مشخصات مقاله | |
ترجمه عنوان مقاله | تحلیل حساسیت ولتاژ جدید برای شبکه های توزیع هوشمند با استفاده از مشتق تحلیلی: مدل ABCD |
عنوان انگلیسی مقاله | Long-term financial predictions based on Feynman–Dirac path integrals, deep Bayesian networks and temporal generative adversarial networks |
انتشار | مقاله سال ۲۰۲۲ |
تعداد صفحات مقاله انگلیسی | ۱۵ صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
۴٫۶۳۰ در سال ۲۰۲۰ |
شاخص H_index | ۱۳۰ در سال ۲۰۲۰ |
شاخص SJR | ۱٫۰۵۰ در سال ۲۰۲۰ |
شناسه ISSN | ۰۱۴۲-۰۶۱۵ |
شاخص Quartile (چارک) | Q1 در سال ۲۰۲۰ |
فرضیه | ندارد |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مهندسی برق |
گرایش های مرتبط | تولید، توزیع و انتقال، مهندسی الکترونیک، سیستم های قدرت |
نوع ارائه مقاله |
ژورنال |
مجله | مجله بین المللی برق و سیستم های انرژی – International Journal of Electrical Power & Energy Systems |
دانشگاه | Electrical Engineering Department, Faculty of Engineering, Philadelphia University, Jordan |
کلمات کلیدی | تجزیه و تحلیل میزان حساسیت، کنترل ولتاژ، شبکه های برق هوشمند، واحدهای DG، ماتریس ژاکوبین، مختصات کارتزین |
کلمات کلیدی انگلیسی | Sensitivity analysis – Voltage control – Smart power networks – DG units – Jacobian matrix – Cartesian coordinates |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.ijepes.2021.107799 |
کد محصول | E15979 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Highlights Abstract Keywords Introduction Proposed sensitivity analysis approach Simulation results Conclusions Declaration of Competing Interest Acknowledgment References |
بخشی از متن مقاله: |
ABSTRACT Sensitivity Analysis plays a significant role in voltage prediction and control of power networks. However, the classical sensitivity methods require significant computation time. As active distribution networks require realtime implementation for voltage control, reducing the computation time becomes a necessary task for network operators, especially in the context of optimization techniques. This work develops a new analytical and fast voltage sensitivity analysis method via the derivative of the nodal quantities (power, current and voltage) with respect to power injections. The proposed method mainly depends on the construction of the ABCD matrix. The values of the matrix elements remain the same regardless of the bus on which the power is injected. Thus, it has a high potential to be implemented in online applications. To make a complete separation between the sensitivities to active and the sensitivities to reactive power injections, the analytical formulations are expressed in Cartesian coordinates. A radial distribution network including several DG units is used to verify and assess the proposed sensitivity method under different scenarios. Introduction |Future Power grids will meet new challenges in voltage control due to the high penetration levels of Distributed Generation (DG) units [1]. DG units can be actively involved in power systems for voltage regulation [2]. Voltage control methods mainly depend on the relationship between the system voltages and control variables (i.e. power injections). The sensitivity analysis is usually used to find the voltage sensitivity coefficients with respect to nodal reactive and real power injections. These sensitivities can be actively used to manage control variables to solve voltage problems in an accurate way. Many approaches have been proposed in the literature to compute these sensitivities. One of the well-known approaches is based on the Jacobian matrix [3,4]. This approach is a classical method and depends on solving a Newton Raphson power flow [5]. The voltage sensitivities are found by taking the Jacobian matrix (J) inverse at one operating condition. However, the sensitivity coefficients have to be updated with any change in system state (e.g. changes of demand, generation, topology, and/or network parameters). This requires performing new Newton Raphson-based power flow calculations and, therefore, more computation time is required. Besides, convergence may not be obtained by this method. Such methods developed for transmission load flow studies are unsuitable for distribution systems due to poor convergence [6]. |