A novel approach for unit commitment problem via an effective hybrid particle swarm optimization

By Tiew On Ting, Machavaram Venkata Chalapathy Rao, C. Loo. IEEE Transactions on Power Systems, 2006

484 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/92ca85ca6d461fe5e008371bdfc09dd65d7e1b6f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. B. Goswami
2. Ganesh Kumar Venayagamoorthy
3. Sarmila Patra
4. Swapan Kumar Goswami
5. Ahmed Yousuf Saber

In Electrical and Electronic Engineering

1. Ahmed Yousuf Saber
2. B. Goswami
3. Ganesh Kumar Venayagamoorthy
4. Sarmila Patra
5. Swapan Kumar Goswami
6. Joy Chandra Mukherjee
7. Arobinda Gupta

Citations in the corpus

• Plug-in Vehicles and Renewable Energy Sources for Cost and Emission Reductions (2011, background): “The load demand and unit characteristics of the tenunit system are collected from [25].”
• A new approach for solving the unit commitment problem by adaptive particle swarm optimization (2008, background): “particle swarm optimization [ 5 ]-[8], genetic algorithms [9], evolutionary programming [10], simulated annealing [11], ant colony optimization [12] and tabu search [13] are able to overcome the shortcomings of traditional optimization techniques.”
• Differential Evolution Algorithm for Solving Unit Commitment with Ramp Constraints (2008, methodology): “[7, 8], tabu search [9], genetic algorithm (GA) [10–12], LR-genetic algorithm (LRGA) [5], ant colony [13], particle swarm optimization (PSO) [14], and evolutionary programming (EP) [15], which are applied to the UC problem.”
• Resource Scheduling Under Uncertainty in a Smart Grid With Renewables and Plug-in Vehicles (2012, background): “collected from [24], and emission coefficients are collected from [25].”