A predictive algorithm for maximum power point tracking in solar photovoltaic systems through load management

•A predictive algorithm for MPPT in load-matching PV systems is demonstrated.•The algorithm allows PV systems to perform MPPT without a power converter.•The algorithm improves PV system efficiency over systems with a power converter.•The cost of the control electronics for load-matching PV systems i...

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Bibliographic Details
Published in:Solar energy Vol. 265; p. 112127
Main Authors: Tan, Kelvin, Parquette, William J., Tao, Meng
Format: Journal Article
Language:English
Published: Elsevier Ltd 15.11.2023
Subjects:
Load management
Maximum power point tracking (MPPT)
Photovoltaic (PV) systems
Solar energy
Load management
Maximum power point tracking (MPPT)
Photovoltaic (PV) systems
Solar energy
ISSN:0038-092X
Online Access:Get full text
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Summary:•A predictive algorithm for MPPT in load-matching PV systems is demonstrated.•The algorithm allows PV systems to perform MPPT without a power converter.•The algorithm improves PV system efficiency over systems with a power converter.•The cost of the control electronics for load-matching PV systems is below 1¢/Wp.•Applications in PV-powered electrolysis, such as hydrogen production, is proposed. In solar photovoltaic (PV) systems, maximum power point tracking (MPPT) is achieved when the impedance of the system load matches that of the PV array. The conventional approach to MPPT is to manage the output power of the PV array to adjust its impedance. This requires power electronics such as an inverter or charge controller, which induces cost and power loss. A PV system can also vary the system load by switching on and off parts of the load to match the impedances and find the maximum power point. It offers an inexpensive and efficient solution to MPPT as it does not require any conventional MPPT device. However, the demonstrated load-matching PV system is subject to power loss due to many unsuccessful switches. The algorithm in that system deployed a trial-and-error approach since the optimum switch points are typically unknown. This paper presents a predictive algorithm that can dynamically estimate the optimum switch points throughout the day using the powers measured from unsuccessful switches. It allows the system to track the maximum power point with minimum switches. The improved load-matching PV system has applications in PV-powered electrolytic hydrogen production.
ISSN:0038-092X
DOI:10.1016/j.solener.2023.112127