引用本文:赵波,倪筹帷,李志浩,张维桐,陈健.基于自适应步长ADMM的电-气混联系统多时间尺度优化调度[J].电力自动化设备,2019,39(8):
ZHAO Bo,NI Chouwei,LI Zhihao,ZHANG Weitong,CHEN Jian.Multi-time scale optimal scheduling of electricity-gas hybrid system based on adaptive step size ADMM[J].Electric Power Automation Equipment,2019,39(8):
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基于自适应步长ADMM的电-气混联系统多时间尺度优化调度
赵波1, 倪筹帷1, 李志浩1, 张维桐2, 陈健2
1.国网浙江省电力有限公司电力科学研究院,浙江 杭州 310014;2.山东大学 电气工程学院,山东 济南 250061
摘要:
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。
关键词:  电-气混联系统  优化调度  分布式优化  多时间尺度  自适应步长交替方向乘子法  模型
DOI:10.16081/j.epae.201908017
分类号:TM734
基金项目:国家自然科学基金资助项目(51877039)
Multi-time scale optimal scheduling of electricity-gas hybrid system based on adaptive step size ADMM
ZHAO Bo1, NI Chouwei1, LI Zhihao1, ZHANG Weitong2, CHEN Jian2
1.Electric Power Research Institute of State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310014, China;2.School of Electrical Engineering, Shandong University, Jinan 250061, China
Abstract:
With the large-scale configuration of MT(Micro-Turbine) and the CHP(Combined Heat and Po-wer) 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 la-yer 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.
Key words:  electricity-gas hybrid system  optimal scheduling  distributed optimization  multi-time scale  adaptive step size ADMM  models

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