Flexibility Demand Decomposition and Operation Optimization for Power System Based on Hybrid Mathematical Morphology

LUO Renjie; JU Jiaxin; LI Zhiyi

doi:10.7500/AEPS20240906008

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Flexibility Demand Decomposition and Operation Optimization for Power System Based on Hybrid Mathematical Morphology

Basic Research | 更新时间：2025-06-16

- Flexibility Demand Decomposition and Operation Optimization for Power System Based on Hybrid Mathematical Morphology
- Automation of Electric Power Systems Vol. 49, Issue 11, Pages: 37-47(2025)
- 作者机构：
  
  浙江大学电气工程学院，浙江省杭州市 310027
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2022YFB2404002)
- DOI：10.7500/AEPS20240906008
  CLC：
- Received：06 September 2024，
  
  Revised：2025-01-09，
  
  Published Online：28 February 2025，
  
  Published：10 June 2025
- 稿件说明：
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罗仁杰,鞠家鑫,李知艺.基于混合数学形态学的电力系统灵活性需求分解与运行优化[J].电力系统自动化,2025,49(11):37-47.

LUO Renjie,JU Jiaxin,LI Zhiyi.Flexibility Demand Decomposition and Operation Optimization for Power System Based on Hybrid Mathematical Morphology[J].Automation of Electric Power Systems,2025,49(11):37-47.
罗仁杰,鞠家鑫,李知艺.基于混合数学形态学的电力系统灵活性需求分解与运行优化[J].电力系统自动化,2025,49(11):37-47. DOI： 10.7500/AEPS20240906008.

LUO Renjie,JU Jiaxin,LI Zhiyi.Flexibility Demand Decomposition and Operation Optimization for Power System Based on Hybrid Mathematical Morphology[J].Automation of Electric Power Systems,2025,49(11):37-47. DOI： 10.7500/AEPS20240906008.

摘要

考虑到新型电力系统灵活性需求激增并呈现多时间尺度波动特征，针对调频和爬坡等调节容量单独量化的传统方法易造成预留容量过度冗余的问题，亟须挖掘资源调节能力并量化系统灵活性需求，以提升系统安全运行能力。文中提出一种基于混合数学形态学分解的电力系统灵活性需求分解与多时间尺度调节容量预留方法。首先，通过核密度分布模型生成预测区间内灵活性需求曲线集合；其次，设计考虑调节资源出力特性的混合数学形态学滤波器，将灵活性需求曲线分解为规律分量和随机分量，并根据随机分量集合计算所需调频容量；最后，在灵活性需求分解的规律分量基础上，构建调节资源长/短时爬坡容量预留的随机优化模型。算例结果表明，与传统方法相比，所提模型可实现分解结果与调节资源出力特性相匹配，预留方案能满足电力系统灵活性需求并提升容量调用率。

Abstract

Considering the rapid increase of flexibility demand characterized by multi-timescale fluctuations in the new power system

the traditional separate quantization method for the regulation capacity such as frequency regulation and ramp may cause excessive capacity reservation. It is urgent to explore the resource regulation performance and quantify the system flexibility demand to improve the safe operation of power systems. This paper proposes a flexibility demand decomposition of power system and multi-timescale regulation capacity reservation method based on hybrid mathematical morphology decomposition. Firstly

the kernel density distribution model is used to generate the set of flexibility demand curves within the prediction interval. Secondly

the hybrid mathematical morphology filter considering the output characteristics of regulation resources is designed to decompose the flexibility demand curves into regular and random components. The needed frequency regulation capacity is then calculated according to the set of random components. Finally

based on the regular components obtained by the flexibility demand decomposition

the stochastic optimization model is constructed for long- and short-term ramping capacity reservation of regulation resources. Numerical results show that

compared with traditional methods

the proposed model can match the decomposition results with the output characteristics of regulation resources. Meanwhile

the reservation scheme can meet the flexibility demand of power systems and enhance the capacity utilization rate.

关键词

Keywords

references

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