scholarly journals Virtual storage plants in parking lots of electric vehicles providing local/global power system support

2021 ◽  
Vol 43 ◽  
pp. 103249
Author(s):  
Hessam Golmohamadi
Keyword(s):  
Power System ◽  
Electric Vehicles ◽  
System Support ◽  
Virtual Storage ◽  
Parking Lots ◽  
Global Power

The Control Strategy Of V2G Participating in Peak Regulation in Power System

2011 ◽  
Vol 383-390 ◽  
pp. 4151-4157
Author(s):  
Wen Qi Tian ◽  
Jing Han He ◽  
Jiu Chun Jiang ◽  
Cheng Gang Du
Keyword(s):  
Power System ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Control Strategy ◽  
Distributed Energy ◽  
Control Center ◽  
Distributed Energy Storage ◽  
New Energy ◽  
Regulation Function ◽  
Control Layer

With the increase of new energy power generation, the requirement of smart grid and the popularity of electric vehicles, the research focus on V2G. With Electric vehicles being distributed energy storage or distributed generation, peak regulation in power system is involved in important functions of V2G. In order to achieve peak regulation function, the paper has analyzed the control relationship between the electric vehicles, V2G station and electric vehicle charge\ discharge control center, presented charge and discharge control strategy based on the two levels of electric vehicle charge\discharging control center and V2G station control layer and introduced algorithms and examples to achieve these strategies.

scholarly journals Energy Trading with Electric Vehicles in Smart Campus Parking Lots

2018 ◽  
Vol 8 (10) ◽  
pp. 1749 ◽  
Author(s):  
Mohamed Ahmed ◽  
Young-Chon Kim
Keyword(s):  
Electric Vehicles ◽  
Market Mechanism ◽  
University Campus ◽  
Energy Trading ◽  
Control Center ◽  
Parking Lots ◽  
Electric Vehicle Charging ◽  
Parking Lot ◽  
Demand Information ◽  
Knapsack Algorithm

Energy trading with electric vehicles provides opportunities to eliminate the high peak demand for electric vehicle charging while providing cost saving and profits for all participants. This work aims to design a framework for local energy trading with electric vehicles in smart parking lots where electric vehicles are able to exchange energy through buying and selling prices. The proposed architecture consists of four layers: the parking energy layer, data acquisition layer, communication network layer, and market layer. Electric vehicles are classified into three different types: seller electric vehicles (SEVs) with an excess of energy in the battery, buyer electric vehicles (BEVs) with lack of energy in the battery, and idle electric vehicles (IEVs). The parking lot control center (PLCC) plays a major role in collecting all available offer/demand information among parked electric vehicles. We propose a market mechanism based on the Knapsack Algorithm (KPA) to maximize the PLCC profit. Two cases are considered: electric vehicles as energy sellers and the PLCC as an energy buyer, and electric vehicles as energy buyers and the PLCC as an energy seller. A realistic parking pattern of a parking lot on a university campus is considered as a case study. Different scenarios are investigated with respect to the number of electric vehicles and amount of energy trading. The proposed market mechanism outperforms the conventional scheme in view of costs and profits.

scholarly journals Load area aggregation considering integration of electric vehicles to the system

2015 ◽  
Vol 35 (1Sup) ◽  
pp. 42-49 ◽  
Author(s):  
Luis Fernando Rodríguez-García ◽  
Sandra Milena Pérez-Londoño ◽  
Juan José Mora-Flórez
Keyword(s):  
Power Systems ◽  
Power System ◽  
Electric Vehicles ◽  
System Analysis ◽  
Original System ◽  
Computational Effort ◽  
Computational Technique ◽  
Equivalent Network ◽  
Optimal Dispatch ◽  
Equivalent Load

<span>Current electric power systems have an increasing penetration of electric vehicles, and its effect has to be considered in different <span>studies, such as optimal dispatch or voltage stability, among others. Additionally, considering that power system analysis becomes <span>complex when the number of buses increase, this paper presents a methodology for aggregation of load areas that use a measurement-based load modeling approach based on an evolutionary computational technique and a classical reduction method. This aggregate <span>load area model is proposed to reduce areas that consider electric vehicle (EV) load models. The proposed method provides a static <span>equivalent load model and an equivalent network that can be used to reduce the computational effort required by power system<br /><span>studies. In order to validate the application of the proposed methodology, a 30-bus power system considering several disturbances <span>and levels of penetration of the electric vehicles was used. The results show that the equivalent network model allows the reproduction <span>of different events with an acceptable accuracy when it is compared to the original system behavior.</span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span>

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