含高比例气象敏感可再生能源电网日前调度时间颗粒度优化

doi:10.16183/j.cnki.jsjtu.2022.277

上海交通大学学报 ›› 2023, Vol. 57 ›› Issue (7): 781-790.doi: 10.16183/j.cnki.jsjtu.2022.277

所属专题：《上海交通大学学报》2023年“新型电力系统与综合能源”专题

• 新型电力系统与综合能源 • 上一篇下一篇

含高比例气象敏感可再生能源电网日前调度时间颗粒度优化

叶志亮¹, 黎灿兵¹(), 张勇军², 李立浧², 肖银璟¹, 吴雨杭¹, 邰能灵¹

1.上海交通大学电子信息与电气工程学院, 上海 200240
2.华南理工大学电力学院, 广州 510640

收稿日期:2022-07-15 修回日期:2022-09-07 接受日期:2022-09-22 出版日期:2023-07-28 发布日期:2023-07-28
通讯作者: 黎灿兵 E-mail:licanbing@sjtu.edu.cn
作者简介:叶志亮(1998-),硕士生,从事电力系统调度研究.
基金资助:
国家自然科学基金(51977062)

Optimization of Day-Ahead Dispatch Time Resolution in Power System with a High Proportion of Climate-Sensitive Renewable Energy Sources

YE Zhiliang¹, LI Canbing¹(), ZHANG Yongjun², LI Licheng², XIAO Yinjing¹, WU Yuhang¹, TAI Nengling¹

1. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University,Shanghai 200240, China
2. School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China

Received:2022-07-15 Revised:2022-09-07 Accepted:2022-09-22 Online:2023-07-28 Published:2023-07-28
Contact: LI Canbing E-mail:licanbing@sjtu.edu.cn

摘要/Abstract

摘要：

调度计划的时间颗粒度指调度计划中每个时段长度.随着气象敏感可再生能源占比的提高,调度时段内电网净负荷的波动性显著增强,造成系统爬坡能力不足、频率异常等风险.因此,不同可再生能源渗透率下时间颗粒度的设置成为当前迫切需要解决的问题.提出基于全局灵敏度的日前调度时间颗粒度优化方法,采用Sobol'方法和多项式混沌展开的全局灵敏度方法量化不同时间颗粒度下净负荷波动性、不确定性对优化调度影响,在精细化程度和负荷预测准确率之间取得一种平衡,选择合适的时间颗粒度使优化调度效果最优.分析和仿真结果表明:时间颗粒度的选择主要由净负荷波动率决定,依据净负荷波动率选择合适时间颗粒度,使得不平衡功率最小化,可达到提升优化调度效果和降低调度成本的目的.

关键词: 电力系统调度, 调度计划, 可再生能源, 全局灵敏度

Abstract:

The time resolution of scheduling plan refers to the length of each time interval in the scheduling plan. With the increasing proportion of climate-sensitive renewable energy sources (RES), the volatility of net load during the dispatch interval is significantly enhanced, resulting in an insufficient system climbing capacity and abnormal frequency. Therefore, the setting of time resolution at different renewable energy penetration rates becomes an urgent problem to be solved at present. A global sensitivity-based day-ahead dispatch time resolution selection optimization method is proposed to select the time resolution for different volatility grids. To achieve a balance between the degree of refinement and the accuracy of load prediction, the global sensitivity analysis method based on Sobol' method and sparse chaos expansion is used to evaluate the impact of net load volatility and uncertainty on dispatch at different time resolutions, and an appropriate time resolution is chosen to optimize the scheduling effect. The analysis and simulation results show that the choice of time resolution is mainly determined by the net load fluctuation rate. The appropriate time granularity is chosen according to the net load fluctuation rate, which minimizes the unbalanced power, and the purpose of improving the optimal scheduling effect and reducing the dispatching cost is achieved.

Key words: power system dispatch, scheduling plan, renewable energy sources (RES), global sensitivity

中图分类号:

TM732

叶志亮, 黎灿兵, 张勇军, 李立浧, 肖银璟, 吴雨杭, 邰能灵. 含高比例气象敏感可再生能源电网日前调度时间颗粒度优化[J]. 上海交通大学学报, 2023, 57(7): 781-790.

YE Zhiliang, LI Canbing, ZHANG Yongjun, LI Licheng, XIAO Yinjing, WU Yuhang, TAI Nengling. Optimization of Day-Ahead Dispatch Time Resolution in Power System with a High Proportion of Climate-Sensitive Renewable Energy Sources[J]. Journal of Shanghai Jiao Tong University, 2023, 57(7): 781-790.

图/表 11

图1

图2

图3

图4

表1

系统机组参数

机组	$P m m a x$ /MW	$P m m i n$ /MW	a_m/[美元· (MW²·h)^-1]	b_m/[美元· (MW·h)^-1]	c_m/ [美元·h^-1]	$R m +$ /MW	$R m -$ /MW	$c m s u$ /美元	$c m s d$ /美元
1	470	150	4.3×10^-4	21.60	958.20	120	-120	3000	3000
2	460	130	6.3×10^-4	21.05	1313.60	120	-120	3000	3000
3	340	73	5.9×10^-4	20.81	604.97	120	-120	2200	2200
4	300	60	7.0×10^-4	22.90	471.60	100	-100	1800	1800
5	243	73	7.9×10^-4	21.62	480.29	100	-100	900	900
6	160	57	5.6×10^-4	17.87	601.75	100	-100	900	900
7	130	20	2.1×10^-3	16.51	502.70	50	-50	260	260
8	120	47	4.8×10^-3	23.23	639.40	50	-50	260	260
9	80	20	10.9×10^-1	19.58	455.60	50	-50	30	30
10	55	20	9.5×10^-3	22.54	629.40	50	-50	30	30

表1

图5

表2

表3

图6

表4

图7

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γ/min	Δβ	P_sum/(MW·h)	D/%
5	0.21	3 230	90.74
15	0.10	3 187	90.87
30	0.27	3 247	90.70
60	0.46	3 281	90.60

γ/min	f₁/美元	f₂/美元	f₃/美元	F/%
5	826723	83915	910640	2.02
15	826555	82794	909350	1.93
30	825736	84352	910090	2.09
60	824864	85249	910110	2.17

γ/min	Δβ	F/%	D/%	f₃/美元
5	0.07	2.19	89.17	932860
15	0.11	2.30	88.87	932900
30	0.31	2.45	88.79	933270
60	0.54	2.52	88.69	933480

含高比例气象敏感可再生能源电网日前调度时间颗粒度优化

Optimization of Day-Ahead Dispatch Time Resolution in Power System with a High Proportion of Climate-Sensitive Renewable Energy Sources

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