Vehicle to grid and demand side management - an assessment of different strategies for the integration of electric vehicles

Nebel, Arjuna; Krüger, Christine; Merten, Frank

doi:10.1049/cp.2011.0156

Cited by 9 publications

(14 citation statements)

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“…However, many existing literatures have focused on the intelligent charging strategy [15][16][17][18][19][20] in distribution grids, although discharging management [21][22][23][24][25] has attracted increased attentions in recent years. Smoothing the daily load profile is considered to be the most important issue [15-17, 21, 22] whereas electricity price and economic benefits of EV owners are the main motivating factors to obtain load leveling [17].…”

Section: Introductionmentioning

confidence: 99%

“…Several management strategies for EV charging/discharging were established to achieve this objective [24,25]. In these discharging strategies studied in [21][22][23][24][25], EVs were mostly treated as storage systems while discharging procedure was considered. Strategies for combined charging/discharging with respect to the uncertainties such as travel patterns and initial battery state of charge (SOC), which are more close to the real condition, have not been investigated to date.…”

Section: Introductionmentioning

confidence: 99%

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Day-ahead optimal charging/discharging scheduling for electric vehicles in microgrids

Cai

Chen

Guan

et al. 2018

Prot Control Mod Power Syst

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Microgrid as an important part of smart grid comprises distributed generators (DGs), adjustable loads, energy storage systems (ESSs) and control units. It can be operated either connected with the external system or islanded with the support of ESSs. While the daily output of DGs strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the unbalance between the daily load curve and generation curve. In this paper, a statistic model is presented to describe daily EV charging/discharging behaviors considering the randomness of the initial state of charge (SOC) of EV batteries. The optimization problem is proposed to obtain the economic operation for the microgrid based on this model. In dayahead scheduling, with the estimated power generation and load demand, the optimal charging/discharging scheduling of EVs during 24 h is achieved by serial quadratic programming. With the optimal charging/discharging scheduling of EVs, the daily load curve can better track the generation curve. The network loss in grid-connected operation mode and required ESS capacity in islanded operation mode are both decreased.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Day-ahead optimal charging/discharging scheduling for electric vehicles in microgrids

Cai

Chen

Guan

et al. 2018

Prot Control Mod Power Syst

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“…EVs' functionality to be used as distributed energy storage system provides the possibility for various ancillary services such as energy trading [4], power quality improvement [5], frequency regulation [6][7][8], load regulation and spinning reserves [9] and regulation services for renewable energy resources [10][11][12]. V2G services along with the PV power to reduce peak demand are demonstrated in [11,13]. By aggregating the EVs available/parked in commercial or office buildings, an SES device can be created [11].…”

Section: Introductionmentioning

confidence: 99%

Loss‐of‐life investigation of EV batteries used as smart energy storage for commercial building‐based solar photovoltaic systems

Kandasamy

Tseng

2017

IET Electrical Systems in Transportation

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This study presents a loss-of-life (LoL) analysis for electric vehicle (EV) batteries, when they are being used as smart energy storage (SES) systems in a typical solar photovoltaic (PV) system installed in building environment. EVs can be considered as ideal energy storage for solar PV system installed in commercial/office buildings. This is attributable to the fact that the idle time-period of the EVs during the daytime, and the time-period during which the solar PV requires the energy storage intersect perfectly. However, it is to be demonstrated that using EVs as SES for solar PV system in commercial/office buildings would not have a significant impact on the battery lifetime and driving range of EVs. Hence, LoL analysis is essential to get a clear picture on the expected LoL for the EV batteries when EVs are used as SES for solar PV. Furthermore, the LoL of the individual EV batteries depends on the priority criteria used for charging/discharging the EVs, namely time coordinated and power coordinated vehicle-to-grid (V2G) algorithms. Hence, a comparison of LoL for different types of EVs while using different priority criteria in both the types of V2G is presented.

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“…A summary of prior art discovered relating to EV charge control for providing ancillary services is listed in Table 4. These include demand profile smoothing or balancing [30], [31], [20], frequency and voltage control of the grid [32], and integration of renewable energy sources [33]. These control strategies focus only on the behavior of the utility grid and any cost benefits or drawbacks are secondary.…”

Section: Ancillary Servicesmentioning

confidence: 99%

“…In Figure 20, A. Nebel shows that EV charging and discharging activity can be incorporated into the utility grid to help smooth the demand profile [31]. Again, this control strategy assumes that technologies enabling vehicle to grid and energy storage are available in plug-in hybrid electric vehicles.…”

Section: Ancillary Servicesmentioning

confidence: 99%

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

Jewell¹

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Vehicle to grid and demand side management - an assessment of different strategies for the integration of electric vehicles

Cited by 9 publications

References 0 publications

Day-ahead optimal charging/discharging scheduling for electric vehicles in microgrids

Day-ahead optimal charging/discharging scheduling for electric vehicles in microgrids

Loss‐of‐life investigation of EV batteries used as smart energy storage for commercial building‐based solar photovoltaic systems

Development of a power monitoring and control system to provide demand side management of electric vehicle charging activity.

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