Integration of open source hardware Arduino platform in automation systems applied to Smart Grids/Micro-Grids

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

Sustainability ◽

10.3390/su13158182 ◽

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.

Download Full-text

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

Sensors ◽

10.3390/s21227650 ◽

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.

Download Full-text

Comparativa de entornos Open-Source para sistemas de supervisión aplicables a Smart Grids/Smart Micro-Grids

Libro de actas ◽

10.17979/spudc.9788497497169.428 ◽

2020 ◽

Author(s):

José María Portalo Calero ◽

Isaías González Pérez ◽

Antonio José Calderón Godoy ◽

Manuel Calderón Godoy

Keyword(s):

Open Source ◽

Smart Grids ◽

Micro Grids

Download Full-text

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

Computer systems and network ◽

10.23939/csn2020.01.080 ◽

2017 ◽

Vol 2 (1) ◽

pp. 80-87

Author(s):

Puyda V. ◽

◽

Stoian. A.

Keyword(s):

Computer Vision ◽

Object Detection ◽

Open Source ◽

Feature Detection ◽

Video Stream ◽

Object Identification ◽

Vision Systems ◽

Modern Computer ◽

Computer Vision Systems ◽

Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

Download Full-text