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This paper describes very short-term wind prediction for power generation, utilizing a case study from Tasmania, Australia. Windpower presently is the fastest growing power generation sector in the world. However, windpower is intermittent. To be able to trade efficiently, make the best use of transmission line capability, and address concerns with system frequency in a re-regulated system, accurate very short-term forecasts are essential. The research introduces a novel approach—the application of an adaptive neuro-fuzzy inference system to forecasting a wind time series. Over the very short-term forecast interval, both windspeed and wind direction are important parameters. To be able to be gain the most from a forecast on this time scale, the turbines must be directed toward on oncoming wind. For this reason, this paper forecasts wind vectors, rather than windspeed or power output. [ABSTRACT FROM AUTHOR]

Advancements in quantum computing present a security threat to classical cryptography algorithms. Lattice-based key exchange protocols show strong promise due to their resistance to theoretical quantum-cryptanalysis and low implementation overhead. By contrast, their physical implementations have shown vulnerability against side-channel attacks (SCAs) even with a single power measurement. The state-of-the-art SCAs are, however, limited to simple, sequentialized executions of post-quantum key-exchange (PQKE) protocols, leaving the vulnerability of complex, parallelized architectures unknown. This article proposes 2Deep—a deep-learning (DL)-based SCA—targeting parallelized implementations of PQKE protocols, namely, Frodo and NewHope with data augmentation techniques. Specifically, we explore approaches that convert 1-D time-series power measurement data into 2-D images to formulate SCA an image recognition task. The results show our attack’s superiority over conventional techniques including horizontal differential power analysis (DPA), template attacks (TAs), and straightforward DL approaches. We demonstrate improvements up to 1.5 × to recover a 100% success rate compared to DL with 1-D input data while using fewer data. We furthermore show that machine learning improves the results up to 1.25 × compared to TAs. Furthermore, we perform cross-device attacks that obtain profiles from a single device, which has never been explored. Our 2-D approach is especially favored in this setting, improving the success rate of attacking Frodo from 20% to 99% compared to the 1-D approach. Our work thus urges countermeasures even on parallel architectures and single-trace attacks. [ABSTRACT FROM AUTHOR]

Grote Reber, amateur radio operator W9GFZ, died December 20, 2002 in Tasmania. He would have been 91 years old on December 22nd. Reber is acknowledged as the Father of Radio Astronomy and the inventor of the first true radio telescope. With the advent of space satellites, his greatest legacy may well be his invention of the parabolic dish, designed to receive nonterrestrial electro-magnetic radiation, a concept that has revolutionized worldwide communication. [ABSTRACT FROM AUTHOR]

Describes a coordinated approach to short-term hydro scheduling and dispatch that was developed as part of the Tasmanian Hydro Electric Commission's Energy Management System. Functional hierarchy; Problem definition; Generating unit constants; Objective function; Variable definition.