This research paper gives solution for Economic Load Dispatch (ELD) problem with considering valve point effect. ELD is the oldest and most important problem of optimal power flow. Objective of the ELD problems is to find out the optimal combination of power outputs of generating units so as to cope up the load demand at minimum cost while satisfying all the equality and inequality constraints. Conventionally, the function of cost for each unit in ELD problems has been approximately represented by a quadratic equation and is solved using various conventional and artificial intelligent techniques of optimization. Unfortunately, high non-linearity is present in the input-output characteristics of generating units' due to presences of prohibited operating zones, valve point loading effects, and multi-fuel effects, etc. Thus, the practical ELD problem is formulated as optimization problem of a non-smooth function with equality and inequality constraints, which cannot be solved by the conventional optimization methods. The performance of Cuckoo Search method and PSO with some modifications is tested on a standard test bed system i.e. IEEE 30-bus 6-generators system.
Saccadic eye movements land at precise places within simple target forms implying that a spatial pooling process operates over attended regions to determine the saccadic endpoint. To study pooling, we used large, unstructured targets and looked for evidence of differential spatial weighting based on local pattern characteristics. Subjects made a saccade to targets composed of 19 dots scattered randomly within a 4 deg diameter region horizontally displaced 3.8 – 4.2 deg to the left or right of initial fixation. Dot intensity was either uniform or variable. Saccadic landing positions were close to the centre-of-gravity (overshooting or under- shooting by 5% – 10% depending on subject, direction and eccentricity). Precision was excellent (SD=10% ecc), although not as good as with single target points (SD=7% ecc). Correlations between the presence of a dot and saccadic landing position showed that all regions of the pattern contributed. Differential weighting of dots according to location (eg near vs far; central vs boundary) did not yield better predictions of the saccadic landing position. However, predictions of the landing position were improved by assigning more weight to higher-intensity dots. Local dot clusters contributed less than would be expected from the contributions of individual dots. Spatial pooling is highly effective over a large region. Saccadic overshoots or undershoots were not due to differential spatial weighting, and may originate after the centre-of-gravity computation. The differential weighting of high-intensity dots and dot clusters demonstrates sensitivity to local characteristics, and implies that the saccadic endpoint may be determined by pooling the activity of units centred on different subregions of the target. The pooling mechanism supports precise saccadic localisation of large, unstructured targets, and accounts for the ease with which we direct saccades to chosen objects in natural scenes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.