基于自适应步长ADMM的电-气混联系统多时间尺度优化调度

Multi-time scale optimal scheduling of electricity-gas hybrid system based on adaptive step size ADMM

随着微型燃气轮机和以其为基础的热电联供单元的大量配置,电力、天然气系统之间的联合优化调度越来越受到关注。针对电-气混联系统的优化调度问题,提出双层多时间尺度优化调度框架,考虑到各子系统间信息的不透明特性,上层基于日前预测数据和自适应步长交替方向乘子法(ADMM)建立以系统成本为目标函数的分布式日前优化调度模型;针对可再生能源和负荷的波动,下层基于短时预测数据建立以遵循日前调度方案为目标的实时调度模型。通过算例分析验证了所提电-气混联系统优化调度模型和框架的有效性。

With the large-scale configuration of MT(Micro-Turbine)and the CHP(Combined Heat and Power)unit based on MT,the joint optimal scheduling between the electricity system and the natural gas system has attracted more and more attention.Aiming at the optimal scheduling problem of electricity-gas hybrid system,a bi-layer multi-time scale optimal scheduling framework is proposed.Considering the opacity characteristic of information among subsystems,the distributed day-ahead optimal scheduling model is established with the system cost as its objective function in the upper layer,which is based on the day-ahead forecasting data and the adaptive step size ADMM(Alternating Direction Method of Multipliers).In view of the fluctuations of renewable energy and load,a real-time scheduling model is established in the lower layer based on the short-term forecasting data,which aims at following the day-ahead scheduling scheme.The effectiveness of the proposed optimal scheduling model and framework of electricity-gas hybrid system is verified by case study.