S
Souma Chowdhury
Researcher at University at Buffalo
Publications - 181
Citations - 2435
Souma Chowdhury is an academic researcher from University at Buffalo. The author has contributed to research in topics: Wind speed & Surrogate model. The author has an hindex of 22, co-authored 162 publications receiving 2062 citations. Previous affiliations of Souma Chowdhury include State University of New York System & Georgia Institute of Technology.
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Unrestricted wind farm layout optimization (UWFLO): Investigating key factors influencing the maximum power generation
TL;DR: In this paper, a new methodology, the Unrestricted Wind Farm Layout Optimization (UWFLO), is presented to address critical aspects of optimal wind farm planning, simultaneously determining the optimum farm layout and the appropriate selection of turbines (in terms of their rotor diameters) that maximizes the net power generation.
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Optimizing the arrangement and the selection of turbines for wind farms subject to varying wind conditions
TL;DR: In this paper, an advanced version of the Unrestricted wind farm layout optimization (UWFLO) method is proposed to simultaneously optimize the placement and the selection of turbines for commercial-scale wind farms that are subject to varying wind conditions.
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An adaptive hybrid surrogate model
TL;DR: The Adaptive Hybrid Functions (AHF) formulates a reliable Crowding Distance-Based Trust Region (CD-TR), and adaptively combines the favorable characteristics of different surrogate models to capture the global trend of the function as well as the local deviations.
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A mixed-discrete Particle Swarm Optimization algorithm with explicit diversity-preservation
TL;DR: A modification of the Particle Swarm Optimization (PSO) algorithm is presented, which can adequately address system constraints while dealing with mixed-discrete variables, and is applied to a wide variety of standard test problems.
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A Multivariate and Multimodal Wind Distribution model
TL;DR: In this paper, a smooth multivariate wind distribution model is developed to capture the coupled variation of wind speed, wind direction, and air density, which avoids the limiting assumption of unimodality of the distribution.