Optimal Location of SVC Devices for Transmission Congestion Management in a Deregulated Power System

2020 ◽  
Vol 12 (SP4) ◽  
pp. 1833-1844
Author(s):  
Vengadesan A.
Keyword(s):  
Power System ◽  
Congestion Management ◽  
Optimal Location ◽  
Transmission Congestion ◽  
Deregulated Power System

scholarly journals Optimal Location of multi-type FACTS for Power System Security Enhancement

2019 ◽  
Vol 9 (2) ◽  
pp. 5345-5349
Keyword(s):  
Power System ◽  
Transmission Lines ◽  
Power Transmission ◽  
Transmission Loss ◽  
Optimal Parameter ◽  
Congestion Management ◽  
Optimal Location ◽  
Transmission Congestion ◽  
Facts Devices ◽  
Improved Stability

-Transmission congestion results from the contingencies in the power system and increasing load demand that has to be supplied through predetermined corridors in case of restructured environment. The Flexible AC Transmission Systems (FACTS) devices when deployed in a power system can result in improving the system performance in terms increased loading capability of transmission lines, reduction in losses, improved stability and security of the system by relieving stress on congested lines. This work deals with congestion management of the power transmission network by employing FACTS devices, with the help of Genetic Algorithm (GA) based optimization algorithm. Optimal location of FACTS placement and optimal parameter settings of these devices are the objectives for the optimization problem. The optimization process aims at maximizing the loading capability by the network by transferring power from overloaded lines to adjacent lightly loaded lines. FACTS devices considered are TCSC, SVC and UPFC for the alleviation of the overload on transmission lines and to reduce overall transmission loss of the system. An IEEE 30-bus system is used to illustrate the effectiveness of the proposed method.

scholarly journals Congestion Management in Deregulated Power System using Adaptive Moth Swarm Optimization

2021 ◽  
Author(s):  
R Ramaporselvi ◽  
G. Geetha
Keyword(s):  
Power System ◽  
Congestion Management ◽  
Optimal Location ◽  
Bacterial Foraging Optimization ◽  
Swarm Optimization ◽  
The Past ◽  
Deregulated Power System ◽  
Thyristor Controlled Series Capacitor ◽  
Compensation Rate ◽  
Bacterial Foraging Optimization Algorithm

Abstract Transmission line congestion is considered the most acute trouble during the operation of the power system. Therefore, congestion management acts as an effective tool in utilizing the available power without breaking the system hindrances or limitations. Over the past few years, determining an optimal location and size of the devices have pinched a great deal of consideration. Numerous approaches have been established to mitigate the congestion rate and this paper aims to enhance the line congestion and minimize power loss by determining the compensation rate and optimal location of thyristor-controlled series capacitor (TCSC) using adaptive moth swarm optimization (AMSO) algorithm. An adaptive moth swarm AMSO algorithm utilizes the performances of moth flame and chaotic local search-based shrinking scheme of the bacterial foraging optimization algorithm. The proposed AMSO approach is executed and discussed for IEEE-30 bus system for determining the optimal location of single TCSC and dual TCSC. In addition to this, the proposed algorithm is compared with various other existing approaches and the results thus obtained provide better performances when compared with other techniques.

scholarly journals Transmission Congestion Management Considering Modeling of Solar Photovoltaic Distributed Generator in Deregulated Power System

2019 ◽  
Vol 8 (3) ◽  
pp. 2086-2093
Keyword(s):  
Power System ◽  
Electricity Market ◽  
Power Output ◽  
Solar Irradiance ◽  
Real Life ◽  
Congestion Management ◽  
Solar Photovoltaic ◽  
Transmission Congestion ◽  
Distributed Generator ◽  
Deregulated Power System

This paper presents an effective methodology for transmission congestion management (TCM) in deregulated power system considering random nature of solar photovoltaic distributed generator (SPVDG). Solar photovoltaic power generation has gained popularity worldwide. Its’ optimal sitting in the grid can provide congestion relief and reduce line losses etc. However, to maximize the potential benefits of this renewable energy source, its’ stochastic power output which mainly depends on solar irradiance needs due consideration. In this paper, seasonal variations of solar irradiance have been modeled using beta probability density function to determine expected power output of SPVDG over various seasons of one year. TCM problem has been formulated as a non-linear programming with the objective of social welfare maximization of electricity market subject to equality and inequality constraints incorporating seasonal load demand variations. The optimal siting of SPVDG integration in the grid has been discussed. The proposed methodology has been simulated by incorporating practical data of a real-life SPVDG in standard IEEE 30-bus, IEEE 118-bus and practical Indian Utility 62-bus systems. Simulation results show the benefits of proposed methodology on market indices. The effectiveness of proposed approach is also discussed in comparison with existing methodology of distributed generation modeling

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