A multi-objective optimization model for fast electric vehicle charging stations with wind, PV power and energy storage

Sun, Bin

doi:10.1016/j.jclepro.2020.125564

Cited by 112 publications

(40 citation statements)

References 54 publications

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“…In larger scale systems, similar studies have been conducted to take advantage of smart charging schemes to help integrate with larger volumes of renewable generation facilities even in the presence of uncertainty in generation due to intermittency (Laurischkat and Jandt, 2018;Ata et al, 2019;Mehrjerdi and Rakhshani, 2019;Langenmayr et al, 2020;Rezaeiet al, 2020). Studies have investigated these integrated renewable, storage, and EV systems both on hypothetical circuits (Rahbariet al, 2017;Morshed et al, 2018) and in real locations such as New York City (Freeman et al, 2017) and regions within China (Sun, 2021). Simply from the perspective of renewables and storage integration, these studies demonstrate a substantial theoretical cost savings and provide valuable insight into the operational aspects of such systems-both on a distributed and largerscale systems.…”

Section: Introductionmentioning

confidence: 99%

Distribution grid impacts of electric vehicles: A California case study

Jenn

Highleyman²

2022

iScience

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Section: Introductionmentioning

confidence: 99%

Distribution grid impacts of electric vehicles: A California case study

Jenn

Highleyman²

2022

iScience

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“…The main aim of this component is to perform the balance between the generation sources and loads. The mathematical model used for the BESS is shown in ( 5)-( 7) [11].…”

Section: B Battery Energy Storage Systemmentioning

confidence: 99%

“…Ultimately, the two decision variables 𝑁 𝑃𝑉 and 𝑁 𝐵𝐸𝑆𝑆 are chosen to be positive integer numbers. 2) Inequality constraints: this type of constraint includes the limits related to the BESS component which are reported from (11) to (13) and, in addition, the limit shown in (22), which states that the station can only purchase electricity from the gird.…”

Section: ) Constraintsmentioning

confidence: 99%

“…A GA was used to minimize the functions. In [11] instead, the optimization aimed to minimize both the COE and the environmental impact of an EV charging station with 10 piles and a maximum charging power for each pile of 40 kW. To solve the problem, a hybrid optimization algorithm joining the multi-objective particle swarm optimization (MOPSO) algorithm and technique for order preference by similarity to ideal solution (TOPSIS) method was used.…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimization of PV and Energy Storage Systems for Ultra-Fast Charging Stations

et al. 2022

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The installation of ultra-fast charging stations (UFCSs) is essential to push the adoption of electric vehicles (EVs). Given the high amount of power required by this charging technology, the integration of renewable energy sources (RESs) and energy storage systems (ESSs) in the design of the station represents a valuable option to decrease its impact on the grid and the environment. Therefore, this paper proposes a multi-objective optimization problem for the optimal sizing of photovoltaic (PV) system and battery ESS (BESS) in a UFCS of EVs. The proposed multi-objective function aims to minimize, on one side, the annualized cost of the station, and on the other side, the produced pollutant emissions. The decision variables are the number of PV panels and the capacity of the ESS to be installed. The optimization problem is reduced to a single-objective problem by applying the linear scalarization method. Then the equivalent singleobjective function is optimized through a genetic algorithm (GA). The proposed optimization framework is applied to a study case and the results prove that PV and ESS could lead to a significant reduction of both the annualized cost and the pollutant emissions. Finally, a sensitivity analysis is also presented to validate the effectiveness of the proposed solution.INDEX TERMS extreme fast charging, integrated charging station, bi-objective optimization, electric vehicles, fast-charging load demand.

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“…The dynamic EV charging via the real time coordination between the PV power station, the grid and the storage for enhancing the station working as a stand-alone system as long as possible and satisfying the EVs requirement has been proposed [15]. The time-of-use adjustment method is adopted also by other authors [16], by the charging/discharging priorities calculation and electricity prices. The proposed approach would ensure that the energy usage does not exceed contract capacity, giving also directions for optimizing the contract capacity.…”

Section: Introductionmentioning

confidence: 99%

A Provisional Model for the Optimal Management of a Charging Station Assisted by Photovoltaic Panels for Plug-In Electric Vehicles

Rizzo

Antonio²,

Massaro³

2021

J. Solar Eneg. Res. Updat.

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There is a strongly increasing diffusion of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV), in order to reduce air pollution in urban environment and to mitigate the global warming issues. Anyway, the achievement of this latter goal strictly depends on the source of primary energy used to generate electrical energy. In the paper, a model for the optimal design and operation of a charging station for EV and PHEV assisted by a PhotoVoltaic (PV) plant is presented. A provisional model for the estimation of the incoming insolation, based on cloudiness prevision, is integrated with a nonlinear constrained optimization algorithm, in order to satisfy the load while minimizing the recourse to electrical grid for battery storage charging. Simulations on different locations and charging loads for various size of PV plant and battery capacity are presented, and the benefits in terms of CO2 reduction discussed.

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A multi-objective optimization model for fast electric vehicle charging stations with wind, PV power and energy storage

Cited by 112 publications

References 54 publications

Distribution grid impacts of electric vehicles: A California case study

Distribution grid impacts of electric vehicles: A California case study

Multi-Objective Optimization of PV and Energy Storage Systems for Ultra-Fast Charging Stations

A Provisional Model for the Optimal Management of a Charging Station Assisted by Photovoltaic Panels for Plug-In Electric Vehicles

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