Smart Grid State Estimation by Weighted Least Square Estimation
Nithin V G1, Libish T M2
1Nithin V G, Department of Electronics and Communication Engineering, Sree Chitra Thirunal College of Engineering, Thiruvananthapuram (Kerala), India.
2Libish T M, Department of Electronics and Communication Engineering, Sree Chitra Thirunal College of Engineering, Thiruvananthapuram (Kerala), India.
Manuscript received on 13 August 2016 | Revised Manuscript received on 20 August 2016 | Manuscript Published on 30 August 2016 | PP: 20-25 | Volume-5 Issue-6, August 2016 | Retrieval Number: F4671085616/16©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The smart grid is an advanced power grid with many new added functions and more reliability than the traditional grid. More controlled power flow is enabled in the smart grid by use of features from fields of communication, control system, signal processing etc. Knowing the present condition of the system is critical for signal processing applications and hence more accurate state estimation is important. State of the system along with information about the network topology will give complete information about the power grid network. In this paper the network topology is modeled using the MATPOWER package, a powerful software package of MATLAB. Weighted Least Square (WLS) state estimation is used to develop equations and algorithms for state estimation. The linear state estimation problem is formulated with linear methods using phasor measurement unit (PMU) data. The measurements which are included in the observation vector and also the size of the system (given by number of busses in the system) are important and these features affect the accuracy of the system state estimate. In this paper, state estimates of IEEE standard bus system of different size are stimulated using MATPOWER package. Also state estimates are stimulated, with different measurement parameters in the observation vector and the stimulation result obtained are compared.
Keywords: Smart Grid, State Estimation, Weighted Least Square Estimation, Modeling of Smart Grid.
Scope of the Article: Smart Grid Communications