Murat Gol

State-Estimation-Based Determination of Harmonic Current Contributions of Iron and Steel Plants Supplied from PCC

In this paper, a state-estimation-based method is proposed to determine harmonic current contributions of iron and steel (IS hence, it provides accurate harmonic contributions of the electric arc furnace (EAF) plants.

A modified Chi-Squares test for improved bad data detection

Current state estimators employ the Weighted Least Squares (WLS) estimator to solve the state estimation problem. Once the state estimates are obtained, Chi-Square test is commonly used to detect the presence of bad data in the measurement sets. Regretfully, this test is not entirely reliable, that is, bad data existing in the measurement set could be missed for certain cases. One reason for this is the approximations used to compute the bad data suspicion threshold, which is set based on an assumed chi-squares distribution for the objective function. In this paper, a modified metric is proposed in order to improve the bad data detection accuracy of the commonly used chi-square test. The bad data detection performance of the proposed test is compared with that of conventional chi-square test.

Fault location based on state estimation in PMU observable systems

Accurate location of a fault on a line is extremely important to restore the line in the shortest time possible, which directly affects the operational cost and system reliability. This paper presents an accurate and computationally fast strategy for fault location based on well-known state estimation method. The proposed method employs PMU measurements recorded during the fault (before the circuit breakers open). Those measurements are used for determination of the fault currents flowing on the faulted line and locating the fault using Weighted Least Squares (WLS) estimator. The proposed method reduces the required number of measurements for the solution of the fault location problem by making use of the fast refresh rates of the PMUs. This work also presents comments on the selection of the initial values of the iterative fault location estimation problem. Simulation results are presented to validate the proposed method.

Determination of harmonic current contributions of plants supplied from PCC based on state estimation

In this paper, a state estimation based method is proposed to determine harmonic current contributions of plants supplied from a Point of Common Coupling (PCC). By using Weighted Least Squares (WLS) state estimation, it is aimed to improve harmonic voltage measurements acquired from conventional voltage transformers, which are employed commonly in the power systems. Using measured harmonic currents and estimated harmonic voltages, harmonic contributions of all plants have been determined by employing the Norton equivalent circuits of the plants and the superposition theorem. Absence of reliable harmonic voltage measurements necessitates employing harmonic filter current measured from at least one of the plants. Using the new measurement set built after the estimation process, a model to determine the harmonic current contribution of plants supplied from a PCC has been developed.

A Decentralization Method for Hybrid State Estimators

Hybrid state estimation determines the states of systems monitored both by conventional SCADA measurements and PMUs. This paper proposes a decentralization method in order to improve the computational performance of hybrid state estimators with minimum loss of accuracy. The proposed method utilizes sensitivity matrix that relates measurement errors to state estimates in order to form the so-called isolated bus groups and observable subislands. Although the proposed decentralization method can be applied to any state estimator, the paper is developed using a least absolute value (LAV) estimator for demonstration purposes, which is known to be robust against bad data. The high computational burden of LAV estimator compared to the well-known weighted least squares estimator is eliminated, thanks to the proposed decentralization method.

Identification of bad solar power generation data

In this paper, a novel method has been presented for the bad data identification of the data recovery process from a solar power measurement data set. Due to failures in solar power measurement logging devices, a long period of solar power generation data might necessary to be recovered. In order to ensure that the recovered data is the correct one, the daily solar generation curve has to be investigated. Due to the high data amount, this control process has to be done automatically. It is observed that the daily solar generation curve is much similar to cosine wave. In this study, the recovered data is compared to reference cosine wave and it is aimed to identify the suspicious data group. In this context, this work is based on the normalized residuals test.

Voltage variation model for DC catenary line of a subway system

Considering the increasing number of electrified traction systems and changing technological advances in power electronics industry, it is required to successfully model electrified train systems. In this paper a DC catenary voltage model is proposed for a multi substation subway system. The proposed method is capable of simulating dynamic behavior of the train during different modes of operation. In this study, firstly, the electrical parameters of the system will be found to form distributed parameter model. In order to simplify analytic calculations, an approximate yet accurate solution method is proposed. Secondly, relations modeling voltage variation are linearized for improved computational performance. Finally, developed model is extended to multi substation case. Developed model is verified using real field data.

Evaluation of the effects of photovoltaic systems on voltage quality

Because of the governmental incentives, the distributed photovoltaic systems are populating rapidly in Turkish Electric System. This work aims to evaluate the effects of those plants to the electrical system in terms of voltage quality by focusing on the specific example of the solar plant being built under the National Solar Power Plant Development Project (Milli Günes Enerjisi Santrali Gelistirilmesi Projesi, MILGES). In order to be able to evaluate the effects of the PV system under the most challenging situations in terms of power quality, it is assumed that the solar plant is connected to a substation that also supplies an iron and steel plant with an electric arc furnace (EAF). The EAF system is modeled based on the collected real field data, while PV system parameters are obtained from the project documents.

Binary integer programming based PMU placement in the presence of conventional measurements

This paper proposes an optimal Phasor Measurement Unit (PMU) placement method based on a modified version of the well-known binary integer linear programming formulation, which will utilize the installed PMUs and conventional measurements, i.e. active and reactive power flow and power injection measurements, to reduce the number of PMUs to be placed required for system observability. The proposed method applies conventional observability analysis to evaluate the system of concern and to reduce the size of the PMU placement problem. The analysis is followed by the proposed modified optimal PMU placement method. Although the method is applicable to PMUs with any number of channels, the paper employs branch PMUs, i.e. PMUs with single voltage phasor and single current phasor channels, since this is the most common PMU type in industry. The method is illustrated by a tutorial example and validated on IEEE 14-bus and 30-bus test systems.

A robust parameter estimation method based on LAV estimator

In a power system, it is known that parameters may carry small errors due to the weather conditions, such as temperature and humidity changes, as well as gross errors due to the miscommunication between the control center and circuit breakers and tap changers. Those incorrect parameters may cause biased state estimates, which may have serious results. Therefore, those parameter errors should be identified and corrected. Considering the increasing number of Phasor Measurement Units (PMUs), in this paper it is proposed to use PMU measurements in local parameter estimation. The developed parameter estimation will employ the robust Least Absolute Value (LAV) estimator to obtain unbiased estimates even in the presence of bad measurements.