scholarly journals Configurable IoT Open-Source Hardware and Software I-V Curve Tracer for Photovoltaic Generators

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7650
Author(s):  
Isaías González ◽  
José María Portalo ◽  
Antonio José Calderón
Keyword(s):  
Data Acquisition ◽  
Open Source ◽  
Smart Grids ◽  
Operating Conditions ◽  
Raspberry Pi ◽  
Modern Trend ◽  
Curve Tracer ◽  
Open Source Hardware ◽  
Curve Tracing ◽  
Photovoltaic Generators

Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.

scholarly journals Monitoring System for Tracking a PV Generator in an Experimental Smart Microgrid: An Open-Source Solution

2021 ◽  
Vol 13 (15) ◽  
pp. 8182
Author(s):  
José María Portalo ◽  
Isaías González ◽  
Antonio José Calderón
Keyword(s):  
Open Source ◽  
Monitoring System ◽  
Smart Grids ◽  
Raspberry Pi ◽  
Operator Interface ◽  
Open Source Hardware ◽  
Real Time Information ◽  
And Storage ◽  
Time Information ◽  
Pv Generator

Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal.

scholarly journals Open-Source Hardware Platforms for Smart Converters with Cloud Connectivity

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 367 ◽  
Author(s):  
Massimo Merenda ◽  
Demetrio Iero ◽  
Giovanni Pangallo ◽  
Paolo Falduto ◽  
Giovanna Adinolfi ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Renewable Energies ◽  
Operating Conditions ◽  
Maximum Power ◽  
System Level ◽  
Impedance Match ◽  
Solar Module ◽  
Open Source Hardware ◽  
Photovoltaic Generators

This paper presents the design and hardware implementation of open-source hardware dedicated to smart converter systems development. Smart converters are simple or interleaved converters. They are equipped with controllers that are able to online impedance match for the maximum power transfer. These conversion systems are particularly feasible for photovoltaic and all renewable energies systems working in continuous changing operating conditions. Smart converters represent promising solutions in recent energetic scenarios, in fact their application is deepening and widening. In this context, the availability of a hardware platform could represent a useful tool. The platform was conceived and released as an open hardware instrument for academy and industry to benefit from the improvements brought by the researchers’ community. The usage of a novel, open-source platform would allow many developers to design smart converters, focusing on algorithms instead of electronics, which could result in a better overall development ecosystem and rapid growth in the number of smart converter applications. The platform itself is proposed as a benchmark in the development and testing of different maximum power point tracking algorithms. The designed system is capable of accurate code implementations, allowing the testing of different current and voltage-controlled algorithms for different renewable energies systems. The circuit features a bi-directional radio frequency communication channel that enables real-time reading of measurements and parameters, and remote modification of both algorithm types and settings. The proposed system was developed and successfully tested in laboratory with a solar module simulator and with real photovoltaic generators. Experimental results indicate state-of-art performances as a converter, while enhanced smart features pave the way to system-level management, real-time diagnostics, and on-the-flight parameters change. Furthermore, the deployment feasibility allows different combinations and arrangements of several energy sources, converters (both single and multi-converters), and modulation strategies. To our knowledge, this project remains the only open-source hardware smart converter platform used for educational, research, and industrial purposes so far.

scholarly journals LOW COST SEISMIC DATA ACQUISITION SYSTEM BASED ON OPEN SOURCE HARDWARE AND SOFTWARE TOOLS

2020 ◽  
Author(s):  
Arvid Ramdeane ◽  
Lloyd Lynch
Keyword(s):  
Data Acquisition ◽  
Open Source ◽  
Seismic Data ◽  
Low Cost ◽  
Data Acquisition System ◽  
Software Tools ◽  
Acquisition System ◽  
Seismic Data Acquisition ◽  
Private Network ◽  
Open Source Hardware

The University of the West Indies Seismic Research Centre, Trinidad and Tobago, operates a network of over 50 stations for earthquake and volcanic monitoring in the Eastern Caribbean islands. These stations form a seismic network consisting of various types of instrumentation, and communication systems. Over a period of 11 years, the Centre has embarked on an initiative of upgrading and expanding the current network with combinations of broadband and/or strong motion sensors, high dynamic range digitizers and networking equipment to link each station to centralized observatories via high speed digital data transmission medium. To realize such an upgrade and expansion, the Centre has developed a seismic data acquisition system prototype built using open-source hardware and software tools. The prototype is intended to be low-cost using off the shelf hardware components and open-source seismic related software handling data acquisition and data processing in two separate modules. The prototype uses a three-channel accelerometer sensor and can process data into standard MiniSEED format for easy data archiving and seismic data analysis. A global position module provides network time protocol time synchronization within 1 millisecond for accurate timestamping of data. Data can be stored locally on the prototype in twenty-minute data files or securely transferred to a central location via internet with the use of virtual private network capabilities. The prototype is modular in design allowing for components to be replaced easily and the system software can be updated remotely thus reducing maintenance cost.

scholarly journals Elemental: An Open-Source Wireless Hardware and Software Platform for Building Energy and Indoor Environmental Monitoring and Control

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4017 ◽  
Author(s):  
Akram Syed Ali ◽  
Christopher Coté ◽  
Mohammad Heidarinejad ◽  
Brent Stephens
Keyword(s):  
Environmental Monitoring ◽  
Open Source ◽  
Environmental Quality ◽  
Printed Circuit Boards ◽  
Operating Conditions ◽  
Sensor Data ◽  
Raspberry Pi ◽  
Software Platform ◽  
Energy Usage ◽  
Efficient Operation

This work demonstrates an open-source hardware and software platform for monitoring the performance of buildings, called Elemental, that is designed to provide data on indoor environmental quality, energy usage, HVAC operation, and other factors to its users. It combines: (i) custom printed circuit boards (PCBs) with RFM69 frequency shift keying (FSK) radio frequency (RF) transceivers for wireless sensors, control nodes, and USB gateway, (ii) a Raspberry Pi 3B with custom firmware acting as either a centralized or distributed backhaul, and (iii) a custom dockerized application for the backend called Brood that serves as the director software managing message brokering via Message Queuing Telemetry Transport (MQTT) protocol using VerneMQ, database storage using InfluxDB, and data visualization using Grafana. The platform is built around the idea of a private, secure, and open technology for the built environment. Among its many applications, the platform allows occupants to investigate anomalies in energy usage, environmental quality, and thermal performance via a comprehensive dashboard with rich querying capabilities. It also includes multiple frontends to view and analyze building activity data, which can be used directly in building controls or to provide recommendations on how to increase operational efficiency or improve operating conditions. Here, we demonstrate three distinct applications of the Elemental platform, including: (1) deployment in a research lab for long-term data collection and automated analysis, (2) use as a full-home energy and environmental monitoring solution, and (3) fault and anomaly detection and diagnostics of individual building systems at the zone-level. Through these applications we demonstrate that the platform allows easy and virtually unlimited datalogging, monitoring, and analysis of real-time sensor data with low setup costs. Low-power sensor nodes placed in abundance in a building can also provide precise and immediate fault-detection, allowing for tuning equipment for more efficient operation and faster maintenance during the lifetime of the building.

scholarly journals PrintrLab incubator: A portable and low-cost CO2 incubator based on an open-source 3D printer architecture

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251812
Author(s):  
Arunkumar Arumugam ◽  
Cole Markham ◽  
Saurabh S. Aykar ◽  
Barbara Van Der Pol ◽  
Paula Dixon ◽  
...  
Keyword(s):  
Open Source ◽  
Low Cost ◽  
Raspberry Pi ◽  
3D Printer ◽  
Software Application ◽  
G Code ◽  
Temperature Levels ◽  
Controller Board ◽  
Open Source Hardware ◽  
Hardware Designs

Growth in open-source hardware designs combined with the decreasing cost of high-quality 3D printers have supported a resurgence of in-house custom lab equipment development. Herein, we describe a low-cost (< $400), open-source CO2 incubator. The system is comprised of a Raspberry Pi computer connected to a 3D printer controller board that has controls for a CO2 sensor, solenoid valve, heater, and thermistors. CO2 is supplied through the sublimation of dry ice stored inside a thermos to create a sustained 5% CO2 supply. The unit is controlled via G-Code commands sent by the Raspberry Pi to the controller board. In addition, we built a custom software application for remote control and used the open-source Grafana dashboard for remote monitoring. Our data show that we can maintain consistent CO2 and temperature levels for over three days without manual interruption. The results from our culture plates and real-time PCR indicate that our incubator performed equally well when compared to a much more expensive commercial CO2 incubator. We have also demonstrated that the antibiotic susceptibility assay can be performed in this low-cost CO2 incubator. Our work also indicates that the system can be connected to incubator chambers of various chamber volumes.

OpenDroneMap360, an affordable DIY open-source hardware and software workflow for 3D point clouds and terrain models

2021 ◽  
Author(s):  
Hessel Winsemius ◽  
Stephen Mather ◽  
Ivan Gayton ◽  
Iddy Chazua
Keyword(s):  
Open Source ◽  
Low Income ◽  
Urban Areas ◽  
Service Providers ◽  
Point Clouds ◽  
Low Income Countries ◽  
Raspberry Pi ◽  
Data Generation ◽  
3D Point Clouds ◽  
Open Source Hardware

&lt;p&gt;The state of the art in terrain data generation is Light Detection And Ranging (LiDAR). LiDAR is usually deployed through manned or unmanned aerial vehicles. As typical payloads are high, an aircraft with LiDAR needs to be significant in size. Therefore, LiDAR is currently only done by specialized companies with expensive equipment, and cannot be deployed by local service providers in low income countries, despite the plethora of use cases for its data.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;A promising avenue to replace LiDAR is photogrammetry. It can be applied with much lighter and more affordable aircrafts and its use to provide extensive terrain datasets is steadily increasing. The scalable open-source software OpenDroneMap allows for extending datasets to very large amounts. Photogrammetry however, cannot penetrate vegetation, and (as is the case with LiDAR) does not resolve ground terrain in obscured areas such as dense urban areas with narrow alleys.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;That is why we are developing OpenDroneMap360, a free and open-source DIY hardware-software camera-ball platform for collection of high quality photos with any carrier you can think of. This can be a self-built drone, a backpack rig or another setup we haven&amp;#8217;t considered yet, equipped with enough lenses to discover any ground that you can think of. Our current hardware offers a backpack rig with a total of 7 lenses and contains a parts list, 3D-printable hull, connection scheme, software deployment and a Sphinx manual how to build, deploy and operate the rig. The technology contains raspberry pi cameras connected to raspberry pi zeros for each lens, a Ardusimple u-blox ZED-F9P GNSS chipset, a raspberry pi4 to instruct the cameras, collect GPS positions, and perform file and data management, and a LiPo battery solution. The entire setup is available on https://github.com/localdevices/odm360&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

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