一种基于液态空气储能枢纽站的分布式压缩空气储能系统模型预测控制方法

A novel model predictive control method for distributed compressed air energy storage system based on liquid air energy storage hub station

再电气化是应对环境污染和气候变化的重要发展趋势。终端能源的深度再电气化,如以电代煤,以电代油,交通电气化等,将大幅提高电能在终端能源利用的比例,提高配电网,特别是城市电网的电力负荷水平,为配电网的运行、安全及可靠性带来新的挑战。储能是智能电网的重要组成部分,是提高供电可靠性和安全性的重要措施之一,因此提出一种基于液态空气储能枢纽站(LAES)的分布式压缩空气储能系统(CAES)模型预测控制(MPC)方法。文章建立基于液态空气储能枢纽站的分布式压缩控制储能配置方法;在此基础上,提出以日前运行成本最小和实时运行偏差最小为目标的双层优化MPC控制模型,满足配电网及液态空气-压缩空气储能系统安全运行条件;以改进IEEE 30节点测试系统为例,验证了所提方法的正确性和实用性。

Re-electrification is an emerging development trend in dealing with environmental pollution and climate change.Deep re-electrification of final energy consumption,such as replacing coal,oil with electricity,and transport electrification,etc.,will greatly increase the share of electricity in the final energy consumption,increasing the load level of distribution networks,especially urban networks,and pose great challenges to the reliability and safe operation of the distribution networks.Energy storage is an important part of smart grid,which is one of important measures to ensure security and reliability of the system.This paper proposes a novel model predictive control(MPC)method for compressed air energy storage(CAES)systems based on liquid air energy storage(LAES)energy hub station.Firstly,a distributed installation framework for LAES and CAES system based on LAES hub is proposed,then,a model predictive control method combined with hierarchical optimization that meet the requirements of network security and LAES and CAES system operations.Finally,the correctness and practicability of the proposed method are verified through using the modified IEEE-30 test system.