Modeling and Solving Method for Supporting ‘Vehicle-to-Anything’ EV Charging Mode

Mao, Tian; Zhang, Xin; Zhou, Baorong

doi:10.3390/app8071048

Cited by 25 publications

(10 citation statements)

References 22 publications

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“…There are four locations where vehicle owners will be able to charge their vehicles: in their own home, at their place of service, at the fleet's fleet, or at commercial charging stations [38].…”

Section: Energy Managementmentioning

confidence: 99%

Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives

et al. 2019

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The goal of the study presented in this article is to provide a general overview of the various aspects related to electric vehicles (EVs), along with all associated emerging challenges and perspectives. In this context, the basic types of EVs and the corresponding charging technologies are analyzed. Since EVs are expected to be a key component of future smart electrical grids (SEG), connection to the grid issues, along with advanced charging techniques (i.e., wireless power transfer), are analyzed as well. To this end, the main features, the requirements of vehicle to grid (V2G) communications, as well as future developments and scenarios of electrification, are also presented and analyzed. Moreover, integration issues with currently deployed fifth generation (5G) mobile wireless networks are also outlined, in order to ensure optimum transmission and reception quality in V2G communications and improved user experience. This integration is also expanded in autonomous vehicles (AVs) technology (self-driving objects), since optimized information processing from various diverse sources is required in order to ensure advanced traffic management aspects.In this context, two major categories can be classified: a. Battery electric vehicles (BEV), and b. Hybrid electric vehicles (HEV). BEVs use batteries as a source of energy and they are also called "green vehicles, or clean vehicles, or eco-friendly vehicles" because they have zero emissions. In order to cover a travel distance, they are equipped with larger storage batteries than HEVs. However, the limited traveling distance of BEVs is an important drawback because it is often necessary to recharge the battery by connecting to an external power source (in city cars, autonomy starts from 100 to 120 km and reaches 500 km or more in high power cars-Tesla Model). A HEV is classified as a car that uses two or more different technologies to achieve its movement. These technologies usually include the classic internal combustion engine and a more "mild" environmentally-friendly technology, usually an electric motor. However, the electric motor is used as a supplementary power source in cases where the HEV requires more power.It is apparent from the above that proper energy management is of vital importance for the smooth operation of EVs. A challenging research field includes the design and implementation of efficient charging schemes that ensure fast and reliable EV charging in order to increase vehicle autonomy. In this concept, the vehicle-to-grid (V2G) approach aims to optimize the way we transport, use, and produce electricity by turning electric cars into "virtual power plants" [9]. V2G technology refers to a bi-directional flow system operation, in which plug-in battery electric vehicles communicate with a recipient and allow the reciprocal flow between the EV and an electric grid [10,11]. Under this relatively new concept, electric cars would store and dispatch electrical energy stored in networked vehicle batteries which together act as one collective battery fleet ...

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Section: Energy Managementmentioning

confidence: 99%

Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives

et al. 2019

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“…Lastly, bringing the EV and other residential loads together in a smart home environment, the idea of the vehicle to anything (V2A) has been proposed in [24]. In V2A, the active power compensation through EV forms the basis of a vehicle to home scenario.…”

Section: Related Literaturementioning

confidence: 99%

Agent‐based system to control the air‐conditioner and EV charging for residents in smart cities

2019

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Air-conditioner (AC) accounts for a significant share of residential energy consumption. Considering the widespread rise in electric vehicle (EV) usage, its charging would also contribute a considerable percentage of consumer's total energy consumption. Consequently, the concurrent operation of AC and EV charging would result in peaky load curves. Hence, this study proposes a system of agents for AC and EV charging applications, which incorporates load-management strategies to flatten the load curve. Thereby, the presented system includes two agents, namely: a smart load node for a thermostatically controlled load (SLN-TCL) and a smart battery charge controller. Subsequently, a subagent, namely micro-node, has been introduced to support SLN-TCL and to implement the concept of distributed temperature sensing (DTS). The implementation of DTS subdues the conventional temperature sensing mechanism of AC and ensures a more flexible operation. This study includes the design, development, and features of agents and subagents for AC and EV applications. Furthermore, this study also demonstrates the agent-based control actions for peak-shaving under real conditions to showcase the performance of this system.

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“…"Vehicle-to-grid" (V2G) sistem jeste sistem koji konceptualno omogućava sve benefite koji se očekuju od učestvovanja električnih vozila u mreži (slika 1) [13]. Za funkcionisanje ovog sistema potrebni su distribuirani sistemi kontrole, jer bi centralizovana kontrola svakog električnog vozila predstavljala ogroman komputacioni zadatak.…”

Section: Uticaj Električnih Vozila Na Elektroenergetski Sistemunclassified

Implementation of the V2G model for optimising the load curve of the power system using PSO algorithm

Ostojić¹,

Ćalasan²,

Mujović³

2019

Tehnika

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Ovaj rad se bavi uticajem električnih vozila na elektroenergetsku mrežu, kroz koncept Vehicle-to-grid, sa stanovišta popravljanja dnevne karakteristike opterećenja. U cilju traženja optimalnog rasporeda razmjene energije između baterija električnih automobila i mreže korišćen je Particle swarm optimisation (PSO) algoritam. U radu je pokazana efikasnost primjene navedenog algoritma, kao i mogućnost korišćenja električnih vozila u popravljanju karakteristike sistema, posebno smanjujući uzimanje energije iz mreže u periodima velikog mrežnog opterećenja i povećavajući uzimanje energije iz mreže u periodima malog mrežnog opterećenja. Svi zaključci su izvedeni uz poštovanje ograničenja u pogledu stepena napunjenosti (state-of-charge-SOC) baterija automobila koji učestvuju u V2G sistemu.

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Modeling and Solving Method for Supporting ‘Vehicle-to-Anything’ EV Charging Mode

Cited by 25 publications

References 22 publications

Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives

Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives

Agent‐based system to control the air‐conditioner and EV charging for residents in smart cities

Implementation of the V2G model for optimising the load curve of the power system using PSO algorithm

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