refrigerated containers.Then,the day-ahead output values of each unit in the system are obtained with the goal of the lowest operating cost.In intra-day scheduling,a two-layer rolling model is proposed to obtain the adjusted output of the port energy equipment,which considers the prediction error of shore power load and renewable energy as well as the different response speeds of cooling,heating and power.The calculation results show that the collaborative optimization scheduling of refrigerated containers and the container IPES can effectively reduce the port operation cost and carbon emissions.The two-stage day-ahead and intra-day rolling optimization scheduling can improve the economy and stability of the system.
关键词
集装箱港口/综合能源系统/冷藏集装箱/岸电负荷/两阶段优化调度Key words
container port/integrated energy system/refrigerated container/shore power load/two-stage optimization scheduling引用本文复制引用
基金项目
国家自然科学基金项目(52177100)
电力传输与功率变换控制教育部重点实验室开放课题(2022AA05)
出版年
2024
NETL
NSTL
万方数据