Abstract

Solar photovoltaic (PV) direct current (DC) microgrids have gained significant popularity during the last decade for low cost and sustainable rural electrification. Various system architectures have been practically deployed, however, their assessment concerning system sizing, losses, and operational efficiency is not readily available in the literature. Therefore, in this research work, a mathematical framework for the comparative analysis of various architectures of solar photovoltaic-based DC microgrids for rural applications is presented. The compared architectures mainly include (a) central generation and central storage architecture, (b) central generation and distributed storage architecture, (c) distributed generation and central storage architecture, and (d) distributed generation and distributed storage architecture. Each architecture is evaluated for losses, including distribution losses and power electronic conversion losses, for typical power delivery from source end to the load end in the custom village settings. Newton–Raphson method modified for DC power flow was used for distribution loss analysis, while power electronic converter loss modeling along with the Matlab curve-fitting tool was used for the evaluation of power electronic losses. Based upon the loss analysis, a framework for DC microgrid components (PV and battery) sizing was presented and also applied to the various architectures under consideration. The case study results show that distributed generation and distributed storage architecture with typical usage diversity of 40% is the most feasible architecture from both system sizing and operational cost perspectives and is 13% more efficient from central generation and central storage architecture for a typical village of 40 houses. The presented framework and the analysis results will be useful in selecting an optimal DC microgrid architecture for future rural electrification implementations.

Highlights

  • Reliable access to electricity is one of the basic indicators for the quality of life and the economic standing of any community [1,2]

  • It has been observed that central generation and central storage architecture (CGCSA) and distributed generation and distributed storage architecture (DGDSA) without sharing among households outperform compared to central generation and distributed storage architecture (CGDSA) and distributed generation and central storage architecture (DGCSA), various sharing scenarios of DGDSA are compared with the base scenario of CGCSA for the comparative evaluation

  • In an islanded solar PV direct current (DC) microgrid, where the grid connection is not available, the only source of generation is through PV modules, system losses directly impact the required PV sizing for the fulfillment of load demand

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Summary

Introduction

Reliable access to electricity is one of the basic indicators for the quality of life and the economic standing of any community [1,2]. Our second contribution mainly includes the identification and the quantification of various parameters that are coupled with the architectural design and impact the operational efficiency of the microgrid system These parameters mainly include converter count, percentage output power loading of each converter, distribution conductor size, power demand at each household, and intra-village special distribution of houses [24]. Though each of these components affects the operational efficiency of the system, their impact on system efficiency can be quantified in terms of two generic categories, i.e., (a) distribution losses and (b) power electronic conversion losses.

Commonly Used System Architecture for Rural Electrification
Central Generation and Central Storage Architecture
Central Generation and Distributed Storage Architecture
Distributed Generation and Central Storage Architecture
Distributed Generation and Distributed Storage Architecture
Distribution Loss Analysis Using Newton–Raphson Modified for DC Power Flow
Power Electronic Conversion Loss Analysis
Power Flow Diagrams and Village Scale PV Sizing Estimation
Power Flow Diagram and PV Sizing Estimation for CGCSA
Power Flow Diagram and PV Sizing Estimation for CGDSA
Power Flow Diagram and PV Sizing Estimation for DGCSA
Village Scale Battery Sizing
Case Study Parameters
Results and Discussions
Distribution and Power Electronic Conversion Loss Analysis
PV and Battery Sizing Comparison
Conclusions

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