مشخصات مقاله | |
ترجمه عنوان مقاله | مدیریت شبکه معین نرم افزار برای ترافیک گرید هوشمند پویا |
عنوان انگلیسی مقاله | Software defined network management for dynamic smart GRID traffic |
انتشار | مقاله سال 2019 |
تعداد صفحات مقاله انگلیسی | 30 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) |
7.007 در سال 2018 |
شاخص H_index | 93 در سال 2019 |
شاخص SJR | 0.835 در سال 2018 |
شناسه ISSN | 0167-739X |
شاخص Quartile (چارک) | Q1 در سال 2018 |
رشته های مرتبط | مهندسی کامپیوتر، مهندسی فناوری اطلاعات |
گرایش های مرتبط | مهندسی نرم افزار، شبکه های کامپیوتری |
نوع ارائه مقاله |
ژورنال |
مجله / کنفرانس | سیستم های کامپیوتری نسل آینده-Future Generation Computer Systems |
دانشگاه | Faculty of Technical Sciences, Unversity of Novi Sad, Trg Dositeja Obradovica 6, Novi Sad 21000 |
کلمات کلیدی | گرید هوشمند، AGC، Volt/VAr، QoS، تراکم داده |
کلمات کلیدی انگلیسی | Smart grid، AGC، Volt/VAr، QoS، Data aggregation |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.future.2019.02.022 |
کد محصول | E12074 |
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: |
Abstract 1. Introduction 2. Related work 3. Requirements 4. SDN control framework design and implementation 5. Performance evaluation 6. Conclusion and future work Acknowledgment References |
بخشی از متن مقاله: |
Abstract One of the more challenging issues in Smart Grid (SG) communications is in handling the ever-increasing number of new SG applications that are being provisioned by the utility companies. These applications are resulting in an exponential increase in the amount of data that utility companies are collecting. Appropriate communication infrastructure and its management is vital for providing this data to unlock the full potential of the SG. Typically, these applications generate different types of data traffic that can be divided into multiple traffic classes with different QoS parameters (priority, throughput, latency etc.). Traditionally, these classes are handled with static network configuration based on individual application policies. However, due to increasing network dynamism, the problem arises as to how to adjust these configurations, based on changing traffic situations. In this paper, a software defined networking (SDN) based solution for distributed and dynamic Smart Grid network management is presented. Proposed solution responsiveness to complex dynamicity of Smart Grid communications is evaluated on a developed evaluation platform for the following cases: (1) Automatic Generation Control (AGC) during peak load, (2) Volt/Var optimization (VVO) during peak load, (3) steady-state operation with static (background) traffic load, (4) stress-state under continuous background traffic overload and (5) dynamic prioritization of traffic for data disaggregation. The presented solution provides significant benefits, when compared with traditional networking in tested scenarios, including: over 70 times lower latency for the most time-sensitive traffic (AGC), 25% increased VVO system observability and 5% to 7% decrease in unprivileged traffic bandwidth consumption whenever privileged traffic QoS is threatened. Additionally, it is shown that dynamic prioritization can provide requested QoS on demand as long as overall capacity is larger than the privileged traffic offered load. Introduction Smart Grid is the next generation power grid. It is expected to be efficient, reliable, easily extendable, secure and able to support the ever increasing number of devices [1] as well as growing energy demands [2] in the not so distant future. Since the prerequisite for successful Smart Grid implementation and deployment is in bi-directional information flow (i.e. from utility to field devices and customers and vice versa), the existence of appropriate advanced communication infrastructure is essential [3] [4] [5] [6]. Providing quality of service (QoS) for Smart Grid communication traffic, while taking into consideration dynamic re-prioritization, is addressed in this paper. The Smart Grid communication infrastructure will have to cope with a large number of communication subsystems and be highly adaptive in order to support (growth) trends that are similar to what was observed in the last decade. In the early days, power grid communication systems were used to connect a relatively small number of devices using leased lines or point-to-point radio links [7], often through low-rate serial protocols and early SCADA systems. That was followed by the deployment of Power Line (Carrier) Communication technology providing communication mostly through power lines at high voltages with modest increase in data rates. More recently, a number of different technologies are increasingly used in power grid communication subsystems – from cellular, Wi-Fi, Zigbee, broadband Power Line Communication [8], and leased IP links to novel approaches such as Random Phase Multiple Access technology that has already been selected by Riverside Public Utilities for deployment [9]. At the same time, the public internet has reached almost every household in first world countries and has improved regarding quality and bandwidth. The public internet will be increasingly used for data acquisition, since a majority of end-user equipment can be trivially connected to it and deploying and maintaining a dedicated communication network is prohibitively expensive for individual utility companies. In addition, even for the equipment owned by specific utility companies, creating dedicated networks on a large scale to ensure peak response can turn costly. Utilities will rely on the public internet infrastructure for at least some of their future communication needs [10]. |