Dynamic State Estimation of a Multi-source Isolated Power System Using Unscented Kalman Filter

被引：1

作者：

Aggarwal, Neha ^{[1
]}

Mahajan, Aparna N. ^{[1
]}

Nagpal, Neelu ^{[2
]}

机构：

[1] MAU, ECE Dept, Baddi, India

[2] MAIT, EEE Dept, Delhi, India

来源：

INTERNATIONAL CONFERENCE ON INNOVATIVE COMPUTING AND COMMUNICATIONS, ICICC 2022, VOL 3 | 2023年 / 492卷

关键词：

Dynamic state estimation; Frequency response model; Smart grid; State observer; Renewable energy; Unscented Kalman filter;

D O I：

10.1007/978-981-19-3679-1_10

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In power systems, dynamic state estimation (DSE) is a crucial activity for real-time monitoring and control to ensure the system's safe and efficient operation. This paper presents an method for real-time estimation of dynamic states of an isolated power system integrated with renewable energy sources (RESs) and electric vehicles (EVs) aggregates. The proposed method employs an adapted unscented Kalman filter (UKF) as an observer to estimate the system's dynamic states which are either inaccessible or corrupted with measurement noise. MATLAB/Simulink is used to develop a simulation platform for frequency response model of power system. The simulation results on the developed test system investigated the efficacy of UKF as dynamic state estimator that takes into account the diverse behaviours of the system and provides accurate estimates of the system states.

引用

页码：131 / 140

页数：10

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