Hybrid Differential Evolution With Biogeography-Based Optimization for Solution of Economic Load Dispatch
By Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay. IEEE Transactions on Power Systems, 2010
418 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/c0d72ca33e131febdaa7abd55b971e34104cd0c4
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In Electrical and Electronic Engineering
- Behnam Mohammadi-Ivatloo
- Abbas Rabiee
- Alireza Soroudi
- Mehdi Ehsan
- A. Basu
- Aniruddha Bhattacharya
- S. Chowdhury
Citations in the corpus
- Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems (2012, result): “Unit DE/BBO [43] FAPSO-VDE [13] QPSO [25] HMAPSO [14] BBO [44] HGA [40] Proposed 1 110.7998 110.80182 111.2 111.136 111.0465 111.3793 110.8 2 110.7998 110.80003 111.7 111.135 111.5915 110.9278 110.8 3 97.3999 97.399913 97.4 120 97.60077 97.4104 97.4 4 179.7331 179.7331 179.73 177.221 179.7095 179.73”
- Planned Scheduling for Economic Power Sharing in a CHP-Based Micro-Grid (2012, background): “It is common practice to express the network loss as a quadratic function of the generator power outputs through B-coefficients and its general form containing a linear term and a constant term [8], [21], referred to as Kron’s loss formula, is”
- Biogeography-based optimisation with chaos (2014, neutral): “Generally speaking, the results of the chaotic maps on all the benchmark functions follow the order of: Gauss/mouse Sine Chebyshev Logistic Iterative normal BBO Circle Singer Piecewise Tent Sinusoidal.”
- Optimal Placement and Sizing of Distributed Generation via an Improved Nondominated Sorting Genetic Algorithm II (2015, methodology): “Multiobjective economic/emission dispatch algorithms were investigated in [2] and [3].”