A Comprehensive Classification of State-of-the-Art Distributed Maximum Power Point Tracking Architectures for Photovoltaic Systems
Authors: Afshin Nazer; Olindo Isabella; Patrizio Manganiello
Extended abstract:
Photovoltaic (PV) systems are widely used in residential, commercial, and utility-scale applications, but their performance is often limited by unavoidable mismatch conditions such as partial shading, nonuniform module orientation, dust accumulation, aging, and manufacturing tolerances. These effects reduce energy harvesting efficiency in conventional centralized Maximum Power Point Tracking (MPPT) systems. Distributed Maximum Power Point Tracking (DMPPT) has therefore emerged as a key solution to mitigate mismatch losses by enabling power optimization at finer levels of granularity.
In recent years, DMPPT research has expanded rapidly, leading to a large number of Full Power Processing (FPP) and Differential Power Processing (DPP) architectures, along with diverse converter topologies, modulation techniques, and control strategies. More recently, hybrid and hierarchical approaches have further broadened the design space by combining multiple architectural advantages. While this progress has driven significant innovation, it has also resulted in a fragmented body of literature, making it difficult to systematically compare approaches and identify optimal solutions for specific applications.
This review addresses this challenge by providing a structured and comprehensive classification of state-of-the-art DMPPT architectures for PV systems. It begins by outlining the hierarchical structure of PV systems, from array and string levels down to module, submodule, and cell levels, establishing a unified framework for distributed power conversion. Within this framework, both FPP and DPP architectures are systematically analyzed and compared in terms of operating principles, converter requirements, control strategies, and practical implementation considerations.
For FPP architectures, the paper reviews microinverters, modular multilevel cascade inverters, and DC-based distributed configurations such as parallel, series, and total cross-tied systems. Their advantages, limitations, and industrial relevance are discussed in detail. In contrast, DPP architectures, including Series DPP (SDPP), Parallel DPP (PDPP), and Series-Parallel DPP (SPDPP, are highlighted for their ability to process only mismatch power rather than full system power, significantly reducing converter ratings while maintaining effective energy balancing. This makes DPP particularly attractive for improving efficiency, reliability, and reducing system cost.
The review also compares converter topologies and control methods across different architectures. In addition, emerging hybrid and hierarchical DMPPT solutions are presented, demonstrating how multiple approaches can be integrated to leverage their complementary strengths.
Overall, this paper provides more than a literature survey; it offers a unified roadmap for researchers and engineers working in photovoltaic power electronics. By consolidating recent developments into a coherent taxonomy, evaluating trade-offs among existing solutions, and identifying open research challenges, this review supports the design of next-generation DMPPT systems aimed at enhancing the efficiency, reliability, and economic viability of future photovoltaic installations.
About the first author: Afshin Nazer received his PhD degree from the Photovoltaic Materials and Devices (PVMD) group at Delft University of Technology (TU Delft), the Netherlands, where the content of this work was developed. He is now a Postdoctoral Researcher with the Electrical Power Processing (EPE) Group at Eindhoven University of Technology (TU/e), the Netherlands. His research focuses on advanced power electronic converters for renewable energy systems and electrical machine drive applications. His current research investigates next-generation power converter architectures based on wide-bandgap semiconductor devices to improve the efficiency, reliability, and power density of future energy conversion systems.