Abstract
Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using the input-output quantities i.e., voltages, currents, and power factor of the transmission line. The equivalent π-network model is used and the terminal data i.e., sending-end and receiving-end quantities are assumed as available measured data. The parameter estimation problem is converted to an optimization problem by formulating an error-minimizing objective function. An improved particle swarm optimization (PSO) in terms of time-varying control parameters and chaos-based initialization is used to optimally estimate the line parameters. Two cases are considered for parameter estimation, the first case is when the line conductance is neglected and in the second case, the conductance is considered into account. The results obtained by the improved algorithm are compared with the standard version of the algorithm, firefly algorithm and artificial bee colony algorithm for 30 number of trials. It is concluded that the improved algorithm is tremendously sufficient in estimating the line parameters in both cases validated by low error values and statistical analysis, comparatively.
Highlights
The major part of the power system consists of transmission lines which are the main medium of power flow between generation and distribution ends
The paper presented an optimal method to estimate long transmission line parameters using input-output quantities i.e., voltages, currents, and/or power-factor measured at both ends of the transmission line
The control parameters of the particle swarm optimization (PSO) are made dynamic and the initialization is made chaotic to achieve better exploration and exploitation to support in finding the global solution
Summary
The major part of the power system consists of transmission lines which are the main medium of power flow between generation and distribution ends. The paper provides a technique to accurately estimate transmission line parameters with minimum possible error and assumes that the input-output data of voltages, currents and power factor is available from measurement units at two ends of the line. The PMUs are employed in the power system to measure magnitudes along with phase angles of voltages and currents at different locations [8,9], they process the data acquired by digital recorders at substations By using this measured input-output data the long transmission line, the line parameters from the set of nonlinear equations are estimated. The paper is organized as follows, this Section is followed by Section 2 which presents the model of the transmission line and problem formulation, Section 3 outlines the optimization algorithms, Section 4 presents the simulation results and discussion whereas conclusions and references are provided at the end of the paper
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