| 000 | 06219nam a2200433 4500 | ||
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| 003 | EG-NbEJU | ||
| 005 | 20241204210605.0 | ||
| 008 | 241203b2024 ua | m||| 00| 0 eng d | ||
| 040 |
_aEG-NbEJU _beng _cEG-NbEJU _dEG-NbEJU |
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| 041 |
_aeng _bara |
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| 050 |
_aEPE MSc. 2024 04 _b04 |
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| 100 | 1 | _aMugerwa , Geofrey , | |
| 245 | 1 | 0 |
_aData - Driven Customer - Phase Relationship Identification in Low - Voltage Distribution Networks with Distributed Generations : _bA Thesis Submitted to the Graduate School of Electronics , Communication , and Computer Engineering : Egypt-Japan University of Science and Technology (E-JUST) : In Partial Fulfillment of the Requirements for the Degree of Master of Science in Electrical Power Engineering / _cby Geofrey Mugerwa ; Supervisor Committee Prof. Sobby Abdelkader - Egypt-Japan University of Science and Technology , Prof. Maha Elsabrouty - Egypt-Japan University of Science and Technology , Dr. Tamer Megahed - Egypt-Japan University of Science and Technology , Prof. Tanemasa Asano - Kyushu University ; Examination Committee Prof. Sobby Abdelkader - E-JUST , Prof. Mohamed Abdelazim - Vice President of Mansoura University , Prof. Loay Saad Eldin Nasrat - Vice President of Aswan University for Education and Student Affairs |
| 246 | 1 | 5 |
_aتحديد ارتباط العميل بالوجه باستخدام البيانات في شبكات توزيع الجهد المنخفض المتشملة على مولدات موزعة : _bرسالة علمية مقدمة إلى المدرسة التخصصية للدراسات العليا - هندسة الإلكترونيات و الاتصالات و الحاسوب : الجامعة المصرية اليابانية للعلوم و التكنولوجيا كاستيفاء جزئي لمتطلبات الحصول على درجة ماحستير العلوم في هندسة القوى الكهربية / إعداد جيفري موجيروا ; لجنة الإشراف على الرسالة أ . د صبحي عبدالقادر , أ . د مها الصبروتي , د. تامر مجاهد , أ.د تانيماسا اسانو ; لجنة المناقشة و الحكم على الرسالة أ.د صبحي عبدالقادر , أ.د محمد عبدالعظيم محمد عبدالعظيم , أ . د . لؤي سعد الدين نصرت |
| 260 |
_aAlexandria : _bGeofrey Mugerwa _c2024 |
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| 300 |
_a61 leaves ; _c30 cm |
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| 500 | _aIncludes a title page in Arabic | ||
| 502 |
_aThesis (M.Sc.)
_bMaster _cEgypt - Japan University of Science and Technology (E-JUST) - School of Electronics , Communication , and Computer Engineering - Electrical Power Engineering Department _d2024 |
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| 520 | _aPhase identification involves determining which phase each end-customer is connected to in a multi-phase distribution network Knowing the correct customer-phase connectivity provides Distribution System Operators (DSOs) with critical information for efficient operation and management of Low-Voltage Distribution Networks (LVDNs) Additionally , accurate phase connectivity information is essential for increasing the hosting capacity of Distributed Energy Resources (DERS) , which are key players in modern power systems On the other hand , incorrect customer-phase connectivity increases the risk of phase unbalance , leading to nuisance tripping of protection devices and equipment damage for assets such as transformers Usually , the phase connectivity information of a LVDN is known to DSOs at the time of planning and commissioning the power line However , due to the complexity and the various changes that occur during its operation , such as new customer connections , maintenance and repair operations , cyber attacks , emergency restoration services , etc. , the original data files maintained at the power management center often contain false connectivity information This challenge is traditionally addressed by applying hardware-based phase identification techniques Nevertheless, such approaches are costly , prone to human errors , and time - consuming, as they involve either installing expensive high-precision devices or employing field-based methods To overcome the above challenges , this thesis develops a novel data- driven method to identify the phase connectivity of end-customers using Advanced Metering Infrastructure (AMI) voltage and current measurements , collected every 15 minutes Firstly , a preprocessing method that employs linear interpolation and singular value decomposition is adopted to improve the quality of the smart meter data Secondly , using Kirchoff's current law and correlation analysis , a 0-1 linear integer programming optimization model is built to uniquely identify the phase to which each customer is connected The datasets utilized are obtained by performing power flow simulations on a modified IEEE-906 test system using OpenDSS software The robustness of the proposed identification algorithm is tested against dataset size , missing data , measurement errors , and the influence of rooftop photovoltaic generation systems To explore the benefits associated with knowing the correct phase identification information | ||
| 530 | _aIssued also as a digital file (for more information please check our Digital Repository) | ||
| 590 |
_aAnD _bACM |
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| 700 | 1 |
_aAbdelkader , Sobby , _eSupervisor |
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| 700 | 1 |
_aElsabrouty , Maha , _eco-Supervisor |
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| 700 | 1 |
_aMegahed , Tamer , _eco-Supervisor |
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| 700 | 1 | _aAsano , Tanemasa , | |
| 700 | 1 |
_aAbdelkader , Sobby , _eExaminator |
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| 700 | 1 |
_aAbdelazim , Mohamed , _eco-Examinator |
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| 700 | 1 |
_aNasrat , Loay Saad Eldin , _eco-Examinator |
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| 700 | 1 |
_aعبدالقادر , صبحي , _eمشرف |
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| 700 | 1 |
_aالصبروتي , مها , _eمشرف مساعد |
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| 700 | 1 |
_aمجاهد , تامر , _eمشرف مساعد |
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| 700 | 1 |
_aاسانو , تانيماسا , _eمشرف مساعد |
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| 700 | 1 |
_aعبدالقادر , صبحي , _eمناقش |
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| 700 | 1 |
_aعبدالعظيم , محمد عبدالعظيم محمد , _eمناقش مساعد |
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| 700 | 1 |
_aنصرت , لؤي سعد الدين , _eمناقش مساعد |
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| 901 | _aHaGeR | ||
| 902 | _aTH_02122024_ (1) | ||
| 942 |
_2lcc _n0 _cDISS |
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| 999 |
_c7089 _d7089 |
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