scholarly journals Application Hybrid Eco Campus Vehicle based on Solar Cell

2018 ◽  
Author(s):  
Solly Aryza

In Indonesia, Smart Hybrid Vehicle is an Important issue for vehicle in college. This paper presents a charging process for electric scooter in parking lot areas University Pembangunan PancaBudi. It allows us toevaluate a broad range of Plug-in Smart Hybrid Electric Vehicles (PSHEVs) and Plug-in Electric Vehicles(PEVs) charging scenarios and stochastic models of the power that is the demand by PEVs in the parkinggarage, and the output power of the PV panel are present. To impact of the PSHEVs’ charging on the utilitygrid, a fuzzy logic power-flow controller was designed. The charging with solar cell helps to reduce emissionsfrom the power grid but increases the cost of charging. Moreover, it offers more flexibility to prepare for theemergence of new technologies (e.g., Vehicle-to-Grid, Vehicle-to-Building, and Smart Charging), which willbecome a reality shortly. The system structure and the developed PHEV smart charging algorithm are described.Moreover, a comparison between the impact of the charging process of the PHEVs on the grid with and withoutthe developed smart charging technique is presented and analyzed.

Proceedings ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 2
Author(s):  
Elisavet Koutsi ◽  
Sotirios Deligiannis ◽  
Georgia Athanasiadou ◽  
Dimitra Zarbouti ◽  
George Tsoulos

During the last few decades, electric vehicles (EVs) have emerged as a promising sustainable alternative to traditional fuel cars. The work presented here is carried out in the context of the Horizon 2020 project MERLON and targets the impact of EVs on electrical grid load profiles, while considering both grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation modes. Three different charging policies are considered: the uncontrolled charging, which acts as a reference scenario, and two strategies that fall under the umbrella of individual charging policies based on price incentive strategies. Electricity prices along with the EV user preferences are taken into account for both charging (G2V) and discharging (V2G) operations, allowing for more realistic scenarios to be considered.


Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4717 ◽  
Author(s):  
Sylvester Johansson ◽  
Jonas Persson ◽  
Stavros Lazarou ◽  
Andreas Theocharis

Social considerations for a sustainable future lead to market demands for electromobility. Hence, electrical power distribution operators are concerned about the real ongoing problem of the electrification of the transport sector. In this regard, the paper aims to investigate the large-scale integration of electric vehicles in a Swedish distribution network. To this end, the integration pattern is taken into consideration as appears in the literature for other countries and applies to the Swedish culture. Moreover, different charging power levels including smart charging techniques are examined for several percentages of electric vehicles penetration. Industrial simulation tools proven for their accuracy are used for the study. The results indicate that the grid can manage about 50% electric vehicles penetration at its current capacity. This percentage decreases when higher charging power levels apply, while the transformers appear overloaded in many cases. The investigation of alternatives to increase the grid’s capabilities reveal that smart techniques are comparable to the conventional re-dimension of the grid. At present, the increased integration of electric vehicles is manageable by implementing a combination of smart gird and upgrade investments in comparison to technically expensive alternatives based on grid digitalization and algorithms that need to be further confirmed for their reliability for power sharing and energy management.


Author(s):  
Yue Wang ◽  
David Infield ◽  
Simon Gill

This paper assumes a smart grid framework where the driving patterns for electric vehicles are known, time variations in electricity prices are communicated to householders, and data on voltage variation throughout the distribution system are available. Based on this information, an aggregator with access to this data can be employed to minimise electric vehicles charging costs to the owner whilst maintaining acceptable distribution system voltages. In this study, electric vehicle charging is assumed to take place only in the home. A single-phase Low Voltage (LV) distribution network is investigated where the local electric vehicles penetration level is assumed to be 100%. Electric vehicle use patterns have been extracted from the UK Time of Use Survey data with a 10-min resolution and the domestic base load is generated from an existing public domain model. Apart from the so-called real time price signal, which is derived from the electricity system wholesale price, the cost of battery degradation is also considered in the optimal scheduling of electric vehicles charging. A simple and effective heuristic method is proposed to minimise the electric vehicles’ charging cost whilst satisfying the requirement of state of charge for the electric vehicles’ battery. A simulation in OpenDSS over a period of 24 h has been implemented, taking care of the network constraints for voltage level at the customer connection points. The optimisation results are compared with those obtained using dynamic optimal power flow.


2022 ◽  
pp. 1192-1211
Author(s):  
Cosmin Darab

Electric vehicles were proposed as a good solution to solving energy crisis and environmental problems caused by the traditional internal combustion engine vehicles. In the last years due to the rapid development of the electric vehicles, the problem of power grid integration was addressed. In order to not put additional pressure onto the power grid several new technologies were developed. This chapter presents the smart grid technology, vehicle-to-grid concept, and electric vehicles grid integration. These technologies made possible the integration of electric vehicles without any major changes in the power grid. Moreover, electric vehicles integration brought new benefits to the power grid like better integration of renewable energy.


2020 ◽  
Vol 10 (18) ◽  
pp. 6500
Author(s):  
Dian Wang ◽  
Manuela Sechilariu ◽  
Fabrice Locment

The increase in the number of electric vehicles (EVs) has led to an increase in power demand from the public grid; hence, a photovoltaic based charging station for an electric vehicle (EV) can participate to solve some peak power problems. On the other hand, vehicle-to-grid technology is designed and applied to provide ancillary services to the grid during the peak periods, considering the duality of EV battery “load-source”. In this paper, a dynamic searching peak and valley algorithm, based on energy management, is proposed for an EV charging station to mitigate the impact on the public grid, while reducing the energy cost of the public grid. The proposed searching peak and valley algorithm can determine the optimal charging/discharging start time of EV in consideration of the initial state of charge, charging modes, arrival time, departure time, and the peak periods. Simulation results demonstrate the proposed searching peak and valley algorithm’s effectiveness, which can guarantee the balance of the public grid, whilst meanwhile satisfying the charging demand of EV users, and most importantly, reduce the public grid energy cost.


2019 ◽  
Vol 10 (4) ◽  
pp. 61
Author(s):  
Ahmed Aljanad ◽  
Azah Mohamed ◽  
Tamer Khatib ◽  
Afida Ayob ◽  
Hussain Shareef

Considering, the high penetration of plug-in electric vehicles (PHEVs), the charging and discharging of PHEVs may lead to technical problems on electricity distribution networks. Therefore, the management of PHEV charging and discharging needs to be addressed to coordinate the time of PHEVs so as to be charged or discharged. This paper presents a management control method called the charging and discharging control algorithm (CDCA) to determine when and which of the PHEVs can be activated to consume power from the grid or supply power back to grid through the vehicle-to-grid technology. The proposed control algorithm considers fast charging scenario and photovoltaic generation during peak load to mitigate the impact of the vehicles. One of the important parameters considered in the CDCA is the PHEV battery state of charge (SOC). To predict the PHEV battery SOC, a particle swarm optimization-based artificial neural network is developed. Results show that the proposed CDCA gives better performance as compared to the uncoordinated charging method of vehicles in terms of maintaining the bus voltage profile during fast charging.


Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2383
Author(s):  
Felix Guthoff ◽  
Nikolai Klempp ◽  
Kai Hufendiek

Electrification offers an opportunity to decarbonize the transport sector, but it might also increase the need for flexibility options in the energy system, as the uncoordinated charging process of battery electric vehicles (BEV) can lead to a demand with high simultaneity. However, coordinating BEV charging by means of smart charging control can also offer substantial flexibility potential. This potential is limited by restrictions resulting from individual mobility behavior and preferences. It cannot be assumed that storage capacity will be available at times when the impact of additional flexibility potential is highest from a systemic point of view. Hence, it is important to determine the flexibility available per vehicle in high temporal (and spatial) resolution. Therefore, in this paper a Markov-Chain Monte Carlo simulation is carried out based on a vast empirical data set to quantify mobility profiles as accurately as possible and to subsequently derive charging load profiles. An hourly flexibility potential is derived and integrated as load shift potential into a linear optimization model for the simultaneous cost-optimal calculation of the dispatch of technology options and long-term capacity planning to meet a given electricity demand. It is shown that the costs induced by BEV charging are largely determined by the profile costs from the combination of the profiles of charging load and renewable generation, and not only by the additional energy and capacity demand. If the charging process can be flexibly controlled, the storage requirement can be reduced and generation from renewable energies can be better integrated.


2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jingang Han ◽  
Xiong Zhou ◽  
Song Lu ◽  
Pinxuan Zhao

The smart grid and electric vehicles (EVs) are widely used all over the world. As the key role, the Vehicle-to-Grid (V2G) has been attracting increasing attention. The bidirectional grid-connected AC/DC converter is one of the indispensable parts in the V2G system, which can realize bidirectional power flow and meet the power quality requirements for grid. A three-phase bidirectional grid-connected AC/DC converter is presented in this paper for V2G systems. It can be used to achieve the bidirectional power flow between EVs and grid, supply reactive power compensation, and smooth the power grid fluctuation. Firstly, the configuration of V2G systems is introduced, and the mathematical model of the AC/DC converter is built. Then, for bidirectional AC/DC converters, the grid voltage feedforward decoupling scheme is applied, and the analysis of PI control strategy is proposed and the controller is designed. The system simulation model is established based on MATLAB/Simulink, and the experiment platform of the bidirectional grid-connected converter for V2G is designed in lab. The simulation and experiment results are shown, and the results evaluate the effectiveness of the model and the performance of the applied control strategy.


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