Web based monitoring of solar power systems

Stroia, Nicoleta; Moga, Daniel

doi:10.3182/20130522-3-ro-4035.00046

Cited by 9 publications

(7 citation statements)

References 1 publication

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“…Considering previously developed sensing modules (Figure 10) ( [45,[50][51][52][53]), and the versatile modular architecture that was demonstrated in a broad range of applications (greenhouse climate control, smart-home on-demand ventilation, air-quality monitoring, etc. ), the first approach considered was to reuse the hardware functionality of the host module, based on a 32-bit microcontroller, as much as possible, and to interface it to the energy metering board.…”

Section: Development Of the Smart-meter Node With Wireless Communicationmentioning

confidence: 99%

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Stroia

Moga²,

Petreuş³

et al. 2022

Buildings

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The monitoring of power consumption and the forecasting of load profiles for residential appliances are essential aspects of the control of energy savings/exchanges at multiple hierarchical levels: house, house cluster, neighborhood, and city. External environmental factors (weather conditions) and inhabitants’ behavior influence power consumption, and their usage as part of forecasting activity may lead to added value in the estimation of daily-load profiles. This paper proposes a distributed sensing infrastructure for supporting the following tasks: the monitoring of appliances’ power consumption, the monitoring of environmental parameters, the generation of records for a database that can be used for both identifying load models and testing load-scheduling algorithms, and the real-time acquisition of consumption data. The hardware/software codesign of an integrated architecture that can combine the typical distributed sensing and control networks present in modern buildings (targeting user comfort) with energy-monitoring and management systems is presented. Methods for generating simplified piecewise linear (PWL) representations of the load profiles based on these records are introduced and their benefits compared with classic averaged representations are demonstrated for the case of peak-shaving strategies. The proposed approach is validated through implementing and testing a smart-meter node with wireless communication and other wired/wireless embedded modules, enabling the tight integration of the energy-monitoring system into smart-home/building-automation systems. The ability of this node to process power measurements with a programable granularity level (seconds/minutes/hours) at the edge level and stream the processed measurement results at the selected granularity to the cloud is identified as a valuable feature for a large range of applications (model identification, power saving, prediction).

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Section: Development Of the Smart-meter Node With Wireless Communicationmentioning

confidence: 99%

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Stroia

Moga²,

Petreuş³

et al. 2022

Buildings

Self Cite

View full text Add to dashboard Cite

show abstract

“…PV system monitoring is crucial for various reasons [ 10 ] and the concept of PV monitoring is common even in non-energy applications [ 11 ]. Monitoring regimes vary in frequency, i.e.…”

Section: Study Backgroundmentioning

confidence: 99%

“…Low-cost performance monitoring and data acquisition systems for off-grid applications based on data logging [ 21 ], Arduino [ 22 ] and Visual Basic [ 23 ] have also been developed. Microcontroller-based and LabVIEW or MATLab combinations remote PV monitoring and fault detection softwares have been developed by several researchers [ 11 , 20 , 24 , 25 ]. Mukai et al [ 8 ] conducted a comparative study on the technical benefits of CM over PI based on roof-top grid-tied systems.…”

Section: Study Backgroundmentioning

confidence: 99%

Section: Study Backgroundmentioning

confidence: 99%

“…Modern remote web-based monitoring platforms are able to relay PV array voltages and currents, array tilt angles, PV and ambient temperatures, irradiance, wind speeds, dust, rain and/or snow levels [ 11 , 24 ]. Details of remote solution algorithms currently employed in most applications have been expounded at length by several authors [ 1 , 11 ]. Most modern commercial systems, however, still allow for performance visualization and analysis of transient phenomena only and key suppliers of these systems include; SMA Solar Technologies, Fronius International GmbH, InAccess Networks, Fat Spaniel Technologies, MorningStar Corporation, SolarMax, [ 29 ] Victron Energy, among others.…”

Section: Study Backgroundmentioning

confidence: 99%

See 2 more Smart Citations

Evaluation of IoT-based remote monitoring systems for stand-alone solar PV installations in Kenya

Njoka

Thimo²,

Agarwal

2022

J Reliable Intell Environ

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The deployment of remote monitoring systems based on Internet of Things (IoT) presents an opportunity to curtail operational and maintenance (O&M) costs associated with stand-alone PV systems. This study evaluates the characteristics of the commonly employed IoT platforms, their capabilities and associated O&M cost savings. Analysis of avoided field visit costs based on three remotely monitored solar PV sites is conducted through clustering of system faults and filtering out major ones that would warrant actual site visits. The obtained results are verified with information gathered from four other PV installer companies based in Nairobi, Kenya. Results obtained from the study show that majority of system faults can be monitored and often corrected remotely. Annual site-specific cost savings associated with IoT platforms range from $2040 to $3096. In comparison to ordinarily locally monitored systems, annual operation and maintenance costs can be reduced by 47–95%. This implies that it is now possible to adequately maintain healthy solar PV systems located in remote locations ensuring their longevity and convenience.

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Renewable Energy in Smart Grid: Photovoltaic Power Monitoring System Based on Machine Learning Using an Open-Source IoT Platform

Hakam

Ahessab

Gaga

et al. 2023

Digital Technologies and Applications

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Web based monitoring of solar power systems

Cited by 9 publications

References 1 publication

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Integrated Smart-Home Architecture for Supporting Monitoring and Scheduling Strategies in Residential Clusters

Evaluation of IoT-based remote monitoring systems for stand-alone solar PV installations in Kenya

Renewable Energy in Smart Grid: Photovoltaic Power Monitoring System Based on Machine Learning Using an Open-Source IoT Platform

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