用于并网光伏系统有功和无功功率控制的新型优化调整超扭曲滑动模式控制器

IF 1.6 Q4 ENERGY & FUELS IET Energy Systems Integration Pub Date : 2023-09-18 DOI:10.1049/esi2.12117
Bhabasis Mohapatra, Binod Kumar Sahu, Swagat Pati
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引用次数: 0

摘要

在光伏(PV)系统中,逆变器在供电以满足需求的同时保持电能质量方面发挥着至关重要的作用。对于连接到并网光伏(GIPV)系统的本地负载而言,有功和无功功率控制在配电层面是必要的。因此,本文的首要目的是为有功和无功功率控制设计最佳的鲁棒控制器。本文提出了一种基于改进算术优化算法(IAOA)的超级扭转滑模控制器(ST-SMC)方法的 GIPV 系统,用于有功和无功功率管理。GIPV 系统中最常用的传统 PI 控制器具有相当大的下冲和较长的稳定期。PI 控制器的调整参数也因参考模式的巨大变化而改变。因此,STSMC 和 SMC 被用来确保对外部干扰的鲁棒性。传统的 SMC 会出现颤振问题。此外,还通过一些基准函数验证了所提出的 IAOA 技术。就迭代次数和准确实现有功和无功功率控制的最优解而言,所提出的 IAOA 技术优于粒子群优化(PSO)、基于法证的调查(FBI)和传统算术优化算法(TAOA)。结果表明,所提出的基于 IAOA 的 STSMC 技术在有功和无功功率控制方面的沉降时间和下冲性能都有所改善。本文还介绍了上述控制器的稳定性分析和鲁棒性测试,以说明每个优化设计控制器的有效性。使用 MATLAB 环境对 40 kW GIPV 系统的性能进行了评估,并在实时模拟器平台 OPAL-RT 4510 中对结果进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A novel optimally tuned super twisting sliding mode controller for active and reactive power control in grid-interfaced photovoltaic system

In photovoltaic (PV) systems, inverters play a crucial role for supplying electricity to meet the demand while maintaining power quality. For a local load connected to a grid-interfaced photovoltaic (GIPV) system, active and reactive power control is necessary at the distribution level. Thus, the foremost purpose of this article is to get the best optimally designed robust controller for control of active and reactive power. A GIPV system with Improved Arithmetic Optimisation Algorithm (IAOA)-based Super Twisting Sliding Mode Controller (ST-SMC) methodology has been proposed in this article for active and reactive power management. The conventional PI controller in the GIPV system that is most frequently used has considerable undershoot and a long settling period. PI controller tuning parameters were also changed to account for the wide change in the reference pattern. Therefore, STSMC and SMC are used for ensuring robustness against external disturbances. The conventional SMC comes out to have a chattering issue. Furthermore, the proposed IAOA technique is validated through some benchmark functions. The proposed IAOA technique outperforms Particle Swarm Optimisation (PSO), Forensic Based Investigation (FBI), and Traditional Arithmetic Optimisation Algorithm (TAOA) in terms of the number of iterations and accurately achieving optimal solutions for active and reactive power control. The results show that the proposed IAOA-based STSMC technique has an improved performance of settling time and undershoot for active and reactive power control. This article also presents stability analysis and robustness test of the above mentioned controllers to illustrate the effectiveness of each optimally designed controller. A 40 kW GIPV system performance is evaluated using the MATLAB environment, and the results are validated in a real-time simulator platform OPAL-RT 4510.

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来源期刊
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
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