Finite Action-Set Learning Automata for Economic Dispatch Considering Electric Vehicles and Renewable Energy Sources

Zhu, Junpeng; Jiang, Ping; Gu, Wei; Sheng, Wanxing; Meng, Xiao‐Li; Gao, Jun

doi:10.3390/en7074629

Cited by 5 publications

(4 citation statements)

References 33 publications

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“…Figure 10 compares the interior noise levels of an electric vehicle (Liiondrive) and a combustion engine vehicle (Fiat 500) at different constant speeds with the noise produced by the vehicle's tyres rolling. It was found that the two cars' interior noise levels were relatively similar at constant speeds, only 1 or 2 dB(A) higher than the rolling noise [21].…”

Section: Comparative Noise Analysismentioning

confidence: 88%

“…Figure 6 illustrates this point by showing the total noise emissions from the hybrid vehicle's engine and tyres. At 20 km/h, the reduction is more than 3 dB, drops to 1 dB at 50 km/h, and quickly to zero at 50 km/h and above, when tyre noise becomes the dominant factor and the difference in noise emissions between hybrid and non-hybrid cars almost vanishes [19][20][21].…”

Section: Comparative Noise Analysismentioning

confidence: 98%

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Stochastic Optimization-Based Comparative Study of New Energy Vehicles’ Noise Characteristics

Ye,

2024

J. Comb. Math. Comb. Comput.

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The gearbox gearbox transmission system, which is the foundation of a new energy vehicle, is responsible for the crucial duty of power transmission. In reality, the reducer gearbox system is the primary source of noise inside cars because of the design of the system, mistakes made during manufacturing and assembly, and gear engagement impulses. The research target is the second-stage retarder gearbox system of a new energy vehicle. A three-dimensional model of the retarder gearbox system is created using the Romax software.Static and dynamic analyses were carried out in Romax software based on the five typical conditions of start, acceleration, equal speed, deceleration, and stop in order to derive performance data such as maximum contact and bending stresses of the gears, single-position length load distribution, gearbox error, etc. In the NVH analysis, the system’s vibration acceleration was ascertained using the findings of the gearbox error analysis. In order to provide comparative data for vibration and noise reduction of gear modification, the comparative study analyses the data output results under various working conditions and analyses the relationship between gear engagement force and gear vibration.

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Section: Comparative Noise Analysismentioning

confidence: 88%

Section: Comparative Noise Analysismentioning

confidence: 98%

Stochastic Optimization-Based Comparative Study of New Energy Vehicles’ Noise Characteristics

Ye,

2024

J. Comb. Math. Comb. Comput.

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“…Nunes et al [269] explore the possible complementarities between wind and solar power with EVs charging, the model used is EnergyPLAN. Zhu et al [270] present an economic dispatch model (high-dimensional, non-linear, and stochastic problem and its solution require powerful methods) that considers EV charging, battery stations, and wind farms.…”

Section: Evmentioning

confidence: 99%

A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids

Hernández-Callejo

2019

Energies

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New technological advances based on software, hardware and new materials must be implemented in smart grids. In addition, these advanced electrical grids must incorporate elements of artificial intelligence. Advances in software development must be complemented with the development of new hardware (power electronics and active distribution among others). The aforementioned must rely on the development of new materials and sensors, which should be integrated into the smart grid. Therefore, the four areas of research based on the technologies are: Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering. The review presents the algorithms, materials, devices and others paradigms applied to smart grids, classifying the works according to the four areas of research. This review has focused on the four fundamental pillars of smart grids, on the one hand, the need for more efficient operation and control, followed by advanced maintenance management, to continue planning and designing the new grids, and for conclude with the advanced measurement. As you will see in the article, new devices, new techniques, and future scenarios will make possible the transition from the current grid to the future smart grid.

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“…Statistical information on the mobility patterns and charging behaviors of EVs is usually derived from census data, based on either conventional ICE vehicles or EVs [29,30]. In day-ahead optimal scheduling, optimal schedules of the power flows among EVs and the power grid are determined over a short-term time horizon, of usually 24 h. The expected power demand profiles of EVs are usually computed by applying statistical methods, which take into account probability distributions of the time of arrival and departure of EVs, and the related State Of Charge (SOC) of on-board batteries [31][32][33]. The aim of intraday optimal scheduling is to determine optimal operation plans over short-time periods, of usually few hours.…”

Section: The Smart Charging Conceptmentioning

confidence: 99%

On the Mobile Communication Requirements for the Demand-Side Management of Electric Vehicles

et al. 2018

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The rising concerns about global warming and environmental pollution are increasingly pushing towards the replacement of road vehicles powered by Internal Combustion Engines (ICEs). Electric Vehicles (EVs) are generally considered the best candidates for this transition, however, existing power grids and EV management systems are not yet ready for a large penetration of EVs, and the current opinion of the scientific community is that further research must be done in this field. The so-called Vehicle-to-Grid (V2G) concept plays a relevant role in this scenario by providing the communication capabilities required by advanced control and Demand-Side Management (DSM) strategies. Following this research trend, in this paper the communication requirements for the DSM of EVs in urban environments are discussed, by focusing on the mobile communication among EVs and smart grids. A specific system architecture for the DSM of EVs moving inside urban areas is proposed and discussed in terms of the required data throughput. In addition, the use of a Low-Power Wide-Area Network (LPWAN) solution-the Long-Range Wide Area Network (LoRaWAN) technology-is proposed as a possible alternative to cellular-like solutions, by testing an experimental communication infrastructure in a real environment. The results show that the proposed LPWAN technology is capable to handle an adequate amount of information for the considered application, and that one LoRa base station is able to serve up to 438 EVs per cell, and 1408 EV charging points.Energies 2018, 11, 1220 2 of 27 in the last 40 years, rising from 2.8 GtCO 2 eq of 1970 to 7 GtCO 2 eq in 2010. It is worth noting that the main contribution of this increase is due to road vehicles, whose GHG emissions rose in the same period by almost 200% [2]. A further issue of concern is the contribution of road vehicles to the air pollution in urban centers. Recent studies demonstrated that conventional ICEs are responsible for the emission of the 73% of total urban air pollutants, and also revealed that the growth in chronic health problems in urban areas can be directly related to transportation systems [3]. As a consequence, several restrictions on ICE vehicles have been proposed in European cities, such as the progressive diesel ban in Paris (entered into force since 2015), and the Ultra-Low Emission Zone (ULEZ) that will come into force in London starting from April 2019 [4].Electric Vehicles (EVs), in particular Battery EVs (BEVs), are generally considered the best candidates for the replacement of conventional ICE vehicles, thanks to their independence from the primary energy source, and to the total absence of direct GHG and pollutant emissions. Recent studies demonstrated that BEVs are the less carbon-intensive option if compared to other solutions, such as Plug-in Hybrid EVs (PHEVs) and Hybrid EVs (HEVs) [5], and that the large penetration of EVs could help to significantly reduce indirect GHG emissions and air pollution in urban areas [6,7].Whilst high investment costs and low energy densit...

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Finite Action-Set Learning Automata for Economic Dispatch Considering Electric Vehicles and Renewable Energy Sources

Cited by 5 publications

References 33 publications

Stochastic Optimization-Based Comparative Study of New Energy Vehicles’ Noise Characteristics

Stochastic Optimization-Based Comparative Study of New Energy Vehicles’ Noise Characteristics

A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids

On the Mobile Communication Requirements for the Demand-Side Management of Electric Vehicles

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