IoT‐based low‐cost prototype for online monitoring of maximum output power of domestic photovoltaic systems

Rouibah, N.; Barazane, L.; Benghanem, M.; Mellit, A.

doi:10.4218/etrij.2019-0537

Cited by 21 publications

(5 citation statements)

References 30 publications

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“…To test the PV power system, we plotted in Figure 7 the data acquisition system, the output current, voltage, solar irradiance, and air temperature for a short period (25 May 2021, from 10 am to 12 am, with a time step of 5 s). To track the maximum power, the maximum power point algorithm was integrated, and more details can be found in our previous work [25,26]. From Figure 7b, it can be seen that the produced PV current and voltage were enough to supply the main components of the greenhouse.…”

Section: Photovoltaic Power Supply Systemmentioning

confidence: 99%

Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks

et al. 2021

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To support farmers and improve the quality of crops production, designing of smart greenhouses is becoming indispensable. In this paper, a novel prototype for remote monitoring of a greenhouse is designed. The prototype allows creating an adequate artificial environment inside the greenhouse (e.g., water irrigation, ventilation, light intensity, and CO2 concentration). Thanks to the Internet of things technique, the parameters controlled (air temperature, relative humidity, capacitive soil moisture, light intensity, and CO2 concentration) were measured and uploaded to a designed webpage using appropriate sensors with a low-cost Wi-Fi module (NodeMCU V3). An Android mobile application was also developed using an A6 GSM module for notifying farmers (e.g., sending a warning message in case of any anomaly) regarding the state of the plants. A low-cost camera was used to collect and send images of the plants via the webpage for possible diseases identification and classification. In this context, a deep learning convolutional neural network was developed and implemented into a Raspberry Pi 4. To supply the prototype, a small-scale photovoltaic system was built. The experimental results showed the feasibility and demonstrated the ability of the prototype to monitor and control the greenhouse remotely, as well as to identify the state of the plants. The designed smart prototype can offer real-time remote measuring and sensing services to farmers.

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Section: Photovoltaic Power Supply Systemmentioning

confidence: 99%

Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks

et al. 2021

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“…Likewise, due to the unpredictable performance and limited battery life in wireless sensor networks (WSNs), EH techniques have turned a typical battery‐powered WSN into an autonomous WSN [9]. In addition to WSNs, EH systems can also be applied for providing a power supply for the Internet of Things (IoT) devices to achieve a stable performance without the need of power cords, batteries, or chargers [10]. It is also important to note that hybrid EH (HEH) is turning to the point where it can be considered as a means of realizing the sustainable systems.…”

Section: Introductionmentioning

confidence: 99%

Thermally reused solar energy harvesting using current mirror cells

et al. 2023

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This paper implements a simultaneous solar and thermal energy harvesting system, as a hybrid energy harvesting (HEH) system, to convert ambient light into electrical energy through photovoltaic (PV) cells and heat absorbed in the body of PV cells. Indeed, a solar panel equipped with serially connected thermoelectric generators not only converts the incoming light into electricity but also takes advantage of heat emanating from the light. In a conventional HEH system, the diode block is used to provide the path for the input source with the highest value. In this scheme, at each time, only one source can be handled to generate its output, while other sources are blocked. To handle this challenge of combining resources in HEH systems, this paper proposes a method for collecting all incoming energies and conveying its summation to the load via the current mirror cells in an approach similar to the maximum power point tracking. This technique is implemented using off‐the‐shelf components. The measurement results show that the proposed method is a realistic approach for supplying electrical energy to wireless sensor nodes and low‐power electronics.

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“…Notably, renewable energy is expected to play a crucial role in the needed global energy transformation [3]. Photovoltaic (PV) power generation, a representative renewable resource, has been increasingly leveraged recently [4], and many technologies have been developed to integrate PV generation into commercial and municipal power systems [5,6].…”

Section: Introductionmentioning

confidence: 99%

Control strategies of energy storage limiting intermittent output of solar power generation: Planning and evaluation for participation in electricity market

2023

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Renewable energy generation cannot be consistently predicted or controlled. Therefore, it is currently not widely used in the electricity market, which requires dependable production. In this study, reliability‐ and variance‐based controls of energy storage strategies are proposed to utilize renewable energy as a steady contributor to the electricity market. For reliability‐based control, photovoltaic (PV) generation is assumed to be registered in the power generation plan. PV generation yields a reliable output using energy storage units to compensate for PV prediction errors. We also propose a runtime state‐of‐charge management method for sustainable operations. With variance‐based controls, changes in rapid power generation are limited through ramp rate control. This study introduces new reliability and variance indices as indicators for evaluating these strategies. The reliability index quantifies the degree to which the actual generation realizes the plan, and the variance index quantifies the degree of power change. The two strategies are verified based on simulations and experiments. The reliability index improved by 3.1 times on average over 21 days at a real power plant.

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IoT‐based low‐cost prototype for online monitoring of maximum output power of domestic photovoltaic systems

Cited by 21 publications

References 30 publications

Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks

Design of a Novel Remote Monitoring System for Smart Greenhouses Using the Internet of Things and Deep Convolutional Neural Networks

Thermally reused solar energy harvesting using current mirror cells

Control strategies of energy storage limiting intermittent output of solar power generation: Planning and evaluation for participation in electricity market

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