Optimal management of electric vehicles in an intelligent parking lot in the presence of hydrogen storage system

Razipour, Reza; Moghaddas-Tafreshi, Seyed-Masoud; Farhadi, Payam

doi:10.1016/j.est.2019.02.001

Cited by 53 publications

(22 citation statements)

References 22 publications

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“…The obtained distribution results for both signals are exhibited in Figure 11. Based on the owner signals and the real-time ETR (see Figure 4) [16] which is provided by the DSM, the developed DSM based on the queuing theory gives the priority for the EV to charge or to be in the idle state. Figure 12 shows the demand for this case and it can be noted that an amount of demand has been shifted to the time where the ETR is low to avoid the high charging cost.…”

Section: Case 2 Results (Owner Preferences)mentioning

confidence: 99%

“…In consequence, the EVs charging process is managed to reduce congestion or to balance the load and achieve peak load shaving [8]. Various studies have been reported to explore the effects of EVs charging on electrical power systems [9][10][11][12][13][14][15][16][17]. As an example, EV charging could lead to voltage variation, increase the load, and increase power losses of electrical grids [18].…”

Section: Introductionmentioning

confidence: 99%

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Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

et al. 2021

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The paper proposes a real-time model for electric vehicles (EVs) controlled load charging. The proposed demand-side management (DSM) of EVs is implemented based on queuing analysis with a nonhomogeneous arrival rate and charging service periods dataset. An electric vehicle model is used which is based on a statistical survey to represent the uncontrolled demand of the EVs. A probability distribution for the time at which EVs are plugged and the corresponding value of the state of charges (SOCs) are considered. The preferences of individual EVs have been fully exploited through a set of instructions to fulfill the needs of the vehicles’ owners. The designated preferences include the owner setting for both, charging price preferences (OPR), and the maximum estimated parking time duration (EPTD). The quasi-static time-series (QSTS) simulation is used to simulate real-time scenarios of the 24-h simulation period. The IEEE 123 nodes radial test feeder is analyzed with different daily load curves, EV charging scenarios, and wind power penetrations. The results show the effectiveness of the proposed DSM in avoiding excessive levels of charging with/without penetration of non-dispatchable wind power generation. The proposed DSM enables the EVs to charge with low tariff rates either at excessive renewable power generation or late evening hours with available committed bulk power plants and light loading conditions.

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Section: Case 2 Results (Owner Preferences)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

et al. 2021

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“…In [32], an energy management system for optimal operation of photovoltaic, battery, and hydrogen storage systems using PSO algorithm is presented. In [33], optimal scenario‐based management was presented for a grid‐connected microgrid with various RESs such as FC, wind turbine, microturbine, and electrical storage system to improve energy management and reduce microgrid costs.…”

Section: Introductionmentioning

confidence: 99%

Interval optimization‐based scheduling of interlinked power, gas, heat, and hydrogen systems

Nasiri

Yazdankhah

Mirzaei

et al. 2021

IET Renewable Power Gen

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The combined heat and power (CHP) plant is one of the emerging technologies of gas‐fired units, which plays an important role in reducing environmental pollutants and delivering high energy efficiency. Moreover, the hydrogen energy storage (HES) system with extra power storage from wind turbine via power to hydrogen technology allows the injection of stored energy into the power grid by reverse hydrogen to power services, offsetting in this way the uncertainty of wind power. Consequently, simultaneous usage of CHP and HES units not only makes the maximum use of wind power distribution but also increases flexibility and reduces the operating costs of the entire network. Therefore, this paper proposes an interval optimization technique for managing the uncertainty of wind power generation in the integrated electricity and natural gas (NG) networks considering CHP–HES. Moreover, to enhance the flexibility of the NG network, a linearized Taylor series‐based model is proposed for modelling linepack of gas pipelines in the proposed scheduling framework that is formulated mixed‐integer linear programming and solved using the Cplex solver. The obtained results indicate that the simultaneous use of CHP–HES in the day‐ahead scheduling reduces the operating cost and increases the flexibility of the whole network.

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“…[11,12]. The implementation of EVs has risen drastically in recent years in the world [13], where there were about 1.04 million EV sales in the year 2017 [14].…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic Analysis of a Renewable Energy-Driven Electric Vehicle Charging Station with On-Site Electricity Generation from Hydrogen and Ammonia Fuel Cells

Biçer

2020

International Journal of Automotive Science and Technology

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The vast implementation of electric vehicles (EVs) greatly depends on developing sustainable and green EV charging stations. This study pro-poses to develop and assess an off-grid and renewable energy-driven EV charging station, which is hybridized with hydrogen and ammonia fuel cells. Chemical energies of hydrogen and ammonia are stored in the stor-age tanks to be used in the hydrogen and ammonia fuel cells. The de-signed hybrid system is capable of storing energy in the chemical form when there is excess production. Ammonia is stored in liquid form rather than gaseous form, which reduces the storage tank capacity considerably and decreases the losses. The designed system, which includes a wind turbine, concentrated photovoltaic (CPV) and fuel cells, can produce about 1.1 MW of power and 15.46 MWh of electricity in a single day, corresponding to about 294 number of EVs. In addition, the hybrid sys-tem can charge up to 644 EVs if the ammonia feed rate is increased to 0.1 kg/s. The fuel cells are capable of generating about 80% of the charging station. The effects of important key parameters such as wind speed, so-lar irradiance and fuel supply rates are investigated to observe the im-pacts on the overall system.

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Optimal management of electric vehicles in an intelligent parking lot in the presence of hydrogen storage system

Cited by 53 publications

References 22 publications

Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

Interval optimization‐based scheduling of interlinked power, gas, heat, and hydrogen systems

Thermodynamic Analysis of a Renewable Energy-Driven Electric Vehicle Charging Station with On-Site Electricity Generation from Hydrogen and Ammonia Fuel Cells

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