یک مطالعه جامع در مورد اندازه گیری و ضریب توان تولید توزیع شده
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یک مطالعه جامع در مورد اندازه گیری و ضریب توان تولید توزیع شده

عنوان فارسی مقاله: جایایی بهینه، اندازه گیری و ضریب توان تولید توزیع شده: پوشش دادن یک مطالعه جامع از مرحله برنامه ریزی تا مرحله بهره برداری
عنوان انگلیسی مقاله: Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage
مجله/کنفرانس: انرژی - Energy
رشته های تحصیلی مرتبط: برق
گرایش های تحصیلی مرتبط: انتقال و توزیع، برق قدرت، سیستم های قدرت، الکترونیک، الکترونیک قدرت، مهندسی کنترل
کلمات کلیدی فارسی: تکامل تفاضلی، تولید توزیع شده، تخصیص بهینه، بهینه سازی، ضریب توان
کلمات کلیدی انگلیسی: Differential evolution، Distributed generation، Optimal allocation، Optimisation، Power factor
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.energy.2020.117011
دانشگاه: Institute of Power Engineering, Department of Electrical Power Engineering, College of Engineering, Universiti Tenaga Nasional, Malaysia
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 6/153 در سال 2019
شاخص H_index: 158 در سال 2020
شاخص SJR: 2/048 در سال 2019
شناسه ISSN: 0360-5442
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 26
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: خیر
آیا این مقاله مدل مفهومی دارد: ندارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: ندارد
کد محصول: E14945
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

ABSTRACT


1- Introduction


2- Design of the proposed optimal DG algorithm


3- Formulation of algorithm objectives and constraints


4- Modelling of test system with component profiles


5- Optimal DG planning


6- Optimal DG operation


7- Conclusion


References

نمونه متن انگلیسی مقاله

ABSTRACT


In this paper, an optimised framework utilising a Differential Evolution algorithm is presented to optimally integrate multiple distributed generation sources simultaneously into the distribution grid. By considering the important power system constraints, the proposed algorithm optimises the location, sizing and power factor setting for each distributed generation source to minimise network losses and maximise distributed generation integration. Various case studies were conducted at constant or varying levels of load and generation in both the planning stage and the real-time operation stage. The results of all case studies revealed that the proposed Differential Evolution-based algorithm delivered better performance in terms of network loss reduction and maximised distributed generation compared to other existing methods. The network loss reduction of 95.71% was achieved when all three parameters of placement, sizing and power factor of distributed generation were optimised simultaneously. In addition, a practical framework with a varying optimal power factor for distributed generation was designed. The optimal power factor setting for each distributed generation source was dynamically adjusted during real-time power grid operation, resulting in further minimisation of the system loss reduction. The overall loss reduction achieved was 96.04% relative to the base case of no distributed generation connection.


Introduction


In recent decades, global warming has resulted in worldwide desert expansion, temperature increase and rise in sea level. If this global warming issue is not addressed properly, some of the main landmasses and islands will eventually become uninhabitable. In the energy sector, the conventional electricity generation process based on the burning fossil fuels emits greenhouse gases, which are known to be the main cause of global warming. The use of Renewable Energy (RE) serves as an excellent countermeasure to the effects of global warming because RE is a non-depleting indigenous resource that produces insignificant waste pollutants [1]. Therefore, RE-based Distributed Generation (DG) has emerged as a preferred choice in the energy sector to reduce the amount of greenhouse gases emission [2]. Despite the environmental benefits, the technical aspects of RE-based DG integration to the power grid must be carefully assessed because these resources are intermittent in nature and rely heavily on weather conditions [3]. While integrating a small portion of RE into a large power grid is relatively easy to accomplish, the escalating penetration of RE is posing new challenges to both system planning and operation [4]. In the literature, researchers have reported various technical impacts on the grid due to DG connection to the power network [5]. The main impacts are grid voltage rise, reverse power flow and power quality problems. Severe grid voltage rise occurs if DG sources are connected in a weak power network [6]. Reverse power flow, which occurs during periods with high DG power generation and low demand, may affect the existing power protection schemes [7]. Moreover, power quality problems, such as harmonics and flickers, are caused by the switching of DG inverters [8].

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