Static State Estimation with Inequality Constraints in a Complementarity Framework for Detecting Infeasible Operation States

2021 ◽  
Vol 195 ◽  
pp. 107129
Author(s):  
R. Martínez-Parrales ◽  
O. Romay ◽  
C.R. Fuerte-Esquivel ◽  
B.A. Alcaide-Moreno
Keyword(s):  
State Estimation ◽  
Inequality Constraints ◽  
Static State

Static State Estimation

2010 ◽  
pp. 45-78
Author(s):  
Soliman Abdel-hady Soliman ◽  
Ahmad M. Al-Kandari
Keyword(s):  
State Estimation ◽  
Static State

State Estimation of Active Distribution Networks

2020 ◽  
pp. 270-308
Author(s):  
Razan Al Rhia ◽  
Haithm Daghrour
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
Distribution Systems ◽  
Operating Performance ◽  
Distribution Networks ◽  
Dynamic State ◽  
State Estimator ◽  
Static State ◽  
Active Distribution Networks

Monitoring and controlling the electrical distribution system for real time is becoming very important to improve its operating performance after transition to active distribution systems. So, many sensors are needed to monitor all parts in the systems. But if sensors are installed at all buses, investment cost becomes huge. To reduce the number of sensors, state estimation approach can be used to estimate the voltage of buses, which do not have sensors. State Estimation (SE) algorithms are broadly classified into Static State Estimator (SSE) and Dynamic State Estimator (DSE). This chapter classifies most algorithms used in active distribution networks, also State estimation in unbalanced distribution systems, and Role of PMU in Distribution System State Estimation.

A new method for solving equality-constrained power system static-state estimation

1990 ◽  
Vol 5 (4) ◽  
pp. 1260-1266 ◽  
Author(s):  
K.A. Clements ◽  
G.W. Woodzell ◽  
R.C. Burchett
Keyword(s):  
Power System ◽  
State Estimation ◽  
New Method ◽  
Static State

Linear State Estimation Based on Measured Quantity Transformation and Calculation of Transmission Losses

2014 ◽  
Vol 672-674 ◽  
pp. 1027-1031
Author(s):  
Gui Hua Lin ◽  
Tao Wang ◽  
Yu Ying Wang
Keyword(s):  
State Estimation ◽  
Transmission Loss ◽  
Information Matrix ◽  
Test System ◽  
Measured Quantity ◽  
Voltage Measurement ◽  
Static State ◽  
Calculation Results ◽  
Linear State ◽  
Nodal Voltage

A linear static state estimation on measured quantity transformation is proposed in this paper utilizing the high precision measurements of WAMS. Using transformation of measured quantity, the current measurements of WAMS are transformed into equivalent voltage measurement, and after simplification a constant real number information matrix is obtained, so the decoupling calculation of real part and imaginary part of nodal voltage is realized. The calculation has many advantages such as fast proposed algorithm, high estimation precision and better numerical stability. Finally, the algorithm is applied to the calculation of network loss in theory, the calculation accuracy of transmission loss is improved. The calculation results of IEEE 30-bus test system validate the effectiveness of the proposed method.

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