Design and implementation of an intelligent low-cost IoT solution for energy monitoring of photovoltaic stations

Cheddadi, Youssef; Cheddadi, Hafsa; Cheddadi, Fatima; Errahimi, Fatima; Es-Sbai, Najia

doi:10.1007/s42452-020-2997-4

Cited by 81 publications

(41 citation statements)

References 26 publications

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“…Some threshold limits are also applied to decision-based on the result in accordance with ISO 10,186-3 standard [15]. Cheddadi et al [16] demonstrated the design of an intelligent IoT enabled energy monitoring system and effectively implemented at photovoltaic stations.…”

Section: Development Of Strategy For An In-house Adaptive Controllermentioning

confidence: 99%

Development of in-situ adaptive controller for end milling based on vibration feedback

Reddy

Prasad

Raghuram³

et al. 2021

SN Appl. Sci.

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This study establishes a tool condition monitoring methodology builds on the vibration signal attained via data acquisition system which is integrated with the in house developed adaptive controller for an end milling. As the quality of the products and the machine tool performance are the key parameters in maintaining machine stability. Proposed Adaptive control optimization system is validated with the experimentation trials and data analysis on 3 axis CNC milling machine. The rotational speed of the spindle and vibration signals is found to be reactive to milling cutter condition and therefore capable of sustaining the set-out methodology. A novel hybrid transformation, coupled with FFT and HHT is proposed to distinguish between a source of variation for adaptive control optimization, cutting region with the non-cutting region. In this study, decisions are made to evaluate the tool condition by combining all related information into a rule base. The investigation trajectories unveil the established system be able to accomplish the mechanism properly as anticipated.

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Section: Development Of Strategy For An In-house Adaptive Controllermentioning

confidence: 99%

Development of in-situ adaptive controller for end milling based on vibration feedback

Reddy

Prasad

Raghuram³

et al. 2021

SN Appl. Sci.

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“…Furthermore, equipment named AFCI is developed in [67] to protect PV plants from an arc fault. c) Tele-monitoring Controlling and diagnosing the PVG from long distance using new smart protocols such as ZigBee technology [74] and Internet of Thing (IoT) [75]. Cost reduction is required for any envisaged solutions for diagnosing PV generators.…”

Section: Pvg Faults Detection and Diagnosis Used Techniquesmentioning

confidence: 99%

A comprehensive study of diagnosis faults techniques occurring in photovoltaic generators

et al. 2021

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Recently, many focuses have been done in the field of renewable energies, especially in solar photovoltaic energy. Photovoltaic generator, considered as the heart of any photovoltaic installation, exhibits sometimes malfunctions which involve degradations on the overall photovoltaic plant. Therefore, diagnosis techniques are required to ensure failures detection. They avoid dangerous risks, prevent damages, allow protection, and extend their healthy life. For these purposes, many recent studies have given focuses on this field. This paper summarizes a large number of such interesting works. It presents a survey of photovoltaic generator degradations kinds, several types of faults, and their major diagnosis techniques. Comparative studies and some critical analyses are given. Other trending diagnosis solutions are also discussed. A proposed neural networks-based technique is developed to clarify the main process of diagnosis techniques, using artificial intelligence. This method shows good results for modelling and diagnosing the healthy and faulty (shaded) photovoltaic array.

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“…Recently some hybrid intelligent renewable EMSs have been proposed, which employ two-way communication and artificial intelligence (AI) or big data analytics approaches for lowering consumer' bills. [13][14][15][16] Lin presented an IoT-oriented EMS based on neuro-fuzzy classification for distinguishing electrical appliances operated under similar electrical features. 17 Lin and Tsai proposed an advanced HEMS for implementing residential DR for demand-side load management by autonomously and meta-heuristically scheduling household appliances without user intervention, however, costbenefit analysis, which is an important consideration for such a system has been suggested as future work.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Their work is closely related to ours but there are some differences; our system does not employ fog nodes and we use message queuing telemetry transport (MQTT) protocol, which is a light‐weight data‐centric IoT protocol specifically developed for real‐time telemetry data. Recently some hybrid intelligent renewable EMSs have been proposed, which employ two‐way communication and artificial intelligence (AI) or big data analytics approaches for lowering consumer' bills 13‐16 . Lin presented an IoT‐oriented EMS based on neuro‐fuzzy classification for distinguishing electrical appliances operated under similar electrical features 17 .…”

Section: Literature Reviewmentioning

confidence: 99%

Internet of things and cloud computing‐based energy management system for demand side management in smart grid

Hashmi¹,

2020

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Design and implementation of an intelligent low-cost IoT solution for energy monitoring of photovoltaic stations

Cited by 81 publications

References 26 publications

Development of in-situ adaptive controller for end milling based on vibration feedback

Development of in-situ adaptive controller for end milling based on vibration feedback

A comprehensive study of diagnosis faults techniques occurring in photovoltaic generators

Internet of things and cloud computing‐based energy management system for demand side management in smart grid

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