Smart Charging and Discharging of Plug-in Electric Vehicles for Peak Shaving and Valley Filling of the Grid Power

Ramadan, Hassanien; Ali, Abdelfatah; Nour, Morsy; Farkas, Csaba

doi:10.1109/mepcon.2018.8635173

Cited by 24 publications

(9 citation statements)

References 13 publications

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“…Table IV presents material properties (relative permittivity and conductivity) of all the elements within the scenario. The dielectric constant and conductivity of the foliage of the trees is variable with humidity, as shown in equations (5) and (6) with the parameter h, where a humidity level of 20% has been considered [61]: Simulation parameters have been selected as a function of convergence analysis criteria, given by the scenario volume [57]. In this way cuboids with a resolution of (6m, 6m, 2m) have been employed.…”

Section: B V2g Scenario Simulation Setupmentioning

confidence: 99%

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Aggregator to Electric Vehicle LoRaWAN Based Communication Analysis in Vehicle-to-Grid Systems in Smart Cities

et al. 2020

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Recently, there has been growing attention to the power grid management due to the increasing concerns on global warming. With the advancement in electric vehicles (EV) industry and the evolution in batteries, EVs become an important contributor to the grid with capability of bidirectional power exchange with the grid. In this context, Vehicle-to-Grid (V2G) systems enable multiple functionalities between EVs and the corresponding aggregator. Thus, reliable, long-range communication capabilities between aggregator and EVs is compulsory. In this paper, wireless channel analysis for aggregator and electrical vehicle communication using Long-Range Wide Area Network (LoRaWAN) technology in V2G is presented, in order to test a low-cost solution with large coverage and reduced power consumption profile. Wireless channel and system-level measurements have been performed in a real urban scenario between EV's charging station in Pamplona (Spain) and a vehicle in motion using LoRaWAN 868 MHz devices. Wireless channel characterization is performed by implementing a full 3D urban scenario model, including elements such as buildings, vehicles, users and urban infrastructure such as lamp posts and benches. By means of in-house developed 3D Ray Launching algorithm with hybrid simulation capabilities, estimations of received power levels, signal to noise ratio and time domain parameters have been obtained, for the complete volume of the scenario under test in dense urban conditions. V2G end to end communication has been validated by implementing an intra-vehicle Controller Area Network-BUS (CAN BUS) data gathering system connected to the vehicle LoRaWAN transceiver and subsequently, to a cloud-based web service. The results show that the accurate deterministic based radio channel analysis enables to optimize the network design of LoRaWAN networks in a vehicular environment, considering inter-vehicular and infrastructure links, enabling scalable, low cost end to end data exchange for the deployment of ancillary V2G services.

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Section: B V2g Scenario Simulation Setupmentioning

confidence: 99%

“…These features provide power grid stability insurance. Demand based analysis solutions have also been implemented to optimize and balance power grid operation [5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Aggregator to Electric Vehicle LoRaWAN Based Communication Analysis in Vehicle-to-Grid Systems in Smart Cities

et al. 2020

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“…Control can either be centralised, where one actor schedules the charging of a group of EVs, or decentralised, where EVs control their own charging in response to a price signal [22]. The proposed objectives include: flattening load [23], minimising losses [24], reducing phase imbalance [25], and maximising the consumption of renewables [26]. Most algorithms include an energy constraint, which ensures that vehicles achieve the appropriate level of charge.…”

Section: Introductionmentioning

confidence: 99%

The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems

2020

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A rapid increase in the number of electric vehicles is expected in coming years, driven by government incentives and falling battery prices. Charging these vehicles will add significant load to the electricity network, and it is important to understand the impact this will have on both the transmission and distribution level systems, and how smart charging can alleviate it. Here we analyse the effects that charging a large electric vehicle fleet would have on the power network, taking into account the spatial heterogeneity of vehicle use, electricity demand, and network structure. A conditional probability based method is used to model uncontrolled charging demand, and convex optimisation is used to model smart charging. Stochasticity is captured using Monte Carlo simulations. It is shown that for Great Britain's power system, smart charging can simultaneously eliminate the need for additional generation infrastructure required with 100% electric vehicle adoption, while also reducing the percentage of distribution networks which would require reinforcement from 28% to 9%. Discussion is included as to how far these results can be extended to other power systems.

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“…Cars, including EVs, spend the majority of their lifetime (95% on average) parked. In these periods of inactivity, EVs could charge their batteries when demand is low (valley-filling) and send power back to the grid (discharge) when demand is high (peak shaving) [15], thus becoming part of the solution and curtailing the need for costly infrastructure upgrades. V2G services may include also ancillary services (spinning reserve), active power support, and reactive power compensation [16].…”

Section: Introductionmentioning

confidence: 99%

Electromobility and Flexibility Management on a Non-Interconnected Island

et al. 2021

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The increasing penetration of electrical vehicles (EVs), on the way to decarbonizing the transportation sector, presents several challenges and opportunities for the end users, the distribution grid, and the electricity markets. Uncontrollable EV charging may increase peak demand and impact the grid stability and reliability, especially in the case of non-interconnected microgrids such as the distribution grids of small islands. On the other hand, if EVs are considered as flexible loads and distributed storage, they may offer Vehicle to Grid (V2G) services and contribute to demand-side management through smart charging and discharging. In this work, we present a study on the penetration of EVs and the flexibility they may offer for services to the grid, using a genetic algorithm for optimum valley filling and peak shaving for the case of a non-interconnected island where the electricity demand is several times higher during the summer due to the influx of tourists. Test cases have been developed for various charging/discharging strategies and mobility patterns. Their results are discussed with respect to the current generating capacity of the island as well as the future case where part of the electricity demand will have to be met by renewable energy sources, such as photovoltaic plants, in order to minimize the island’s carbon footprint. Higher EV penetration, in the range of 20–25%, is enabled through smart charging strategies and V2G services, especially for load profiles with a large difference between the peak and low demands. However, the EV penetration and available flexibility is subject to the mobility needs and limited by the population and the size of the road network of the island itself rather than the grid needs and constraints. Limitations and challenges concerning efficient V2G services on a non-interconnected microgrid are identified. The results will be used in the design of a smart charging controller linked to the microgrid’s energy management system.

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Smart Charging and Discharging of Plug-in Electric Vehicles for Peak Shaving and Valley Filling of the Grid Power

Cited by 24 publications

References 13 publications

Aggregator to Electric Vehicle LoRaWAN Based Communication Analysis in Vehicle-to-Grid Systems in Smart Cities

Aggregator to Electric Vehicle LoRaWAN Based Communication Analysis in Vehicle-to-Grid Systems in Smart Cities

The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems

Electromobility and Flexibility Management on a Non-Interconnected Island

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