An ANN based approach for voltage stability assessment

Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.

Modeling of room temperature current-voltage measurements on homo-junction HgCdTe diodes exhibiting nonequilibrium effects

HgCdTe mid wave infrared (MWIR) n(+)/nu/p(+) homo-junction photodiodes with planar architecture are designed, fabricated, and measured at room temperature. An improved analytical I-V model is reported by incorporating trap assisted tunneling and electric field enhanced Shockley-Read-Hall generation recombination process due to dislocations. Tunneling currents are fitted before and after the Auger suppression of carriers with energy level of trap (E-t), trap density (N-t), and the doping concentrations of n(+) and nu regions as fitting parameters. Values of E-t and N-t are determined as 0.79 E-g and similar to 9 x 10(14) cm(-3), respectively, in all cases. Doping concentration of nu region was found to exhibit nonequilibrium depletion from a value of 2 x 10(16) to 4 x 10(15) cm(-3) for n(+) doping of 2 x 10(17) cm(-3). Pronounced negative differential resistance is observed in the homo-junction HgCdTe diodes. (C) 2012 American Institute of Physics. [doi:10.1063/1.3682483]

Voltage stability : some reflections on Q-V characteristics of loads

Considering voltage stability as a static viability problem, this paper takes a particular concern of Q-V characteristics and reflects on certain notions that do not seem to have been explicitly mentioned or derived in the existing documented literature. The equations of Q-V characteristics are rederived in exactness, some salient points on the curve are discovered and analysed. The results of the analysis are illustrated through a case study

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

Artificial neural network application to power system voltage stability improvement

As power systems grow in their size and interconnections, their complexity increases. Rising costs due to inflation and increased environmental concerns has made transmission, as well as generation systems be operated closer to design limits. Hence power system voltage stability and voltage control are emerging as major problems in the day-to-day operation of stressed power systems. For secure operation and control of power systems under normal and contingency conditions it is essential to provide solutions in real time to the operator in energy control center (ECC). Artificial neural networks (ANN) are emerging as an artificial intelligence tool, which give fast, though approximate, but acceptable solutions in real time as they mostly use the parallel processing technique for computation. The solutions thus obtained can be used as a guide by the operator in ECC for power system control. This paper deals with development of an ANN architecture, which provide solutions for monitoring, and control of voltage stability in the day-to-day operation of power systems.

Novel algorithm for online voltage stability assessment based on feed forward neural network

This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

Simulation of surface and volume stress for high voltage transmission insulators

The bulk of power transmission from the generating stations to the load centres is carried through overhead lines. The distances involved could span several hundreds of kilometres. To minimize line losses, power transmission over such long distances is carried out at high voltages (several hundreds of kV). A network of outdoor lines operating at different voltages has been found to be the most economical method of power delivery. The disc insulators perform dual task of mechanically supporting and electrically isolating the live phase conductors from the support tower. These insulators have to perform under various environmental conditions; hence the electrical stress distribution along the insulators governs the possible flashover, which is quite detrimental to the system. In view of this the present investigation aims to simulate the surface electric field stress on different types of porcelain/ceramic insulators; both normal and anti-fog type discs which are used for high voltage transmission/distribution systems are considered. The surface charge simulation method is employed for the field computation to simulate potential, electric field, surface and bulk/volume stress.

Optimization of vibrating structures to reduce radiated noise

In this work, we propose an approach for reducing radiated noise from `light' fluid-loaded structures, such as, for example, vibrating structures in air. In this approach, we optimize the structure so as to minimize the dynamic compliance (defined as the input power) of the structure. We show that minimizing the dynamic compliance results in substantial reductions in the radiated sound power from the structure. The main advantage of this approach is that the redesign to minimize the dynamic compliance moves the natural frequencies of the structure away from the driving frequency thereby reducing the vibration levels of the structure, which in turn results in a reduction in the radiated sound power as an indirect benefit. Thus, the need for an acoustic and the associated sensitivity analysis is completely bypassed (although, in this work, we do carry out an acoustic analysis to demonstrate the reduction in sound power levels), making the strategy efficient compared to existing strategies in the literature which try to minimize some measure of noise directly. We show the effectiveness of the proposed approach by means of several examples involving both topology and stiffener optimization, for vibrating beam, plate and shell-type structures.

Dynamic Supply and Threshold Voltage Scaling for CMOS Digital Circuits Using In-Situ Power Monitor

A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.