Self-Organizing Hierarchical Particle Swarm Optimization for Nonconvex Economic Dispatch

By Krishna Teerth Chaturvedi, Manjaree Pandit, Laxmi Srivastava. IEEE Transactions on Power Systems, 2008

515 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/8b915422607a32cf381e1129688a7146d96ec17c

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Citations in the corpus

A bare-bones multi-objective particle swarm optimization algorithm for environmental/economic dispatch (2012, methodology): “Due to its advantages such as simplicity, fast convergence and population-based feature, the PSO is a favorable technique to tackle the optimization problems of power systems [9,27,39,42].”
Economic dispatch using chaotic bat algorithm (2016, methodology): “Algorithm Best fuel cost($/hr) Mean fuel cost($/hr) Max. fuel cost($/hr) Standard deviation Average computation/run time (seconds) 1 CBA 15,450.2381 15,454.76 15,518.6588 2.965 0.704 2 DE [46] 15,449.5826 15,449.62 15,449.6508 NA 3.634 s 3 GAAPI [32] 15,449.78 15,449.81 15,449.85 NA NA 4 MABC [41] 1”
Particle swarm optimization algorithm: an overview (2017, background): “and dynamically determining the search space Chaturvedi et al. (2008) dynamically controlled the acceleration coefﬁcients in maximum and minimum limits.”
A GA-API Solution for the Economic Dispatch of Generation in Power System Operation (2012, methodology): “For the smooth 6-generator test system (Table III), it can be noticed that GAAPI gives comparable results with the NPSO-LRS, SOHPSO in terms of the minimum best solution, and better average than all other methods used in the comparison table.”
A Bi-Level Branch and Bound Method for Economic Dispatch With Disjoint Prohibited Zones Considering Network Losses (2015, methodology): “Note, the meta-heuristics are somewhat population- or parameter-based which is also non-deterministic, although having good convergence property, such as reported PSO [27], PCPSO and SOHPSO.”
Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems (2012, methodology): “It is observed that original PSO suffers from premature convergence, especially for problems with multiple local optimums [26,27].”
Hybrid Differential Evolution With Biogeography-Based Optimization for Solution of Economic Load Dispatch (2010, methodology): “Recently, different hybridization and modification of GA, EP, PSO, methods like IFEP [12], IGAMU, RQEA, DSGA, UHGA, PSOSQP, NPSO-LRS [13], APSO [14], SOH-PSO [15], SA-PSO, ESO, etc. are being proposed for solving ELD in search of better quality and fast solution.”
Biogeography-Based Optimization for Different Economic Load Dispatch Problems (2010, methodology): “The performance of the proposed method in terms of solution quality and computational efficiency has been compared 1) with SOH_PSO [12] and other methods for a 40-generator system including valve-point loading; 2) with Hopfield model [4] and other techniques for a 20-generator system with quadratic ”
Economic Load Dispatch—A Comparative Study on Heuristic Optimization Techniques With an Improved Coordinated Aggregation-Based PSO (2009, methodology): “In this application the results are compared with those given by SA-PSO [2], SOH-PSO [4], BF-NM [5], APSO [6], DE [8], PSO-CG [9], DSGA [10], AIS [13], HDE and VSHDE [14], IGAMU [16], ESO [18], [19], PSO [24].”