New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm

With the rapid expansion of new energy in China, the large-scale grid connection of new energy is increasing, and the operating safety of the new energy power system is being put to the test. The static security and stability region (SSSR) with hyper-plane expression is an effective instrument for s...

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Main Authors: Saniye Maihemuti, Weiqing Wang, Jiahui Wu, Haiyun Wang, Muladi Muhedaner
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/15/24/9655
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author Saniye Maihemuti
Weiqing Wang
Jiahui Wu
Haiyun Wang
Muladi Muhedaner
author_facet Saniye Maihemuti
Weiqing Wang
Jiahui Wu
Haiyun Wang
Muladi Muhedaner
author_sort Saniye Maihemuti
collection DOAJ
description With the rapid expansion of new energy in China, the large-scale grid connection of new energy is increasing, and the operating safety of the new energy power system is being put to the test. The static security and stability region (SSSR) with hyper-plane expression is an effective instrument for situational awareness and the stability-constrained operation of power systems. This paper proposes a hybrid improved particle swarm optimization (IPSO) and recursive least square (RLS) approach for rapidly approximating the SSSR boundary. Initially, the operating point data in the high-dimensional nodal injection space is examined using the IPSO algorithm to find the key generators, equivalent search space, and crucial points, which have a relatively large impact on static stability. The RLS method is ultimately utilized to fit the SSSR border that best suits the crucial spots. Consequently, the adopted algorithm technique was used to rapidly approximate the SSSR border in power injection spaces. Finally, the suggested algorithm is confirmed by simulating three kinds of generators of the new energy 118 bus system using the DIgSILENT/Power Factory. As a result, this method accurately characterized the stability border of the new energy power system and created the visualization space of the SSSR. Using the SSSR, a rapid state analysis could be undertaken on a variety of parameters, such as security evaluation with diverse energy supply capacities. This study’s findings confirmed the accuracy and efficacy of the suggested modeling for the considered system and may thus give technical support for the new energy power system’s stability.
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spelling doaj.art-a530dbe001e04cda8e460331103d63e92023-11-24T14:40:59ZengMDPI AGEnergies1996-10732022-12-011524965510.3390/en15249655New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid AlgorithmSaniye Maihemuti0Weiqing Wang1Jiahui Wu2Haiyun Wang3Muladi Muhedaner4College of Electrical Engineering, Xinjiang University, Urumqi 830047, ChinaCollege of Electrical Engineering, Xinjiang University, Urumqi 830047, ChinaCollege of Electrical Engineering, Xinjiang University, Urumqi 830047, ChinaCollege of Electrical Engineering, Xinjiang University, Urumqi 830047, ChinaStudent Affairs Department, Changsha University of Science and Technology, Changsha 410114, ChinaWith the rapid expansion of new energy in China, the large-scale grid connection of new energy is increasing, and the operating safety of the new energy power system is being put to the test. The static security and stability region (SSSR) with hyper-plane expression is an effective instrument for situational awareness and the stability-constrained operation of power systems. This paper proposes a hybrid improved particle swarm optimization (IPSO) and recursive least square (RLS) approach for rapidly approximating the SSSR boundary. Initially, the operating point data in the high-dimensional nodal injection space is examined using the IPSO algorithm to find the key generators, equivalent search space, and crucial points, which have a relatively large impact on static stability. The RLS method is ultimately utilized to fit the SSSR border that best suits the crucial spots. Consequently, the adopted algorithm technique was used to rapidly approximate the SSSR border in power injection spaces. Finally, the suggested algorithm is confirmed by simulating three kinds of generators of the new energy 118 bus system using the DIgSILENT/Power Factory. As a result, this method accurately characterized the stability border of the new energy power system and created the visualization space of the SSSR. Using the SSSR, a rapid state analysis could be undertaken on a variety of parameters, such as security evaluation with diverse energy supply capacities. This study’s findings confirmed the accuracy and efficacy of the suggested modeling for the considered system and may thus give technical support for the new energy power system’s stability.https://www.mdpi.com/1996-1073/15/24/9655new energy power systemIPSORLSSSSR
spellingShingle Saniye Maihemuti
Weiqing Wang
Jiahui Wu
Haiyun Wang
Muladi Muhedaner
New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
Energies
new energy power system
IPSO
RLS
SSSR
title New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
title_full New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
title_fullStr New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
title_full_unstemmed New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
title_short New Energy Power System Static Security and Stability Region Calculation Research Based on IPSO-RLS Hybrid Algorithm
title_sort new energy power system static security and stability region calculation research based on ipso rls hybrid algorithm
topic new energy power system
IPSO
RLS
SSSR
url https://www.mdpi.com/1996-1073/15/24/9655
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AT jiahuiwu newenergypowersystemstaticsecurityandstabilityregioncalculationresearchbasedonipsorlshybridalgorithm
AT haiyunwang newenergypowersystemstaticsecurityandstabilityregioncalculationresearchbasedonipsorlshybridalgorithm
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