Open Access

ARTICLE

Research on Equivalent Modeling Method of AC-DC Power Networks Integrating with Renewable Energy Generation

Weigang Jin¹, Lei Chen^2,*, Yifei Li², Shencong Zheng², Yuqi Jiang², Hongkun Chen²

1 Central China Branch of State Grid Corporation of China, Wuhan, 430077, China
2 School of Electrical Engineering and Automation, Wuhan University, Wuhan, 430072, China

* Corresponding Author: Lei Chen. Email:

(This article belongs to the Special Issue: Renewable Energy Technologies for Sustainable Energy Production)

Energy Engineering 2023, 120(11), 2469-2487. https://doi.org/10.32604/ee.2023.043021

Received 19 June 2023; Accepted 04 August 2023; Issue published 31 October 2023

Abstract

Along with the increasing integration of renewable energy generation in AC-DC power networks, investigating the dynamic behaviors of this complex system with a proper equivalent model is significant. This paper presents an equivalent modeling method for the AC-DC power networks with doubly-fed induction generator (DFIG) based wind farms to decrease the simulation scale and computational burden. For the AC-DC power networks, the equivalent modeling strategy in accordance with the physical structure simplification is stated. Regarding the DFIG-based wind farms, the equivalent modeling based on the sequential identification of multi-machine parameters using the improved chaotic cuckoo search algorithm (ICCSA) is conducted. In light of the MATLAB simulation platform, a two-zone four-DC interconnected power grid with wind farms is built to check the efficacy of the proposed equivalent modeling method. From the simulation analyses and comparative validation in different algorithms and cases, the proposed method can precisely reflect the steady and dynamic performance of the demonstrated system under N-1 and N-2 fault scenarios, and it can efficiently achieve the parameter identification of the wind farms and fulfill the equivalent modeling. Consequently, the proposed approach’s effectiveness and suitability are confirmed.

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Keywords

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