A novel fault diagnostic strategy for PV micro grid to achieve Reliability Centered Maintenance

Rao, K. Uma; Parvatikar, Akash G.; Gokul, S; Nitish, N; Rao, P. Bhasker

doi:10.1109/icpeices.2016.7853546

Cited by 9 publications

(1 citation statement)

References 4 publications

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“…Sophisticated distributed sensing and decision-making functions are performed at different levels collaboratively, ranging from local nodes that locally optimize performance, bandwidth, and maintenance to cloudbased platforms that integrate information from diverse systems and execute distributed processing and analytics algorithms for global decision-making. In 2016, Rao (7) proposed an intelligent approach towards the fault diagnostics of a solar microgrid with a battery backup for a reliabilitycentered maintenance approach to supersede and improve the preventive maintenance strategy.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Maintenance Scheduling System for Maximum Performance of Solar Energy Generating System

2017

Sensors and Materials

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In this research, an intelligent maintenance scheduling system for gaining the maximum performance of a solar-energy-generating system is proposed. In the system, the particle swarm optimization (PSO) algorithm is used for the intelligent maintenance scheduling of the solarenergy-generating system. The maintenance center receives many maintenance prescription requests from all solar-energy-generating stations. For various uncertainties, the optimal solution of maintenance scheduling is considered. To reduce maintenance costs and improve maintenance efficiency, the intelligent scheduling system using the PSO method is constructed. In the maintenance scheduling model, the maintenance time and prework time are set to be the optimal computing parameters, and the lowest cost is set to be the optimal target. By design and implementation, we can determine the advantages of the PSO-based intelligent system. It meets both requirements of real time and integration for intelligent systems. Experimental results show the advantages of the intelligent maintenance scheduling system for the maximum performance of the solar-energy-generating system; that is, such a scheduling system meets both requirements of efficiency and lowest cost for the intelligent maintenance of the solar-energy-generating system.

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Section: Introductionmentioning

confidence: 99%

Intelligent Maintenance Scheduling System for Maximum Performance of Solar Energy Generating System

2017

Sensors and Materials

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Reconfiguration of Micro-grid for Future Forecasting to Maintain High Reliability

Mishra

Viral

2021

Innovations in Cyber Physical Systems

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A comprehensive review on failure modes and effect analysis of solar photovoltaic system

Pimpalkar¹,

Sahu²,

Patil³

et al. 2023

Materials Today: Proceedings

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A novel fault diagnostic strategy for PV micro grid to achieve Reliability Centered Maintenance

Cited by 9 publications

References 4 publications

Intelligent Maintenance Scheduling System for Maximum Performance of Solar Energy Generating System

Intelligent Maintenance Scheduling System for Maximum Performance of Solar Energy Generating System

Reconfiguration of Micro-grid for Future Forecasting to Maintain High Reliability

A comprehensive review on failure modes and effect analysis of solar photovoltaic system

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