Valley- Filling Strategy for Coordinated Charging of Large- Scale Electric Vehicles

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Valley- Filling Strategy for Coordinated Charging of Large- Scale Electric Vehicles

ارائه دهنده: Provider: Atiye Arabi

اساتید راهنما: Supervisors: Mohammad Hasan Moradi (Ph. D) - Alireza Hatami (Ph. D)

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: دکتر صالح رازینی - دکتر محمد مهدی شهبازی

زمان و تاریخ ارائه: Time and date of presentation: November 2020

مکان ارائه: Place of presentation:

چکیده: Abstract: Increasing the peak load curve in the distribution network during peak demand hours leads to problems such as equipment overload، increasing operating costs of power generation units and increasing losses. simultaneous charging of a large number of electric vehicles also creates new peaks in the load curve of the distribution network، which if the normal peak load of the network overlaps، the problems will be doubled. In order to reduce the negative effects of simultaneous charging of electric vehicles during peak hours، various methods such as shifting the demand for charging these vehicles to low hours have been studied. In addition، excess energy stored in electric car batteries during peak hours can be used to meet the load. But in many studies، the issue of the cost of using electric vehicle batteries for peak shaving and load response has not been considered. On the other hand، the issue of reducing the cost of operation of energy production units and the cost of greenhouse gas emissions has been the subject of much research. In this thesis demand response with the aim of peak shaving with the help of batteries of participating electric vehicles in this program is considered along with reducing the operating costs of this batteries. In addition، reducing the operating costs of energy production units and reducing the production costs of greenhouse gases resulting from the production of these units are also taken into account. To optimize the problem، a particle swarm algorithm is used، which eventually leads to the improvement of the load curve.

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