Nonparametric kernel density estimation based wind-solar-hydro-thermal-storage system operational flexibility evaluation

MI Yi; XU Xuesong; YANG Yiming; ZOU Xin

doi:10.11930/j.issn.1004-9649.202508057

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Nonparametric kernel density estimation based wind-solar-hydro-thermal-storage system operational flexibility evaluation

更新时间：2026-04-30

- Nonparametric kernel density estimation based wind-solar-hydro-thermal-storage system operational flexibility evaluation
- Vol. 59, Issue 4, Pages: 12-23(2026)
- 作者机构：
  
  1. 国网经济技术研究院有限公司,北京,102209
  2. 华北电力大学经济管理系,河北,保定,071003
- 作者简介：
- 基金信息：
- DOI：10.11930/j.issn.1004-9649.202508057
  CLC：
- Online First：20 April 2026，
  
  Published：2026
- 稿件说明：
移动端阅览
米熠, 徐雪松, 杨一鸣, 邹鑫. 基于非参数核密度估计的风光水火储系统灵活性评估方法研究[J]. 中国电力, 2026, 59(4): 12-23.

MI Yi, XU Xuesong, YANG Yiming, et al. Nonparametric kernel density estimation based wind-solar-hydro-thermal-storage system operational flexibility evaluation[J]. 2026, 59(4): 12-23.
米熠, 徐雪松, 杨一鸣, 邹鑫. 基于非参数核密度估计的风光水火储系统灵活性评估方法研究[J]. 中国电力, 2026, 59(4): 12-23. DOI： 10.11930/j.issn.1004-9649.202508057.

MI Yi, XU Xuesong, YANG Yiming, et al. Nonparametric kernel density estimation based wind-solar-hydro-thermal-storage system operational flexibility evaluation[J]. 2026, 59(4): 12-23. DOI： 10.11930/j.issn.1004-9649.202508057.

摘要

随着新能源渗透率持续提升，源荷双侧不确定性对电力系统稳定运行构成显著风险。为科学评估风光水火储多源耦合新型电力系统的灵活性，提出融合源荷双侧不确定性区间估计与随机生产模拟的协同分析框架。首先，通过非参数核密度估计生成新能源出力与负荷的置信区间，构建极端供需情景以量化不确定性。其次，结合分级调度策略，优先将风电、光伏和径流式水电等效为负值负荷，再考虑系统爬坡约束，利用改进的随机生产模拟算法安排火电机组出力。最后，调度库容式水电承接系统剩余负荷。当发生切负荷或弃新能源事件时，通过储能设备充放电进行调节。案例分析表明，非参数估计可有效表征源荷双侧不确定性；系统因爬坡能力不足引发的切负荷和弃新能源电量占比分别为14.8%和91.5%，即爬坡约束是影响系统稳定运行的重要因素；配置储能可显著提升系统调节能力，使系统失负荷概率和弃新能源概率分别降低8.6%和34.1%。

Abstract

With the rising penetration of new energy

uncertainties on both generation and load sides pose significant risks to power system stability. To scientifically assess the flexibility of a novel multi-source coupled power system (integrating wind

solar

thermal

hydro and energy storage)

a collaborative analysis framework is proposed

combining interval estimation of bilateral generation-load uncertainties with stochastic production simulation. First

non-parametric kernel density estimation generates confidence intervals for new energy output and load

and extreme supply-demand scenarios are constructed to quantify such uncertainties. Second

via a hierarchical dispatching strategy

wind

photovoltaic and run-of-river hydropower are prioritized as equivalent negative loads. Considering system ramping constraints

an improved stochastic production simulation algorithm schedules thermal power unit output. Finally

reservoir-type hydropower undertakes remaining system load. In case of load shedding or new energy curtailment

energy storage devices regulate the system through charging and discharging. Case studies show non-parametric estimation effectively characterizes bilateral generation-load uncertainties. The proportions of load shedding and new energy curtailment due to insufficient system ramping capacity are 14.8% and 91.5%

respectively

indicating ramping constraints are critical to system stability. Energy storage configuration significantly enhances regulation capacity

reducing the loss of load probability (LOLP) and new energy curtailment probability by 8.6% and 34.1%

respectively.

关键词

Keywords

references

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