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.

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.

scholarly journals Biobjective Optimization-Based Frequency Regulation of Power Grids with High-Participated Renewable Energy and Energy Storage Systems

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Tingyi He ◽  
Shengnan Li ◽  
Shuijun Wu ◽  
Chuangzhi Li ◽  
Biao Xu
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Large Scale ◽  
Frequency Control ◽  
Renewable Energy Sources ◽  
Automatic Generation ◽  
Load Frequency Control ◽  
Total Power ◽  
Frequency Regulation ◽  
Entropy Weight

Large-scale renewable energy sources connected to the grid bring new problems and challenges to the automatic generation control (AGC) of the power system. In order to improve the dynamic response performance of AGC, a biobjective of complementary control (BOCC) with high-participation of energy storage resources (ESRs) is established, with the minimization of total power deviation and the minimization of regulation mileage payment. To address this problem, the strength Pareto evolutionary algorithm is employed to quickly acquire a high-quality Pareto front for BOCC. Based on the entropy weight method (EWM), grey target decision-making theory is designed to choose a compromise dispatch scheme that takes both of the operating economy and power quality into account. At last, an extended two-area load frequency control (LFC) model with seven AGC units is taken to verify the effectiveness and the performance of the proposed method.

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.

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.

scholarly journals Methodology for the Optimal Design of a Hybrid Charging Station of Electric and Fuel Cell Vehicles Supplied by Renewable Energies and an Energy Storage System

2019 ◽  
Vol 11 (20) ◽  
pp. 5743 ◽  
Author(s):  
Higinio Sánchez-Sáinz ◽  
Carlos-Andrés García-Vázquez ◽  
Francisco Llorens Iborra ◽  
Luis M. Fernández-Ramírez
Keyword(s):  
Energy Storage ◽  
Fuel Cell ◽  
Electric Vehicles ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy System ◽  
Energy Storage System ◽  
Design System ◽  
Charging Station ◽  
Electrical Generation

The global energy system is changing, mainly to achieve sustainable transport technologies and clean electrical generation based on renewable sources. Thus, as fuels, electricity and hydrogen are the most promising transport technologies in order to reduce greenhouse emissions. On the other hand, photovoltaic and wind energies, including energy storage, have become the main sources of distributed generation. This study proposes a new optimal-technical sizing method based on the Simulink Design Optimization of a stand-alone microgrid with renewable energy sources and energy storage to provide energy to a wireless power transfer system to charge electric vehicles along a motorway and to a hydrogen charging station for fuel cell-powered buses. The results show that the design system can provide energy for the charging of electric vehicles along the motorway and produce the hydrogen consumed by the fuel cell-buses plus a certain tank reserve. The flexibility of the study allows the analysis of other scenarios, design requirements, configurations or types of microgrids.

scholarly journals The Potential of Vehicle-to-Grid to Support the Energy Transition: A Case Study on Switzerland

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4812
Author(s):  
Loris Di Natale ◽  
Luca Funk ◽  
Martin Rüdisüli ◽  
Bratislav Svetozarevic ◽  
Giacomo Pareschi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Energy Transition ◽  
Energy Sources ◽  
Large Share ◽  
Vehicle To Grid ◽  
Production And Consumption ◽  
The Impact

Energy systems are undergoing a profound transition worldwide, substituting nuclear and thermal power with intermittent renewable energy sources (RES), creating discrepancies between the production and consumption of electricity and increasing their dependence on greenhouse gas (GHG) intensive imports from neighboring energy systems. In this study, we analyze the concurrent electrification of the mobility sector and investigate the impact of electric vehicles (EVs) on energy systems with a large share of renewable energy sources. In particular, we build an optimization framework to assess how Evs could compete and interplay with other energy storage technologies to minimize GHG-intensive electricity imports, leveraging the installed Swiss reservoir and pumped hydropower plants (PHS) as examples. Controlling bidirectional EVs or reservoirs shows potential to decrease imported emissions by 33–40%, and 60% can be reached if they are controlled simultaneously and with the support of PHS facilities when solar PV panels produce a large share of electricity. However, even if vehicle-to-grid (V2G) can support the energy transition, we find that its benefits will reach their full potential well before EVs penetrate the mobility sector to a large extent and that EVs only contribute marginally to long-term energy storage. Hence, even with a widespread adoption of EVs, we cannot expect V2G to single-handedly solve the growing mismatch problem between the production and consumption of electricity.

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