Routing Renewable Energy Using Electric Vehicles in Mobile Electrical Grid

2013 ◽  
Author(s):  
Ping Yi ◽  
Ting Zhu ◽  
Guangyu Lin ◽  
Qingquan Zhang
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Electrical Grid

Revolution of Energy Storage System in Smart Grids

2016 ◽  
pp. 181-206
Author(s):  
Jianhui Wong ◽  
Yun Seng Lim
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Smart Grid ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Sources ◽  
Electrical Grid ◽  
Technical Issues

Electrical grid is no longer featured in a conventional way nowadays. Today, the growing of new technologies, primarily the distributed renewable energy sources and electric vehicles, has been integrated with the distribution networks causing several technical issues. As a result, the penetration of the renewable energy sources can be limited by the utility companies. Smart grid has been emerged as one of the solutions to the technical issues, hence allowing the usage of renewable and improving the energy efficiency of the electrical grid. The challenge is to develop an intelligent management system to maintain the balance between the generation and demand. This task can be performed by using energy storage system. As part of the smart grid, the deployment of energy storage system plays a critical role in stabilizing the voltage and frequency of the networks with renewable energy sources and electric vehicles. This book chapter illustrates the revolution and the roles of energy storage for improving the network performance.

Revolution of Energy Storage System in Smart Grids

2017 ◽  
pp. 1669-1694
Author(s):  
Jianhui Wong ◽  
Yun Seng Lim
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Smart Grid ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Sources ◽  
Electrical Grid ◽  
Technical Issues

Electrical grid is no longer featured in a conventional way nowadays. Today, the growing of new technologies, primarily the distributed renewable energy sources and electric vehicles, has been integrated with the distribution networks causing several technical issues. As a result, the penetration of the renewable energy sources can be limited by the utility companies. Smart grid has been emerged as one of the solutions to the technical issues, hence allowing the usage of renewable and improving the energy efficiency of the electrical grid. The challenge is to develop an intelligent management system to maintain the balance between the generation and demand. This task can be performed by using energy storage system. As part of the smart grid, the deployment of energy storage system plays a critical role in stabilizing the voltage and frequency of the networks with renewable energy sources and electric vehicles. This book chapter illustrates the revolution and the roles of energy storage for improving the network performance.

scholarly journals Critical Analysis of the Application of Fuzzy Logic in Renewable Energy Systems

TEM Journal ◽  
2021 ◽  
pp. 1610-1615
Author(s):  
Mohammed Y. Ghadi ◽  
Fadi Sakka ◽  
Ahmed Al Nakeeb ◽  
Tamara al Shloul
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Fuzzy Controller ◽  
Storage System ◽  
Energy Storage System ◽  
Vital Role ◽  
Power Requirement ◽  
Power Generators ◽  
Vehicle To Grid ◽  
Electrical Grid

This study describes the effectiveness of applying Fuzzy controller into the renewable energy storage system for better efficiency. Different small size power generators need to be initially started up in order to fulfil the demand of power at the rush hours. V2G (Vehicle to grid) technology is an interface of bidirectional electrical grid which allows electric vehicles to take energy from the mesh. The calculation for the power requirement of the battery is initiated for identifying the charging load. When it comes to power management for the electric vehicles (EVs), information technology plays a vital role for the V2G framework. The delivery of power request to the aggregate of EVs through the aggregator is done with the help of sending a signal from the RTO/ISO. The load is generated with the help of huge as well as continuously running units of power generation and gradable EVs. In V2G optimization, lowering the overall operational cost may be achieved by using wind power as well as using the grid.

Energy After COVID

2020 ◽  
Vol 119 (820) ◽  
pp. 317-322
Author(s):  
Michael T. Klare
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
White Collar ◽  
Peak Oil ◽  
Business Travel ◽  
Reduce Energy Consumption ◽  
The Cost ◽  
Energy Companies

By transforming patterns of travel and work around the world, the COVID-19 pandemic is accelerating the transition to renewable energy and the decline of fossil fuels. Lockdowns brought car commuting and plane travel to a near halt, and the mass experiment in which white-collar employees have been working from home may permanently reduce energy consumption for business travel. Renewable energy and electric vehicles were already gaining market share before the pandemic. Under pressure from investors, major energy companies have started writing off fossil fuel reserves as stranded assets that are no longer worth the cost of extracting. These shifts may indicate that “peak oil demand” has arrived earlier than expected.

Machine learning roles in advancing the power network stability due to deployments of renewable energies and electric vehicles

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohamad Nassereddine
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Power Network ◽  
Network Stability ◽  
Fast Charging ◽  
Electrical Loads ◽  
Charging Stations

AbstractRenewable energy sources are widely installed across countries. In recent years, the capacity of the installed renewable network supports large percentage of the required electrical loads. The relying on renewable energy sources to support the required electrical loads could have a catastrophic impact on the network stability under sudden change in weather conditions. Also, the recent deployment of fast charging stations for electric vehicles adds additional load burden on the electrical work. The fast charging stations require large amount of power for short period. This major increase in power load with the presence of renewable energy generation, increases the risk of power failure/outage due to overload scenarios. To mitigate the issue, the paper introduces the machine learning roles to ensure network stability and reliability always maintained. The paper contains valuable information on the data collection devises within the power network, how these data can be used to ensure system stability. The paper introduces the architect for the machine learning algorithm to monitor and manage the installed renewable energy sources and fast charging stations for optimum power grid network stability. Case study is included.

scholarly journals Analysis of EV Cost-Based Charging Load Profiles

Proceedings ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 2
Author(s):  
Elisavet Koutsi ◽  
Sotirios Deligiannis ◽  
Georgia Athanasiadou ◽  
Dimitra Zarbouti ◽  
George Tsoulos
Keyword(s):  
Electric Vehicles ◽  
User Preferences ◽  
Reference Scenario ◽  
Electricity Prices ◽  
Horizon 2020 ◽  
Vehicle To Grid ◽  
Electrical Grid ◽  
Incentive Strategies ◽  
Grid Load ◽  
The Impact

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.

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