Impact of vehicle-to-grid on power system operation costs: The Spanish case study

Fernandes, Camila; Frías, Pablo; Latorre, Jesús M.

doi:10.1016/j.apenergy.2011.11.058

Cited by 109 publications

(53 citation statements)

References 11 publications

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“…Several authors point out that a large amount of EVs in the charging mode can have a negative influence in distribution networks [25]. It is possible that new power demand peaks appear in inappropriate periods, and that the voltage drops increase.…”

Section: Impact Of Electric Vehiclesmentioning

confidence: 99%

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Morais

Sousa

Vale

et al. 2014

Energy Conversion and Management

124

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a b s t r a c tSmart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management.

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Section: Impact Of Electric Vehiclesmentioning

confidence: 99%

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Morais

Sousa

Vale

et al. 2014

Energy Conversion and Management

124

View full text Add to dashboard Cite

show abstract

“…Smart EVs and HPs could not only reduce 53 the required generation/network capacity [3] and the incremental carbon emissions 54 driven by EVs and HPs, but also facilitate the integration of RES through energy 55 arbitrage [6] [7] and ancillary service provision [4] [8]. In this context, this paper focuses 56 on analysing and quantifying the implications of deploying smart EVs and HPs for the 57 carbon emissions and RES integration cost within the UK electricity system.…”

Section: Res Integration 39mentioning

confidence: 99%

Benefits of flexibility from smart electrified transportation and heating in the future UK electricity system

2016

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EVs/HPs could significantly enhance both the carbon benefit and the RES integration 29 benefit of smart EVs/HPs. 30 31 Introduction 32Rapid expansion of Renewable Energy Sources (RES) is expected to make a key 33 contribution to electricity system decarbonisation. However, high penetration of 34 2 intermittent RES will increase the requirements for various reserve and frequency 35 response services, leading to reduced carbon benefit and increased balancing cost. 36Moreover, large amount of additional generation capacity is required to provide "RES 37 firming" for system security reasons, which causes additional costs associated with 38 RES integration. 39At the same time, the electrification of transport through electric vehicles (EVs) and 40 heating systems through heat pumps (HPs) is seen as another key policy measure to 41 further reduce the use of fossil fuel in energy supply and hence reduce carbon carbon emissions and RES integration cost within the UK electricity system. Therefore, 58 the key specific objectives of this paper can be summarized as: 591. Analyse the benefits of smart EVs/HPs trialled in LCL in reducing carbon emissions 60 in a broader UK electricity system. 61 2. Quantify the economic benefits of carbon savings from smart EVs/HPs in terms of 62 lower requirements to invest in zero-carbon generation capacity in order to achieve 63 the same carbon emission target. 64 3. Analyse the benefits of smart EVs/HPs in reducing system integration cost of RES, 65 including balancing cost associated with RES intermittency and investment cost 66 associated with back-up capacity to ensure system security. 67The impact of smart EVs/HPs is investigated for three future system development 68 scenarios, with particular emphasis on different possible evolution trajectories of RES 69

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“…However, the integration of massive numbers of EVs is still regarded as a great challenge for electric power systems. The random charging behaviors of large-scale EVs in spatial and temporal domains may lead to a series of problems in the power grid, such as power congestion, under-voltage, and grid instability [2,3]. Considering that EVs can represent the distributed and mobile power demands in the near future, it's meaningful and valuable to study the optimal charging strategy of EVs [4,5], so as to promote the large-scale application of EVs.…”

Section: Introductionmentioning

confidence: 99%

A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles

Yang

Chen

et al. 2016

Energies

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Abstract:With the popularization of electric vehicles (EVs), the out-of-order charging behaviors of large numbers of EVs will bring new challenges to the safe and economic operation of power systems. This paper studies an optimal charging strategy for EVs. For that a typical urban zone is divided into four regions, a regional time-of-use (RTOU) electricity price model is proposed to guide EVs when and where to charge considering spatial and temporal characteristics. In light of the elastic coefficient, the user response to the RTOU electricity price is analyzed, and also a bilayer optimization charging strategy including regional-layer and node-layer models is suggested to schedule the EVs. On the one hand, the regional layer model is designed to coordinate the EVs located in different time and space. On the other hand, the node layer model is built to schedule the EVs to charge in certain nodes. According to the simulations of an IEEE 33-bus distribution network, the performance of the proposed optimal charging strategy is verified. The results demonstrate that the proposed bilayer optimization strategy can effectively decrease the charging cost of users, mitigate the peak-valley load difference and the network loss. Besides, the RTOU electricity price shows better performance than the time-of-use (TOU) electricity price.

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Impact of vehicle-to-grid on power system operation costs: The Spanish case study

Cited by 109 publications

References 11 publications

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

Benefits of flexibility from smart electrified transportation and heating in the future UK electricity system

A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles

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