• Proceedings of the KIEE Conference
• /
• 1988.11a
• /
• pp.107-110
• /
• 1988

The quadratic cost function J(x) and the normalized residuals $r_N$ are conventionally used for identifying the presence and location of bed measurements in power system state estimation. These are "post estimation" tests and therefore require the complete re-estimation of system states whenever bed data is identified. This paper presents a pre-filter for reducing errors of the raw measurements using an adaptive filter. Each measurement is processed by the adaptive filter before being used in the state estimation. The performance of the adaptive filter is tested and the results are shown in this paper.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.11
• /
• pp.2101-2106
• /
• 2009

The power system state estimation and prediction are very important for operation. Because that accidents of the Power system are the cause that many devices and etc are damaged. Currently, almost every power systems have 2nd,3rd back-upsystem for prevention of accident. But prevention of accident by miss-operation, due to operator or miss data, has not acounter plan. Because, we need to estimate the power system for correcting miss data and preventing miss operation by operator. We suggest algorithm for integrity of power system network data.

• Proceedings of the KIEE Conference
• /
• 1999.11b
• /
• pp.279-281
• /
• 1999

This paper addresses the issues of the parameter error detection and identification in power system. The parameter error identification is carried out as part of the state estimation procedure. The weighted least absolute value(WLAV) estimation method is used for this procedure. The standard formulation of the state estimation problem is modified to include the effects of the parameter errors as well. A two step procedure for the detection and identification of faulted parameters is proposed. Supporting examples are given using IEEE 14 bus system.

• Proceedings of the KIPE Conference
• /
• 2007.07a
• /
• pp.369-371
• /
• 2007

Due to the measurement noise or system noise, the performance of photovoltaic power generation system can be degraded. If this noise is contained in the solar array voltage measurement signal, the correct operation of the maximum power point tracker can not be guaranteed. The application of the extended Kalman filter to the photovoltaic system can obtain enhanced states estimation result. The Kalman filter provides a recursive solution to optimally estimate from random noise signals. Additionally, as a consequence of Kalman filter, the unmeasurable state such as inductor current can be estimated without current sensor. The methods for system modeling and extended Kalman filter design are presented and the experimental results verify the validity of the proposed system.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.5
• /
• pp.1729-1738
• /
• 2014

The offline verification of state of charge estimation, power estimation, fault diagnosis and emergency control of battery management system (BMS) is one of the key technologies in the field of electric vehicle battery system. It is difficult to test and verify the battery management system software in the early stage, especially for algorithms such as system state estimation, emergency control and so on. This article carried out the virtual environment modeling for verification of battery management system. According to the input/output parameters of battery management system, virtual environment is determined to run the battery management system. With the integration of the developed BMS model and the external model, the virtual environment model has been established for battery management system in the vehicle's working environment. Through the virtual environment model, the effectiveness of software algorithm of BMS was verified, such as battery state parameters estimation, power estimation, fault diagnosis, charge and discharge management, etc.

• Journal of Electrical Engineering and Technology
• /
• v.9 no.2
• /
• pp.461-470
• /
• 2014

This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.

• Proceedings of the KIEE Conference
• /
• 2000.11a
• /
• pp.129-131
• /
• 2000

We must precisely understand the current state of system for efficiently and safely operating the power system of subway and it is the important problem to secure the high-quality data for state estimation. The current state of subway system is calculated by data to be transmitted to central control office from every place to install the measuring instruments so the high accuracy and trust can be maintained if the measured data have a high quality. But it is difficult to estimate the accurate state of system because of the noises in transit data and the inaccuracy due to errors of measuring instruments. So the object is to reduce the difference from the real value in terms of improving considerably the inaccuracy due to instrumental errors and noises using the state estimation method. In this paper we estimate the accurate state of the subway power system in the arbitrary measured values of a Sangin station in Deagu subway, and consider the possibility to apply to the real subway power system on the basis of that. This test shows to make sure of the possibility to apply to the real system usefully.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.2
• /
• pp.107-117
• /
• 1992

This paper presents an improved algorithm of optimal measurement design with a reliability evaluation method for a large power system. The proposed algorithm is developed to consider the dummy bus and to achieve highest accuracy of the state estimator as well with the limited investment cost. The dummy bus in the power system is impossible to install measurement meter, while real and reactive power measurements is considered in the proposed algorithm. On the other hand, P/C model is developed by taking advantage of the matrix sparsity. The improved program is successfully tested for KEPCO system with PSS/E lineflow calculated data package.

• Proceedings of the KIEE Conference
• /
• 1996.11a
• /
• pp.182-185
• /
• 1996

The purpose of slate estimation in power system is to estimate the best-fit Slate variables from the measurements contaminated by various kind of noise. But because the majority of state estimation modules in EMS lack the convergence characteristics, sometimes the desirable outputs can't be obtained. So, in this paper, the new algorithm using the load now output as initial values in the state estimation calculation is proposed to guarantee the convergence. And if the load now outputs were used as the initial values in the calculation, the change in each step would be small compared to the original method using the flat start point. And the Inverse Lemma is used in the algorithm to calculate the new stale in each iteration step for reducing the calculation time. The proposed algorithm was tested on the IEEE 14, 30, 118 bus systems. Eventually, we were able to verity that the differences between the results obtained by the original method and proposed method were relatively small, and the effectiveness of the proposed algorithm increased when applied to the bigger systems.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.49 no.6
• /
• pp.259-265
• /
• 2000

The purpose of this paper is to detect and identify topological errors in order to maintain a reliable database for the state estimator. In this paper, a two stage estimation procedure is used to identify the topology errors. At the first stage, the WSAV state estimator which has characteristics to remove bad data during the estimation procedure is run for finding out the suspected branches at which topology errors take place. The resulting residuals are normalized and the measurements with significant normalized residuals are selected. A set of suspected branches is formed based on these selected measurements; if the selected measurement is a line flow, the corresponding branch is suspected; if it is an injection, then all the branches connecting the injection bus to its immediate neighbors are suspected. A new WLAV state estimator adding the branch flow errors in the state vector is developed to identify the branch topology errors. Sample cases of single topology error and topology error with a measurement error are applied to IEEE 14 bus test system.