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Elena Malz

Researcher at Chalmers University of Technology

Publications -  10
Citations -  101

Elena Malz is an academic researcher from Chalmers University of Technology. The author has contributed to research in topics: Wind power & Electricity generation. The author has an hindex of 4, co-authored 9 publications receiving 41 citations.

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Journal ArticleDOI

A reference model for airborne wind energy systems for optimization and control

TL;DR: This paper provides a reference model for pumping mode AWE systems based on rigid wings in form of differential-algebraic equations, based on Lagrange dynamics, that has been validated against flight data and is well suited for trajectory and power output simulation and optimization.
Journal ArticleDOI

Drag-mode airborne wind energy vs. wind turbines: An analysis of power production, variability and geography

TL;DR: In this article, the performance of AWE systems relative to traditional wind power turbines (WT) is compared to the hourly power production of classical WTs, and the results show that AWE system with multiple smaller wings have the highest annual production.
Proceedings ArticleDOI

Operational Regions of a Multi-Kite AWE System

TL;DR: It is shown that pumping-cycle MAWES have three distinct operational regions: Region I, where power is consumed to stay aloft; Region II, where the power harvesting factor grows until the design wind speed; and Region III, wherepower extraction is curtailed so as to respect the physical limitations of the system.
Journal ArticleDOI

Computing the power profiles for an Airborne Wind Energy system based on large-scale wind data

TL;DR: This paper proposes a method how to reduce the computational effort when using an OCP for power computations of large-scale wind data, based on homotopy-path-following strategies, which make use of the similarities between successively solved OCPs.
Proceedings ArticleDOI

A Quantification of the Performance Loss of Power Averaging in Airborne Wind Energy Farms

TL;DR: In order to assess the viability of mitigating the power fluctuation by power averaging at the wind farm level, this paper quantifies the loss of performance it yields.