scholarly journals Pricing of Vehicle-to-Grid Services in a Microgrid by Nash Bargaining Theory

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Hossein Sarparandeh ◽  
Mehdi Ehsan
Keyword(s):  
Electric Vehicles ◽  
Storage Capacity ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Economic Benefits ◽  
Nash Bargaining ◽  
Policy Makers ◽  
Vehicle To Grid ◽  
Automotive Market ◽  
Nash Bargaining Theory

Owners of electric vehicles (EVs) can offer the storage capacity of their batteries to the operator of a microgrid as a service called vehicle-to-grid (V2G) to hold the balance between supply and demand of electricity, particularly when the microgrid has intermittent renewable energy sources. Literature review implies that V2G has economic benefits for both microgrid operator and EV owners, but it is unclear how these benefits are divided between them. The challenge grows when the policy makers rely on the V2G revenue as an incentive for expanding the penetration of EVs in the automotive market. This paper models the interaction between microgrid operator and EV owners as a bargaining game to determine how the benefits of V2G should be divided. The method has been implemented on a hybrid power system with high wind penetration in addition to diesel generators in Manjil, Iran. The results indicate that, in addition to V2G benefits, government subsidies are necessary to promote the use of EVs.

scholarly journals Frequency regulation with vehicle-to-grid (V2G) option in multi-generation power network

Energetika ◽  
2016 ◽  
Vol 62 (1-2) ◽  
Author(s):  
Hitesh Dutt Mathur ◽  
Yogesh Krishan Bhateshvar
Keyword(s):  
Energy Storage ◽  
Electric Vehicles ◽  
Magnetic Energy ◽  
Renewable Energy Sources ◽  
Automatic Generation ◽  
Frequency Regulation ◽  
Pollution Level ◽  
Power Network ◽  
Vehicle To Grid ◽  
Generation Power

In a smart grid scenario, penetration of large scale renewable energy sources is increasing rapidly. Even at global level, serious discussions are being done to reduce carbon emission. In order to achieve this goal of cleaner and greener environment for newer generations, fossil fuel based vehicles are being replaced with electric vehicles. This concept of having more electric vehicles will not only control pollution level but also supply electrical power back to the grid when have surplus power stored. It is going to be a win-win situation for both consumers and the grid. The concept termed as Vehicle-to-Grid (V2G) is explored for frequency regulation aspect in a multi-generation power network in this paper. When established automatic generation control (AGC) in interconnected power system is not sufficient to manage balance between demand and supply, vehicle energy storage is considered a viable option for a shortterm active power support in order to bring frequency back to normal. In energy storage possibilities, super conducting magnetic energy storage, ultra-capacitor, etc. are primarily discussed. This paper focuses on an integrated model of vehicle-to-grid (V2G) and wind power as alternatives to supply instant power to regulate frequency when the  system is subjected to sudden perturbation. APSO (adaptive particle swarm optimization) optimized fuzzy logic controller is used to intelligently suppress frequency and tie-line power oscillations. Results obtained are comprehensively presented and discussed in achieving power-frequency balance. MATLAB/Simulink is used for the simulation purpose.

scholarly journals Learning capacity: predicting user decisions for vehicle-to-grid services

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Rob Shipman ◽  
Sophie Naylor ◽  
James Pinchin ◽  
Rebecca Gough ◽  
Mark Gillott
Keyword(s):  
Machine Learning ◽  
Electric Vehicles ◽  
Supply And Demand ◽  
Learning Model ◽  
Grid Services ◽  
Vehicle To Grid ◽  
Learning Capacity ◽  
Machine Learning Model ◽  
Storage Resource ◽  
Ev Charging

AbstractThe electric vehicles (EV) market is projected to continue its rapid growth, which will profoundly impact the demand on the electricity network requiring costly network reinforcements unless EV charging is properly managed. However, as well as importing electricity from the grid, EVs also have the potential to export electricity through vehicle-to-grid (V2G) technology, which can help balance supply and demand and stabilise the grid through participation in flexibility markets. Such a scenario requires a population of EVs to be pooled to provide a larger storage resource. Key to doing so effectively however is knowledge of the users, as they ultimately determine the availability of a vehicle. In this paper we introduce a machine learning model that aims to learn both a) the criteria influencing users when they decided whether to make their vehicle available and b) their reliability in following through on those decisions, with a view to more accurately predicting total available capacity from the pool of vehicles at a given time. Using a series of simplified simulations, we demonstrate that the learning model is able to adapt to both these factors, which allows the required capacity of a market event to be satisfied more reliably and using a smaller number of vehicles than would otherwise be the case. This in turn has the potential to support participation in larger and more numerous market events for the same user base and use of the technology for smaller groups of users such as individual communities.

Design and Analysis of a Power Transmission Network Model of Electric Vehicle

2016 ◽  
Vol 693 ◽  
pp. 45-52
Author(s):  
L.H. Liu
Keyword(s):  
Renewable Energy ◽  
Energy Distribution ◽  
Electric Vehicles ◽  
Power Transmission ◽  
Renewable Energy Sources ◽  
Operation Mode ◽  
Distribution Network ◽  
Linear Constraints ◽  
Energy Sources ◽  
Vehicle To Grid

Fossil energy is increasing depletion, renewable energy sources plays an important role in our life and Vehicle-to-Grid (V2G) is proved to be feasible. Electric Vehicles (EVs) can not only store energy, but also can be used as a medium between the battery energy stored in EVs and the power grid through Vehicle-to-Grid (V2G). And then, the energy in the batteries of electric vehicles can move with EVs. This paper introduces an energy distribution network, which is consisting of EVs, charge stations and renewable energy sources. After analyzing the characteristics of energy distribution network, we introduce a new commercial operation mode called mobile electrical grid, which is compared with the integrated grids. To calculate the life cycle energy loss for this novel operation mode, a mathematical model is developed, and then what we have deduced is demonstrated to be a lasso optimization problem with linear constraints, which is convex.

Application of Plug-In Electric Vehicles and Controllable Loads to Frequency Regulation

2012 ◽  
Vol 588-589 ◽  
pp. 1640-1643
Author(s):  
Shu Lei Deng ◽  
Bao Ping Liu ◽  
An Jun Li ◽  
Xiong Zhou ◽  
Yu Xiang Huang
Keyword(s):  
Renewable Energy ◽  
Feedback Control ◽  
Power Systems ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Frequency Regulation ◽  
Battery Charging ◽  
Vehicle To Grid ◽  
Simulation Results

High renewable energy penetration in power systems may bring a series of problems such as frequency fluctuations. Plug-in electric vehicles (PEVs) and controllable loads have been shifting into focus for this. A dynamic vehicle-to-grid (V2G) model with feedback control is proposed by considering the battery charging/discharging characteristics and the dynamic model of frequency regulation with PEVs and controllable loads for a single area is established. Simulation results demonstrate that the application of PEVs and controllable loads can relief the frequency refutation due to the randomness of renewable energy sources.

Electric vehicles and smart grid interaction: A review on vehicle to grid and renewable energy sources integration

2014 ◽  
Vol 34 ◽  
pp. 501-516 ◽  
Author(s):  
Francis Mwasilu ◽  
Jackson John Justo ◽  
Eun-Kyung Kim ◽  
Ton Duc Do ◽  
Jin-Woo Jung
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Vehicle To Grid

scholarly journals Effect of Renewable Energy and Electric Vehicles on Smart Grid

2015 ◽  
Vol 2 (1-2.) ◽  
Author(s):  
Alaa A. Zaky
Keyword(s):  
Renewable Energy ◽  
Smart Grid ◽  
Electric Vehicles ◽  
Power Plants ◽  
Distribution Systems ◽  
Renewable Energy Sources ◽  
Future Research ◽  
Electricity Grid ◽  
Vehicle To Grid ◽  
Energy Technologies

Global electricity demands are increasing at rapid pace. Energy supply, their usage and technologies involved need to be more economical, environment friendly and socially sustainable. Efforts are being done all over the globe to reduce this green house effect; and renewable energy technologies to combat climate changes, which require extensive changes to the current electricity generation and distribution systems. To meet this goal, it is required to optimize the grid operations and available resources to meet the ever increasing energy demands in an efficient, effective and environment sustainable way. So strong and huge interests on smart grid have increased extensively in recent years around the world. This scenario could be a promising reason for future research in this area. This next form of electricity grid will be able to manage various parts of power production from power plants to the customers. Renewable energy sources appear strongly in smart grid so in this paper the effect of this sources will be studied also electric vehicles have a great effect on smart grid infrastructure ,communication and control this paper will discuss this effect if it come from the electric vehicle mode or vehicle to grid mode.

scholarly journals An Efficient Algorithm for Peer-to-Peer Energy Trading Using Blockchain in Microgrid Energy Markets

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Nahid-Ur-Rahman Chowdhury ◽  
Khairul Islam ◽  
Fayazul Hasan
Keyword(s):  
Renewable Energy ◽  
Efficient Algorithm ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy System ◽  
Economic Benefits ◽  
Peer To Peer ◽  
Energy Sources ◽  
Energy Trading

Electricity generation from distributed renewable energy sources is strongly increasing worldwide. Due to their intermittency in nature, the large scale integration of these renewable energy sources creates acute challenges to the existing energy system network. Thus, it is highly demanding to secure a reliable balance between energy generation and consumption. To overcome such challenges, peer-to-peer energy trading using blockchains on microgrid networks can play a significant role. In this paper, we present the concept of an efficient algorithm that can be useful for energy trading using blockchain from both the prosumers and consumers end. We also show the detailed outline of the methodology for energy transactions in a comprehensive way. The outcome of this study prove that if implemented properly this methodology can efficiently balance supply and demand locally and provide socio-economic benefits to the participants.

scholarly journals Potential Exergy Storage Capacity of Salt Caverns in the Cheshire Basin Using Adiabatic Compressed Air Energy Storage

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1065 ◽  
Author(s):  
Mark Dooner ◽  
Jihong Wang
Keyword(s):  
Energy Storage ◽  
Large Scale ◽  
Storage Capacity ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Power Input ◽  
Compressed Air ◽  
Compressed Air Energy Storage ◽  
Salt Caverns ◽  
Full Charge

As the number of renewable energy sources connected to the grid has increased, the need to address the intermittency of these sources becomes essential. One solution to this problem is to install energy storage technologies on the grid to provide a buffer between supply and demand. One such energy storage technology is Compressed Air Energy Storage (CAES), which is suited to large-scale, long-term energy storage. Large scale CAES requires underground storage caverns, such as the salt caverns situated in the Cheshire Basin, UK. This study uses cavern data from the Cheshire Basin as a basis for performing an energy and exergy analysis of 10 simulated CAES systems to determine the exergy storage potential of the caverns in the Cheshire Basin and the associated work and power input and output. The analysis revealed that a full charge of all 10 caverns could store 25.32 GWh of exergy, which can be converted to 23.19 GWh of work, which requires 43.27 GWh of work to produce, giving a round trip efficiency of around 54%. This corresponds to an input power of 670.07 GW and an output power of 402.74 GW. The Cheshire Basin could support around 100 such CAES plants, giving a potential total exergy storage capacity of 2.53 TWh and a power output of 40 TW. This is a significant amount of storage which could be used to support the UK grid. The total exergy destroyed during a full charge, store, and discharge cycle for each cavern ranged from 299.02 MWh to 1600.00 MWh.

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