Application of Particle Swarm Optimization for Economic Load Dispatch Problems

Sudhakaran, M.; Raj, P. Ajay-D-Vimal; Palanivelu, T.G.

doi:10.1109/isap.2007.4441694

Cited by 29 publications

(23 citation statements)

References 9 publications

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“…Since the valve point results in the ripples [20][21], a cost function contains higher order nonlinearity. Therefore, the cost function should be modified to consider the valve-point effects.…”

Section: B Non-smooth Fuel Cost Functions Including Valve-point Loadmentioning

confidence: 99%

“…The Fuel cost characteristics in $/ h of the six units and the unit operating min/max (in MW) ranges [19] Table I shows optimal scheduling of a Six-unit system by GA Method (including transmission losses) with comparison with PSO results reported in [20]. Fig.…”

Section: A Case I: 6-generators System With Line Losses (Not Includementioning

confidence: 99%

“…Losses are neglected for sake of comparisons and the case of load demand of 10,500 MW is considered as in [20][21]. Table III shows self-explanatory numerical results obtained with GA in comparisons with PSO approaches in [21][22].…”

Section: B Case Ii: 40-units With Valve-loading Effect (Neglect Lossmentioning

confidence: 99%

“…The data of 6 generating units and 40 generating units have taken to which are numerical tested and compared. The results are compared with [20][21][22].…”

mentioning

confidence: 99%

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Solution of Economic Load Dispatch Problem with Smooth and Non-Smooth Fuel Cost Functions Including Line Losses Using Genetic Algorithm

El‐Fergany¹

2011

IJCEE

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Abstract-The paper presents an application of Genetic Algorithm (GA) to solve Economic Load Dispatch (ELD) problems with smooth and non-smooth fuel cost objective functions. Main objective of ELD is to determine the most economic generating dispatch required to satisfy the predicted load demands including line losses over a certain period of time while relaxing various equality and inequality constraints. The unit Min/Max operational constraints, effects of valve-point loading ripples and line losses are considered for the practical applications. Several cases were tested and verified, among of them, two cases of 6-units and 40-units systems including losses with smooth and non-smooth cost functions were tested, verified and compared with previous reported researches. Finally, it can be concluded that GA proves an excellent viability to optimize and solve problems of ELD. Numerical simulations indicate an improvement in total fuel cost savings.Index Terms-Economic load dispatch problem, Genetic Algorithm (GA), Smooth and non-smooth cost functions.

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Section: B Non-smooth Fuel Cost Functions Including Valve-point Loadmentioning

confidence: 99%

Section: A Case I: 6-generators System With Line Losses (Not Includementioning

confidence: 99%

Section: B Case Ii: 40-units With Valve-loading Effect (Neglect Lossmentioning

confidence: 99%

“…The data of 6 generating units and 40 generating units have taken to which are numerical tested and compared. The results are compared with [20][21][22].…”

mentioning

confidence: 99%

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Solution of Economic Load Dispatch Problem with Smooth and Non-Smooth Fuel Cost Functions Including Line Losses Using Genetic Algorithm

El‐Fergany¹

2011

IJCEE

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“…D.N. Jeyakumar [10]presents a successful adaptation of the particle swarm optimisation (PSO) algorithm to solve various types of economic dispatch (ED) problems in power systems such as, multi-area ED with tie line limits, ED with multiple fuel options, combined environmental economic dispatch, and the ED of generators with prohibited operating zones. Numerical examples typical to each type are solved on Matlab 6.5 platform, using both the PSO method and the classical evolutionary programming (CEP) approach.…”

Section: Introductionmentioning

confidence: 99%