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Abstract The predispatch price forecast plays a key element in the electricity market. However, such a forecast usually depends on the traditional offline batch-learning technologies, which cannot respond in time to the unexpected changes in the local power system environment. Further, the predispatch local price forecast is often affected by the dynamic price changes from the neighboring regions. This article proposes a novel online learning forecast approach to overcome the above issues to provide a better predispatch price forecast by using the online sequential extreme learning machine (O...

Abstract This work concerns the receiver design for light emitting diode (LED) communications, where the LED nonlinearity can severely degrade the system performance. The LED nonlinearity makes high speed LED communications more challenging when it is time-varying (e.g., due to temperature drifting) and/or combined with time-varying channels (due to the relative movement between the transmitter and the receiver). In this work, we use adaptive neural network techniques to address this issue. We first propose a new adaptive extreme learning machine (AELM) with a variable forgetting factor for a...

Abstract Visible light communications (VLC) employ visible light for communication within the frequency spectrum from 430 THz to 790 THz. The ultra-wide bandwidth resolves the spectrum exhaustion in radio frequency communications. Light-fidelity (LiFi) takes VLC further to achieve high speed, bi-directional and fully networked wireless communications. Light-emitting diode (LED) is the major light source employed by LiFi as LED is energy efficient for illumination, and at the same time can achieve high speed data transmission thanks to the LED fast switching capability. Now, LED communications...