A new reactive,distortion and non-active power measurement method for nonstationary waveforms using wavelet packet transform

The definitions of power components that are contained in the IEEE Standard 1459-2000 [IEEE Std. 1459-2000, Definitions for the measurement of electric quantities under sinusoidal, non-sinusoidal, balanced or unbalanced conditions, 2000] are based on the Fourier transform (FT) which is suitable only for the case of stationary waveforms. However, for nonstationary waveforms, the FT produces large errors. Therefore, the power components based on this transform become inaccurate. A new approach based on the wavelet packet transform (WPT) for defining these power components is developed in this paper. The advantages of using the wavelet transform are that it can accurately represent and measure nonstationary waveforms, providing uniform frequency bands while preserving both time and frequency information. In addition, this paper addresses the problem of choosing the most appropriate mother wavelet for power components measurements. The results of applying both approaches to stationary and nonstationary waveforms show that the currently used definitions according to the IEEE Standard 1459-2000 result in large errors for the case of nonstationary waveforms while the proposed approach (WPT based) gives more accurate results in this situation.     

Selection of objectives in minimum loss power flow in hydrothermal electric power systems

Two formulations of the optimal minimum loss hydrothermal power flow problem in electric power systems are discussed. The formulations — one based on Kron's loss objective function and the other a network-based loss formulation — are treated in detail and the results of the two approaches are compared using two standard test systems. For the systems investigated, Kron's loss minimization schedules higher thermal generation than that required by the network loss minimization during lower demand. Kron's loss minimization involves lower active power transmission losses than those involved by the network-based loss minimization during low demand, and higher active power transmission losses than those required by the network-based loss minimization during higher demand. The total energy loss involved in the outcome of the Kron's loss minimization results is higher than that due to the network-based loss minimization schedule. There is a negligible difference in voltage magnitudes. Reactive power generation results favour the network-based loss approach. On the basis of the experiments, it is concluded that a network-based loss model is preferable in this application.     

Load forecasting via suboptimal seasonal autoregressive models anditeratively reweighted least squares estimation

Suboptimal least squares or iteratively reweighted least-squares (IRWLS) procedures for estimating the parameters of a seasonal multiplicative autoregressive (AR) model encountered during power system load forecasting are proposed. The method involves using an interactive computer environment to estimate the parameters of a seasonal multiplicative AR process. The method comprises five major computational steps. The first determines the order of the seasonal multiplicative AR process, and the second uses the least squares or the IRWLS to estimate the optimal nonseasonal AR model parameters. In the third step one obtains the intermediate series by back forecast, which is followed by using the least squares or the IRWLS to estimate the optimal seasonal AR parameters. The final step uses the estimated parameters to forecast future load. The method is applied to predict the Nova Scotia Power Corporation's 168 lead time hourly load. The results obtained are documented and compared with results based on the Box and Jenkins method     

Characterization of copolyester of polyethylene terephthalate and polyoxyethylene terephthalate by 1H NMR and GPC

Summary The copolyester of polyethylene terephthalate-polyoxyethylene terephthalate (PET-POET) has been characterized by ¹H NMR and GPC (Gel Permeation Chromatography). The ¹H NMR method provides a ready determination of the PET/POET mole ratio as well as the number of ethoxylate (EO) units in POET. Factors that may affect the accuracy of the determination are also discussed.     

Serum mineral changes in dithizone-induced diabetes before and after insulin treatment

In this study, diabetes was induced by intravenous injection of dithizone. In dithizonised diabetic animals, the levels of serum zinc, iron, and potassium were found to be higher than normal, while those of serum calcium and sodium were lower. Copper and magnesium levels were unchanged. After treatment with insulin, most of these serum levels approached the normal, except for serum potassium and magnesium.     

Selection of suitable fuzzy operators for representative power factor evaluation in non-sinusoidal situations

Power factor is well defined in sinusoidal situations, however, in the presence of harmonics, different power factors exist and they may provide different values in which case, evaluation becomes problematic. In Morsi and El-Hawary (2008) [1], [2] and [3], fuzzy systems have been used by the authors to develop a representative index that quantifies the power factor in different operating conditions including sinusoidal and non-sinusoidal situations. However, since different fuzzy operators can be used in the fuzzy system, which will affect the measured output power factor index, this paper investigates the implementation of different fuzzy operators when applied to the developed fuzzy system-based power factor evaluation, in different operating conditions. It is found that the use of the ‘algebraic product-sum’ operation offers the most suitable connection method, while the ‘algebraic product’ is the most preferred as an implication method and the ‘maximum’ operation is best suited for the aggregation operation. These combinations offer the most suitable means for establishing a representative power factor under non-sinusoidal conditions with the least computational burden.     

Use of an ion selective electrode to determine the complexing of copper in food extracts dependent upon the pH

Speciation affects the bioavailability of elements and is very important in nutrition. In fact, it can provide knowledge about absorption, distribution, reactivity to binding sites, bioavailability, toxicity and excretion of elements. Availability for absorption depends upon the characteristic chemical state of the intestinal mucosa cells, namely the solubility, oxidation state and binding strength of ligands in the lumen of the gastrointestinal tract. Crucially important for the resorption of the elements from food is the chemical form of complexes in which the element is present. The elements exist probably not in the intestine as free ions, but as a complex partner. The organic and inorganic components of food that can bind with elements affect the transport of the latter and consequently their resorption in the intestine. This phenomenon essentially depends on the pH, the concentration of the element as well as the chemical ratio. Potentiometric measurements with an ion selective electrode (ISE) were made to determine the copper species in food samples. Different model solutions containing copper, and organic or inorganic substances of food, which form pH dependent complexes with copper ions, were potentiometrically analysed by means of a copper selective electrode to determine the dominant binding partners. The above mentioned method is suitable to characterise and quantify the bioavailability and main binding partners of copper both of which are dependent upon the pH in foodstuffs. The results obtained provide information concerning the resorption of copper when food moves from the acid pH environment of the stomach to the alkaline milieu of the small intestine.     

An approach to implement electricity metering in real-time using artificial neural networks

As many utilities move toward deregulation, the research focus on spot pricing of electricity has led to the development of complex spot pricing-based electricity rate models. As research matures to implementation stages, approaches to meter the actual power consumption in real time are required. In this work, the authors model a real-time electric power metering approach based on neural networks. A carefully designed artificial neural network (ANN) is trained to recognize the complex optimal operating point of an all-thermal electricity generating utility. A real-time rate is allocated to each bus for a given power system's loading pattern and the recall process is instantaneous. The proposed approach is tested using a spot pricing model on five- and 14-bus electric power systems. Different loading levels are used for each bus.     

Security-constrained OPF: influence of fixed tap transformer fedloads

The behavior of the conventional security-constrained optimal power flow (OPF) solutions is studied in the presence of loads not controlled by under load tap changing (ULTC) transformers. modified versions of the AEP/IEEE 30 bus system with exponential-type load models were used to create a variety of test situations. The study reveals that with loads not controlled by ULTC transformers, the solution to a conventional security-constrained OPF can be different from its practically observed version. This conclusion is similar to that obtained for OPF neglecting contingencies. In the present case, since the voltages are usually higher than for OPF neglecting contingencies, it follows that an increase in fuel costs, power demand, and total and net revenue can be expected in more cases than in the previous study. Moreover, limit violations in the present case are observed mainly during contingencies     

Stochastic Optimal Load Flow Using Newton-Raphson Iterative Technique

ABSTRACT

In this paper we consider the problem of stochastic optimal power flow for an all thermal electric power system. The formulation includes the effects of variables uncertainty modeled as stochastic and normally distributed. The system performance is represented by the load flow equations in polar form, reformulated to include the uncertainty aspect. Inequality constraints are handled using Powell's penalty function method. We employ a variational approach to derive the optimality conditions resulting in a set of nonlinear equations. Newton's method is employed, to actually implement the optimum strategy by solving the nonlinear set of optimality conditions iteratively. An application example involving the IEEE standard 14 bus system is presented and the stochastic solution is compared with a deterministic solution for the same system in order to demonstrate the applicability of the proposed method.