An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems
By Jong-Bae Park, Yun-Won Jeong, Joong-Rin Shin, Kwang.Y. Lee. IEEE Transactions on Power Systems, 2010
611 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/d1210000a5d35f96dd1df161ca2968aaa7c14193
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In Electrical and Electronic Engineering
- Behnam Mohammadi-Ivatloo
- M. Fotuhi‐Firuzabad
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Citations in the corpus
- Multiagent Genetic Algorithm: An Online Probabilistic View on Economic Dispatch of Energy Hubs Constrained by Wind Availability (2014, methodology): “An improved particle swarm optimization model is proposed in [8] for nonconvex ED problems.”
- Economic Allocation for Energy Storage System Considering Wind Power Distribution (2015, background): “The authors in [13] proposed an improved PSO algorithm to dispatch 140 thermal generation units for a large-scale power system of South Korea.”
- Continuous quick group search optimizer for solving non-convex economic dispatch problems (2012, methodology): “[6] J.”
- Particle swarm optimization algorithm: an overview (2017, background): “The modified PSO of Park et al. (2010) introduced chaotic inertia weight which decreased and oscillated simultaneously under the decreasing line in a chaotic manner.”
- Grey wolf optimization applied to economic load dispatch problems (2016, neutral): “The system data including fuel cost coefficients are adopted from [56,58].”
- An improved particle swarm optimization for feature selection (2011, methodology): “[13] used the chaotic sequences and crossover operations in PSO to improve global search capability by preventing premature convergence.”
- Convergence Analysis of the Incremental Cost Consensus Algorithm Under Different Communication Network Topologies in a Smart Grid (2012, methodology): “More sophisticated techniques have been employed to solve the nonconvex cost function, such as genetic algorithms (GA) [3], particle swarm optimization (PSO) [4], and more recently the improved particle swarm optimization (IPSO) [5].”