Suppr超能文献

用于改善静态电压稳定裕度的多目标最优潮流

Multiobjective optimal power flow for static voltage stability margin improvement.

作者信息

Kyomugisha Rebeccah, Muriithi Christopher Maina, Edimu Milton

机构信息

Electrical Engineering Department, Pan African University Institute for Basic Sciences, Technology and Innovation, Nairobi, Kenya.

Electrical Engineering Department, Murang'a University of Technology, Murang'a, Kenya.

出版信息

Heliyon. 2021 Dec 17;7(12):e08631. doi: 10.1016/j.heliyon.2021.e08631. eCollection 2021 Dec.

Abstract

Worldwide, utilities are aiming to increase the stability of modern power systems during system disturbances. Optimizing generation scheduling can improve system security in contingency and stressed conditions while lowering losses and generation costs. An efficient operating strategy for maintaining power system stability is proposed in this work. The paper focuses on incorporating a Voltage Collapse Proximity Index (VCPI) in the traditional optimal power flow problem for multiobjective optimization (MO). Different case studies are assessed to evaluate the impact on the control variables. A Preference Selection index (PSI) is utilized to determine the best-case study for optimal system operation. The effectiveness of the proposed approach is tested on standard IEEE 30-bus and IEEE 57-bus during normal, contingency, and stressed conditions using MATPOWER. During normal conditions, the MO voltage stability constrained optimal power flow (VSC-OPF) increases the system stability by 28.13 % higher than the single objective (SO) case. Furthermore, the transmission losses are lowered by 14.69% with the proposed MO approach. During line outage contingency conditions, the voltage stability enhancement and loss reduction are higher in the MO than in the SO case by 13.60% and 23.19%. However, the loss minimization and stability improvement during normal and contingency conditions come at a slightly higher generation cost of 5.05% in both systems. On the other hand, during stressed conditions, the SO performs better in voltage stability improvement (by 8.77%) and loss reduction (by 6.97%) than in the MO voltage stability constrained OPF. Additionally, PV Curve analysis for the two systems indicates that voltage stability in MO OPF problems provides a more significant margin enhancement of 9.00%, 118.95% in normal and contingency, respectively, higher than the SO case. However, the SO case increases the load margin by 12.36% more than the MO case in stressed conditions. Consequently, the PSI ranks the multiobjective optimization of the three objectives as the most optimal way for operating the systems in normal and line outage contingency conditions. However, during increased load conditions, the system performance is better if a singular objective function is considered. This is due to the lack of adequate reactive power generation during stressed conditions, and hence a singular objective focus is sufficient to assure system stability. Therefore, the proposed approach is an effective preventive control measure for possible voltage collapse in typical power systems. The resulting improvement also brings about a sufficient system stability margin, causing the system to become more secure.

摘要

在全球范围内,电力公司旨在提高现代电力系统在系统故障期间的稳定性。优化发电调度可以在紧急情况和压力条件下提高系统安全性,同时降低损耗和发电成本。本文提出了一种维持电力系统稳定性的有效运行策略。本文重点将电压崩溃接近指数(VCPI)纳入传统最优潮流问题中,以进行多目标优化(MO)。评估了不同的案例研究,以评估对控制变量的影响。利用偏好选择指数(PSI)来确定最优系统运行的最佳案例研究。使用MATPOWER在正常、紧急和压力条件下,在标准IEEE 30节点和IEEE 57节点上测试了所提方法的有效性。在正常条件下,多目标电压稳定性约束最优潮流(VSC-OPF)比单目标(SO)情况将系统稳定性提高了28.13%。此外,所提多目标方法使输电损耗降低了14.69%。在线路停电紧急情况下,多目标优化在电压稳定性增强和损耗降低方面比单目标情况分别高出13.60%和23.19%。然而,在正常和紧急情况下,损耗最小化和稳定性提高在两个系统中都带来了略高5.05%的发电成本。另一方面,在压力条件下,单目标在电压稳定性改善(提高8.77%)和损耗降低(降低6.97%)方面比多目标电压稳定性约束最优潮流表现更好。此外,对两个系统的PV曲线分析表明,多目标最优潮流问题中的电压稳定性在正常和紧急情况下分别比单目标情况提供了更显著的裕度增强,分别为9.00%、118.95%。然而,在压力条件下,单目标情况比多目标情况使负荷裕度增加了12.36%。因此,偏好选择指数将三个目标的多目标优化列为正常和线路停电紧急情况下系统运行的最优方式。然而,在负荷增加的情况下,如果考虑单一目标函数,系统性能会更好。这是因为在压力条件下缺乏足够的无功功率发电,因此单一目标关注足以确保系统稳定性。因此,所提方法是典型电力系统中可能发生电压崩溃的有效预防控制措施。由此带来的改进也带来了足够的系统稳定性裕度,使系统变得更加安全。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/536d/8715161/d2d3911fffec/gr1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验