مقاله انگلیسی رایگان در مورد مبدل DC-DC خود انطباق برای کنترل سیستم هیبریدی – IEEE 2018

مقاله انگلیسی رایگان در مورد مبدل DC-DC خود انطباق برای کنترل سیستم هیبریدی – IEEE 2018

 

مشخصات مقاله
انتشار مقاله سال ۲۰۱۸
تعداد صفحات مقاله انگلیسی ۵ صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
منتشر شده در نشریه IEEE
نوع مقاله ISI
عنوان انگلیسی مقاله Agent-based self-adaptive DC-DC converter for hybrid energetic system control
ترجمه عنوان مقاله مبدل DC-DC خود انطباق مبتنی بر عامل برای کنترل سیستم پر انرژی هیبریدی
فرمت مقاله انگلیسی  PDF
رشته های مرتبط مهندسی برق
گرایش های مرتبط مهندسی الکترونیک، الکترونیک قدرت، مهندسی کنترل
مجله ششمین کنگره و نمایشگاه شهرها و شبکه های هوشمند استانبول – ۶th International Istanbul Smart Grids and Cities Congress and Fair
دانشگاه Mohammadia School of Engineers (EMI) – Mohammed V University – Morocco
کلمات کلیدی مبدل های DC-DC؛ کنترل ولتاژ گذرگاه DC؛ سیستم های چند عامل؛ متلب Simulink؛ MaximJX؛ مبدل های DC-DC خودانطباق
کلمات کلیدی انگلیسی DC-DC converters; DC bus voltage control; Multi Agent System (MAS); Matlab Simulink; MaximJX; selfadaptive DC-DC converters
شناسه دیجیتال – doi
https://doi.org/10.1109/SGCF.2018.8408939
کد محصول E8870
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بخشی از متن مقاله:
I. INTRODUCTION

The hybrid energetic system (HES) is generally an energy system operating simultaneously several sources with different capacities and proprieties. It is principally based on renewable energy sources (RES) and distributed generators DG. Their distributed production should meet an increasingly variable demand. The RES depend strongly on meteorological conditions, thereby they cannot be considered as a continuous energy supply and therefore behave as passive generator. To balance between consumption and generation the RES should be coupled with other sources and storage systems. Diversifying the energy sources is now a real issue. Hybridizing the RES with the storage system and DG as cogeneration system can meet the distributed production requirements allowing the RES intensive integration. The HES ensure a long-term energetic availability and it is able to deliver a subscribed power when the RES act as active generators. The HES can be shown as a supply system consisting of small distributed energy systems [1-2]. However, the DGs and the storage technologies life cycle should be respected. To take full advantages of the HES a distributed energy management (DEM) is necessary. It deals with the simultaneous operation of the different generators, the storage system and DGs constraints, and the variable load demand. Furthermore; other requirements should be satisfied in the DEM, as voltage limit control, the produced energy cost, the system effectiveness, the energy quality improvement, the energy flexible use and the environmental issue. Thanks to DEM, the HES can produce and consume effectively depending on the capacity of each generator and the loads’ needs. The HES studied in this paper consists of PV generator and wind turbine as a RES and battery as storage technology system. This configuration can lead to prematurely lose battery life, because of the quickly battery charge and discharge. Many studies have dealt with the effective battery use [3-4]. Linking a hybrid generator to the RES and the battery as the Fuel cell (FC)-electrolyser combination generator is the HES suggested in this paper. A custom role for power electronics is the development of HES, by meeting the distributed production constraints. Several studies have brought more interest to HES control containing DGs, RES and storage technologies. The Fuzzy logic and neural networks [5] were the subjects of many studies regarding the HES control, but the complexity and the difficulty in their implementation and comprehension can be their main inconvenient. Furthermore, these approaches can make the system non-scalable which conflicting with the distributed generation and therefore the future energy networks. This paper proposes a distributed energy management system based on the bus voltage control allowing simultaneously a flexible energy generation and consumption depending on the capacity of each generator and the variable demand by the bias of multi-agent system (MAS).

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