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A Genetic algorithm is applied to the problem of determining the optimal hourly schedule of power generation in a hydro thermal power system. A multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. The water transport delay between connected reservoirs is also taken into account. The main control parameters that affect the genetic algorithm performance are discussed and a summary of the theoretical basis of the genetic algorithm method is presented. It is shown that a multiple step genetic algorithm search sequence can provide the optimal hourly loading of the system generators.

Nodal admittance matrix models are obtained for Wye-connected three-phase transformers with various grounding impedance configurations. The derivations have been performed using computational symbolic algebra, avoiding the necessity for simplifying assumptions. An original model for the general case of a Wye-Wye transformer, with grounding impedances on both primary and secondary neutrals, is given. It is shown that this model does not correspond to the simple combination of the previously known formulae for cases where neutral impedance occurs on either the primary side only or the secondary side only. It is also demonstrated that the new model simplifies to the well-known limiting cases for solid grounding and no grounding. A model is also given for multiple transformers sharing a single neutral grounding impedance. Index Terms--Grounding impedances, neutral grounding, nodal admittance matrices, three-phase transformers.

This letter describes a robust state estimator based on the solution of a mixed integer program. A tolerance range is associated with each measurement and an estimate is chosen to maximize the number of estimated measurements that remain within tolerance (or equivalently minimize the number of measurements out of tolerance). Some small-scale examples are given which suggest that this approach is robust in the presence of gross errors, is not susceptible to leverage points, and can solve some pathological cases that have previously caused problems for robust estimation algorithms. Index Terms--Mathematical programming, robustness, state estimation.

This letter presents a comparative study between two methods for estimating the uncertainty interval in power system state estimation. Constrained nonlinear and linear formulations are proposed to estimate the tightest possible upper and lower bounds on the states. The study compares the performance of these methods in terms of estimating the bounds of the uncertainty interval. In addition, an assessment of time performance for both methods is carried out with varying measurement redundancy levels. Index Terms--State estimation and measurement uncertainty.

ABSTRACT Ambitious offshore wind energy targets continue to drive technological innovation, with the latest direct-drive permanent magnet generator-based wind turbines promising higher efficiency and availability. However, these machines have fixed rotor flux, provided by the magnets, which means that their voltage rises with speed. Further, high machine stator reactance leads to significant magnetic energy storage in the stator windings. Both these aspects provide new challenges for the power converter when designing to meet modern low-voltage ride-through requirements. This paper therefore proposes a novel control strategy, using a minimally rated chopper and dynamic brake resistor (DBR) integrated with the wind turbine's power converter, to help these systems to meet the demands of modern grid codes. This control method may allow the chopper and DBR to be rated at only 40% of a fully rated version. Despite only partially rating the DBR system, the control method minimizes the torsional oscillations in the drive train, thereby protecting the mechanical system. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Abstract: A method for uncertainty analysis in power system state estimation is proposed. The uncertainty is expressed in both measurements and network parameters. Uncertainties in both measurements and parameters are known and bounded. The problem is formulated as a constrained non-linear optimization problem. To find the tightest possible upper and lower bounds of any state variable, the problem is solved by sequential quadratic programming (SQP) techniques. When applied to the 6-bus, IEEE 14-bus and IEEE 30-bus networks, the proposed method shows reliability and accuracy in estimating the uncertainty bounds in power system state estimation. In addition, assessment of time performance is carried out to demonstrate that the proposed method is suitable for either an on-line or an off-line application. [Copyright &y& Elsevier]

This paper presents a comparative study between three least squares-based state estimators. The study compares the performance of these estimators in identifying the presence of bad measurements of different types and magnitudes. Running a series of simulations with varying measurement redundancies assesses the performance of these estimators. [ABSTRACT FROM AUTHOR]

The application of constrained optimisation methods to the problem of economic dispatch in power systems is considered, and a unified presentation of problem formulations and appropriate solution methods is given. In particular, the methods of merit-ordering, linear programming, quadratic programming, and recursive quadratic programming are described. It is shown that the application of increasingly sophisticated methods leads to a more secure and economic dispatch of power generation. Experience with computer optimisation is presented, and the various methods are compared in terms of computational overhead, accuracy of modelling, availability of appropriate measurements, and suitability for networks of different sizes and characteristics. [ABSTRACT FROM PUBLISHER]