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العنوان
Optimal Management for EVs’ Aggregator Agent\
المؤلف
Hassan,Ahmed Mohammed Asim
هيئة الاعداد
باحث / أحمد محمد عاصم حسن
مشرف / حسام الدين عبد الله طلعت
مشرف / عمرو محمد ابراهيم حسن
مناقش / حمدي احمد عاشور
مناقش / مصطفي ابراهيم مرعي
تاريخ النشر
2017.
عدد الصفحات
102p.:
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الكهربائية والالكترونية
تاريخ الإجازة
1/1/2017
مكان الإجازة
جامعة عين شمس - كلية الهندسة - كهربة قوى
الفهرس
Only 14 pages are availabe for public view

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Abstract

Transportation systems electrification is a global aim to limit severe irreversible environmental impacts and to preserve transportation systems sustainability. Thus, the number of on-road Electrical Vehicles (EVs) will continue to increase. This introduces new challenges and opportunities to many actors: utility, EV owner, EV manufactures, retailers, and system operators. The different use-cases of Vehicle-grid-integration have been discussed by many literatures and reports. However, relativity complex two use cases have been considered in this work (unidirectional aggregated charging with unified and fragmented actors). In these two cases, the EVs charging and degraded battery replacement are controlled by an energy retailer called an aggregator. In this work, a stochastic multi-trip linear optimal bidding model including battery degradation cost and user charging preference is introduced. The model allows the aggregator to bid in the wholesale energy and regulatory markets. The main contributions of this work are:
1- Developing a bidding model that includes battery degradation cost.
2- Developing general Constant-Current Constant-Voltage (CC-CV) Li-ion charging model. The new charging model is general and valid for various EVs types and charging levels.
3- Modeling the user charging preference.
4- Modeling multi-trip traveling behavior.
The model is applied to PJM (system operator in USA) electricity market for various owner traveling models. The results showed the validity of the model, the importance of users charging preferences and their effect on the aggregator total expenses, and the weaknesses encountering single trip based models.