• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.425-426
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• 2007

In power systems operation, state estimation takes an important role in security control. For the state estimation problem, conventional optimization algorithm, such as weighted least squares (WLS) method, has been widely used. But these algorithms have disadvantages of converging local optimal solution. In these days, a modern heuristic optimization methods such as Particle Swarm Optimization (PSO), are introducing to overcome the problems of classical optimization. In this paper, we suggested parallel particle swarm optimization (PPSO) to search an optimal solution of state estimation in power systems. To show the usefulness of the proposed method over the conventional PSO, proposed method is applied on the IEEE-57 bus system.

• 한국수소및신에너지학회논문집
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• 제27권1호
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• pp.36-41
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• 2016

The development need of new renewable energy is more and more important to resolve exhaustion of chemical fuels and environmental pollution. Polymer electrolyte membrane fuel cell has been widely studied to the extent that it can be used commercially. But there are many problems to be solved. One of them is to enhance the stability of fuel cell stacks. This paper proposes a new fault diagnosis method using Least Square Method (LSM) which is one of parameter estimation methods. The proposed method extracts equivalent circuit parameters from on-line measurements. Parameters of the circuit are estimated according to normal and abnormal states using simulation. The variation of parameters estimated in each states enables the estimation of state in fuel cells. Thus the LSM presented can be a suitable on-line parameter estimation method in PEMFC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1464-1468
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• 1997

We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.

• 대한전기학회논문지
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• 제33권9호
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• pp.364-371
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• 1984

This paper describes a method for the state estimation in electric power system. The state values are estimated through the weighted least square method considering the bad data. Then, the bad data are identified by using sensitivity coefficients of power system after being detected the bad data through the distribution of T. This method was applied to the model power system, and, the results of test for proposed method are given.

• 전기학회논문지P
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• 제57권2호
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권4호
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• pp.137-143
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• 2002

Because Block Pulse functions are used in a variety of fields such as the analysis and controller design of systems, it is necessary to find the more exact value of the Block Pulse series coefficients. This paper presents a method for the state estimation of the time-invariant linear systems via the improved estimation method for the Block Pulse coefficients by using the Simpson's rule. The proposed method using the Simpson's rule improve the accuracy of the Block Pulse coefficients.

• 대한조선학회논문집
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• 제40권5호
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• pp.43-52
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• 2003

Two methods which estimate manoeuvring derivatives in the model of hydrodynamic force and moment acting on a manoeuvring ship using sea trial data were compared. One is the widely used parameter estimation method by using the Extended Kalman Filter (EKF), which estimates state variables of linearized state space model at every instant after dealing with the coefficients as the augmented state variables. The other one is the Estimation-Before-Modeling (EBM) technique, so called the two-step method. In the first step, hydrodynamic force of which dynamic model is assumed the third-order Gauss-Markov process is estimated along with motion variables by the EKF and the modified Bryson-Frazier smoother. Then, in the next step, manoeuvring derivatives are identified through the regression analysis. If the exact structure of hydrodynamic force could be known, which was an ideal case, the EKF method would be regarded as being more superior compared to the EBM technique. However the EBM technique was more robust than the EKF method from a realistic point of view where the assumed model structure was slightly different from the real one.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
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• pp.279-281
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• 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.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2016년도 전력전자학술대회 논문집
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• pp.309-310
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• 2016

Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

• ETRI Journal
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• 제36권1호
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• pp.134-140
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• 2014

Many reports have shown that the access pattern for geospatial tiles follows Zipf's law and that its parameter ${\alpha}$ represents the access characteristics. However, visits to geospatial tiles have temporal and spatial popularities, and the ${\alpha}$-value changes as they change. We construct a mathematical model to simulate the user's access behavior by studying the attributes of frequently visited tile objects to determine parameter estimation algorithms. Because the least squares (LS) method in common use cannot obtain an exact ${\alpha}$-value and does not provide a suitable fit to data for frequently visited tiles, we present a new approach, which uses a moment method of estimation to obtain the value of ${\alpha}$ when ${\alpha}$ is close to 1. When ${\alpha}$ is further away from 1, the method uses the associated cache hit ratio for tile access and uses an LS method based on a critical cache size to estimate the value of ${\alpha}$. The decrease in the estimation error is presented and discussed in the section on experiment results. This new method, which provides a more accurate estimate of ${\alpha}$ than earlier methods, promises more effective prediction of requests for frequently accessed tiles for better caching and load balancing.