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دسته بندی:
مدیریت انرژی - Energy Management
سال انتشار:
2020
عنوان انگلیسی مقاله:
A novel approach for multi-objective optimal scheduling of large-scale EV fleets in a smart distribution grid considering realistic and stochastic modeling framework
ترجمه فارسی عنوان مقاله:
یک رویکرد جدید برای برنامه ریزی بهینه چند منظوره از ناوگان های مقیاس بزرگ EV در یک شبکه توزیع هوشمند با توجه به چارچوب مدل سازی واقع گرایانه و تصادفی
منبع:
Sciencedirect - Elsevier - Electrical Power and Energy Systems, 117 (2020) 105617. doi:10.1016/j.ijepes.2019.105617
نویسنده:
Alireza Hatefi Einaddin, Ahmad Sadeghi Yazdankhah⁎
چکیده انگلیسی:
The ever-increasing number of grid-connected electric vehicles (EVs) has led to emerging new opportunities and
threats in electrical distribution systems (DS). Developing a realistic model of EV interaction with the DS, as well
as developing a strategy to optimally manage these interactions in line with distribution system operators (DSOs)
intentions, are the most important prerequisites for gaining from this phenomenon especially in modern smart
distribution systems (SDS). In this paper, a comprehensive model describing the electric vehicle integration to an
SDS is presented by considering the real-world data from EV manufacturers and DSOs. Moreover, a novel energy
management strategy (EMS) based on the multi-objective optimization problem (MOOP) is developed to fulfill
the operational objectives of DSO and EV owner, including peak load shaving, loss minimization, and EV owner
profit maximization. In this regard, an innovative dimension reduction approach is presented, to make it feasible
to apply the heuristic optimization methods to a MOOP with a large number of decision variables. Thanks to this
method, the improved electromagnetism like algorithm (IEMA) is employed to perform the multi-objective
energy scheduling for a large-scale EV fleet. In addition, a novel method is devised for estimating the optimal
hosting capacity of an SDS in adopting EVs without the need for sophisticated computations. The presented
method is applied to the modified IEEE-33 bus test system. Obtained results reveal that employment of a realistic
model concludes to more accurate results than a simplified model. In addition, the efficiency of the proposed
EMS in satisfying EV owner and DSO objectives are approved by analyzing obtained computation results.
Keywords: Smart grid | Energy management | Electric vehicle | Vehicle to grid | Multi-objective optimization
قیمت: رایگان
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