Windfarm optimization using Nelder-Mead and Particle Swarm optimization

Bhardwaj, Bhavya; Jaiharie, J; Dadhich, R Sorabh; Ahmed, Syed Ishtiyaq; Ganesan, Markkandan

doi:10.1109/icees51510.2021.9383684

Cited by 8 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Section: Introductionmentioning

confidence: 99%

“…Over the years, the various literature [2][3][4][5][6][7][8] had devoted much effort to the study of windfarm optimization. Among them, [2] evaluated time series models for predicting the power of a windfarm at different time scales, while [3] proposed a Particle Swarm Optimization (PSO) scheme for windfarm optimization. An optimal function-provided scheme and corresponding control strategies were adopted by [4] for a utility-scale energy storage system ESS configured in the windfarm.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm

et al. 2021

View full text Add to dashboard Cite

The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines’ layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines’ layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.

show abstract