A Multi-Timescale Flexibility Demand Quantification Method for Power Grids

This paper proposes a multi-timescale flexibility demand quantification method for power grids. The seasonal power generation demand fluctuation index and uncertainty index are used to describe the monthly power balance pressure of the grid. The extreme fluctuation days and extreme condition power generation demand fluctuation index are employed to quantify the mid-term power compensation pressure caused by consecutive extreme fluctuations in renewable energy generation. The anti-peak shaving characteristic index and intraday fluctuation index describe the adjustment pressure resulting from intermittent renewable energy output at the hourly and minute timescales. By coupling long-term, mid-term, and short-term quantification indicators, the method provides a comprehensive description of the grid’s multi-timescale flexibility demand and constructs a comprehensive flexibility quantification index. Analysis of Huadong Power Grid demonstrates that the index effectively identifies flexibility demand in grid operation across different time scales, providing accurate decision support for inter-provincial power exchange on large grid platforms.

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Publication Details

Published
2025-04-11
DOI
https://doi.org/10.1109/icgeps65133.2025.11034598
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.73

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A Multi-Timescale Flexibility Demand Quantification Method for Power Grids

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Abstract

This paper proposes a multi-timescale flexibility demand quantification method for power grids. The seasonal power generation demand fluctuation index and uncertainty index are used to describe the monthly power balance pressure of the grid. The extreme fluctuation days and extreme condition power generation demand fluctuation index are employed to quantify the mid-term power compensation pressure caused by consecutive extreme fluctuations in renewable energy generation. The anti-peak shaving characteristic index and intraday fluctuation index describe the adjustment pressure resulting from intermittent renewable energy output at the hourly and minute timescales. By coupling long-term, mid-term, and short-term quantification indicators, the method provides a comprehensive description of the grid’s multi-timescale flexibility demand and constructs a comprehensive flexibility quantification index. Analysis of Huadong Power Grid demonstrates that the index effectively identifies flexibility demand in grid operation across different time scales, providing accurate decision support for inter-provincial power exchange on large grid platforms.

Dalian University of Technology (CN), Shanghai Electric (China) (CN)
Science and Technology Project of State Grid
Affordable and clean energy
Openalex Percentile: Top 27%
Smart Grid Energy Management
0.73
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