A weight-aggregation multi-objective PSO algorithm for load scheduling of PHEVs
Document Type
Conference Proceeding
Publication Date
11-14-2016
Abstract
As the supply potential has declined gradually and the pressure for better environment intensifies, the demand for clean energy arises continuously. The consumptive demand for Plug-in Hybrid Electric Vehicle (PHEV) thus increases. However, load peak caused by their disordered charging can be detrimental to an entire power grid. Several methods have been proposed to establish ordered PHEV charging. While focusing on single-objective optimal load scheduling, they fail to meet the real requirements for efficient multiple objective optimization. This work proposes a novel weight-aggregation based multi-objective particle swarm optimization method to solve the load scheduling problem. Its effectiveness and efficiency to generate a Pareto front of this problem are verified and compared with those of the state-of-the-art approaches.
Identifier
85008246003 (Scopus)
ISBN
[9781509006229]
Publication Title
2016 IEEE Congress on Evolutionary Computation CEC 2016
External Full Text Location
https://doi.org/10.1109/CEC.2016.7744155
First Page
2896
Last Page
2902
Recommended Citation
Feng, Shuwei; Kang, Qi; Chen, Xiaoshuang; Zhou, Mengchu; Li, Sisi; and An, Jing, "A weight-aggregation multi-objective PSO algorithm for load scheduling of PHEVs" (2016). Faculty Publications. 10159.
https://digitalcommons.njit.edu/fac_pubs/10159
