Preprint Article Version 1 This version is not peer-reviewed

Data–Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants

Version 1 : Received: 23 January 2019 / Approved: 26 January 2019 / Online: 26 January 2019 (10:08:46 CET)

A peer-reviewed article of this Preprint also exists.

Simani, S.; Alvisi, S.; Venturini, M. Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants. Electronics 2019, 8, 237. Simani, S.; Alvisi, S.; Venturini, M. Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants. Electronics 2019, 8, 237.

Journal reference: Electronics 2019, 8, 237
DOI: 10.3390/electronics8020237

Abstract

The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, data--driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods, such as fuzzy and adaptive self--tuning controllers, were already verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. The working conditions of these systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.

Subject Areas

wind turbine system; hydroelectric plant simulator; model--based control; data–driven approach; self–tuning control; robustness and reliability

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.