The New Insulating Technology for Oil-Immersed Large Capacity Transformers

1992 ◽  
Vol 112 (4) ◽  
pp. 289-293 ◽  
Author(s):  
Yuzuru Kamata ◽  
Masaaki Maejima
Keyword(s):  
Large Capacity

Spread of Large Capacity Servo Motors to Press Machines

2013 ◽  
Vol 133 (2) ◽  
pp. 92-95
Author(s):  
Hiroshi NAGASE ◽  
Shigeki MORINAGA
Keyword(s):  
Large Capacity

Study on Large Capacity 4-Pole Synchronous Generator Excitation System

2016 ◽  
Vol 136 (1) ◽  
pp. 18-24
Author(s):  
Daisuke Hiramatsu ◽  
Yoichi Uemura ◽  
Dai Nozaki ◽  
Shinji Mukoyama ◽  
Kazuma Tsujikawa ◽  
...  
Keyword(s):  
Synchronous Generator ◽  
Excitation System ◽  
Large Capacity ◽  
Synchronous Generator Excitation

Superconducting Low-Speed Large-Capacity Electrical Machines

2019 ◽  
Vol 11 ◽  
pp. 58-68
Author(s):  
Yury N. SHUMOV ◽  
◽  
Alexander S. SAFONOV ◽  
Keyword(s):  
Electrical Machines ◽  
Large Capacity ◽  
Low Speed

scholarly journals Optimal Allocation of Large-Capacity Distributed Generation with the Volt/Var Control Capability Using Particle Swarm Optimization

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3112
Author(s):  
Donghyeon Lee ◽  
Seungwan Son ◽  
Insu Kim
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Power ◽  
Distributed Generation ◽  
Optimal Allocation ◽  
Power Grid ◽  
Particle Swarm ◽  
Renewable Energy Resources ◽  
Swarm Optimization ◽  
Large Capacity ◽  
Electric Power Grid

Widespread interest in environmental issues is growing. Many studies have examined the effect of distributed generation (DG) from renewable energy resources on the electric power grid. For example, various studies efficiently connect growing DG to the current electric power grid. Accordingly, the objective of this study is to present an algorithm that determines DG location and capacity. For this purpose, this study combines particle swarm optimization (PSO) and the Volt/Var control (VVC) of DG while regulating the voltage magnitude within the allowable variation (e.g., ±5%). For practical optimization, the PSO algorithm is enhanced by applying load profile data (e.g., 24-h data). The objective function (OF) in the proposed PSO method considers voltage variations, line losses, and economic aspects of deploying large-capacity DG (e.g., installation costs) to transmission networks. The case studies validate the proposed method (i.e., optimal allocation of DG with the capability of VVC with PSO) by applying the proposed OF to the PSO that finds the optimal DG capacity and location in various scenarios (e.g., the IEEE 14- and 30-bus test feeders). This study then uses VVC to compare the voltage profile, loss, and installation cost improved by DG to a grid without DG.

A Novel Virtualization Intelligent Power Supply with Large Capacity Energy Storage

2020 ◽  
Author(s):  
Guangwei Liu ◽  
Wenxiang Xue ◽  
Zhen Hao ◽  
Zheng Niu ◽  
Ka Mu ◽  
...  
Keyword(s):  
Energy Storage ◽  
Power Supply ◽  
Large Capacity
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