Sharif Digital Repository

The state estimation (SE) is a fundamental data processing algorithm used by the control centers of modern power networks. The most widely used state estimator is rooted to the weighted least squares (WLS) estimator which is not sufficiently robust to the gross errors in the measurements. This paper, presents a new robust algorithm for power system SE environments. The proposed approach not only has the comparative performance of the conventional loss function based on the estimator of the WLS additionally, it also considers loss function based on the quasi weighted least squares (QWLS) estimator. The performance analysis is evaluated on the ability of the state estimator for reducing the... 

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state estimator is used. Some modifications are proposed to avoid the singularity of the observer gain. The second controller is designed based on the reduced state equation. Through computer simulations, it has been shown that the performances of the second GLC is superior and it is more robust to process... 

This paper presents a hierarchically distributed algorithm for the execution of distribution state estimation function in active networks equipped with some phasor measurement units. The proposed algorithm employs voltage-based state estimation in rectangular form and is well-designed for large-scale active distribution networks. For this purpose, as the first step, the distribution network is supposed to be divided into some overlapped zones and local state estimations are executed in parallel for extracting operating states of these zones. Then, using coordinators in the feeders and the substation, the estimated local voltage profiles of all zones are coordinated with the local state... 

Fuel cells belong to an avant-garde technology family for a wide variety of applications including micro-power, transportation power, stationary power for buildings and other distributed generation applications. The first objective of this contribution is to find a suitable reduced model of a Solid Oxide Fuel Cell (SOFC). The derived reduced model is then used to design a state estimator. In the first step, the distributed model of the SOFC that is derived using the first principle balance equations is solved by the method of lines. Since this model is too complex and sluggish for real-time applications, a representation of this model with lower number of states and good accuracy is needed.... 

This paper concerns molecular weight control of a batch polymerization reactor where suspension polymerization of methyl methacrylate(MMA) takes place. For this purpose, a cascade control structure with two control loops has been selected. The slave loop is used for temperature control using on-line temperature measurements, and the master loop controls the average molecular weights based on its estimated values. Two different control algorithms namely proportional-integral(PI) controller and globally linearizing controller (GLC) have been used for temperature control. An estimator, which has the structure of an extended Kalman filter (EKF), is used for estimating monomer conversion and... 

This paper concerns non-linear state estimation in a batch polymerization reactor where suspension polymerization of methyl methacrylate takes place. A kinetic model proposed in the literature is selected and its validity has been verified through an experimental set-up. Based on this model monomer conversion and average molecular weights of the polymer are estimated using only one output measurement (reactor temperature). The performance of the estimator, which has the structure of an extended Kalman filter, is examined through simulation and experimental studies in the presence of different levels of parameter uncertainties. The effects of adding 'fictitious noise' and parameter state' to... 

The dynamic state estimation (DSE) applied to power systems with synchrophasor measurements would estimate the system's true state based on measurements and predictions. In this application, as phasor measurement units (PMUs) are not deployed at all power system buses, state predictions would enhance the redundancy of DSE input data. The significance of predicted and measured data in DSE is affected by their confidence levels, which are inversely proportional to the corresponding variances. In practice, power system states may undergo drastic changes during hourly load fluctuations, component outages, or network switchings. In such conditions, the inclusion of predicted values could degrade... 

Harmonic State Estimation (HSE) is a technique for identifying harmonic distributions in power systems with limited measurements. The main problem in HSE is the optimal placement of measurement meters such that the estimation error is minimized, while making the system fully observable. The second issue is the HSE method. This method must be accurate and fast enough in order to have an accurate HSE. This paper presents a new algorithm that uses minimum variance criterion (MVC) and a sequential method for optimal meters placement, SVD method for observability analysis and finally WLS method for harmonic estimation. The proposed method minimizes the number of measurement devices and the error... 

Partial state estimation of dynamical systems provides significant advantages in practical applications. Likewise, pre-compensator design for multi variable systems invokes considerable increase in the order of the original system. Hence, applying functional observer to pre-compensated systems can result in lower computational costs and more practicability in some applications such as fault diagnosis and output feedback control of these systems. In this note, functional observer design is investigated for pre-compensated systems. A lower order pre-compensator is designed based on a H2 norm optimization that is designed as the solution of a set of linear matrix inequalities (LMIs). Next, a... 

In this paper, a framework for distributed and decentralized state estimation in high-pressure and long-distance gas transmission networks (GTNs) is proposed. The non-isothermal model of the plant including mass, momentum and energy balance equations are used to simulate the dynamic behavior. Due to several disadvantages of implementing a centralized Kalman filter for large-scale systems, the continuous/discrete form of extended Kalman filter for distributed and decentralized estimation (DDE) has been extended for these systems. Accordingly, the global model is decomposed into several subsystems, called local models. Some heuristic rules are suggested for system decomposition in gas pipeline... 

In this paper a novel fuzzy approach exploiting Active Learning Method is employed in order to estimate the immeasurable states required to control a non-observable double inverted pendulum. Active Learning Method (ALM) is a fuzzy modeling method which exploits Ink Drop Spread (IDS) as its main engine. IDS is a universal fuzzy modeling technique which is very similar to the way human brain processes different phenomena. The ALM system is trained by the data obtained from Linear Quadratic Regulator (LQR) controller. LQR uses an optimal control approach which under certain conditions guarantees robustness. Instead of an expert's knowledge, the LQR controller output is used as a priori... 

Due to the lack of data in active distribution networks, employing new accurate measurement devices like phasor measurement units (PMUs) and micro-PMUs with a high reporting rate becomes an inevitable choice for the future vision of distribution systems. As a result, different algorithms have been presented to optimally place PMUs cost-effectively based on the estimation errors of the distribution state estimation (DSE) results. However, any component failure in measurement devices or communication links between sending ends and monitoring system of the distribution management system can significantly affect the DSE results. In response, this study introduces the reliability of satisfying... 

This paper presents a new and efficient formulation for the state estimation (SE) which can be solved in one single shot of computation. The proposed approach adopts line flows and the square of voltage magnitudes as the problem state variable and considers both active and reactive power quantities. The objective function is to minimize the weighted sum of the least square values of measurement residuals. The nonlinearity associated with line losses is left by assuming these values as slack variables. Numerical studies are conducted through two standard networks. In order to compare the performance of the proposed method, the conventional weighted least square (WLS) state estimation with... 

State estimation in power engineering is used as a tool to find the unknown parameter values from the hypothesized model by utilizing the specified information available about the system. Due to random noises that are added from different sources, the exact value of the state vector cannot be found. This study is an effort to describe the simultaneous and individual confidence intervals for the state parameters in view of the heteroscedastic structure of the error terms. The performance of the constructed intervals in terms of coverage probability has been evaluated by using the Monte Carlo simulation study. The results of the study demonstrate that it is an effective method for practical... 

Harmonic state estimation (HSE) method has been used to locate harmonic sources and estimate harmonic distribution in power systems with limited number of harmonic meters. This paper focuses on a new technique for optimal placement of measurement devices and observability analysis for power systems harmonic state estimation. The proposed method optimizes the number of measurements and minimizes the error of estimation at the same time. The method is tested on the IEEE 14-bus power system to show its precision  

In this paper, a new algorithm for fault detection/location on transmission line based on linear state estimation is presented. The proposed technique uses phasor measurements from PMU's. Fault location and voltage of fault point are added as the new state variables in a linear state estimator based on PMU data. In addition, by using the ability of bad data identification in the state estimation, a new scheme for fault location and identification of faulted transmission line is proposed. For test and validation of the proposed algorithm, simulation results on a six bus test case are presented. ©2009 IEEE