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Using IoT and smart monitoring devices to optimize the efficiency of large-scale distributed solar farms

Authors:
Salsabeel Shapsough at American University of Sharjah
Salsabeel Shapsough
Mohannad Takrouri at American University of Sharjah
Mohannad Takrouri
Rached Dhaouadi at American University of Sharjah
Rached Dhaouadi
Imran A. Zualkernan at American University of Sharjah
Imran A. Zualkernan
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This paper presents a novel IoT-based architecture that utilizes IoT hardware, software, and communication technologies to enable real-time monitoring and management of solar photovoltaic systems at large scales. The system enables stakeholders to remotely control and monitor the photovoltaic systems and evaluate the effect of various environmental factors such as weather, air quality, and soiling. The system was implemented and evaluated in terms of network delay and resource consumption. Message Queueing Telemetry Transport (MQTT) was used to facilitate wide-scale real-time communication. The average network delay was found to be less than 1 s, proving the architecture to be ideal for solar and smart grid monitoring systems. As for resource consumption, the evaluation showed the hardware to consume about 3% of the panel’s output, while the application also utilized a very small percentage of the CPU. This led to the conclusion that the proposed architecture is best deployed using low-cost constrained edge devices where a combination of IoT-based paradigm, efficient MQTT communication, and low resources consumption makes the system cost-effective and scalable.
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Using IoT and smart monitoring devices to optimize the efficiency
of large-scale distributed solar farms
Salsabeel Shapsough
1
•Mohannad Takrouri
1
•Rached Dhaouadi
1
•Imran A. Zualkernan
1
Published online: 19 December 2018
ÓSpringer Science+Business Media, LLC, part of Springer Nature 2018
Abstract
This paper presents a novel IoT-based architecture that utilizes IoT hardware, software, and communication technologies to
enable real-time monitoring and management of solar photovoltaic systems at large scales. The system enables stake-
holders to remotely control and monitor the photovoltaic systems and evaluate the effect of various environmental factors
such as weather, air quality, and soiling. The system was implemented and evaluated in terms of network delay and
resource consumption. Message Queueing Telemetry Transport (MQTT) was used to facilitate wide-scale real-time
communication. The average network delay was found to be less than 1 s, proving the architecture to be ideal for solar and
smart grid monitoring systems. As for resource consumption, the evaluation showed the hardware to consume about 3% of
the panel’s output, while the application also utilized a very small percentage of the CPU. This led to the conclusion that
the proposed architecture is best deployed using low-cost constrained edge devices where a combination of IoT-based
paradigm, efficient MQTT communication, and low resources consumption makes the system cost-effective and scalable.
Keywords IoT Solar photovoltaic monitoring Smart renewable energy Smart grid
1 Introduction
Solar power is increasingly becoming an integral part of
world-wide energy production. This can be attributed to a
combination of factors including the depletion of conven-
tional energy sources [1], mainly fossil fuels, and a world-
wide awakening to the magnitude of the consequences
greenhouse emissions pose on the planet’s vital resources
[2]. This led to great leaps not only in photovoltaic-related
technology, but also in the scale of utility-grade solar farms
built every year, with global solar photovoltaic capacity
totaling over 385 Gigawatt (GW) in the year 2017 [3]. In
the light of such advances in scale, the study of solar panel
performance [4,5] is more than ever recognized as the key
to cost-effective implementation and operation. While
increasing efficiency of photovoltaic cells has been an
ongoing challenge for years, recent work puts equal
emphasis on the effect that external factors can have on
power output. Such factors can be grouped into two
categories: man-made influences such as the Photovoltaic
(PV) array size and configuration [6,7], module configu-
ration [8,9], and panel orientation in relation to the angle
of sun incidence [10], and natural influences such as
atmospheric conditions [11], shading [12–14], and soiling
[15]. Many of the described methods for mitigating
external influences require the ability to collect data from
remote solar farms, communicate it in real-time, as well as
store it for processing and analysis. Remote control and
dynamic reconfiguration are also essential functionalities in
several solutions where a reaction is required. PV moni-
toring systems have appeared in literature as early as the
late 90 s [16,17]. Since then, several designs and imple-
mentations exist for solar monitoring systems [18]. Pro-
posed designs utilize hardware and software architectures
from computer applications, web applications, and industry
ecosystems, and adapt them to the specific requirements of
a PV monitoring system. However, the recent rise of
Internet of Things (IoT) technologies generated an influx of
software, hardware, and communication technologies
optimized for distributed smart systems such as smart
health monitoring, smart cities, and smart education. Such
systems share considerable requirements with PV
&Salsabeel Shapsough
salsabeelshapsough@gmail.com
1
American University of Sharjah, Sharjah, UAE
123
Wireless Networks (2021) 27:4313–4329
https://doi.org/10.1007/s11276-018-01918-z(0123456789().,-volV)(0123456789().,-volV)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... Statistics from "World Energy Data" explain that energy consumption with renewable energy resources reaches 23.6% of world energy consumption [19]. Installation configuration of solar panels (such as PV array size, module configuration, and panel orientation in reference to sun direction) also affects each module's energy output [20,21]. Solar arrays are installed facing south at a certain angle to capture optimum solar irradiance. ...
... • Power optimization for minimum human intervention. • Flexibility from modification perspective [16,20]. • Scalability and independence from solar panel layout and configuration. ...
... In Tables 2 and 3, a comprehensive list of popular microcontroller boards for solar plant monitoring is presented, including Uno, Nano, Mega, and NodeMCU. In the majority of the proposed solutions, Raspberry Pi (RPi) has been employed as presented by [3,4,6,7,16,20,32,37,41,43,49,50]. However, RPi is not an optimum choice for end devices considering its monetary cost and power requirements. ...
Harnessing the Cloud: A Novel Approach to Smart Solar Plant Monitoring
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Renewable Energy Sources (RESs) such as hydro, wind, and solar are merging as preferred alternatives to fossil fuels. Among these RESs, solar energy is the most ideal solution; it is gaining extensive interest around the globe. However, due to solar energy’s intermittent nature and sensitivity to environmental parameters (e.g., irradiance, dust, temperature, aging and humidity), real-time solar plant monitoring is imperative. This paper’s contribution is to compare and analyze current IoT trends and propose future research directions. As a result, this will be instrumental in the development of low-cost, real-time, scalable, reliable, and power-optimized solar plant monitoring systems. In this work, a comparative analysis has been performed on proposed solutions using the existing literature. This comparative analysis has been conducted considering five aspects: computer boards, sensors, communication, servers, and architectural paradigms. IoT architectural paradigms employed have been summarized and discussed with respect to communication, application layers, and storage capabilities. To facilitate enhanced IoT-based solar monitoring, an edge computing paradigm has been proposed. Suggestions are presented for the fabrication of edge devices and nodes using optimum compute boards, sensors, and communication modules. Different cloud platforms have been explored, and it was concluded that the public cloud platform Amazon Web Services is the ideal solution. Artificial intelligence-based techniques, methods, and outcomes are presented, which can help in the monitoring, analysis, and management of solar PV systems. As an outcome, this paper can be used to help researchers and academics develop low-cost, real-time, effective, scalable, and reliable solar monitoring systems.
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... It is worth noting that, in the last few years, the implementation of Internet of Things (IoT) in the monitoring of solar PV systems is becoming a promising solution for intelligent remote and real-time monitoring of such systems. For instance, a novel approach for real-time monitoring and management of solar PV systems, based on IoT architecture, is proposed in [11]. The authors of the paper [11] prefer the use of current and voltage sensors to monitor the performance of panels, while a surveillance camera was used to observe anomalies like shading. ...
... For instance, a novel approach for real-time monitoring and management of solar PV systems, based on IoT architecture, is proposed in [11]. The authors of the paper [11] prefer the use of current and voltage sensors to monitor the performance of panels, while a surveillance camera was used to observe anomalies like shading. More recently and in the same context, Gupta et al. [12] have proposed an IoT-based data acquisition system, based on open-access software and cloud service, for monitoring and gathering operational information of the PV system to assess its performance. ...
Real-Time Monitoring of Partial Shading in PV Plants Using Smartphone
Conference Paper
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In a typical string-connected Photovoltaic (PV) panels, its performance can be dramatically impacted when one or more of panels are partially shaded. Therefore, the monitoring of these PV panels becomes an important task to improve the durability functioning of the whole PV system. In this paper, a practical low-cost solution for monitoring and diagnosing of PV panels, to enhance their output power as well as their useful life span, is proposed. It consists mainly of an Android application that read remotely, via a Bluetooth wireless connection, the value of individual panel voltage in order to be compared to a threshold, to know if the host panel is under shaded conditions or not. However, it should be noted that each panel of the proposed monitoring system is equipped with a voltage sensor, a disconnection circuit and a servo motor, which are connected to a microcontroller of an Arduino Uno board. Thus, if a panel is under partial shading conditions, its voltage should be less than a threshold, and therefore the panel will be firstly disconnected from the string; then turned right and left to reject any undesired objects such as tree leaves or any other things accumulated on its surface; and finally, it will be reconnected to the string. If, however, the problem persists, then the host panel will be disconnected in order to undergo, this time, an offline diagnostic to detect eventual other types of faults, which may be the leading cause of its malfunction. Several experiments were carried out in this work have shown the reliability of the proposed system.
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... This research aims to create a very precise solar tracking system via IoT-based data transmission [24], [25]. The tracking mechanism functions through a bifurcated process: the initial stage entails coarse correction based on the sun-Earth geometric relationship. ...
Remote Monitoring and Cleaning Management Using Efficient Solar Power
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Throughout history, solar energy has been widely utilized in conventional technologies, especially when alternative energy sources are unavailable. As awareness of environmental costs grows and alternatives like gasoline face limitations, solar energy has gained broader adoption. Solar tracking devices are considered highly successful in enhancing the efficiency of solar panels by precisely tracking the sun’s trajectory. These devices enhance solar panel alignment, augmenting energy output by ensuring constant sunlight exposure. Solar energy entails the conversion of sunlight into thermal or electrical energy. The United States, one of the globe’s most affluent solar resources, utilizes solar power as one of the cleanest and most plentiful renewable energy sources.
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... Once 'no-go zones' have been established, the further stages of the mitigation hierarchy can be applied to a site-based applications. A key way to manage impact is through site design to reduce the area of a site impacted, for example by applying innovative artificial intelligence (AI), the Internet of Things (IoT) and tracking technology to make panels more efficient (Mohammad and Mahjabeen, 2023;Patel et al., 2021;Shapsough et al., 2021). Further to this, restoring the biodiversity at solar farms should be incorporated into the operational design (Blaydes et al., 2022;Nordberg et al., 2021;Randle-Boggis et al., 2020). ...
The location of solar farms within England's ecological landscape: Implications for biodiversity conservation
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Full-text available
  • Nov 2024
  • J ENVIRON MANAGE
A global energy transition to using sustainable renewable sources is being driven by global agreements. Simultaneously there is a call for increased biodiversity conservation. This creates a green-green dilemma, where the expansion of renewables could lead to the demise of biodiversity if not carefully assessed, managed and monitored. Recognition of the dilemma is central to the development of Sustainable Development Goals. It is therefore important to understand whether renewable energy sources such as solar farms are being sited in areas where they have minimal impact on biodiversity. If solar farms were sited with minimal impacts on biodiversity, we hypothesised that they would be less likely to be sited close to ecologically sensitive areas than near random points. We used Geographic Information System methods to explore the density of solar photovoltaic (PV) farms in England and assessed their siting relative to sensitive ecological features, including priority habitat types, designated sites, and land conservation initiatives. We compared the area of 25 sensitive ecological features around solar farms and random points across three spatial scales (100 m, 1000 m, and 6000 m radius scales). Solar farms were distributed throughout England, with the highest concentration in South West England. Solar sites were primarily surrounded by habitats with anthropogenic influences, such as agricultural and urban settings. Priority habitats, such as woodland, grassland, wetland and heathland, were more extensive around random points across spatial scales (except for woodland at the largest scale). Most designated sites were significantly more extensive around random points. We conclude that, under current planning regulations, solar sites in England are being placed appropriately with regard to sensitive ecological habitats, and are often sited in areas already impacted by farming and development. Adaptive planning should be implemented to ensure that the evolving research around biodiversity and solar farms is incorporated into decision making, and monitoring is completed across the lifespan of solar farms to assess impacts and effective mitigation.
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... IoT-based monitoring systems facilitate remote management and data collection, while low-cost wireless solutions bridge communication gaps. Real-time monitoring platforms offer insight into PV system performance and grid integration [40]. However, cybersecurity concerns persist, leading to the adoption of sliding mode-based observers and machine learning-based anomaly detection algorithms. ...
CHALLENGES AND SOLUTIONS OF SOLAR PV SYSTEM INTEGRATION WITH ELECTRICITY GRID: A LITERATURE SURVEY
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  • Nov 2024
The solar photovoltaic (PV) integration with existing electricity grids represents a essential effort towards the sustainable energy solutions and greenhouse gas emission reduction. This chapter provides a wide-range challenges of the solar PV to grid integration and represents a spectrum of innovative solutions. Further, examining the challenges, this chapter delve into the intermittent nature of solar power generation, power quality issues, grid stability concerns arising from voltage and angular deviations, etc. Simultaneously, this chapter explores a diverse array of solution methodologies, advanced control strategies, the strategic deployment of energy storage systems to capture and dispatch surplus energy, and the essential role played by renewable energy policies and motivations in streamlining the grid management.
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Wearable Plant-Shape Bioinspired PCB Antennas for 5G Band at 3.5 GHz
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The technology of cellular communication for the fifth generation, 5G, is used in several applications that require high speed data, broadband, and low latency, such as Industry 4.0, wireless sensor networks, high-speed mobile communications, smart cities, smart grids, and other emergent technologies. Antennas for wireless wearable devices are required to have a compact structure and withstand temperature variations and mechanical tensions. The use of bioinspired plant shapes in the printed circuit board (PCB) antenna technology enables the development of compact devices, featuring omnidirectional radiation pattern, and wideband. This work introduces a type of PCB antenna, flexible and wearable, bioinspired on Neem plant-shapes ( Azadirachta indica ), applied to 5G band at 3.5 GHz, operating in the range of 3.3 GHz to 3.6 GHz. The antennas are built using polyamide as a dielectricin polyamide dielectric, a flexible material resistant to high temperatures and mechanical tensions, with the plant shape generated by the Gielis formula. The wearable bioinspired antennas feature a wideband characteristic, with measured bandwidth of over 500 MHz, a compact structure measuring 23.36 mm in length and 17.52 mm in width, an omnidirectional radiation pattern, a half power beamwidth of 84 degrees, a maximum gain of 2.03 dBi, and coverage of the 5G band at 3.5 GHz. Simulation results show that displacement of the ground plane affects the resonance frequency, with optimal results at a distance of 1 mm.
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The Internet of Things (IoT) is no longer a newbie; it has a long history of serving as the primary commercial growth driver. Every business nowadays has begun to rely on IoT technology for market operational excellence. Smart Farming has also adopted IoT technology and farmers utilize these technologies to monitor crop production, evaluate soil moisture content, and deploy drones to assist with operations like pesticide spraying. As more devices link to the Internet, the problems of safeguarding smart farming settings' cybersecurity threats and vulnerabilities grow. Digitalization in agriculture is regarded as the fourth agricultural revolution, as evidenced by a wide range of available digital technologies and data applications. This paper describes a systematic literature review (SLR) on IoT security and privacy and domains in the agricultural industry. This SLR was summarized by studying the research papers published in reputable journals between January 2017 and July 2023. A total of 37 articles were carefully selected from 6 databases using a systematic method, quality assessment, and classification. The primary objective of this study is to consolidate all relevant studies on IoT-based Smart Farming (SF) applications domains, privacy/security, communication/Network protocols, and sensors/devices. It also highlighted the fundamental difficulties and how smart Farming works in different countries. Moreover, this review paper analyzes the security difficulties that IoT devices face in agriculture. Finally, open issues and challenges were discussed to give research with interesting future approaches in IoT agriculture.
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