We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Optimal power flow with stochastic wind power and FACTS devices: a modified hybrid PSOGSA with chaotic maps approach.
- Authors
Duman, Serhat; Li, Jie; Wu, Lei; Guvenc, Ugur
- Abstract
Nowadays, the increasing usage of renewable energy sources (RES) in modern power systems introduces new challenges in power system planning and operation. Specifically, a high penetration of RESs introduces additional complexity into the optimal power flow (OPF) problem, which has a highly nonlinear complex structure. Under this environment, this paper discusses a modified hybrid particle swarm optimization and gravitational search algorithm (PSOGSA) integrated with chaotic maps (CPSOGSA) to apply the composite benchmark test functions and to solve the OPF problem with stochastic wind power and flexible alternating current transmission system (FACTS) devices. Numerical studies are used to illustrate effectiveness of the proposed CPSOGSA approach against other approaches such as moth swarm algorithm, grey wolf optimizer, and whale optimization algorithm. Additionally, to demonstrate the superiority and robustness of CPSOGSA algorithm, Wilcoxon signed-rank test is applied for all case studies. Case studies indicate the potential of CPSOGSA method in effectively solving OPF problem with stochastic wind power and FACTS devices.
- Subjects
WIND power; FLEXIBLE AC transmission systems; RENEWABLE energy sources; WIND forecasting; WILCOXON signed-rank test; PARTICLE swarm optimization; ENERGY consumption
- Publication
Neural Computing & Applications, 2020, Vol 32, Issue 12, p8463
- ISSN
0941-0643
- Publication type
Article
- DOI
10.1007/s00521-019-04338-y