Advanced modular photovoltaic system for Plug-in Small Electric Vehicles (PsEV)

2017 ◽  
Author(s):  
Bogdan-Alexandru Onose ◽  
Mihai Aurelian Hanek ◽  
Gabriel Vataselu ◽  
Lucian Nicolae Demeter
Keyword(s):  
Electric Vehicles ◽  
Photovoltaic System

scholarly journals A Robust Optimization for Designing a Charging Station Based on Solar and Wind Energy for Electric Vehicles of a Smart Home in Small Villages

2018 ◽  
Author(s):  
Amir Ahadi ◽  
Shrutidhara Sarma ◽  
Jae Sang Moon ◽  
Jang Ho Lee
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Storage System ◽  
Real Life ◽  
Energy Systems ◽  
Energy Storage System ◽  
Photovoltaic System ◽  
Design Stage ◽  
Renewable Energy Systems ◽  
Charging Station

In recent years, integration of electric vehicles (EVs) has increased dramatically due to their lower carbon emissions and reduced fossil fuel dependency. However, charging EVs could have significant impacts on the electrical grid. One promising method for mitigating these impacts is the use of renewable energy systems. Renewable energy systems can also be useful for charging EVs where there is no local grid. This paper proposes a new strategy for designing a renewable energy charging station consisting of wind turbines, a photovoltaic system, and an energy storage system to avoid the use of diesel generators in remote communities. The objective function is considered to be the minimization of the total net present cost, including energy production, components setup, and financial viability. The proposed approach, using stochastic modeling, can also guarantee profitable operation of EVs and reasonable effects on renewable energy sizing, narrowing the gap between real-life daily operation patterns and the design stage. The proposed strategy should enhance the efficiency of conventional EV charging stations. The key point of this study is the efficient use of excess electricity. The infrastructure of the charging station is optimized and modeled.

scholarly journals Economic Impacts of the Demand Response of Electric Vehicles Considering Battery Degradation

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5771
Author(s):  
Yumiko Iwafune ◽  
Kazuhiko Ogimoto
Keyword(s):  
Power Systems ◽  
Electric Vehicles ◽  
Demand Response ◽  
Degradation Mechanism ◽  
Evaluation Model ◽  
Photovoltaic System ◽  
Driving Patterns ◽  
Battery Degradation ◽  
Reduction Of Co2 ◽  
The Impact

The increase in the number of electric vehicles (EVs) has led to increased global expectations that the application of this technology may result in the reduction of CO2 emissions through the replacement of conventional petrol vehicles and ensure the flexibility of power systems such as batteries. In this paper, we propose a residential demand response (DR) evaluation model that considers the degradation mechanism of the EV battery and examines the effective battery operation. We adopted the already-proposed NiMnCo battery degradation model to develop an EV DR evaluation model. In this model, the battery operation is optimized to minimize the electricity and degradation costs affected by ambient temperature, battery state of charge (SOC), and depth of discharge. In this study, we evaluated the impact of the relevant parameters on the economics of the DR of EV batteries for 10 all-electric detached houses with photovoltaic system assuming multiple EV driving patterns and battery (dis)charging constraints. The results indicated that the degradation costs are greatly affected by the SOC condition. If a low SOC can be managed with a DR strategy, the total cost can be reduced. This is because the sum of the reduction of purchased cost from the utility and calendar degradation costs are higher than the increase of the cycle degradation cost. In addition, an analysis was conducted considering different driving patterns. The results showed that the cost reduction was highest when a driving pattern was employed in which the mileage was low and the staying at home time was large. When degradation costs are included, the value of optimized charging and discharging operations is more apparent than when degradation costs are not considered.

scholarly journals Hybrid Microgrid Energy Management and Control Based on Metaheuristic-Driven Vector-Decoupled Algorithm Considering Intermittent Renewable Sources and Electric Vehicles Charging Lot

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3423 ◽  
Author(s):  
Tawfiq M. Aljohani ◽  
Ahmed F. Ebrahim ◽  
Osama Mohammed
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Reactive Power ◽  
Renewable Energy Sources ◽  
Synchronous Generator ◽  
Photovoltaic System ◽  
Severe Condition ◽  
Electric Vehicle Charging ◽  
Bidirectional Converter ◽  
And Control

Energy management and control of hybrid microgrids is a challenging task due to the varying nature of operation between AC and DC components which leads to voltage and frequency issues. This work utilizes a metaheuristic-based vector-decoupled algorithm to balance the control and operation of hybrid microgrids in the presence of stochastic renewable energy sources and electric vehicles charging structure. The AC and DC parts of the microgrid are coupled via a bidirectional interlinking converter, with the AC side connected to a synchronous generator and portable AC loads, while the DC side is connected to a photovoltaic system and an electric vehicle charging system. To properly ensure safe and efficient exchange of power within allowable voltage and frequency levels, the vector-decoupled control parameters of the bidirectional converter are tuned via hybridization of particle swarm optimization and artificial physics optimization. The proposed control algorithm ensures the stability of both voltage and frequency levels during the severe condition of islanding operation and high pulsed demands conditions as well as the variability of renewable source production. The proposed methodology is verified in a state-of-the-art hardware-in-the-loop testbed. The results show robustness and effectiveness of the proposed algorithm in managing the real and reactive power exchange between the AC and DC parts of the microgrid within safe and acceptable voltage and frequency levels.

scholarly journals Vehicle-Mounted Photovoltaic System Energy Management in Intelligent Transportation Systems: A Maximum Power Point Tracking Control

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jingao Wang ◽  
Qifei Liu ◽  
Silan Jing
Keyword(s):  
Output Power ◽  
Electric Vehicles ◽  
Intelligent Transportation Systems ◽  
Tracking Control ◽  
Transportation Systems ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point

Electric vehicles have become the main contributor in terms of reducing fuel consumption and CO2 emission. Although the government is vigorously promoting the use of electric vehicles worldwide, the range anxiety still impedes the rapid development of electric vehicles, especially when air-conditioning also adds battery power consumption and aggravates the range anxiety. To this end, this paper proposes an improved vehicle-mounted photovoltaic system energy management in intelligent transportation systems, which is a maximum power point tracking control system. Meanwhile, since the power of solar panels is usually relatively small and the power changes at any time, low power density and poor controllability are difficult to avoid. In order to solve this problem, this paper offers a tracking control method to improve the output efficiency of solar panels. For improving photovoltaic conversion efficiency and maximizing output power, traditional photovoltaic power panels are often dominated by a centralized maximum power point tracing control, which is named MPPT. Although the cost under this case is lower, the output power of all photovoltaic panels cannot be maximized under the condition of uneven illumination or local mismatch. To improve the situation, a micro-scale inverter is proposed to provide MPPT control of photovoltaic modules, which can effectively improve the output power of each photovoltaic panel. Moreover, our MPPT algorithm is applicable to cloud shadow, building shadow, and shade, and it is more suitable for the car roof. Firstly, the Diode 5-parameter model is used to deduce the I-U equation of the photovoltaic module considering shadow shading, and then the real-time 5 parameter equation is formed by using the measured data group and selected. The reasonable initial value is used to iteratively solve the real-time value of 5 parameters, which is further to judge the masking situation. The maximum power point (MPP) is solved directly by the mathematical method based on the mathematical model of I-U relation mathematics, and the DC-DC circuit is used to adjust the running point to MPP. Unlike the traditional MPPT method, the method in this paper is based on the physical model of solar cells, and MPP tracking is based on mathematical methods. Based on this, it does not need to cause multiple interference to the circuit, and the tracking efficiency is high. Finally, the relative experimental results are provided to verify the performance of the proposed method.

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