引用本文: | 王文睿,瞿凯平,余涛,王克英,史守圆.消纳大规模风电的电–气互联系统鲁棒区间调度模型与方法[J].控制理论与应用,2020,37(6):1270~1283.[点击复制] |
WANG Wen-rui,QU Kai-ping,YU Tao,WANG Ke-ying,SHI Shou-yuan.A robust interval scheduling model and method accommodating large-scale wind power generation for integrated electric and gas system[J].Control Theory and Technology,2020,37(6):1270~1283.[点击复制] |
|
消纳大规模风电的电–气互联系统鲁棒区间调度模型与方法 |
A robust interval scheduling model and method accommodating large-scale wind power generation for integrated electric and gas system |
摘要点击 2194 全文点击 737 投稿时间:2019-02-17 修订日期:2019-11-17 |
查看全文 查看/发表评论 下载PDF阅读器 |
DOI编号 10.7641/CTA.2019.90089 |
2020,37(6):1270-1283 |
中文关键词 电–气互联系统 鲁棒优化 风电预测区间 天然气网约束 凸松弛 |
英文关键词 integrated electric and gas system robust optimization forecast interval of wind power constraints of gas network convex relaxation |
基金项目 国家自然科学基金项目(51777078), 中国南方电网有限责任公司科技项目(GDKJXM20180576)资助. |
|
中文摘要 |
现有的电–气互联系统联合调度模型在利用燃气机组的快速调整能力应对风电波动时, 难以考虑到对气网
运行约束的影响, 同时往往忽略了电转气(P2G)装置进一步消纳风电的能力. 为解决上述问题, 本文计及燃气机组
和P2G装置追踪风电波动提出了一种鲁棒区间调度模型, 所提模型在保证风电消纳区间最大化的同时, 将优化得到
的燃气机组和P2G装置允许出力区间转换为最大、最小进气量场景以进一步校验气网的可行性. 为进一步扩大风电
消纳区间, 本文将AGC机组和P2G装置的风电承担系数作为待优化变量, 并对因此引入的非线性项进行松弛处理.
最后, 通过一种计及再调整的日后校正模型对各个算例场景进行蒙特卡洛模拟, 验证了本文模型和方法的有效性. |
英文摘要 |
When the existing integrated electric and gas system utilizes the rapid adjustment capacity of gas-fired units
to deal with wind power output fluctuations, it is difficult to consider the impact on the operation constraints of gas network,
and the ability of power to gas (P2G) device to further accommodate wind power is often neglected. To solve the above
problem, this paper establishes a interval scheduling model considering that gas-fired unit and P2G device tracks wind
power fluctuations. While maximizing the wind power accommodation interval, the proposed model converts the allowable
output range of the gas unit and P2G device into the maximum and minimum intake of gas amount to further verify the
feasibility of the gas network. In order to further expand the wind power accommodation interval, this paper takes the
wind power undertaking coefficient of the unit and P2G device as variables and relaxes the nonlinear term introduced
thereby. Finally, Monte Carlo simulation is carried out for each case scenario by using a dayafter correction model with
re-adjustment, which verifies the effectiveness of the model and method presented in this paper. |
|
|
|
|
|