Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources

Ye Guo; Yifei Xu; Hongbin Sun; Boming Zhang

doi:10.17775/CSEEJPES.2021.05070

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Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources

Regular Papers | 更新时间：2026-10-15

- Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources
- Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources
- 中国电机工程学会电力与能源系统学报(英文) 2025年11卷第1期页码：115-123
- 作者机构：
  
  1. Tsinghua-Berkeley Shenzhen Institute (TBSI), Tsinghua Shenzhen International Graduate School Tsinghua University,Shenzhen,China
  2. Department of Electrical Engineering, State Key Laboratory of Power Systems, Tsinghua University,Beijing,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2021.05070
  中图分类号：
- 纸质出版：2025-01-01
- 稿件说明：
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Ye Guo, Yifei Xu, Hongbin Sun, 等. Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources[J]. 中国电机工程学会电力与能源系统学报(英文), 2025,11(1):115-123.

Ye Guo, Yifei Xu, Hongbin Sun, et al. Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources[J]. CSEE Journal of Power and Energy Systems, 2025, 11(1): 115-123.
Ye Guo, Yifei Xu, Hongbin Sun, 等. Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources[J]. 中国电机工程学会电力与能源系统学报(英文), 2025,11(1):115-123. DOI： 10.17775/CSEEJPES.2021.05070.

Ye Guo, Yifei Xu, Hongbin Sun, et al. Multi-Time Interval Forecasting-Aided State Estimation Incorporating Phasor Measurements for Power Systems with Renewable Energy Sources[J]. CSEE Journal of Power and Energy Systems, 2025, 11(1): 115-123. DOI： 10.17775/CSEEJPES.2021.05070.

摘要

Abstract

To achieve more precise monitoring of state fluctuations in the power network close to renewable energy sources

it is necessary to utilize phasor measurements and shorten the time interval between state estimations. For large-scale power systems

however

estimating all of their states with shorter time intervals means a drastic increase in computational burden. As a tradeoff between accuracy and computational efficiency

a multi-time interval forecasting-aided state estimation approach is proposed in this paper

where states with various degrees of fluctuations are estimated asynchronously with different time intervals. Based on the newest state estimate

forecasting-aided state estimators are employed to predict states at time moments prior to the next round of measurement update and state estimation. Extensive numerical tests have demonstrated the effectiveness of the proposed approach.

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