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WIREs Energy Environ.
Impact Factor: 3.297

The role of electric vehicles in smart grids

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The electrification of transportation is seen as one of the solutions to challenges such as global warming, sustainability, and geopolitical concerns on the availability of oil. From the perspective of power systems, an introduction of plug‐in electric vehicles presents many challenges but also opportunities to the operation and planning of power systems. On the one hand, if vehicles are considered regular loads without flexibility, uncontrolled charging can lead to problems at different network levels endangering secure operation of installed assets. However, with direct or indirect control approaches the charging of vehicles can be managed in a desirable way, e.g., shifted to low‐load hours. Furthermore, vehicles can be used as distributed storage resources to contribute to ancillary services for the system, such as frequency regulation and peak‐shaving power or help integrate fluctuating renewable resources. All these modes of operation need appropriate regulatory frameworks and market design if the flexibility of the vehicles is to be capitalized. In most of the proposed approaches, a so‐called aggregator could be in charge of directly or indirectly controlling the charging of vehicles and serve as an interface with other entities such as the transmission system operator or energy service providers. However, fully decentralized schemes without an aggregator are also conceivable, for instance, to provide primary frequency control. Communication also plays a key role, as in most of the control schemes a significant amount of information needs to be transmitted between vehicles and control entities. The management of electric vehicles as distributed resources fits well in the paradigm of smart grids, where an advanced use of communication technologies and metering infrastructure, increased controllability and load flexibility, and a larger share of fluctuating and distributed resources are foreseen. This article is categorized under: Energy Infrastructure > Economics and Policy Energy Systems Economics > Systems and Infrastructure Energy Systems Analysis > Systems and Infrastructure
Typical charge curve of a lithium‐ion battery.
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Aggregator integration framework for future power system operation.
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Plug‐in electric vehicle (PEVs) and controllable loads are used to provide secondary frequency control by following a load frequency control (LFC) signal. The cluster of PEVs and controllable loads is assumed to provide maximally 40 MW of up and down control. (a) Shows the contribution of PEVs, controllable loads and the CHP to provide the demanded LFC. (b) Shows explicitly the control setpoint sent to the actuators and (c) shows the SOC of the different storages.
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Plug‐in electric vehicle demand in the 11/22 kV distribution network when providing vehicle‐to‐grid (V2G). The load peaks are introduced by the V2G service.
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Plug‐in electric vehicle demand in the 11/22 kV distribution network. The load plateaus plateaus are introduced by the controlled charging approach and indicate stations which face congestion.
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Vehicle‐to‐grid service for balancing a renewable energy source prediction infeed error. (a) The share of power, which is either consumed or fed into the network to balance the error. (b) The power setpoints calculated by the model predictive control scheme for the actuators available in the system. (c) The SOC of the plug‐in electric vehicle aggregated storage and a CHP heat storage.
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Load profiles resulting from different smart‐charging schemes.
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Fraction of vehicles driving or parked on a typical weekday in Switzerland.
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Transformer loading at the 150 kV network level. The impacts of uncontrolled plug‐in electric vehicle charging are noticeable but do not introduce congestions at this level for the given electric mobility scenario.
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Line loading at the 150 kV network level. The impacts of uncontrolled plug‐in electric vehicle charging are noticeable but do not introduce congestions at this level for the given electric mobility scenario.
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Loading of transformers and distribution lines on the 11/22 kV network level at 10.00 in the morning. The color code illustrates overloaded assets in dark red, whereas assets which are only partly or fully loaded are illustrated according to the colorbar.
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Voltage levels in a low voltage network in a metropolitan area at peak load. The PHEV load in a 100% electric mobility scenario causes the voltage to drop below the minimum voltage level of 95%, indicated by the red, horizontal line.
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Loading of 400 V distribution lines in a low voltage network in a metropolitan area. The plug‐in electric vehicle load in a 100% electric mobility scenario heavily overloads the several distribution lines.
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Loading of two transformers feeding a low voltage network in a metropolitan area. The plug‐in electric vehicle load in a 100% electric mobility scenario overloads the transformers during the day. No N‐1 security is considered here.
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Decentralized control architecture for electric vehicles.
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