New EPS state estimation algorithms based on the technique of test equations and PMU measurements

2011 IEEE Trondheim PowerTech

Korkina

Paltsev

2011

Bad data detection is the most important problem in electric power system (EPS) state estimation. The paper addresses the algorithm of bad data detection by the test equation method at decomposition of state estimation problem. The decomposition algorithm includes structural and functional decomposition of the problem. The structural decomposition is carried out by dividing the calculated scheme into subsystems with respect to voltage levels. The functional decomposition is performed in accordance with the problems solved during the state estimation process: bad data detection, state estimation on the basis of the quadratic and robust criteria. This makes it possible to increase the efficiency of bad data detection and, hence, the accuracy of estimates; organize flexible choice of the method for solving one or another state estimation problem for each subsystem, accelerate the process of measurement processing and, hence, reduce the time of the entire scheme state estimation.Measurements from PMUs placed at boundary nodes are used to increase the efficiency of methods for bad data detection in subsystems and in boundary regions of subsystems.Efficiency of the suggested approaches has been confirmed by the results of experimental studies.Paper accepted for presentation at the 2011 IEEE Trondheim PowerTech 978-1-4244-8417-1/11/$26.00 ©2011

Section: Introductionmentioning

confidence: 99%

Bad data detection at decomposition of state estimation problem

2011 IEEE Trondheim PowerTech

Korkina

Paltsev

2011

“…At the same time, the small-scale networks existing in different countries are well-equipped with the quality telemetry, and, therefore, they do not need the improvement in the speed of the SE problem which is represented by a linear algorithm of state estimation [7]. Results of the studies on the combined use of SCADA and PMU measurements, including those obtained by the authors of this paper in [2] indicate that in this case the main flaws characteristic of traditional SE still exist:…”

Section: Introductionmentioning

confidence: 84%

“…The main measurement equipment in the system is SMART WAMS recorders of voltage and current phasors (Russian analogue of PMU). The synchronized voltage and current phasor measurements obtained from WAMS and their derivatives make it possible to considerably enhance the efficiency of the computation procedure of the electric power system state estimation [2].…”

Section: Introductionmentioning

confidence: 99%

The test equation method for linear state estimation based on PMU data

2014 Power Systems Computation Conference

Korkina

Buchinsky

2014

The advent of next generation devices for synchronized phasor measurements (voltage and current values in lines) -PMU-makes it possible to realize linear algorithms of state estimation. The paper suggests the development of the test equation technique for linear state estimation of power system facilities that are monitored on the basis of PMU measurements. New algorithms for the construction of the test equations on the basis of PMU measurements are presented. The algorithms are based on the exclusion of unmeasured variables or state vector components from the electrical circuit equations written in the rectangular coordinates. By virtue of linear nature of these equations the obtained test equations are also linear. The paper presents the algorithms for bad data detection in PMU measurements as well as the algorithms for calculation of estimates, using linear test equations which make it possible to obtain a solution within one iteration. Performance of the algorithms was tested on a test network equipped with PMUs. The developed algorithms allow us to make local state estimation of individual power system facilities (power plants, substations, network sections) that are monitored online on the basis of PMU measurements

“…The best result is when bad data detection (BDD) procedure is fulfilled a priory. For a priory BDD and SE the test equations (TE) method was developed [22]. The State Estimation algorithm can be reduced to minimization of objective function with constraints in the form of a system of TEs.…”

Section: ) State Estimation For Each Subsystemmentioning

confidence: 99%

Coordinated monitoring of large scale interconnected power systems

Gorner¹,

Rehtanz²,

2013 IEEE Power &Amp; Energy Society General Meeting

et al. 2013

This paper presents the final result of a joint EU and Russian project called ICOEUR (Intelligent Coordination of Operation and Emergency Control of EU and Russian Power Grids). The presented results are about the extension and interconnection of large scale power systems from the perspective of monitoring and control. In this paper the authors identify algorithms and monitoring technologies for the identification of full system states and dynamic behavior of system. The algorithms are validated with realistic models from the European and Russian power system. The results lead to a coordination platform which applies Distributed and Dynamic State Estimation in order to manage cross border flows.