Development of Available Transfer Capability Enhancement Using Intelligent Genetic Algorithm for IEEE Bus System

2018 ◽  
pp. 1-9
Author(s):  
R. Rohini ◽  
Dasari Rao ◽  
S. Ravi ◽  
V. Kumar
Keyword(s):  
Genetic Algorithm ◽  
Available Transfer Capability ◽  
Transfer Capability ◽  
Intelligent Genetic Algorithm ◽  
Bus System

scholarly journals Evaluation and Analysis of Available Transfer Capability in Deregulated Power System Environment

2018 ◽  
Vol 7 (1.8) ◽  
pp. 188
Author(s):  
M Dhana Sai Sri ◽  
P Srinivasa Varma
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Simulation Analysis ◽  
Available Transfer Capability ◽  
High Efficient ◽  
Transfer Capability ◽  
Power System Market ◽  
Bus System

Reliability of network is need of the hour in the present power system market and is constrained by capability of the network. The network calculations are performed using accurate and high efficient strategies. In order to perform power transactions in the system, the computation of available transfer capability is essential which a metric of capability of the system. Generally, effect wattless power is not taken into account in the methodologies for computation of linear available transfer capability. In this paper, a methodology which considers the reactive power flows for enhancement of linear ATC is presented. In order to perform analysis theoretically, a standard IEEE 3 bus system is considered. Another case study i.e., 14 bus system available in IEEE test systems is used for simulation analysis. FACTS technology is incorporated in the existing system in order to enhance capability of the network. To facilitate transfer maximum power in the system, an optimal power-flow-based ATC enhancement model is formulated and presented along with simulation results. Studies based on the IEEE 3-bus system and 14-bus systems with TCSC demonstrate the effectiveness of FACTS control on ATC enhancement.  

scholarly journals Available Transfer Capability Calculation Constrained with Small-Signal Stability Based on Adaptive Gradient Sampling

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Peijie Li ◽  
Ling Zhu ◽  
Xiaoqing Bai ◽  
Hua Wei
Keyword(s):  
High Efficiency ◽  
Computing Time ◽  
Small Signal ◽  
Small Signal Stability ◽  
Available Transfer Capability ◽  
Sqp Method ◽  
Signal Stability ◽  
Gradient Sampling ◽  
Transfer Capability ◽  
Bus System

Due to the nonsmoothness of the small-signal stability constraint, calculating the available transfer capability (ATC) limited by small-signal stability rigorously through the nonlinear programming is quite difficult. To tackle this challenge, this paper proposes a sequential quadratic programming (SQP) method combined with gradient sampling (GS) in a dual formulation. The highlighted feature is the sample size of the gradient changes dynamically in every iteration, yielding an adaptive gradient sampling (AGS) process. Thus, the computing efficiency is greatly improved owing to the decrease and the parallelization of gradient evaluation, which dominates the computing time of the whole algorithm. Simulations on an IEEE 10-machine 39-bus system and an IEEE 54-machine 118-bus system prove the effectiveness and high efficiency of the proposed method.

scholarly journals Evolutionary Algorithm for Calculating Available Transfer Capability

2013 ◽  
Vol 64 (5) ◽  
pp. 1-7 ◽  
Author(s):  
Darko Šošić ◽  
Ivan Škokljev
Keyword(s):  
Power Systems ◽  
Evolutionary Algorithm ◽  
Transmission Network ◽  
Available Transfer Capability ◽  
Commercial Activity ◽  
Matlab Software ◽  
Transfer Capability ◽  
Deregulated Power Systems ◽  
Thermal Voltage ◽  
Bus System

Abstract The paper presents an evolutionary algorithm for calculating available transfer capability (ATC). ATC is a measure of the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses. In this paper, MATLAB software is used to determine the ATC between any bus in deregulated power systems without violating system constraints such as thermal, voltage, and stability constraints. The algorithm is applied on IEEE 5 bus system and on IEEE 30 bus system.

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