Identification of fault location in power distribution system with distributed generation using support vector machines

This paper presents a multi-class support vector machine (SVMs) approach for locating and diagnosing faults in electric power distribution feeders with the penetration of Distributed Generations (DGs). The proposed approach is based on the three phase voltage and current measurements which are available at all the sources i.e. substation and at the connection points of DG. To illustrate the proposed methodology, a practical distribution feeder emanating from 132/11kV-grid substation in India with loads and suitable number of DGs at different locations is considered. To show the effectiveness of the proposed methodology, practical situations in distribution systems (DS) such as all types of faults with a wide range of varying fault locations, source short circuit (SSC) levels and fault impedances are considered for studies. The proposed fault location scheme is capable of accurately identify the fault type, location of faulted feeder section and the fault impedance. The results demonstrate the feasibility of applying the proposed method in practical in smart grid distribution automation (DA) for fault diagnosis.

Autocalibration of dynamic bacterial growth model for water distribution system using GA

The presence of residual chlorine and organic matter govern the bacterial regrowth within a water distribution system. The bacterial growth model is essential to predict the spatial and temporal variation of all these substances throughout the system. The parameters governing the bacterial growth and biodegradable dissolved organic carbon (BDOC) utilization are difficult to determine by experimentation. In the present study, the estimation of these parameters is addressed by using simulation-optimization procedure. The optimal solution by genetic algorithm (GA) has indicated that the proper combination of parameter values are significant rather than correct individual values. The applicability of the model is illustrated using synthetic data generated by introducing noise in to the error-free measurements. The GA was found to be a potential tool in estimating the parameters controlling the bacterial growth and BDOC utilization. Further, the GA was also used for evaluating the sensitivity issues relating parameter values and objective function. It was observed that mu and k(cl) are more significant and dominating compared to the other parameters. But the magnitude of the parameters is also an important issue in deciding the dominance of a particular parameter. GA is found to be a useful tool in autocalibration of bacterial growth model and a sensitivity study of parameters.

Water quality parameter estimation in steady-state distribution system

The maintenance of chlorine residual is needed at all the points in the distribution system supplied with chlorine as a disinfectant. The propagation and level of chlorine in a distribution system is affected by both bulk and pipe wall reactions. It is well known that the field determination of wall reaction parameter is difficult. The source strength of chlorine to maintain a specified chlorine residual at a target node is also an important parameter. The inverse model presented in the paper determines these water quality parameters, which are associated with different reaction kinetics, either in single or in groups of pipes. The weighted-least-squares method based on the Gauss-Newton minimization technique is used for the estimation of these parameters. The validation and application of the inverse model is illustrated with an example pipe distribution system under steady state. A generalized procedure to handle noisy and bad (abnormal) data is suggested, which can be used to estimate these parameters more accurately. The developed inverse model is useful for water supply agencies to calibrate their water distribution system and to improve their operational strategies to maintain water quality.

Neural network approach for fault location in unbalanced distribution networks with limited measurements

This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.

Parameter estimation in water-distribution systems by least squares

The weighted-least-squares method using sensitivity-analysis technique is proposed for the estimation of parameters in water-distribution systems. The parameters considered are the Hazen-Williams coefficients for the pipes. The objective function used is the sum of the weighted squares of the differences between the computed and the observed values of the variables. The weighted-least-squares method can elegantly handle multiple loading conditions with mixed types of measurements such as heads and consumptions, different sets and number of measurements for each loading condition, and modifications in the network configuration due to inclusion or exclusion of some pipes affected by valve operations in each loading condition. Uncertainty in parameter estimates can also be obtained. The method is applied for the estimation of parameters in a metropolitan urban water-distribution system in India.

Optimal scheduling of multiple chlorine sources in water distribution systems

The specified range of free chlorine residual (between minimum and maximum) in water distribution systems needs to be maintained to avoid deterioration of the microbial quality of water, control taste and/or odor problems, and hinder formation of carcino-genic disinfection by-products. Multiple water quality sources for providing chlorine input are needed to maintain the chlorine residuals within a specified range throughout the distribution system. The determination of source dosage (i.e., chlorine concentrations/chlorine mass rates) at water quality sources to satisfy the above objective under dynamic conditions is a complex process. A nonlinear optimization problem is formulated to determine the chlorine dosage at the water quality sources subjected to minimum and maximum constraints on chlorine concentrations at all monitoring nodes. A genetic algorithm (GA) approach in which decision variables (chlorine dosage) are coded as binary strings is used to solve this highly nonlinear optimization problem, with nonlinearities arising due to set-point sources and non-first-order reactions. Application of the model is illustrated using three sample water distribution systems, and it indicates that the GA,is a useful tool for evaluating optimal water quality source chlorine schedules.

Modeling Equitable Distribution of Water: Dynamic Inversion-Based Controller Approach

It is a well-known fact that most of the developing countries have intermittent water supply and the quantity of water supplied from the source is also not distributed equitably among the consumers. Aged pipelines, pump failures, and improper management of water resources are some of the main reasons for it. This study presents the application of a nonlinear control technique to overcome this problem in different zones in the city of Bangalore. The water is pumped to the city from a large distance of approximately 100km over a very high elevation of approximately 400m. The city has large undulating terrain among different zones, which leads to unequal distribution of water. The Bangalore, inflow water-distribution system (WDS) has been modeled. A dynamic inversion (DI) nonlinear controller with proportional integral derivative (PID) features (DI-PID) is used for valve throttling to achieve the target flows to different zones of the city. This novel approach of equitable water distribution using DI-PID controllers that can be used as a decision support system is discussed in this paper.

An algorithm for optimum control of static VAR compensators to meet phase-wise unbalanced reactive power demands

The operation of thyristor-controlled static VAR compensators (SVCs) at various conduction angles can be used advantageously to meet the unablanced reactive power demands in a system. However, such operation introduces harmonic currents into the AC system. This paper presents an algorithm to evaluate an optimum combination of the phase-wise reactive power generations from SVC and balanced reactive power supply from the AC system, based on the defined performance indices, namely, the telephone influence factor (TIF), the total harmonic current factor (IT) and the distortion factor (D). Results of the studies conducted on a typical distribution system are presented and discussed.

Minimization of the effects of harmonics and voltage dip caused by electric arc furnace

This study examines the thermal efficiency of the operation of arc furnace and the effects of harmonics and voltage dips of a factory located near Bangkok. It also attempts to find ways to improve the performance of the arc furnace operation and minimize the effects of both harmonics and voltage dips. A dynamic model of the arc furnace has been developed incorporating both electrical and thermal characteristics. The model can be used to identify potential areas for improvement of the furnace and its operation. Snapshots of waveforms and measurement of RMS values of voltage, current and power at the furnace, at other feeders and at the point of common coupling were recorded. Harmonic simulation program and electromagnetic transient simulation program were used in the study to model the effects of harmonics and voltage dips and to identify appropriate static and dynamic filters to minimize their effects within the factory. The effects of harmonics and voltage dips were identified in records taken at the point of common coupling of another factory supplied by another feeder of the same substation. Simulation studies were made to examine the results on the second feeder when dynamic filters were used in the factory which operated the arc furnace. The methodology used and the mitigation strategy identified in the study are applicable to general situation in a power distribution system where an arc furnace is a part of the load of a customer

The incongruous observation of magnetic phase separation in La0.85Sr0.15CoO3 spin glass system

Phase separation (PS) in hole-doped cobaltites (La1-xSrxCoxO3) is drawing renewed interest recently. In particular, the magnetic behavior of La0.85Sr0.15CoO3 has been subjected to a controversial debate for the past several years; while some groups show evidence for magnetic PS, others show spin glass (SG) behavior. Here, an attempt is made to resolve the controversy related to ``PS versus SG'' behavior in this compound. We present the results of a comprehensive investigation of the dc magnetization, ac susceptibility, and the magnetotransport properties of La0.85Sr0.15CoO3 samples. We contemplate that the magnetic PS in La0.85Sr0.15CoO3 is neither intrinsic nor inherent, but it is a consequence of the preparation conditions. It is realized that a low temperature annealed (LTA) sample shows PS whereas the high temperature annealed (HTA) sample shows SG behavior. The Brillouin-like behavior of field cooled dc magnetization and apparently no frequency dependent peak shift in ac susceptibility for the LTA sample characterize it to be of ferromagneticlike whereas a kink in field cooled dc magnetization and a considerable amount (similar to 3 K) of frequency dependent peak shift in the ac susceptibility for the HTA sample characterize it to be of SG state. The magnetotransport properties show that the HTA sample is more semiconducting as compared to the LTA sample. This is interpreted in terms of the presence of isolated as well as coalescing metallic ferromagnetic clusters in the case of LTA sample. The magnetoresistance (MR) at 10 K for the HTA sample exhibits a huge value (similar to 65%) as compared to the LTA sample, and it monotonically decreases with the rise in temperature. Such a high value of MR in the case of HTA sample is strongly believed to be due to the spin dependent part of random potential distribution. Further, the slow decay of remnant magnetization with progress of time and the existence of hysteresis at higher temperatures (up to 200 K) in the case of LTA sample as compared to the HTA sample clearly unveil different magnetic states associated with them.

Optimal reactive power dispatch based on voltage stability criteria in a large power system with AC/DC and FACTs devices

An algorithm for optimal allocation of reactive power in AC/DC system using FACTs devices, with an objective of improving the voltage profile and also voltage stability of the system has been presented. The technique attempts to utilize fully the reactive power sources in the system to improve the voltage stability and profile as well as meeting the reactive power requirements at the AC-DC terminals to facilitate the smooth operation of DC links. The method involves successive solution of steady-state power flows and optimization of reactive power control variables with Unified Power Flow Controller (UPFC) using linear programming technique. The proposed method has been tested on a real life equivalent 96-bus AC and a two terminal DC system under normal and contingency conditions.

Predictive distribution modeling for rare Himalayan medicinal plant Berberis aristata DC

Predictive distribution modelling of Berberis aristata DC, a rare threatened plant with high medicinal values has been done with an aim to understand its potential distribution zones in Indian Himalayan region. Bioclimatic and topographic variables were used to develop the distribution model with the help of three different algorithms viz. GeneticAlgorithm for Rule-set Production (GARP), Bioclim and Maximum entroys(MaxEnt). Maximum entropy has predicted wider potential distribution (10.36%) compared to GARP (4.63%) and Bioclim (2.44%). Validation confirms that these outputs are comparable to the present distribution pattern of the B. atistata. This exercise highlights that this species favours Western Himalaya. However, GARP and MaxEnt's prediction of Eastern Himalayan states (i.e. Arunachal Pradesh, Nagaland and Manipur) are also identified as potential occurrence places require further exploration.

Inference for the Component and System Lifetime Distribution of a k-unit Parallel System Based on System Data

In this paper, we consider the inference for the component and system lifetime distribution of a k-unit parallel system with independent components based on system data. The components are assumed to have identical Weibull distribution. We obtain the maximum likelihood estimates of the unknown parameters based on system data. The Fisher information matrix has been derived. We propose -expectation tolerance interval and -content -level tolerance interval for the life distribution of the system. Performance of the estimators and tolerance intervals is investigated via simulation study. A simulated dataset is analyzed for illustration.

Constraints on Be-10 and Ca-41 distribution in the early solar system from Al-26 and Be-10 studies of Efremovka CAIs

Three refractory coarse grained CAIs from the Efremovka CV3 chondrite, one (E65) previously shown to have formed with live Ca-41, were studied by ion microprobe for their Al-26-Mg-26 and Be-10-B-10 systematic in order to better understand the origin of Be-10. The high precision Al-Mg data and the inferred Al-26/Al-27 values attest that the precursors of the three CAIs evolved in the solar nebula over a period of few hundred thousand years before last melting-crystallization events. The initial Be-10/Be-9 ratios and delta B-10 values defined by the Be-10 isochrons for the three Efremovka CAIs are similar within errors. The CAI Be-10 abundance in published data underscores the large range for initial Be-10/Be-9 ratios. This is contrary to the relatively small range of Al-26/Al-27 variations in CAIs around the canonical ratio. Two models that could explain the origin of this large Be-10/Be-9 range are assessed from the collateral variations predicted for the initial delta B-10 values: (i) closed system decay of Be-10 from a ``canonical'' Be-10/Be-9 ratio and (ii) formation of CAIs from a mixture of solid precursors and nebula gas irradiated during up to a few hundred thousand years. The second scenario is shown to be the most consistent with the data. This shows that the major fraction of Be-10 in CAIs was produced by irradiation of refractory grains, while contributions of galactic cosmic rays trapping and early solar wind irradiation are less dominant. The case for Be-10 production by solar cosmic rays irradiation of solid refractory precursors poses a conundrum for Ca-41 because the latter is easily produced by irradiation and should be more abundant than what is observed in CAIs. Be-10 production by irradiation from solar energetic particles requires high Ca-41 abundance in early solar system, however, this is not observed in CAIs. (C) 2013 Elsevier B.V. All rights reserved.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.