Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services

Venegas, Felipe Gonzalez; Petit, Marc; Pérez, Yannick

doi:10.1016/j.rser.2021.111060

Cited by 101 publications

(77 citation statements)

References 82 publications

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“…The value of V2G LFC may become clearer in future studies when the analysis considers the availability of competing resources such as ESS and heat pumps. However, individual EV owners' decision-making in controlling their EVs should be kept in mind: incentives from other services may affect the availability of V2G, such as vehicle-to-home [33] and other behind-the-meter services or services for local network [3].…”

Section: Discussionmentioning

confidence: 99%

“…This technology is known as vehicleto-grid (V2G) technology [2]. Aggregated EV fleets are expected to provide energy and ancillary services for the system-wide (transmission level) or local network (low-voltage and medium-voltage distribution grids) level by taking advantage of their high responsiveness [3]. However, stakeholders need to better understand and appreciate the benefits of V2G when promoting and supporting its adoption.…”

Section: Introductionmentioning

confidence: 99%

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Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

2021

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Regulating the frequencies of power grids by controlling electric vehicle charging and discharging, known as vehicle-to-grid (V2G) ancillary services, is a promising and profitable means of providing flexibility that integrates variable renewable energy (VRE) into traditional power systems. However, the ancillary services market is a niche, and the scale, saturation, and time-dependency are unclear when assuming future changes in the power system structure. We studied the marginal value of V2G ancillary services as a balancing capacity of the power system operation on the load-frequency control (LFC) timescale and evaluated the reasonable maximum capacity of the LFC provided by V2G. As a case study, we assumed that the Japanese power system would be used under various VRE penetration scenarios and considered the limited availability time of V2G, based on the daily commuter cycle. The power system operation was modeled by considering pumped storage, interconnection lines, and thermal power–partial load operations. The results show that the marginal value of V2G was greater during the daytime than overnight, and the maximum cost saving (USD 705.6/EV/year) occurred during the daytime under the high-VRE scenario. Improving the value and size of V2G ancillary services required coordination with energy storage and excess VRE generation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

2021

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“…In general, one would probably agree with the fact that the optimal management of demand-side response appears to be crucial for smart grids that encompass the electrical equipment in combination with such novel elements as electric vehicles (EV) and the use of smart grid technology (Eseye et al, 2019;Wu et al, 2019;Venegas et al, 2021). New technologies will enable customers to move from event-based demand response, where the supplier demands load relief, to the 24/7-based demand response, where customers request peak load and see an incentive to control the load at all times.…”

Section: Literature Reviewmentioning

confidence: 92%

5G Wireless Networks in the Future Renewable Energy Systems

et al. 2021

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This paper focuses on the strategies that employ the fifth generation (5G) wireless networks in the optimal management of demand-side response in the future energy systems with the high penetration of renewable energy sources (RES). It also provides a comparison between advantages and challenges of 5G networks in demand-response renewable energy grids. Large-scale renewable energy integration always leads to a mismatch between generation and load demand in the short run due to the intermittency. It is often envisioned that 5G wireless networks that were recently launched and would most likely be fully deployed worldwide by 2035 would bring many technological and economic benefits for a plethora of the future high-renewables grids featuring electric transport and heating as well as prosumers generating renewable energy and trading it back to the grid (for example, in the vehicle-to-grid (V2G) framework) and among themselves using peer-to-peer (P2P) networks. Our paper offers a comprehensive analysis of 5G architecture with the perspectives of optimal management of demand-side response in the smart grids of the future. We show that the effective deployment of faster and more reliable wireless networks would allow faster data transfers and processing, including peer-to-peer (P2P) energy trade market, Internet of Vehicles (IoV) market, or faster smart metering, and thence open the path for the full-fledged Internet of Energy (IoE). Moreover, we show that 5G wireless networks might become in the future sustainable energy systems paving the road to even more advanced technologies and the new generations of networks. In addition, we demonstrate that for the effective management of energy demand-side response with a high share of renewables, certain forms of governments funding and incentives might be needed. These are required to strengthen the support of RES and helping to shift to the green economy.

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“…For each charging event, the plug-in time, the plug-out time and the amount of energy charged is logged. This dataset provides the basis for many other publications [8,9] in this area, for instance, in the work of Khan et al [8] to predict user behavior, or in the paper of Venegas et al [9] to analyze the grid integration of renewable energies in more detail. The ElaadNL data platform contains aggregated data from public, private and workplace charging stations distributed over the entire Netherlands [10][11][12].…”

Section: Literature Review 21 Electric Vehicle Charging Data Analysismentioning

confidence: 99%

Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data

Barthel

Schlund

Landes³

et al. 2021

Energies

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A successful transformation of the energy and transportation sector is one of the main targets for our society today. Battery electric vehicles can play a key role in future renewable-based energy supply systems because of their ability to store electrical power. Additionally, they provide significant charging flexibility due to the long parking durations. In this paper, we provide insights into the temporal and power-specific flexibility behavior of three different vehicle fleets. These fleets are pool vehicles of office employees, a public authority, and a logistics company. Several parameters, such as the average charging power per charging event or the average plug-in duration per charging event, are discussed. Additionally, we investigate different charging rates and their impact on the temporal flexibility of the charging events. The data analysis shows that the logistics site has the most homogeneous charging profile as well as high charging flexibility, in contrast to the office and public agency site. The results are of significant importance for future applications in the field of smart charging and ancillary services provision.

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Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services

Cited by 101 publications

References 82 publications

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

Marginal Value of Vehicle-to-Grid Ancillary Service in a Power System with Variable Renewable Energy Penetration and Grid Side Flexibility

5G Wireless Networks in the Future Renewable Energy Systems

Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data

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