Design and Test of a High-Performance Wireless Sensor Network for Irradiance Monitoring

Cloud-induced photovoltaic variability can affect grid stability and power quality, especially in electricity systems with high penetration levels. The availability of irradiance field forecasts in the scale of seconds and meters is fundamental for an adequate control of photovoltaic systems in order to minimize their impact on distribution networks. Irradiance sensor networks have proved to be efficient tools for supporting these forecasts, but the costs of monitoring systems with the required specifications are economically justified only for large plants and research purposes. This study deals with the design and test of a wireless irradiance sensor network as an adaptable operational solution for photovoltaic systems capable of meeting the measurement specifications necessary for capturing the clouds passage. The network was based on WiFi, comprised 16 pyranometers, and proved to be stable at sampling periods up to 25 ms, providing detailed spatial representations of the irradiance field and its evolution. As a result, the developed network was capable of achieving comparable specifications to research wired irradiance monitoring network with the advantages in costs and flexibility of the wireless technology, thus constituting a valuable tool for supporting nowcasting systems for photovoltaic management and control

Double smart energy harvesting system for self-powered industrial IoT

312 p. 335 p. (confidencial)Future factories would be based on the Industry 4.0 paradigm. IndustrialInternet of Things (IIoT) represent a part of the solution in this field. Asautonomous systems, powering challenges could be solved using energy harvestingtechnology. The present thesis work combines two alternatives of energy input andmanagement on a single architecture. A mini-reactor and an indoor photovoltaiccell as energy harvesters and a double power manager with AC/DC and DC/DCconverters controlled by a low power single controller. Furthermore, theaforementioned energy management is improved with artificial intelligencetechniques, which allows a smart and optimal energy management. Besides, theharvested energy is going to be stored in a low power supercapacitor. The workconcludes with the integration of these solutions making IIoT self-powered devices.IK4 Teknike

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an open-source software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost

Low-cost web-based Supervisory Control and Data Acquisition system for a microgrid testbed: A case study in design and implementation for academic and research applications

[EN] This paper presents the design and implementation of a low-cost Supervisory Control and Data Acquisition system based on a Web interface to be applied to a Hybrid Renewable Energy System (HRES) microgrid. This development will provide a reliable and low-cost control and data acquisition systems for the Renewable Energy Laboratory a Universitat Politecnica de Valencia (LabDER-UPV) in Spain, oriented to the research on microgrid stability and energy generation. The developed low-cost SCADA operates on a microgrid that incorporates a photovoltaic array, a wind turbine, a biomass gasification plant and a battery bank as an energy storage system. Sensors and power meters for electrical parameters, such as voltage, current, frequency, power factor, power generation, and energy consumption, were processed digitally and integrated into Arduino-based devices. A master device on a Raspberry-PI board was set up to send all this information to a local database (DB), and a MySQL Web-DB linked to a Web SCADA interface, programmed in HTML5. The communications protocols include TCP/IP, I2C, SPI, and Serial communication; Arduino-based slave devices communicate with the master Raspberry-PI using NRF24L01 wireless radio frequency transceivers. Finally, a comparison between a standard SCADA against the developed Web-based SCADA system is carried out. The results of the operative tests and the cost comparison of the own-designed developed Web-SCADA system prove its reliability and low-cost, on average an 86% cheaper than a standard brandmark solution, for controlling, monitoring and data logging information, as well as for local and remote operation system when applied to the HRES microgrid testbed.Vargas Salgado, CA.; Águila-León, J.; Chiñas-Palacios, C.; Hurtado-Perez, E. (2019). Low-cost web-based Supervisory Control and Data Acquisition system for a microgrid testbed: A case study in design and implementation for academic and research applications. Heliyon. 5(9):1-11. https://doi.org/10.1016/j.heliyon.2019.e02474S1115

Application of Wireless Sensor and Actuator Networks to Achieve Intelligent Microgrids: A Promising Approach towards a Global Smart Grid Deployment

Smart Grids (SGs) constitute the evolution of the traditional electrical grid towards a new paradigm, which should increase the reliability, the security and, at the same time, reduce the costs of energy generation, distribution and consumption. Electrical microgrids (MGs) can be considered the first stage of this evolution of the grid, because of the intelligent management techniques that must be applied to assure their correct operation. To accomplish this task, sensors and actuators will be necessary, along with wireless communication technologies to transmit the measured data and the command messages. Wireless Sensor and Actuator Networks (WSANs) are therefore a promising solution to achieve an intelligent management of MGs and, by extension, the SG. In this frame, this paper surveys several aspects concerning the application of WSANs to manage MGs and the electrical grid, as well as the communication protocols that could be applied. The main concerns regarding the SG deployment are also presented, including future scenarios where the interoperability of different generation technologies must be assured

An autonomous and intelligent system for rotating machinery diagnostics

Rotating machinery diagnostics (RMD) is a process of evaluating the condition of their components by acquiring a number of measurements and extracting condition related information using signal processing algorithms. A reliable RMD system is fundamental for condition based maintenance programmes to reduce maintenance cost and risk. It must be able to detect any abnormalities at early stages to allow preventing severe performance degradation, avoid economic losses and/or catastrophic failures. A conventional RMD system consists of sensing elements (transducers) and data acquisition system with a compliant software package. Such system is bulky and costly in practical deployment. The recent advancement in micro-scaled electronics have enabled wide spectrum of system design and capabilities at embedded scale. Micro electromechanical system (MEMS) based sensing technologies offer significant savings in terms of system’s price and size. Microcontroller units with embedded computation and sensing interface have enabled system-on-chip design of RMD system within a single sensing node. This research aims at exploiting this growth of microelectronics science to develop a remote and intelligent system to aid maintenance procedures. System’s operation is independent from central processing platform or operator’s analysis. Features include on-board time domain based statistical parameters calculations, frequency domain analysis techniques and a time controlled monitoring tasks within the limitations of its energy budget. A working prototype is developed to test the concept of the research. Two experimental testbeds are used to validate the performance of developed system: DC motor with rotor unbalance and 1.1kW induction motor with phase imbalance. By establishing a classification model with several training samples, the developed system achieved an accuracy of 93% in detecting quantified seeded faults while consumes minimum power at 16.8mW. The performance of developed system demonstrates its strong potential for full industry deployment and compliance

Analysis and Real-time Data of Meteorologic Impact on Home Solar Energy Harvesting

Solar energy production increased in the world from 0 TWh in 1965 to 724.09 TWh in 2019. Solar energy is adopted as a source for residential renewable energy sources because, besides Biomass sources, it’s the only one that can be installed and maintained at home. Operating efficiency is an important consideration when evaluating the application of photovoltaic panels (PV) technology. A real-time system monitoring is required to analyse the current production and understand the impact of the weather conditions on PV production. This paper extends the literature on the residence solar energy harvesting subject, by providing a scalable architecture that can be used as starting point on data analysis on PV panels efficiency and how weather conditions impact energy production. A dataset was collected related to PV panel energy production, the residence energy consumption and that’s reading weather conditions. Wind intensity and direction, temperature, precipitation, humidity, atmospheric pressure and radiation were weather conditions analysed. Moreover, this data was analysed and interpreted in order to evaluate the pros and cons of the architecture as well as how the weather impacted the energy production

Analysis and real-time data of meteorologic impact on home solar energy harvesting

Solar energy production increased in the world from 0 TWh in 1965 to 724.09 TWh in 2019. Solar energy is adopted as a source for residential renewable energy sources because, besides Biomass sources, it’s the only one that can be installed and maintained at home. Operating efficiency is an important consideration when evaluating the application of photovoltaic panels (PV) technology. A real-time system monitoring is required to analyse the current production and understand the impact of the weather conditions on PV production. This paper extends the literature on the residence solar energy harvesting subject, by providing a scalable architecture that can be used as starting point on data analysis on PV panels efficiency and how weather conditions impact energy production. A dataset was collected related to PV panel energy production, the residence energy consumption and that’s reading weather conditions. Wind intensity and direction, temperature, precipitation, humidity, atmospheric pressure and radiation were weather conditions analysed. Moreover, this data was analysed and interpreted in order to evaluate the pros and cons of the architecture as well as how the weather impacted the energy production.info:eu-repo/semantics/publishedVersio