计及风电、光伏预测不确定性的抽水蓄能日前全调度优化

doi:10.3969/j.issn.2097-0706.2022.11.003

摘要/Abstract

摘要：

为降低风电、光伏等可再生能源出力预测不确定性对日前优化调度运行经济性的影响，提出一种计及风电-光伏预测不确定性的抽水蓄能日前全调度优化模型。首先，基于Weibull分布对风速进行预测，基于Beta分布对太阳辐照度进行预测，得到风电、光伏预测出力，采用多场景随机规划方法解决日前风电、光伏出力预测不确定性；其次，以日前风电、光伏出力预测场景集和负荷预测曲线为基础，结合水电、火电和抽水蓄能建立抽水蓄能日前全调度优化模型，以净负荷波动改善最优和总调峰成本最小为目标，求解得到抽水蓄能的抽发功率和火电的出力情况。以国内某省实际数据为算例，验证了该模型可充分平抑新能源出力波动，减小火电调峰压力，改善系统运行经济性。

关键词: 风电, 光伏发电, 抽水蓄能, 出力预测, 负荷预测, Weibull分布, Beta分布, 多场景随机规划, 全调度优化

Abstract:

In order to reduce the impact of uncertain forecasting on renewable energy outputs on the economy of day-ahead optimization scheduling， an overall day-ahead scheduling optimization model for pumped storage power stations considering the uncertainty of wind and photovoltaic power prediction is proposed. Firstly， the wind speed and solar irradiance are predicted based on Weibull distribution and Beta distribution，respectively. The predicted outputs of wind and photovoltaic power are obtained. The multi-scenario stochastic programming is adopted to solve the uncertainty of day-ahead wind and photovoltaic output predictions. Secondly， based on the scenario set of the predicted day-ahead wind and photovoltaic outputs and the load prediction curve， the overall day-ahead dispatching optimization model for the pumped storage power station considering wind， PV and thermal power is established. Taking steady net load and the minimum total peak-shaving cost as objectives， the water pumping and power generation outputs of the storage power station and the output of the thermal power units are obtained. Verified by the data from a province in China，the model can fully smooth the fluctuation of new energy outputs， reduce the peak load regulation pressure of thermal power units， and improve the economy of the system.

Key words: wind power, PV power, pumped storage, output prediction, load prediction, Weibull distribution, Beta distribution, multi-scenario stochastic programming, overall scheduling optimization

中图分类号:

TK01⁺9:TK71

欧阳婷, 蔡晔, 王炜宇, 唐夏菲, 谭玉东. 计及风电、光伏预测不确定性的抽水蓄能日前全调度优化[J]. 综合智慧能源, 2022, 44(11): 20-27.

OUYANG Ting, CAI Ye, WANG Weiyu, TANG Xiafei, TAN Yudong. Overall day-ahead scheduling optimization for pumped-storage power stations considering the uncertainty of wind and photovoltaic power prediction[J]. Integrated Intelligent Energy, 2022, 44(11): 20-27.

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机组类型	机组容量/MW	数量/台	总容量/MW
火电机组	660	18	11 880.0
	330	16	5 280.0
	210	2	420.0
抽水蓄能机组	300	4	1 200.0
风电机组			6 690.9
光伏机组			3 906.7
水电机组			15 806.4

场景	发生概率
场景	风电	光伏
1	0.410	0.190
2	0.120	0.160
3	0.150	0.300
4	0.180	0.120
5	0.140	0.230

指标	不含抽水蓄能	本文方法
净负荷峰谷差/MW	4 825.4	2 425.4
净负荷峰谷差减少率/%		49.75
调峰成本/万元	7 883.0	7 840.1
火电机组开机台数	36	32