Variable Structure Control of DFIG for Wind Power Generation and Harmonic Current Mitigation

This paper focuses on wind energy conversion system (WECS) analysis and control for power generation along with problems related to the mitigation of harmonic pollution in the grid using a variable-speed structure control of the doubly fed induction generator (DFIG). A control approach based on the so-called sliding mode control (SMC) that is both efficient and suitable is used for power generation control and harmonic-current compensation. The WECS then behaves as an active power filter (APF). The method aims at improving the overall efficiency, dynamic performance and robustness of the wind power generation system. Simulation results obtained on a 20-kW, 380-V, 50-Hz DFIG confirm the effectiveness of the proposed approach

The deception of an infinite view – exploring machine vision in digital art

This paper examines prediction product called Queryable Earth a project to “make Earth searchable for all”. A project pitched by the company Planet, owner of the largest fleet of Earth-imaging satellites in orbit and an archive of satellite images growing with terabytes of fresh data every day. The aim of Queryable Earth is to combine geospatial intelligence with machine learning. By training artificial neural networks to classify objects, identify geographic features, and monitor change over time, the implied intention is to create a predictive, omniscient oracle. In this paper Queryable Earth functions as an example of a ‘nonconscious cognitive assemblage’ combining aerial image with machine learning techniques such as artificial neural networks. To examine the predictive potential and the assumed objectivity of machine vision systems such as Queryable Earth I turn to histories of aerial photography and examples of contemporary digital art to illustrate how human and technical cognition entwine revealing how seemingly automated processes such as rendering of satellite images and pattern recognition still inherit human biases and are prone to emphasize them. Furthermore, I use digital artworks to illustrate how Queryable Earth as an “all seeing machine” is limited to a singular aerial perspective which cannot penetrate the surface and how predictions produced by such systems are constrained the quality and selection of data they are trained on