To comprehensively consider the impact of uncertainties of variable energy resources (VERs) and load demands on the scheduling plans, the paper proposes a multi-time scale coordinated optimization (MTSCO) method of the energy hub (EH) with multi-energy flows and multi-type energy storage systems (MESSs). The MTSCO involves with global optimization of day-ahead economic dispatch (DAED), local intra-day receding-horizon optimization (IDRHO) and real-time adjustment (RTA). DAED formulates the 24-period output of controllable devices integrated in EH through minimizing its operation cost of a single day. Following the formulated DAED plan, IDRHO minimizes the sum of energy purchase cost and MESSs’ penalty cost within every 15 min. Further, RTA provides real-time feedback to IDRHO and minimizes the total adjustment amount of all controllable devices every 5 min. The simulation results indicate that the proposed multi-time scale dispatching and MESSs enable to promote the EH economy, acquire better dispatching solution aiming at uncertainties of VERs and varying load demands and alleviate the grid’s compensation for fluctuation.

为综合考虑可变能源（VERs）和负荷需求的不确定性对调度计划的影响，提出一种多能源流和多能源枢纽（EH）的多时间尺度协调优化（MTSCO）方法。型储能系统 (MESS)。MTSCO 涉及日前经济调度的全局优化（DAED）、本地日内后视距优化（IDRHO）和实时调整（RTA）。DAED 通过最小化其一天的运行成本，制定了集成在 EH 中的可控设备的 24 周期输出。按照制定的 DAED 计划，IDRHO 在每 15 分钟内最小化能源购买成本和 MESS 的惩罚成本之和。更多，RTA向IDRHO提供实时反馈，每5分钟最小化所有可控设备的总调整量。仿真结果表明，所提出的多时间尺度调度和MESSs能够促进EH经济性，针对VERs的不确定性和变化的负载需求获得更好的调度解决方案，并减轻电网对波动的补偿。