A new tabu search algorithm for the long-term hydro scheduling problem

A new efficient algorithm to solve the long-term hydro scheduling problem (LTHSP) is presented in this paper. The algorithm is based on using the short-term memory of the tabu search (TS) approach to solve the nonlinear optimization problem in continuous variables of the LTHSP. The paper introduces new rules for generating feasible solutions with an adaptive step vector adjustment. Moreover an approximated tabu list for the continuous variables has been designed. The proposed implementation contributes to the enhancement of speed and convergence of the original tabu search algorithm (TSA). A significant reduction in the objective function over previous classical optimization methods and a simulated annealing algorithm has been achieved. Moreover the proposed TS requires less iterations to converge than simulated annealing. The proposed algorithm has been applied successfully to solve a system with four series cascaded reservoirs. Numerical results show an improvement in the solution compared to previously obtained results

An innovative simulated annealing approach to the long-term hydroscheduling problem

This paper presents a new simulated annealing algorithm (SAA) to solve the long-term hydro scheduling problem (LTHSP). A new algorithm for randomly generating feasible trial solutions is introduced. The problem is a hard nonlinear optimization problem in continuous variables. An adaptive cooling schedule and a new method for variables discretization are implemented to enhance the speed and convergence of the original SAA. A significant reduction in the number of the objective function evaluations, and consequently less iterations are required to reach the optimal solution. The proposed algorithm has been applied successfully to solve a system with four series cascaded reservoirs. Numerical results show an improvement in the solutions compared to previously obtained result

Fuzzy time domain and Z-transform for modeling of harmonic electric loads

This paper demonstrates the application of fuzzy systems and Z-transform for electric load modeling in the presence and/or absence of harmonics. The problem is formulated as one of linear optimization, where the objective is to minimize the spread of the model parameters. A triangular membership function is chosen for each load parameter. Having identified the fuzzy load parameters, the fuzzy admittance of the load is formulated in the frequency domain. The proposed algorithm is tested using simulated and actual recorded data for nonlinear loads having different characteristics. The results obtained are reported in the pape

On the application of αβ-transformation for power systems frequency relaying

This paper presents a new and very accurate algorithm for power system frequency measurement. The proposed algorithm is based on αβ-transformation of the three phase voltages or current waveforms in the relay location, where digital samples are available for the three phase waveforms. Having obtained the digital samples of one of the components, α-β components, the finite divided difference formulae are used to calculate the parameters of one of these components; the magnitude, the frequency and phase angle. The necessary formulae are derived within the text and effects of imbalance and harmonics contamination on the waveforms are discussed within the text.Scopu

Identification of individual types of harmonic loads in an electric power system bus

Some buses in a power system feed power to loads that are sources of harmonics. This type of bus is called a complex bus. This paper provides a new application of the constrained least absolute value algorithm (LAV) to identify the type of harmonic loads on a complex bus and their harmonics contribution to the main bus current. The problem is first formulated as least error squares constrained parameter estimation problem using LaGrange multiplier to adjoin the equality constraints. To this stage the equality constrained is used to sum the contribution from each load at certain harmonic frequency. The LAV technique is used to solve the resulting problem. Computational results are given for actual recorded data.Scopu

Identification of individual types of harmonic loads in an electric power system-bus

Some buses in a power system feed power to loads that are sources of harmonics. This type of bus is called a complex-bus. This paper provides a new application of the constrained least absolute value algorithm (LAV) to identify the type of harmonics loads on a complex bus and their harmonics contribution to the main bus current. The problem is first formulated as a least error squares (LES) constrained parameter estimation problem using LaGrange multiplier to adjoin the equality constraints. To this stage the equality constrained is used to sum the contribution from each load at certain harmonic frequency. The LAV technique is used to solve the resulting problem. Computational results are given for actual recorded data.Scopu

Power system frequency estimation based on simulated annealing. Part I: A constant frequency study

In this paper a new algorithm based on Simulated Annealing (SA) method is used to estimate the signal parameters of a system steady power system, having a constant frequency during data window size. The proposed algorithm does not need any filter or model for the system frequency before and during the estimation process. The nonlinear optimization problem, which is the minimization of the sum of the squares of the errors, as a function of the signal amplitude, frequency and phase angle, is solved using the Simulated Annealing Algorithm (SAA). The problem is a nonlinear optimization problem in continuous variables. An adaptive cooling schedule and a new method for variable discretization are implemented to enhance the speed and convergence of the original SAA. The algorithm uses the samples of the voltage or current signal of one phase at the relay location. The proposed algorithm is tested using simulated and actual recorded data for noise free and harmonics contaminated signals. Effects of the critical parameters, such as sampling frequency and number of samples, on the estimated parameters are tested. It has been shown that the SAA is succeeded to estimate accurately the system frequency from a highly contaminated voltage signal