scholarly journals A Low-Cost IoT System for Real-Time Monitoring of Climatic Variables and Photovoltaic Generation for Smart Grid Application

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3293
Author(s):  
Gustavo Costa Gomes de Melo ◽  
Igor Cavalcante Torres ◽  
Ícaro Bezzera Queiroz de Araújo ◽  
Davi Bibiano Brito ◽  
Erick de Andrade Barboza

Monitoring and data acquisition are essential to recognize the renewable resources available on-site, evaluate electrical conversion efficiency, detect failures, and optimize electrical production. Commercial monitoring systems for the photovoltaic system are generally expensive and closed for modifications. This work proposes a low-cost real-time internet of things system for micro and mini photovoltaic generation systems that can monitor continuous voltage, continuous current, alternating power, and seven meteorological variables. The proposed system measures all relevant meteorological variables and directly acquires photovoltaic generation data from the plant (not from the inverter). The system is implemented using open software, connects to the internet without cables, stores data locally and in the cloud, and uses the network time protocol to synchronize the devices’ clocks. To the best of our knowledge, no work reported in the literature presents these features altogether. Furthermore, experiments carried out with the proposed system showed good effectiveness and reliability. This system enables fog and cloud computing in a photovoltaic system, creating a time series measurements data set, enabling the future use of machine learning to create smart photovoltaic systems.

2021 ◽  
Author(s):  
Fabien Momot ◽  
Marie-Jocelyn Comte ◽  
Chloé Lacaze ◽  
Anas Sikal ◽  
Efficience Balou ◽  
...  

Abstract After a first part of the drilling campaign, including about 10 wells and branches achieved within two years, the operator started questioning the geological reservoir model and reserves implications for the field Offshore Congo. Considering the potential economic impact of this development, the decision was made to reduce wellbore positioning uncertainty relying on optimization and survey QAQC processes that could be applied without adding cost of extra equipment, operational time or personnel. With more than 10 wells drilled using recent while drilling measurement and directional tools in the same environment, a wide range of wellbore positioning information was available for analysis, post-correction, and geological/reservoir model deeper understanding. Also, investigation was done to recover existing geomagnetic data acquired during the geophysical campaign. Thanks to this extensive data set, enhanced wellbores positioning was implemented using meticulous combination of processes. The "process" overall impact is often underestimated while most of the data is already available. For lateral positioning correction, it included the processing of geomagnetic IFR data over the Moho field associated to Multi Station Correction. For vertical repositioning, BHA sag correction was applied with scrutinous assessment of residual sag uncertainty and detailed analysis of continuous survey data. This robust, cost-effective, and valuable solution was chosen to be applied by the operator in the Moho field. The process was first applied post-drilling to evaluate the level of improvement that could be brought to another well also exposed to challenging trajectory context (ERD 2 with reduced target 25 × 50 m at almost 8000m MD/RT). It confirmed that the achievable uncertainty reduction would meet well objectives without adding any risk or operational time nor jeopardizing wellbore positioning and collision avoidance. Thus, it brought up to 50 to 60% of uncertainty reduction and about 30m lateral and 3m vertical displacement. The reduction of the uncertainty and trajectory adjustment allowed to enhance geologic context understanding. The vertical position of the well was offset following this revision. This had a 5% consequence in term of oil layer thickness for this well. Then, the team designed and rolled out to the operator and contractors an execution strategy and operational workflow including remote monitoring with near real-time survey QAQC that would ensure the best correction process customized for the specific drilling challenges. This monitoring enabled reducing the ellipsoid to ~20 by 50m radius at TD = 7618m. This allowed entering in the reservoir at the exact top of the structure, behind the fault that was the optimum in term of reserves and secured 90% of potential reserves of this well. The operator's choice of valuing the available information to enhance their asset is a very interesting way to optimize the past efforts put in wellbore positioning to face the current economically constrained environment.


2014 ◽  
Vol 17 (1) ◽  
pp. 5-15
Author(s):  
Dung Quoc Phan ◽  
Dat Ngoc Dao ◽  
Hiep Chi Le

In a large system with a lot of distribution solar sources which are all connected to the national grid, a communication system becomes the important part for data acquisition in order to control the whole system stable and efficiency. To deal with this challenge, this paper presents a solution based on Zigbee and Ethernet communication standard. Zigbee standard was created to be a specification of a high level wireless communication protocol which is not only secure, reliable, simple but also low cost and low power. With Zigbee, we can create a communication network for hundreds to thousands of mini solar sources in a large scale of photovoltaic system. Ethernet is a high speed wired communication technology that is used widely in industrial and automatic applications. Together Zigbee and Ethernet bring to us a real-time communication solution for the system. In the experiment prototype of this paper, we use the CC2530ZNP-Mini Kit to create a simple network includes one coordinate and one end device for the first step. The end device was configured to get current and voltage values from a 3-phase grid-connected solar inverter 800Wpk and then sends the values to the coordinate. After the coordinate received data, it would send them to an Ethernet controller board. To display the data through Ethernet, we embedded a web server on the Ethernet controller board. By this way, the data was easy to visualize and supervised by using any web browser.


Aerospace ◽  
2021 ◽  
Vol 8 (12) ◽  
pp. 361
Author(s):  
Cristóbal Nieto-Peroy ◽  
Marco Sabatini ◽  
Giovanni Palmerini ◽  
Élcio Jeronimo de Oliveira

Federated remote laboratories allow for the execution of experiments ex situ. The coordination of several laboratories can be used to perform concurrent experiments of combined space operations. However, the latency of the communications between facilities is critical to performing adequate real-time experiments. This paper presents an approach for conducting coordinated experiments between floating platforms at two remote laboratories. Two independently designed platforms, one at Luleå University of Technology and the other at La Sapienza University of Rome, were established for this purpose. A synchronization method based on the Simple Network Time Protocol was created, allowing the offset and delay between the agents to be measured.Both platforms exchange data about their measured time and pose through a UDP/IP protocol over the internet. This approach was validated with the execution of simulated operations. A first demonstrative experiment was also performed showing the possibility to realize leader/follower coordinated operations. The results of the simulations and experiments showed communication delays on the order of tens of milliseconds with no significant impact on the control performance. Consequently, the suggested protocol was proven to be adequate for conducting coordinated experiments in real time between remote laboratories.


Author(s):  
Gabriel de Almeida Souza ◽  
Larissa Barbosa ◽  
Glênio Ramalho ◽  
Alexandre Zuquete Guarato

2007 ◽  
Author(s):  
R. E. Crosbie ◽  
J. J. Zenor ◽  
R. Bednar ◽  
D. Word ◽  
N. G. Hingorani

2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).


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