scholarly journals Future of Microgrids with Distributed Generation and Electric Vehicles

2017 ◽  
Author(s):  
Syed Abid Ali Shah Bukhari ◽  
Wen-Ping Cao ◽  
Toufique Ahmed Soomro ◽  
Du Guanhao
Keyword(s):  
Distributed Generation ◽  
Electric Vehicles

Distribution Networks with Distributed Generation and Electric Vehicles

2021 ◽  
pp. 250-260
Author(s):  
Wilson Jhonatan Olmedo Carrillo ◽  
Andrés Santiago Cisneros-Barahona ◽  
María Isabel Uvidia Fassler ◽  
Gonzalo Nicolay Samaniego Erazo ◽  
Byron Andrés Casignia Vásconez
Keyword(s):  
Distributed Generation ◽  
Electric Vehicles ◽  
Distribution Networks

Integration of electric vehicles in smart grids for optimization and support to distributed generation

2018 ◽  
Author(s):  
Gabriel A. Salvatti ◽  
Emerson G. Carati ◽  
Jean P. da Costa ◽  
Rafael Cardoso ◽  
Carlos M.O. Stein
Keyword(s):  
Distributed Generation ◽  
Electric Vehicles ◽  
Smart Grids

scholarly journals On the Determination of Meshed Distribution Networks Operational Points after Reinforcement

2019 ◽  
Vol 9 (17) ◽  
pp. 3501 ◽  
Author(s):  
Vasiliki Vita ◽  
Stavros Lazarou ◽  
Christos A. Christodoulou ◽  
George Seritan
Keyword(s):  
Monte Carlo Simulation ◽  
Distributed Generation ◽  
Electric Vehicles ◽  
Maximum Load ◽  
Distribution Networks ◽  
Network Robustness ◽  
Current Load ◽  
Objective Functions ◽  
Calculation Algorithm

This paper proposes a calculation algorithm that creates operational points and evaluates the performance of distribution lines after reinforcement. The operational points of the line are probabilistically determined using Monte Carlo simulation for several objective functions for a given line. It is assumed that minimum voltage at all nodes has to be balanced to the maximum load served under variable distributed generation production, and to the energy produced from the intermittent renewables. The calculated maximum load, which is higher than the current load, is expected to cover the expected needs for electric vehicles charging. Following the proposed operational patterns, it is possible to have always maximum line capacity. This method is able to offer several benefits. It facilitates of network planning and the estimation of network robustness. It can be used as a tool for network planners, operators and large users. It applies to any type of network including radial and meshed.

scholarly journals Development of a Kernel Extreme Learning Machine Model for Capacity Selection of Distributed Generation Considering the Characteristics of Electric Vehicles

2019 ◽  
Vol 9 (12) ◽  
pp. 2401
Author(s):  
Zhongdong Yin ◽  
Jingjing Tu ◽  
Yonghai Xu
Keyword(s):  
Extreme Learning Machine ◽  
Distributed Generation ◽  
Electric Vehicles ◽  
Distribution Network ◽  
Support Vector ◽  
Kernel Extreme Learning Machine ◽  
Learning Machine ◽  
The Stability ◽  
Capacity Selection ◽  
Selection Of

The large-scale access of distributed generation (DG) and the continuous increase in the demand of electric vehicle (EV) charging will result in fundamental changes in the planning and operating characteristics of the distribution network. Therefore, studying the capacity selection of the distributed generation, such as wind and photovoltaic (PV), and considering the charging characteristic of electric vehicles, is of great significance to the stability and economic operation of the distribution network. By using the network node voltage, the distributed generation output and the electric vehicles’ charging power as training data, we propose a capacity selection model based on the kernel extreme learning machine (KELM). The model accuracy is evaluated by using the root mean square error (RMSE). The stability of the network is evaluated by voltage stability evaluation index (Ivse). The IEEE33 node distributed system is used as simulation example, and gives results calculated by the kernel extreme learning machine that satisfy the minimum network loss and total investment cost. Finally, the results are compared with support vector machine (SVM), particle swarm optimization algorithm (PSO) and genetic algorithm (GA), to verify the feasibility and effectiveness of the proposed model and method.

scholarly journals Optimal Control of Multiple Microgrids and Buildings by an Aggregator

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1058 ◽  
Author(s):  
Giulio Ferro ◽  
Riccardo Minciardi ◽  
Luca Parodi ◽  
Michela Robba ◽  
Mansueto Rossi
Keyword(s):  
Distributed Generation ◽  
Electric Vehicles ◽  
Demand Response ◽  
Electrical Grid ◽  
Energy Management Systems ◽  
New Energy ◽  
Systems Models ◽  
Fair Assignment ◽  
Demand Response Programs

The electrical grid has been changing in the last decade due to the presence of renewables, distributed generation, storage systems, microgrids, and electric vehicles. The introduction of new legislation and actors in the smart grid’s system opens new challenges for the activities of companies, and for the development of new energy management systems, models, and methods. A new optimization-based bi-level architecture is proposed for an aggregator of consumers in the balancing market, in which incentives for local users (i.e., microgrids, buildings) are considered, as well as flexibility and a fair assignment in reducing the overall load. At the lower level, consumers try to follow the aggregator’s reference values and perform demand response programs to contain their costs and satisfy demands. The approach is applied to a real case study.

The V2G Technique and its Application in Distributed Generation

2012 ◽  
Vol 608-609 ◽  
pp. 1665-1670
Author(s):  
Cheng Liu ◽  
Jian Qin
Keyword(s):  
Output Power ◽  
Distributed Generation ◽  
Electric Vehicles ◽  
Energy Sources ◽  
Main Principle ◽  
Load Shifting ◽  
Power Sources ◽  
Battery Electric Vehicles ◽  
Natural Energy ◽  
The Future

Traditional distributed power sources are usually natural energy sources, their output power is not stable and difficult to join up to the grid. Battery electric vehicles(BEV) based on V2G technique is a new kind of Distributed Generation(DG). This paper introduces a V2G technique. A V2G-based BEV could be used to realize load shifting and stabilize the disturbance for DG's joining up with the grid. Many countries started researching V2G technique and in China NARI Group Corporation and Xuji Group Corporation have researched and started manufacturing practical V2G device. This paper also shows the main principle of V2G and its application in China, concludes its advantages and analyzes its development in the future.

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