Data-Driven Intelligent Maintenance Planning of Smart Meter Reparations for Large-Scale Smart Electric Power Grid

Author(s):  
Weifeng Wang ◽  
Hao Chen ◽  
Bing Lou ◽  
Ning Jin ◽  
Xizhong Lou ◽  
...  
2013 ◽  
Vol 291-294 ◽  
pp. 2212-2216
Author(s):  
Meng Zhang ◽  
Liang HUA Zheng ◽  
Tao Lin ◽  
Hua Long Wang ◽  
Fei Fang

In recent years, with the happening of large-scale power cut accidents, the electric network has been concerned widely increasingly. Pattern recognition which could be used in online analysis, can get rid of the mode limit of the operation characteristic of description system, and its counting volume is less influenced by system scale, also its general assessment is in a fast speed. In this text, it elaborates the conception of the power grid vulnerability and some kinds of available ways of assessing vulnerability, and it also tells us the target of electric network’s integrative vulnerability based on integrative vulnerability mode for electric power grid, and used in pattern recognition, which its the sensibility and necessity of pattern recognition has been verified by the IEEE-39 system.


2015 ◽  
Vol 9 (4) ◽  
pp. 90
Author(s):  
Juan Ernesto Wyss Porras ◽  
Sususmu Shimada ◽  
Jun Yoshino ◽  
Tomonao Kobayashi

The impact of the installation of a large-scale photovoltaic (PV) system to the electric power grid management is analyzed numerically in this series of works. In this part 1, the solar irradiance at the target country, Guatemala, is evaluated with a weather forecasting model, and PV energy potential is estimated. From the computed potential distribution, the appropriate area for installation of a large-scale PV system is selected. This area is where the solar irradiance is large and the energy consumption regions are close by. The optimal tilted angle of the PV panels is proposed as well from the PV output simulation. The time series data of the PV output is also evaluated in this part, and it will be applied to the analysis of the impact of the PV installation to the electric power grid management in the following part of this series of works.


2014 ◽  
Vol 413 ◽  
pp. 11-24 ◽  
Author(s):  
A.B.M. Nasiruzzaman ◽  
H.R. Pota ◽  
Most. Nahida Akter

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3112
Author(s):  
Donghyeon Lee ◽  
Seungwan Son ◽  
Insu Kim

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.


Author(s):  
Hans Peter Kraemer ◽  
Anne Bauer ◽  
Michael Frank ◽  
Peter Van Hasselt ◽  
Peter Kummeth ◽  
...  

Author(s):  
Soo-Hoan Lee ◽  
Kang-Wan Lee ◽  
Yong-Beum Yoon ◽  
Ok-Bae Hyun

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