使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器

Ali Darvish Falehi; Ali Mosallanejad

doi:10.1631/FITEE.1500317

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使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器

常规文章 | Updated：2022-05-19

- 使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器
- Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO
- 信息与电子工程前沿（英文） 2017年18卷第3期页码：394-409
- Affiliations：
  
  Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983963113, Iran
- Author bio：
  
  E-mail:a_darvishfalehi@sbu.ac.ir
- Funds：
- DOI：10.1631/FITEE.1500317
  中图分类号： TM76;TP391
- 收稿：2015-09-30，
  
  录用：2016-5-13，
  
  纸质出版：2017-03
- Accepted：
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Ali Darvish Falehi, Ali Mosallanejad. 使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器[J]. 信息与电子工程前沿（英文）, 2017,18(3):394-409.

Ali Darvish FALEHI, Ali MOSALLANEJAD. Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 394-409.
Ali Darvish Falehi, Ali Mosallanejad. 使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器[J]. 信息与电子工程前沿（英文）, 2017,18(3):394-409. DOI： 10.1631/FITEE.1500317.

Ali Darvish FALEHI, Ali MOSALLANEJAD. Dynamic stability enhancement of interconnected multi-source power systems using hierarchical ANFIS controller-TCSC based on multi-objective PSO[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 394-409. DOI： 10.1631/FITEE.1500317.

摘要

在互联有电力系统中，载荷条件变化引起的结线功率交流与频率动态振荡的抑制已成为自动发电控制（automatic generation control

AGC）的重要职责。为缓解因负载变化导致的系统振荡，柔性交流输电系统（flexible AC transmission systems

FACTSs）可视为一种实用有效的解决方案。本文采用了一种隶属于FACTSs族的晶闸管可控串联补偿器（thyristor-controlled series compensator

TCSC），来增强互联电力系统多源的整体动态性能。为此，我们使用一种分层自适应神经模糊推理系统控制器－晶闸管可控串联补偿器（hierarchical adaptive neuro-fuzzy inference system controller-TCSC

HANFISC-TCSC）在多区域互联电力系统中解决了两个重要的问题，即低频振荡和结线功率交换的偏差。为实现这一目标，使用多目标优化技术有其必然性。由于多目标粒子群优化算法（Multi-objective particle swarm optimization

MOPSO）在解决非线性目标问题上具有较高性能，已被用于这一优化问题中。本文对所提出的HANFISC-TCSC效能进行了精确评估，并在两个不同的互联电力系统（即双区域水柴油热和三区域水热发电系统）中，将其与传统的MOPSO-TCSC算法进行了对比。两个电力系统中仿真结果表明都可明确证实，与传统MOPSO-TCSC算法相比，HANFISC-TCSC具有更高性能。

Abstract

Suppression of the dynamic oscillations of tie-line power exchanges and frequency in the affected interconnected power systems due to loading-condition changes has been assigned as a prominent duty of automatic generation control (AGC). To alleviate the system oscillation resulting from such load changes

implementation of flexible AC transmission systems (FACTSs) can be considered as one of the practical and effective solutions. In this paper

a thyristor-controlled series compensator (TCSC)

which is one series type of the FACTS family

is used to augment the overall dynamic performance of a multi-area multi-source interconnected power system. To this end

we have used a hierarchical adaptive neuro-fuzzy inference system controller-TCSC (HANFISC-TCSC) to abate the two important issues in multi-area interconnected power systems

i.e.

low-frequency oscillations and tie-line power exchange deviations. For this purpose

a multi-objective optimization technique is inevitable. Multi-objective particle swarm optimization (MOPSO) has been chosen for this optimization problem

owing to its high performance in untangling non-linear objectives. The efficiency of the suggested HANFISC-TCSC has been precisely evaluated and compared with that of the conventional MOPSO-TCSC in two different multi-area interconnected power systems

i.e.

two-area hydro-thermal-diesel and three-area hydro-thermal power systems. The simulation results obtained from both power systems have transparently certified the high performance of HANFISC-TCSC compared to the conventional MOPSO-TCSC.

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