Photovoltaic maximum power point tracking through reconfiguration and algorithm strategy: a comprehensive review

Document Type

Review

Publication Date

5-1-2026

Abstract

Solar photovoltaic (PV) system efficiency is highly dependent on Maximum Power Point Tracking (MPPT) technology. Currently, MPPT technology achieves performance optimization mainly through two core approaches: hardware-level reconfiguration strategy and software-level algorithm strategy, whose coordination is key to enhancing PV efficiency. First, this paper constructs a dual-core classification system for topology reconfiguration and control algorithms, dividing 36 topology reconfiguration strategies into 2 major categories and 5 subcategories; 105 control algorithm strategies are classified into 4 types, among which intelligent algorithms are further subdivided into 8 subcategories. Second, conduct a quantitative and qualitative comparative analysis focusing on core indicators such as tracking accuracy, dynamic response speed, local shading adaptability, computational complexity, and hardware cost. For example, results show that under local shading conditions, static topology reconfiguration strategies can reduce mismatch loss by up to 76.3%; compared with conventional algorithms, intelligent algorithms improve tracking efficiency by 10%-47%; hybrid strategies can achieve optimal balance of multiple performance indicators. Subsequently, based on capacity scale, shading characteristics and adaptive algorithms, a three-dimensional classification model is established to realize precise matching of MPPT technologies with residential and large-scale grid-connected photovoltaic systems under steady-state or dynamic shading scenarios. This system addresses the lack of scenario pertinence in existing review literature and provides direct technical guidance for the selection of engineering solutions. Finally, core bottlenecks of current MPPT technologies are clarified, and four future innovation directions are proposed: hybrid AI reconfiguration, dynamic cloud processing, standardized evaluation systems and scenario-adaptive engineering deployment, offering clear entry points for subsequent technological breakthroughs.

Keywords

Algorithm Strategy, MPPT, Photovoltaic system, Reconfiguration Strategy

Publication Title

Energy Conversion and Management X

ISSN

2590-1745

DOI

10.1016/j.ecmx.2026.101604

Volume

30

Publisher

Elsevier

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