scholarly journals Impact of Quadrature Booster on Power-System State Estimation in Polar Coordinates

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5992
Author(s):  
Tomasz Okon ◽  
Kazimierz Wilkosz
Keyword(s):  
Comparative Analysis ◽  
Power System ◽  
Coordinate System ◽  
State Estimation ◽  
Phase Shifter ◽  
Test System ◽  
The State ◽  
Polar Coordinate System ◽  
Estimation Process ◽  
Number Of Iterations

The paper concerns the estimation of the state of a power system in which there is a phase shifter called a quadrature booster. The aim of the paper is a comparative analysis of two different cases including the quadrature booster in the state estimation. In the first case, the quadrature booster is represented by a model consisting of two real voltage sources, one in series with a power line and the other in a shunt branch. In the second case, in the power system model, the real branch with the quadrature booster is represented as off at the end where the considered quadrature booster is actually installed. The state estimation is assumed to be carried out in the polar coordinate system. The properties of the state estimation are characterized by: the number of iterations in the calculation process, the index of conditioning of the matrix of coefficients in the equations to be solved (cond(G)), and ratio Je/Jm, which is a measure of the accuracy of the estimation. Using IEEE 14-bus test system, investigations are carried out in such a way as to cover the entire state space of the power system as possible. In the investigations, Monte Carlo experiments are carried out for each of the considered cases of the state estimation. Each of these cases is also analyzed from the point of view of the assumed definition of the state estimation. Investigations show that in the first of the previously described cases, the state estimation is more accurate, but there are more iterations in the calculations and worse conditioning of the estimation process. The comparative analysis also shows that, the accuracy of the results obtained in each of the considered cases is practically independent of the coordinate system in which the estimation calculations are performed. Taking into account the number of iterations in the estimation process and index cond(G), it can be concluded that the implementation of each of the above-mentioned estimation cases in the rectangular coordinate system is more reasonable.

scholarly journals State Estimation for Cooperative Lateral Vehicle Following Using Vehicle-to-Vehicle Communication

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 651
Author(s):  
Wouter Schinkel ◽  
Tom van der Sande ◽  
Henk Nijmeijer
Keyword(s):  
State Estimation ◽  
Cooperative Control ◽  
The State ◽  
State Estimator ◽  
Estimation Process ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Control Schemes ◽  
Input Signals ◽  
Vehicle To Vehicle Communication

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.

scholarly journals Methodology for Implementing the State Estimation in Renewable Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2301
Author(s):  
Yun-Sung Cho ◽  
Yun-Hyuk Choi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
State Estimation ◽  
Measurement Errors ◽  
Large Scale ◽  
Test System ◽  
The State ◽  
Inner Function ◽  
Outer Function ◽  
Bad Data

This paper describes a methodology for implementing the state estimation and enhancing the accuracy in large-scale power systems that partially depend on variable renewable energy resources. To determine the actual states of electricity grids, including those of wind and solar power systems, the proposed state estimation method adopts a fast-decoupled weighted least square approach based on the architecture of application common database. Renewable energy modeling is considered on the basis of the point of data acquisition, the type of renewable energy, and the voltage level of the bus-connected renewable energy. Moreover, the proposed algorithm performs accurate bad data processing using inner and outer functions. The inner function is applied to the largest normalized residue method to process the bad data detection, identification and adjustment. While the outer function is analyzed whether the identified bad measurements exceed the condition of Kirchhoff’s current law. In addition, to decrease the topology and measurement errors associated with transformers, a connectivity model is proposed for transformers that use switching devices, and a transformer error processing technique is proposed using a simple heuristic method. To verify the performance of the proposed methodology, we performed comprehensive tests based on a modified IEEE 18-bus test system and a large-scale power system that utilizes renewable energy.

scholarly journals Distributed State Estimation of Multi-region Power System based on Consensus Theory

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 900 ◽  
Author(s):  
Shiwei Xia ◽  
Qian Zhang ◽  
Jiangping Jing ◽  
Zhaohao Ding ◽  
Jing Yu ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
State Estimation ◽  
Solution Method ◽  
The State ◽  
Rapid Expansion ◽  
Estimation Model ◽  
Consensus Theory ◽  
Distributed State Estimation ◽  
Bus System

Effective state estimation is critical to the security operation of power systems. With the rapid expansion of interconnected power grids, there are limitations of conventional centralized state estimation methods in terms of heavy and unbalanced communication and computation burdens for the control center. To address these limitations, this paper presents a multi-area state estimation model and afterwards proposes a consensus theory based distributed state estimation solution method. Firstly, considering the nonlinearity of state estimation, the original power system is divided into several non-overlapped subsystems. Correspondingly, the Lagrange multiplier method is adopted to decouple the state estimation equations into a multi-area state estimation model. Secondly, a fully distributed state estimation method based on the consensus algorithm is designed to solve the proposed model. The solution method does not need a centralized coordination system operator, but only requires a simple communication network for exchanging the limited data of boundary state variables and consensus variables among adjacent regions, thus it is quite flexible in terms of communication and computation for state estimation. In the end, the proposed method is tested by the IEEE 14-bus system and the IEEE 118-bus system, and the simulation results verify that the proposed multi-area state estimation model and the distributed solution method are effective for the state estimation of multi-area interconnected power systems.

State Estimation of Power System Based on Taylor Series Method

2014 ◽  
Vol 960-961 ◽  
pp. 1039-1042
Author(s):  
Gui Hua Lin ◽  
Yu Ying Wang ◽  
Tao Wang
Keyword(s):  
Power System ◽  
State Estimation ◽  
Taylor Series ◽  
Calculation Method ◽  
Measurement Data ◽  
The State ◽  
System State ◽  
Series Method ◽  
State Time ◽  
Taylor Series Method

Take full advantage of the PMU's accurate mass measurement data is the effective method to improve the calculation accuracy of power system state estimation. This essay puts forward the state estimation method of power system based on the Taylor series method. It analysis of power system operating conditions based on the real-time measurement of Wide area measurement system, divides the state time, establishes the equation of state of the measurement data by curve fitting method in the period of state time, creates a new state estimation calculation method by Taylor series method, constructs a new voltage characteristic curve calculation method, determines the system state and achieve the continuity of power systems steady-state analysis. The method put forward in this essay has been verified through IEEE-30 Node System, and the efficiency of it has been fully proved by the example results.

Weight Set of State Estimation Based on Partition

2013 ◽  
Vol 347-350 ◽  
pp. 2077-2081
Author(s):  
Jia Yi Zang
Keyword(s):  
Power System ◽  
State Estimation ◽  
Great Influence ◽  
Local Area ◽  
The State ◽  
Estimation Result ◽  
System State ◽  
Power System State Estimation ◽  
Accuracy Of Measurement ◽  
Bad Data

In power system state estimation, bad data of local area can make state estimation difficult, and accuracy of measurement can also have great influence on the result of state estimation. Based on grid partition, this paper forms a lot of independent sub area, then measurement weights are adjusted using the state estimation result of sub area. This overcomes the defects of uniform weights distribution, and improves the accuracy of state estimation

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

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