A Multi-Degree-of-Freedom Differential Power Processing Architecture for Photovoltaic System

Differential power processing (DPP) architectures employ distributed, low power processing, submodule-integrated converters to mitigate mismatches in photovoltaic (PV) power systems, while introducing no insertion losses. This paper evaluates the effects of the simple voltage-balancing DPP control approach on the submodule-level maximum power point (MPP) efficiency. It is shown that the submodule MPP efficiency of voltage-balancing DPP converters exceeds 98% in the presence of worst-case MPP voltage variations due to irradiance or temperature mismatches. Furthermore, the effects of reduced converter power rating in the isolated-port DPP architecture are investigated by long-term, high-granularity simulations of five representative PV system scenarios. For partially shaded systems, it is shown that the isolated-port DPP architecture offers about two times larger energy yield improvements compared to full power processing (FPP) module-level converters, and that it outperforms module-level FPP approaches even when the power rating of DPP converters is only 20-30% of the PV system peak power. In the cases of aging-related mismatches, more than 90% of the energy yield improvements are obtained with DPP converters rated at only 10% of the PV peak power.

In order to deal with mismatch issues caused by partial shading in small-scale photovoltaic systems, distributed MPPT (dMPPT) is applied in panel level or submodule level by means of DC-DC converters including full power processing (FPP) architectures and differential power processing (DPP) architectures. Compared with FPP architectures, DPP architectures can achieve higher efficiency and lower cost, because only portion of power is processed through the converter. This paper proposes a modified DPP architecture with a virtual port in series with the submodule string, which can greatly simplify the installation compared with that of conventional submodule level DPP and FPP converters. Meanwhile, it also retains the high efficiency as DPP architectures usually do. MPPT strategy is implemented by utilizing only one current sensor to reduce the hardware cost. Finally, simulations and experiments are presented to verify the proposed structure.

In this paper, a new perspective on the analysis and comparison of Differential Power Processing (DPP) architectures by using Continuous Power Model (CPM) and VA area interpretation is presented. Rather than accounting for the nominal power delivered by the DPP converters, the direct power $\pmb{(P_{dir})}$ and differential power $\pmb{(P_{diff})}$ are used for the comparison. CPM and VA area are used to calculate $\pmb{P_{dir}}$ and $\pmb{P_{diff}}$ at architecture level and to visualize the direct power transfer path, then the equations are derived for each architecture. Afterwards, statistical analysis is conducted to compare different DPP architectures with variations of sunlight irradiance level on each PV module and varied numbers of stacked modules in the strings. Finally, a conceptual architecture which can reach the theoretical limit is proposed.

Differential power processing (DPP) architectures have attracted lots of research interests in recent years to deal with mismatch problem in residential photovoltaic (PV) systems. However, conventional DPP structures may face hardware cost and efficiency challenge when the PV string is long. This paper proposes an improved DPP structure with a virtual port connected in series with the submodule string. Compared with conventional DPP solutions, the proposed structure not only reduces current stress but also has high system efficiency when the number of PV panels increase. Besides, installation requirement is simplified. Furthermore, a single loop control method is proposed with only one current sensor to reduce hardware cost. Distributed maximum power point tracking (dMPPT) in submodule level is realized. Finally, a 300W prototype is built and experimental results verify the proposed structure.

Differential power processing architectures in photovoltaic applications have recently drawn a lot of attentions. As the efficiency and cost-effectiveness of the system is of high demand in today's PV applications, this paper proposes a novel differential power processing (DPP) architecture which enables each PV panel to operate at its local maximum power point (MPP) while processing only a small fraction of its generated power. The fractional power is processed through a modular integrated converter (MIC). Thus, the converters (MICs) are rated for lower current ratings since they process the differential current between PV panel MPP and the local point of the PV string. The MICs are employing a magnetically coupled Cuk converter architecture to reduce the overall system size, weight and cost. The validation results in this paper proved the system effectiveness and high efficient operating under various load and shading conditions.

Recently, the module integrated converter and differential power processing (DPP) architecture were introduced to enable the photovoltaic (PV) power conditioning system to maintain the optimal operating condition of PV cells, such as maximum power point tracking (MPPT), even under partial shading conditions. However, the DPP architecture was found to have more room to optimize the performance of the systems, by the application of an extra extremum-seeking control, the so-called least power point tracking (LPPT) method that was introduced last year. The main idea is that most of the power from the PV modules is processed through the main-string high-efficiency nonisolation converter, and only a minimal fraction of the power that changes depending on the PV-string current is transferred through the low-efficiency bidirectional isolated DPP converters. This paper suggests a second version of the LPPT method, called unit-minimum power-distributing LPPT, which improves the first version of LPPT, called total-minimum centralized power-distributing LPPT. Instead of minimizing the total power of DPPs, the proposed LPPT minimizes the power of the DPP converter unit, which is the largest among them. Then, the system size and cost can be reduced by the proposed LPPT method, which enables the multiple DPP converters to have smaller power capacity and losses than those of the previous LPPT method. The real-time extremum-seeking algorithm employs a perturb-and-observe method, which comes from the conventional MPPT one, while the optimization process directs minimal extremity, not maximal. The peak system efficiency achieved with a 400-W prototype DPP system employing the LPPT algorithm is 96.7%.

When photovoltaic (PV) cells are connected in series, they experience internal and external mismatch that reduces output power. Differential power processing (DPP) architectures achieve high system efficiency by processing a fraction of the total power while maintaining distributed local maximum power point operation. This paper details the computational methods and analysis used to determine the operation of PV-to-bus and PV-to-PV DPP architectures with rating-limited converters. Simulations for both DPP architectures are used to evaluate system performance over 25 years of operation. Based on data from field studies, a PV power coefficient of variation can be estimated as 0.086 after 25 years. An improvement figure of merit reflecting the ratio of energy produced to that delivered in a conventional system is introduced to evaluate comparative performance. Converter ratings of 15-17% for PV-to-bus and 23-33% for PV-to-PV architectures are identified as appropriate ratings for a 15-submodule system (five PV panels in series). Both DPP architectures with these ratings are shown to deliver up to 2.8% more power compared to a conventional series-string architecture based on the expected panel variation over 25 years of operation. DPP converters also outperform dc optimizers in terms of lifetime performance.

This study analyzes, from a power processing architecture standpoint, the recovery of thermal energy waste by means of thermoelectric (TE) modules and arrays. Existence, in many industrial scenarios, of stable and often significant temperature gradients, enables a number of possibilities for effective processing and recovery of waste heat, which could result in marked economic savings and environmental benefits if adopted on a large scale and systematically embedded into industrial processes. A review of the thermoelectric source is provided first, along with an extensive experimental characterization of commercial Bismuth-Telluride TE cells. Results indicate that maximum power extraction from TE generators can be achieved at a thermoelectric efficiency close to optimal, motivating the adoption of maximum power point tracking (MPPT) architectures, traditionally employed in photovoltaic systems, to thermoelectric plants as well. Three power processing architectures are then analyzed and compared in terms of their maximum power extraction capabilities and of the efficiency constraint they pose on the power processors. Differently from the photovoltaic case, the simple series configuration of TE modules allows to extract most of the available power even in presence of rather large mismatches among the modules. For even larger mismatch levels, the differential power processing (DPP) concept, already introduced for dc-dc distribution systems and photovoltaic plants, can be successfully adopted to improve power extraction. On the other hand the module-integrated converter (MIC) architecture, another well-established solution for photovoltaic sources, is found to be much less indicated for TE generators than the DPP solution. Main conclusions are experimentally validated using a DPP architecture with a two-cell test bed operated at different thermal gradients.

This paper proposes a differential power processing (DPP) architecture applied to a series PV string which enables each PV element to operate at its local maximum power point (MPP) while processing only a small portion of its total generated power through the module integrated converters (MICs). The current processed through each converter is the difference between the local PV element MPP current and the local PV string current. This feature allows for a reduced current stress on the MIC components relative to the most common DPP topology. Thus, a higher system efficiency is realized at a reduced cost. A state space model of the proposed system is derived, and a comparison analysis is carried out with respect to the conventional DPP architectures. Additionally, a modular and compact design is proposed for a large number of PV panels in a series PV string. A hardware prototype is designed and built for 3 PV panels connected in series to validate the proposed architectures effectiveness and experimentally demonstrate its robustness. The modularity of the system is also tested to ensure low current and voltage stress on the MICs.

Differential power processing architecture to increase energy harvesting of photovoltaic systems under permanent mismatch

Series-stacked server power delivery architectures have been proposed recently that can achieve much higher energy efficiency than conventional power delivery architectures. When servers are connected in series, differential power processing (DPP) converters can be used to regulate the server voltages when the servers are consuming different amount of currents. Server-to-bus DPP architecture has unique advantages among several other DPP architectures such as being able to achieve the minimum power processed in the DPP converters, and having a higher reliability than other DPP architectures. This work presents the development of a server-to-bus DPP architecture for server power delivery. The hardware prototype is built with four 4-to-1 isolated DPP converters with GaN switches. Four 12V 120W Dell servers are used in the bench test to validate the operation of server-to-bus DPP. 98.99% efficiency is achieved while the servers are running a real-life data center computational load.

The internal and external mismatches experienced on photovoltaic (PV) cells will reduce the actual output power. Compared with the full power processing (FPP) architecture, differential power processing (DPP) architectures achieve high system reliable and efficiency by processing a fraction of total power when maintaining the operation of distributed local maximum power point (MPP). This paper presents a comprehensive review of different DPP architectures in terms of the connection, power converter topologies, and MPPT control. The conclusion was drawn based on the literature review and evaluation.

This paper presents a Differential Power Processing (DPP) architecture applied to series-connected thermoelectric generators (TEG). Currently, thermoelectric technology is being considered as a promising power generation technology that can be used to recover waste heat energy. Thus, a thermoelectric generation system is studied under non-uniform temperature conditions in multiple TEG devices. The main objective is to allow each thermoelectric sub-module to reach its maximum power point more quickly. The purpose has been to improve the maximum power point tracking (MPPT) in each sub-module, thus it is possible to increase the efficiency with respect to the traditional method based on a global MPPT. Differential Power converters have been implemented in each TEG sub-module to provide an effective solution and mitigate the impact of the mismatch in the power obtained. The DPP architecture consists of a small micro-converter, at the submodular level, applied to the thermoelectric cell. The control algorithm is oriented to polarize each TEG device at its optimal point, which allows us an active balancing among the different TEG sub-modules regardless of the operating temperature. Matlab-Simulink has been the software used to develop the TEG module-array.

To avoid mutual interference between the converter least power point tracking (CLPPT) algorithm and the photovoltaic maximum power point tracking (PMPPT) algorithm in the photovoltaic differential power processing (DPP) architecture, the converter-least-photovoltaic-maximum power point tracking (CL-PMPPT) algorithm is proposed in this paper. The proposed algorithm eliminates wrong response between CLPPT and PMPPT by using PMPPT as the control inner loop and CLPPT as the outer loop. Moreover, by adding the steady-state zero-oscillation algorithm and the approximate calculation of the optimal main string current, the proposed algorithm eliminates the steady-state three-level oscillation and improves the tracking speed. Compared with conventional DPP control algorithm, the proposed algorithm achieves faster tracking speed, better steady-state performance and higher efficiency. Followed by theoretical analysis, the simulation verifies the claimed advantages of the proposed CL-PMPPT algorithm.

Differential power processing (DPP) converters are utilized in photovoltaic (PV) power systems to achieve high-efficiency power output, even under uneven lighting or mismatched PV cell situations. Since this DPP concept has been introduced for PV systems, various topologies and control algorithms have been proposed and validated, showing the benefits of DPP converters systems over existing series string and full power processing converter solutions. However, DPP systems are highly coupled and can be challenging to control. Various architectures, topologies, and control strategies for both series and parallel DPP architectures are reviewed and compared. Tradeoffs of different DPP converters and topologies are discussed. Also, the power curve for the PV connected to bus, PV to PV, and PV to independent port series DPP architectures are evaluated in terms of inverter interaction. To date, the PV to PV series DPP systems have been most widely implemented and robust system-level control for all architectures has been a major research focus. Furthermore, research and development is still needed, particularly for commercialization and parallel DPP approaches for emerging PV applications.