Computational intelligence applied to power generation dispatch

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN028889 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Discussion of "New approach with a Hopfield modeling framework to economic dispatch"

WOS: 000166738400044

An educational software package for power systems analysis and operation

WOS: 000234945100007This paper presents a software package developed in Matlab for teaching power systems analysis and operation. The software package is used to support and enhance power engineering education at both undergraduate and postgraduate levels. The application programs in this package include fault analysis, load flow analysis, transient stability, economic dispatch, unit commitment and load forecasting. All modules of the package are independent of each other. The students or researchers can make copies of the software to study and can modify any module of the package

An application of tabu search to economic dispatch problem

Ministry of Macedonia;Aristotle University of Thessaloniki, Thessaloniki, Greece;Insitiute of Electrical Engineers, IEE;Institute of Electrical and Electronic Engineers, IEEE;Technical Chamber of Greece, TCGUPEC 2003, 38th International Universities' Power Engineering Conference -- 1 September 2003 through 3 September 2003 -- Thessaloniki -- 62394In this paper, the tabu search method is applied to economic dispatch problem. The proposed method has achieved efficient and accurate solutions for power systems with 3 and 6 units. The results of the proposed method are compared with those of an improved Hopfield neural network approach (IHN) [1], a fuzzy logic controlled genetic algorithm (FLCGA) [2], an advance engineered-conditioning genetic approach (AECGA) [3] and an advance Hopfield neural network approach (AHNN) [4]. The results show that the proposed method is capable of being applied efficiently to the economic dispatch problem

Comparison of fuzzy logic and PID controllers for TCSC using Matlab

39th International Universities Power Engineering Conference (UPEC 2004) -- SEP 06-08, 2004 -- Univ West England, Bristol, ENGLANDWOS: 000231594700090In this paper, a Fuzzy logic controller and a PID controller are used to control firing angles of TCSC using Matlab Simulink, Power System Blockset and Fuzzy Logic Toolbox. The graphic interface of Simulink provides a user-friendly environment where the power circuit and control system are represented in the same diagram. The design and testing of TCSC are verified using the Matlab environment. The studied power system is a simple two buses system with distributed parameter line. The simulation results show that the fuzzy logic controller can generate beter dynamic response.Power Syst & Elect Res Grp, IEEE Comp Soc, IEE, Int Councik Large Elect Syst, IEEE Reg 8, Power Engn Soc, Natl Grid Transco, EDF, WUHAN HI-TECH Elect Engn Co Chin

A new genetic algorithm with arithmetic crossover to economic and environmental economic dispatch

This paper presents a new genetic approach based on arithmetic crossover for solving the economic dispatch and environmentally constrained economic dispatch problems. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The employed arithmetic crossover operation takes the real values presented by two individuals and produced new generation on the basis of the arithmetic mean. For economic dispatch problem, the new genetic approach is compared with an improved Hopfield NN approach (IHN), a fuzzy logic controlled genetic algorithm (FLCGA), an advance engineered-conditioning genetic approach (AECGA) and an advance Hopfield NN approach (AHNN). The results of the proposed approach for environmentally economic dispatch are compared with the results of the Taboo Search (TS), the Hopfield NN and a neural networks approach. © 2005 CRL Publishing Ltd

Short term and medium term power distribution load forecasting by neural networks

WOS: 000227027800005Load forecasting is an important subject for power distribution systems and has been studied from different points of view. In general, load forecasts should be performed over a broad spectrum of time intervals, which could be classified into short term, medium term and long term forecasts. Several research groups have proposed various techniques for either short term load forecasting or medium term load forecasting or long term load forecasting. This paper presents a neural network (NN) model for short term peak load forecasting, short term total load forecasting and medium term monthly load forecasting in power distribution systems. The NN is used to learn the relationships among past, current and future temperatures and loads. The neural network was trained to recognize the peak load of the day, total load of the day and monthly electricity consumption. The suitability of the proposed approach is illustrated through an application to real load shapes from the Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the daily and monthly electricity consumption in Nigde, Turkey. (C) 2004 Elsevier Ltd. All rights reserved

Power economic dispatch using a hybrid genetic algorithm

This letter outlines a hybrid genetic algorithm (HGA) for solving the economic dispatch problem. The algorithm incorporates the solution produced by an improved Hopfield neural network (NN) [1] as a part of its initial population. Elitism, arithmetic crossover, and mutation are used in the GAs to generate successive sets of possible operating policies. The technique improves the quality of the solution and reduces the computation time, and is compared with the classical optimization technique, an improved Hopfield NN approach (IHN) [1], a fuzzy logic controlled GA (FLCGA) [2], and an improved GA (IGA) [3]

Environmentally constrained economic dispatch via a genetic algorithm with arithmetic crossover

6th IEEE Africon Conference -- OCT 02-04, 2002 -- UNIV PRETORIA, GEORGE, SOUTH AFRICAWOS: 000180673700171For electric power generation and dispatching problems, absolute minimum cost is not any more the only criterion to be met. Environmental considerations have become one of the major management concerns. The environmentally constrained economic dispatch problem can be classified as a multi-objective optimization and non-linear programming problem. This paper proposes a solution for environmental economic dispatch problem using modified GA which based on arithmetic crossover operator. The employed arithmetic crossover operation takes the real values presented by two individuals and produced new generation on the basis of the arithmetic mean. Numerical results for two case studies have been presented to illustrate the performance and applicability of the proposed method.NRF, Cape Technikon, IEEE S Africa Sect, Reg 8, SAiE