Mashood Nasir

Solar PV-Based Scalable DC Microgrid for Rural Electrification in Developing Regions

In this paper, we detail the design, analysis, and implementation of a highly distributed off-grid solar photovoltaic dc microgrid architecture suitable for rural electrification in developing countries. The proposed architecture is superior in comparison with existing architectures for rural electrification because of its 1) generation and storage scalability, 2) higher distribution efficiency (because of distributed generation and distributed storage for lower line losses), 3) ability to provide power for larger communal loads without the requirement for large, dedicated generation by extracting the benefit of usage diversity, and 4) localized control by using the hysteresis-based voltage droop method, thus eliminating the need for a central controller. The proposed microgrid architecture consists of several nanogrids capable of the self-sustained generation, storage, and bidirectional flow of power within the microgrid. Bidirectional power flow and distributed voltage droop control are implemented through the duty cycle control of a modified flyback converter. A detailed analysis in terms of power flow, loss, and system efficiency was conducted by using the Newton–Raphson method modified for dc power flow at varying distribution voltages, conductor sizes, and schemes of interconnection among the contributing nanogrids. A scaled-down version of the proposed architecture with various power sharing scenarios was also implemented on hardware, and yielded satisfactory results.

Analysis on central and distributed architectures of solar powered DC microgrids

In this work, central and distributed architectures of DC microgrids for rural electrification are analyzed under various operating conditions. In the proposed scheme, a single household consumer forms the atomic nanogrid unit which may integrate its resources in a scalable model with the community to form a microgrid, without dependence of the national grid. The flow of power between houses and the microgrid is implemented through a bidirectional flyback converter. The operation of proposed scheme for two different architectures, i.e. distributed generation distributed storage architecture (DGDSA) and centralized generation centralized storage architecture (CGCSA) is evaluated at various distribution voltage levels and conductor sizes. Modified Newton Raphson Method based analysis is performed for both architectures which show that distributed architecture has significant advantages over central architecture due to higher efficiency, low voltage drop and lower line losses. Further, the scalable nature with minimum installation cost for distributed architecture makes it more favorable for rural electrification applications in comparison to central architecture. The simulated results are also verified using a scaled down version of hardware implementation.

A Decentralized Control Architecture applied to DC Nanogrid Clusters for Rural Electrification in Developing Regions

DC microgrids built through a bottom-up approach are becoming popular for swarm electrification due to their scalability and resource-sharing capabilities. However, they typically require sophisticated control techniques involving communication among the distributed resources for stable and coordinated operation. In this work, we present a communication-less strategy for the decentralized control of a photovoltaic (PV)/battery-based highly distributed dc microgrid. The architecture consists of clusters of nanogrids (households), where each nanogrid can work independently along with provisions of sharing resources with the community. An adaptive I–V droop method is used, which relies on local measurements of state of charge and dc bus voltage for the coordinated power sharing among the contributing nanogrids. PV generation capability of individual nanogrids is synchronized with the grid stability conditions through a local controller, which may shift its modes of operation between maximum power point tracking mode and current control mode. The distributed architecture with the proposed decentralized control scheme enables 1) scalability and modularity in the structure, 2) higher distribution efficiency, and 3) communication-less, yet coordinated resource sharing. The efficacy of the proposed control scheme is validated for various possible power-sharing scenarios using simulations on MATLAB/Simulink and hardware-in-the-loop facilities at the Microgrid Laboratory, Aalborg University.

Optimal Planning and Design of Low-Voltage Low-Power Solar DC Microgrids

Low-voltage, low-power solar photovoltaic (PV) based dc microgrids are becoming very popular in nonelectrified regions of developing countries due to lower upfront costs compared to utility grid alternatives and limited power needs of rural occupants. The optimal planning of distribution architecture along with sizing of various system components such as solar panels, batteries, and distribution conductors is essential for minimizing the system cost and enhance its utilization. In this paper, we develop a framework for optimal planning and design of low-power low-voltage dc microgrids for minimum upfront cost. The analysis is based on region-specific irradiance and temperature profiles; constraints in storage and distributions; distribution loss analysis; and optimum component sizing (storage, conductor, and PV panel) requirements based upon an energy balance model for a 24-h operation. We further analyze the merits of tailoring distribution architecture for maximizing the system utility in the planning of future microgrid deployments.

Lifetime maximization of lead-acid batteries in small scale UPS and distributed generation systems

In this paper, we analyze lifetime maximization problem of lead-acid batteries commonly used in small scale Uninterrupted Power Supply (UPS) and distributed renewable energy systems. The aging process of batteries in these systems is a complex phenomenon and depends upon many factors. We consider the most comprehensive lead-acid battery model that is commonly known as the weighted Ah-throughput (Schiffer) model and identify three key factors affecting the lifetime of these batteries: 1) bad recharge, 2) time since last full recharge and 3) the lowest state of charge since last full recharge. Each factor depends on battery state of charge (SoC). An appropriate weighted sum of these three factors dictating the battery life is considered as optimization objective. The appropriate constrained optimization problems for the two common scenarios are solved and SoC-based charge/discharge algorithms are formulated. Simulation results show significant improvement in the lifetime of lead-acid battery (more than 85% in some cases) as compared to the traditional terminal voltage based charge control algorithms.