Power Quality Improvement of a Standalone Power Supply System Powered by PV, Wind, and Batteries via LSTM-based ANN Controllers
Keywords:
Power Supply, Wind Technology, Photovoltaic Technology, Battery, Power QualitySynopsis
This is a Chapter in:
Book:
Competitive Tools, Techniques, and Methods
Print ISBN 978-1-6692-0008-6
Online ISBN 978-1-6692-0007-9
Series:
Chronicle of Computing
Chapter Abstract:
Standalone electric power supply systems that integrate wind and photovoltaic (PV) technologies are widely employed in various applications. These systems require a battery storage system to ensure a continuous power supply, regardless of changes in loads, wind speed, and solar irradiance. To ensure a reliable and uniform power supply, several modifications need to be implemented in these hybrid systems. Power quality is an essential parameter in autonomous power systems, especially those that depend on hybrid energy sources. The battery should undergo the process of charging when there is an excess of energy and discharging when there is a demand from the loads. To achieve this, a bidirectional power flow circuit is utilized to establish a connection between the battery and the network, incorporating an appropriate controlling mechanism. Even in scenarios where there is only partial shading, a Modified Invasive Weed Optimization technique is employed to achieve the most efficient power operation of the photovoltaic (PV) system. Additionally, a Sliding Mode Control strategy is utilized for the wind turbine. This research investigates the application of multiple photovoltaic (PV) systems and wind turbines, each configured with different arrangements of parallel and series combinations of PV panels. The goal is to determine the appropriate rating for the power supply system. The control units in this hybrid standalone power system utilize artificial neural network (ANN) controllers that are based on long short-term memory (LSTM). The aforementioned controllers, when combined with the proposed control methodologies, improve power quality in various scenarios. The results of this investigation are presented using Hardware-in-the-Loop (HIL) on the OPAL-RT platform to evaluate the efficacy of the proposed methodology.
Cite this paper as:
Molu R., Mbasso W.F., Naoussi S., Wira P., Ambe H., Saatong K. T. (2024) Power Quality Improvement of a Standalone Power Supply System Powered by PV, Wind, and Batteries via LSTM-based ANN Controllers. In: Tiako P.F. (ed) Competitive Tools, Techniques, and Methods. Chronicle of Computing. OkIP. CEST24#20. https://doi.org/10.55432/978-1-6692-0007-9_10
Presented at:
The 2024 OkIP International Conference on Energy and Sustainable Technologies (CEST) in Oklahoma City, Oklahoma, USA, and Online, on April 3, 2024
Contact:
Reagan J. J. Molu
molureagan@yahoo.fr
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