Performance Evaluation of On-Grid and Off-Grid Solar Photovoltaic Systems

A, Ajan.; John, Nirmala

doi:10.17148/ijireeice.2015.3205

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…In their research, Miller and Ye [5] evaluated the impact of using DG as a significant portion of the total energy resources by creating a model of Jeju Island, Korea and made use of three distributed generation systems to assess the potential negative power quality effects of high penetration of DG. Also, Ajan and Nirmala [6] modelled a stand-alone and grid-tied PV system using Simulink which was used to evaluate the relationship between PV system parameters and the output. The various Voltages, Current and Power levels are recorded.…”

Section: Introductionmentioning

confidence: 99%

Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

Ogunsina

Petinrin

et al. 2021

SN Appl. Sci.

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A system of power generation whereby the generating equipment is located close to the point of usage, thereby reducing losses and operation cost is called distributed generation (DG). However, it is imperative that DGs are sited such that the quality of power delivered is optimized and the total real power loss within the system minimized. This paper proposes an approach for optimum sizing and siting of DGs sizing in a power distribution system using Ant Colony Optimization (ACO) algorithm. To validate the algorithm the IEEE 30 bus standard test system was employed. A 92% decrease in real power loss within the system relative to the value before the connection of DGs was observed, while the minimum bus voltage increased from 0.656 per unit to 0.965 per unit. The results obtained from ACO are further verified by creating an ETAP model of the IEEE 30 bus system and simulating the impact of DG on the system. A significant reduction in total real power losses within the system and improvement in voltage profile was observed when the DGs are placed at the ACO derived sites relative to at other locations. Therefore, Ant Colony Algorithm can be used in deriving the optimum sites and sizes of DGs in a power distribution system.

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Section: Introductionmentioning

confidence: 99%

Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

Ogunsina

Petinrin

et al. 2021

SN Appl. Sci.

View full text Add to dashboard Cite

show abstract

“…Electricity generation from solar radiation is appealing because of no harmful emissions and the capability to be implemented as an off or on-grid power source. Generating electricity from the roof of houses during the day and then using electricity from the grid during the night minimize the electricity generation from other sources [9], [10]. In addition, in remote locations (without a grid) PV cells become a lowcost and reliable source if they are coupled with an energy storage unit such as a battery [10].…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic System Efficiency Enhancement with Thermal Management: Phase Changing Materials (PCM) with High Conductivity Inserts

2021

ijSmartGrid

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The electrical conversion efficiency of photovoltaic cells from solar radiation heavily depends on the cell temperature.Here we propose a novel thermal management strategy to keep the cell temperature in the same order to attain maximum efficiency. The comparative study presented is based on four solar module configurations: a conventional photovoltaic module (PVT module), a conventional module with PCM layer underneath (PVT/PCM-I), a configuration where fins embedded into PCM (PVT/PCM-II), and configuration where the bottom of the PCM layer in PVT/PCM-II was cooled via convection (PVT/PCM-III). The developed 3D numerical model is solved via ANSYS software involving the solar ray tracing radiation model for incident solar radiations and a transient melting-solidification thermo-fluid model to cater for PCM phase transition. Results from the numerical model were validated via a comparison of experimentally studied results presented in the literature. After 120 minutes, results show that the conversion efficiency of PV cells becomes 16.84%, 18.65%, 18.83%, and 18.98% after 120 minutes for PVT module, PVT/PCM-I, PVT/PCM-II, and PVT/PCM-III with an inlet velocity of 3m/s, respectively. For the respective configurations, the specific electrical power per unit area produced reaches 75.30W/m2, 83.39W/m2, 84.19W/m2, and 89.42W/m2 for solar radiation of 540W/m2 and 26°C ambient temperature. Results reveal that a 5 mm increase in the fin height for PVT/PCM-II results in a 0.22% increase in efficiency while a 0.5m/s increase in the inlet velocity of the cooling air for PVT/PCM-III results in about 0.06% increase in efficiency.

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Performance Evaluation of On-Grid and Off-Grid Solar Photovoltaic Systems

Cited by 2 publications

References 8 publications

Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

Optimal distributed generation location and sizing for loss minimization and voltage profile optimization using ant colony algorithm

Photovoltaic System Efficiency Enhancement with Thermal Management: Phase Changing Materials (PCM) with High Conductivity Inserts

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