A novel approach for multi-objective optimal scheduling of large-scale EV fleets in a smart distribution grid considering realistic and stochastic modeling framework

Einaddin, Alireza Hatefi; Yazdankhah, Ahmad Sadeghi

doi:10.1016/j.ijepes.2019.105617

Cited by 45 publications

(20 citation statements)

References 46 publications

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“…Due to the advantages and disadvantages mentioned above, many studies have used a centralized control method to optimize the charging and discharging of EVs in the power grid. In [44], the centralized control method is used to optimize the charging and discharging of EVs in the distribution network for peak-shaving, minimizing losses, and maximizing the profit of the EV's owner. Additionally, to reduce the dimensions of the problem and apply the proposed method to a large-scale EV fleet, the power exchanged by each bus with the network instead of the power exchanged by each EV with the network is considered as a decision variable.…”

Section: Centralized Control Structurementioning

confidence: 99%

“…In this section, algorithms that minimize network losses by managing the active power of EVs are investigated. The objective function related to power loss minimization is given in (7) [44]:…”

Section: Minimization Of Losses By Managing the Active Powermentioning

confidence: 99%

“…Active power management of EVs has been studied for minimizing network losses [44,46,47,50,83,87,91,97,98,[102][103][104][105][106]. In [50], the battery charge profile of EVs is assumed to be rectangular, and a decentralized charging algorithm is proposed.…”

Section: Minimization Of Losses By Managing the Active Powermentioning

confidence: 99%

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Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies

et al. 2022

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As a result of fossil fuel prices and the associated environmental issues, electric vehicles (EVs) have become a substitute for fossil-fueled vehicles. Their use is expected to grow significantly in a short period of time. However, the widespread use of EVs and their large-scale integration into the power system will pose numerous operational and technical challenges. To avoid these issues, it is essential to manage the charging and discharging of EVs. EVs may also be considered sources of dispersed energy storage and used to increase the network’s operation and efficiency with reasonable charge and discharge management. This paper aims to provide a comprehensive and updated review of control structures of EVs in charging stations, objectives of EV management in power systems, and optimization methodologies for charge and discharge management of EVs in energy systems. The goals that can be accomplished with efficient charge and discharge management of EVs are divided into three groups in this paper (network activity, economic, and environmental goals) and analyzed in detail. Additionally, the biggest obstacles that EVs face when participating in vehicle-to-grid (V2G) applications are examined in this paper.

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Section: Centralized Control Structurementioning

confidence: 99%

Section: Minimization Of Losses By Managing the Active Powermentioning

confidence: 99%

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Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies

et al. 2022

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“…According to the experts' risk evaluation scores, the state vector was constructed, and the constant weight was modified in accordance with Equation (10). The value of the equalization coefficient was set to 0.5.…”

Section: Derivation Of Variable Weightmentioning

confidence: 99%

“…Thus, the research on new energy vehicles mainly focuses on technology [6][7][8], operation mode [9][10][11][12], environmental protection assessment [13][14][15], market demand analysis [16,17], and so on. For example, Perera et al proposed a charging infrastructure planning model in the urban environment.…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China

Yan

Zhang

et al. 2020

Sustainability

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In order to protect the environment and reduce energy consumption, new energy vehicles have begun to be vigorously promoted in various countries. In recent years, the rise of intelligent technology has had a great impact on the supply chain of new energy vehicles, which, coupled with the complexity of the supply chain itself, puts it at great risk. Therefore, it is quite indispensable to evaluate the risk of the new energy vehicle supply chain. This paper assesses the risks faced by China’s new energy vehicle supply chain in this period of technological transformation. First of all, this paper establishes an evaluation criteria system of 16 sub-criterion related to three dimensions: the market risk, operational risk, and the environmental risk. Then, variable weight theory is proposed to modify the constant weight obtained by the fuzzy analytic hierarchy process (FAHP). Finally, a risk assessment of China’s new energy vehicle supply chain is carried out by combining the variable weight and the cloud model. This method can effectively explain the randomness of matters, and avoid the influence of value abnormality on the criteria system. The results show that China’s new energy vehicle supply chain is at a high level. Through the identification of risk factors, mainly referring to the low clustering risk, technical level risk and information transparency risk, this paper can provide a risk prevention reference for corresponding enterprises.

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Bi‐level scheduling of large‐scale electric vehicles based on the generation side and the distribution side

Chang

Niu

Jia

2021

Int Trans Electr Energ Syst

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With the intensification of energy shortages and climate warming, how to achieve the coordinated dispatch of electric vehicles (EVs) and high-proportion renewable energy systems (RESs) in the power system has been attracting more and more attentions. From the generation side and the distribution side, this work investigates the problem of large-scale EVs charging and discharging scheduling via the collaborative optimization among thermal power plants, wind and solar power, and EVs. To this end, an energy scheduling system (ESS) including power transmission and distribution is established, based on which a bi-level scheduling strategy is proposed. The upper level coordinately optimizes EVs, thermal power units, wind and solar power generation, and grid base loads to achieve the minimization of power supply costs. By introducing the node loss sensitivity (NLS) and node electricity price (NEP), the lower level allocates EVs to charging nodes to attain the minimization of the grid loss cost and charging cost. Finally, via the IEEE33-node standard power grid and the ESS model, it is verified that the proposed bi-level scheduling strategy can reduce the overall cost (node loss and charging cost) by 28.5%, and the wind curtailment rate and photovoltaic curtailment rate are 0.0% and 0.4%, respectively, making full use of renewable energy and adapting to its uncertainty.

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A novel approach for multi-objective optimal scheduling of large-scale EV fleets in a smart distribution grid considering realistic and stochastic modeling framework

Cited by 45 publications

References 46 publications

Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies

Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies

Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China

Bi‐level scheduling of large‐scale electric vehicles based on the generation side and the distribution side

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