scholarly journals The impact of system nonlinearities in the problem of optimal PMU placement for power system state estimation

2020 ◽  
Vol 216 ◽  
pp. 01041
Author(s):  
Mikhail Khokhlov ◽  
Olga Pozdnyakova
Keyword(s):  
Power System ◽  
State Estimation ◽  
Measurement Model ◽  
System State ◽  
State Variables ◽  
Placement Problem ◽  
Power System State Estimation ◽  
Pmu Placement ◽  
The Impact ◽  
Optimal Pmu Placement

In PMU-based state estimation, a linear measurement model with phasors of both state variables and measurements expressed in rectangular coordinates has proven efficiency. The rectangular coordinate formulation is also used in optimal PMU placement problem aimed at providing the power system state estimation with the most informative measurements. In this case, it is assumed that the linearity of the measurement model ensures the optimality of the found placement of PMUs for any steady-state operating condition of the power system. The results presented in this paper show that this is not the case.

scholarly journals Particle filter in power system state estimation – bad measurement data and branch disconnection

2015 ◽  
Vol 64 (2) ◽  
pp. 237-248
Author(s):  
Piotr Kozierski ◽  
Marcin Lis ◽  
Adam Owczarkowski ◽  
Dariusz Horla
Keyword(s):  
Power System ◽  
Particle Filter ◽  
State Estimation ◽  
Measurement Data ◽  
The State ◽  
Filter Method ◽  
System State ◽  
State Variables ◽  
Zero Bias ◽  
Power System State Estimation

Abstract An approach to power system state estimation using a particle filter has been proposed in the paper. Two problems have been taken into account during research, namely bad measurements data and a network structure modification with rapid changes of the state variables. For each case the modification of the algorithm has been proposed. It has also been observed that anti-zero bias modification has a very positive influence on the obtained results (few orders of magnitude, in comparison to the standard particle filter), and additional calculations are quite symbolic. In the second problem, used modification also improved estimation quality of the state variables. The obtained results have been compared to the extended Kalman filter method

scholarly journals Real-Time State Estimation in the Cameroon Power System

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Emmanuel Tanyi ◽  
Edwin Mbinkar
Keyword(s):  
Power System ◽  
State Estimation ◽  
Real Time ◽  
Ad Hoc ◽  
Dynamic State ◽  
System State ◽  
State Variables ◽  
Power System State Estimation ◽  
Dynamic State Estimation ◽  
Measurement Units

An important tool for the energy management system (EMS) is state estimation. Based on measurements taken throughout the network, state estimation gives an estimation of the state variables of the power system while checking that these estimates are consistent with the measurements. Currently, in the Cameroon power system, state estimates have been provided by ad hoc supervisory control and data acquisition (SCADA) systems. A disadvantage is that the measurements are not synchronised, which means that state estimation is not very precise during dynamic phenomena in the network. In this paper, real-time phasor measurement units (PMUs) that provide synchronised phasor measurements are proposed for integration into the power system. This approach addresses two important issues associated with the power system state estimation, namely, that of measurement accuracy and that of optimization of the number of measurement sites, their location, and the importance given to their measurements on the dynamic state estimation.

scholarly journals Artificial fish swarm optimization algorithm for power system state estimation

2020 ◽  
Vol 18 (3) ◽  
pp. 1130
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
State Estimation ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Test System ◽  
System State ◽  
State Variables ◽  
Swarm Optimization ◽  
Power System State Estimation ◽  
Artificial Fish Swarm

In this paper, the power system state estimation (SE) problem is formulated as a general non-linear programming problem with equality constraints and boundary limits on the state variables. The proposed SE problem is solved using an evolutionary based Artificial Fish Swarm Optimization Algorithm (AFSOA). The AFSOA is a global search algorithm based on the characteristics of fish swarm and its autonomous model. The detailed algorithm with its flow chart is presented in this paper. To show the effectiveness of the proposed SE approach, six bus test system is considered. The obtained results are compared with other algorithms reported in the literature.

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