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Abstract

In microgrid distribution generation (DG) sources are integrated parallelly for the economic and efficient operation of a power system. This integration of DG sources may cause many challenges in a microgrid. The islanding condition is termed a condition in which the DG sources in the microgrid continue to power the load even when the grid is cut off. This islanding situation must be identified as soon as possible to avoid the collapse of the microgrid. This work presents the hybrid islanding detection technique. This technique consists of both active and parametric estimation methods such as slip mode shift frequency (SMS) and exact signal parametric rotational invariance technique (ESPRIT), respectively. This technique will easily distinguish between islanding and non-islanding events even under very low power perturbations. The proposed method also has no power quality impact. The proposed method is tested with UL741 standard test conditions.
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Authors and Affiliations

S. Jayanthi
1
S. Arockia Edwin Xavier
2
ORCID: ORCID
P.S. Manoharan
2
ORCID: ORCID

  1. Sapthagiri College of Engineering, Periyanahali, Dharmapuri, India
  2. Thiagarajar College of Engineering, Madurai, India
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Abstract

The paper deals with frequency estimation methods of sine-wave signals for a few signal cycles and consists of two parts. The first part contains a short overview where analytical error formulae for a signal distorted by noise and harmonics are presented. These formulae are compared with other accurate equations presented previously by the authors which are even more accurate below one cycle in the measurement window. The second part contains a comparison of eight estimation methods (ESPRIT, TLS, Prony LS, a newly developed IpDFT method and four other 3-point IpDFT methods) in respect of calculation time and accuracy for an ideal sine-wave signal, signal distorted by AWGN noise and a signal distorted by harmonics. The number of signal cycles is limited from 0.1 to 3 or 5. The results enable to select the most accurate/ fastest estimation method in various measurement conditions. Parametric methods are more accurate but also much slower than IpDFT methods (up to 3000 times for the number of samples equal to 5000). The presented method is more accurate than other IpDFT methods and much faster than parametric methods, which makes it possible to use it as an alternative, especially in real-time applications.
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Authors and Affiliations

Józef Borkowski
Dariusz Kania
Janusz Mroczka
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Abstract

A hybrid multi-infeed HVDC (HMIDC) system is composed of line-commutated converter-based high-voltage direct current (LCC-HVDC) and voltage-source converterbased high-voltage direct current (VSC-HVDC), whose receiving ends have electrical coupling. To solve the problem of low-frequency oscillation (LFO) caused by insufficient damping in the HMIDC system, according to the multi-objective mixed H2/H∞ output feedback control theory with regional pole assignment, an additional robust damping controller is designed in this paper, which not only has good robustness, but also has strong adaptability to the change of system operation mode. In the paper, the related oscillation modes and transfer function of the controlled plant are obtained, which are identified by the total least squares estimation of signal parameters via rotary invariance technology (TLS-ESPRIT). In addition, the control-sensitive point (CSP) for suppressing LFO based on the small disturbance test method is determined, which is suitable for determining the installation position of the controller. The results show that the control sensitivity factor of VSC-HVDC is greater than that of LCC-HVDC so that adding an additional damping controller to VSC-HVDC is better than LCC-HVDC in suppressing the LFO of HMIDC. Finally, a hybrid double infeed DC transmission system with three receiving terminals is built on PSCAD/EMTDC where the time-domain simulations are performed to verify the correctness of the CSP selection and the effectiveness of the controller.
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Authors and Affiliations

Congshan Li
1
ORCID: ORCID
Yan Liu
1
ORCID: ORCID
Yikai Li
1
ORCID: ORCID
Ping He
1
ORCID: ORCID
Yan Fang
1
ORCID: ORCID
Tingyu Sheng
1
ORCID: ORCID

  1. School of Electrical and Information Engineering, Zhengzhou University of Light Industry, China

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