MODELING AND ELIMINATION OF LOAD BUSES IN OPTIMAL POWER FLOW SOLUTIONS

ABSTRACT

This paper presents a method to solve the optimal power flow problem after eliminating load buses from the system. Loads are first modeled and reflected in the admittance matrix and then their respective buses are eliminated. The obtained model is a reduced model of the original system. The admittance matrix is of the same order as the number of voltage-controlled buses in the system. The variables of the reduced model are the voltage-controlled buses voltages, angles and active power generations. Newton Raphson method is used to calculate the variables of the reduced model while minimizing an objective function. Voltages and angles of the original system are then calculated by a direct method. These voltages are required to update load models and to check for voltage and line current violations at the eliminated portions of the network. The simulation is carried out on two systems, IEEE 118 bus test system and a 131 bus actual system. It is shown that solution time is significantly reduced when compared to the conventional optimal power flow Newton Raphson method using the original system.     

OPTIMIZATION OF AN ELECTRONICALLY CONTROLLED CAPACITOR FOR A SINGLE-PHASE INDUCTION MOTOR

ABSTRACT

In this paper the performance of a single-phase induction motor with an electronically controlled capacitor is examined. The capacitor in series with the auxiliary winding is controlled with an electronic circuit and different optimization criteria are applied in order to determine the optimum capacitance of subsequent performance of the motor.     

STATIC MINIMUM EMISSIONS POWER FLOW

ABSTRACT

The formulation of the optimal power flow problem designed to recognize an environmental objective such as the minimum emission objective is presented. The formulation considers both the fuel cost-related objective as well as emissions-related objectives (such as NO_x). Treating emissions as constraints is also discussed. Trade-off relations between fuel costs and emissions are also studied in the paper.     

Electrochemical Quantitative Analysis of Uric Acid in Milk

Analysis of cows’ milk by cyclic voltammetry using a carbon electrode showed an oxidation wave at a potential around + 0.8V with respect to a saturated calomel electrode. The compound responsible for the wave was determined to be uric acid. The electrochemical assay of uric acid was without preliminary treatment of the milk. A concentration of 3.3 × 10^?2 g/L milk was detectable. The method proved highly accurate, rapid and precise [coefficient of variation = 3%].     

Quality characteristics of physically refined soyabean oil: effects of pre-treatment and processing time and temperature

Conventional alkali refining of edible oils is being replaced progressively by physical refining, which offers improved yields, reduced processing times and few by-product problems. The variables involved in physical refining- pre-treatment, processing time and processing temperature-have been studied on a laboratory scale for the refining of soyabean oil, and related to the quality characteristics of the refined products. The best results are obtained with phosphoric acid degummed, partially bleached oil processed at up to 250°C for not more than 2 hr. Higher temperatures and longer times lead to quality defects such as loss of stability, increased viscosity, darkening and chemical changes reflected in reduction of iodine value and increase in free fatty acids.     

STATIC MINIMUM EMISSIONS POWER FLOW

ABSTRACT

The formulation of the optimal power flow problem designed to recognize an environmental objective such as the minimum emission objective is presented. The formulation considers both the fuel cost-related objective as well as emissions-related objectives (such as NO_x). Treating emissions as constraints is also discussed. Trade-off relations between fuel costs and emissions are also studied in the paper.     

On identification of parallel block-cascade nonlinear models

The class of nonlinear systems studied in this paper is assumed to be modelled by parallel block-cascades. Such models are composed of parallel branches where each branch has a linear block in cascade with a zero-memory nonlinear block followed by another linear block. These types of models are extensively used to represent nonlinear dynamic systems and are known in the literature as Wiener-Hammerstein models. Using a zero-mean stationary white gaussian sequence as an input to such models, a structure identification criterion is developed, utilizing the bispectrum estimate of the output sequence only. The application of this criterion is shown by several simulation examples. Also, impulse response estimation of an example of such a model is considered to show the effectiveness of the proposed identification technique.