A LoRaWAN based Open Source IOT Solution for Monitoring Rural Electrification Policy
01 Jan 2020-pp 888-890
TL;DR: The methodology involves the development of a low-cost prototype and an open-source based solution to monitor the performance of a DC-based stand-alone solar photovoltaic system, which was set up in the IIT Madras campus.
Abstract: The Government of India has implemented Solar PV based microgrid Decentralized Distributed Generation (DDG) projects in different parts of the country. The monitoring of the performance of DDG projects is a manual process with reliance on the data provided by the system integrators who oversee the DDG projects. With the advent of the Internet of Things (IOT), the monitoring & evaluation can be improved dramatically by making it objective, and also to monitor the performance of the policy progress on a near real-time basis. The characteristics of an LPWAN technology viz., LoRa that makes it an appropriate communication technology for remote monitoring of DDG projects are: Long-range, Low power, Small data requirements, and flexibility to operate in unlicensed spectrum. An open-source Internet of Things (IOT) solution is proposed here to monitor and evaluate the rural electrification projects. The methodology involves the development of a low-cost prototype and an open-source based solution to monitor the performance of a DC-based stand-alone solar photovoltaic system, which was set up in the IIT Madras campus. The integration across the LoRaWAn architecture was demonstrated, and a visualization dashboard was created in the Ubidots IOT platform to monitor basic parameters such as voltage and current. The goal is to monitor the solar DC system in terms of the objectives set in DDG policy.
TL;DR: In this paper , a scaled-down prototype of an IoT-enabled datalogger for photovoltaic system that is installed in a remote location where human intervention is not possible due to harsh weather conditions or other circumstances is presented.
Abstract: Climate change and the energy crisis substantially motivated the use and development of renewable energy resources. Solar power generation is being identified as the most promising and abundant source for bulk power generation. However, solar photovoltaic panel is heavily dependent on meteorological data of the installation site and weather fluctuations. To overcome these issues, collecting performance data at the remotely installed photovoltaic panel and predicting future power generation is important. The key objective of this paper is to develop a scaled-down prototype of an IoT-enabled datalogger for photovoltaic system that is installed in a remote location where human intervention is not possible due to harsh weather conditions or other circumstances. An Internet of Things platform is used to store and visualize the captured data from a standalone photovoltaic system. The collected data from the datalogger is used as a training set for machine learning algorithms. The estimation of power generation is done by a linear regression algorithm. The results are been compared with results obtained by another machine learning algorithm such as polynomial regression and case-based reasoning. Further, a website is developed wherein the user can key in the date and time. The output of that transaction is predicted temperature, humidity, and forecasted power generation of the specific standalone photovoltaic system. The presented results and obtained characteristics confirm the superiority of the proposed techniques in predicting power generation.
TL;DR: This work focuses on the study of the current challenges for the mass scale SHSs monitoring in developing countries, highlighting the weaknesses and the strengths of the applicable methods available and presenting low-cost IoT-based monitoring systems as a potential solution.
14 Jun 2020
TL;DR: In this paper, an integrated solar-photovoltaic (SPV) battery and micro-hydro-based DC microgrid (DC-MG) is proposed to meet the need of electrical energy in remote rural areas.
Abstract: The decreasing cost and simplicity in deployment of Solar-Photovoltaic (SPV) system have led to its penetration extended to the highly remote/rural areas. The SPV systems possessing non-dispatchable characteristics are typically deployed in the form of a DC microgrid or an AC microgrid in such areas. For rural electrification, a low voltage DC microgrid with SPV source suitably integrated with local resources like wind or micro-hydro generation plant supported with energy storage becomes highly desirable to enhance the availability of power throughout the day. This paper presents implementation and control of an autonomous Integrated SPV-battery and Micro-hydro based DC microgrid (DC-MG) meeting the need of electrical energy in remote rural areas. This paper proposes the hierarchical power control which enhances the operational reliability and flexibility.
TL;DR: In this paper , the authors developed an ontology to describe small-scale photovoltaic (PV) installations, which enables them to represent subsystems and their components in the form of Web of Things Thing Descriptions.
Abstract: Small-scale photovoltaic (PV) systems of up to a few kilowatts capacities are becoming increasingly available and affordable for off-grid installations. However, in our experience with using PV energy in farming in India, we found that many installations had faults or were lying underutilized. Though integrating such systems into IoT applications is now practical, analyzing the system’s performance and utilization requires knowledge of the components and the system design. Off-band infusion of this knowledge into the software applications leads to tight coupling and vertical silos. To address this challenge, we have developed an ontology to describe small-scale PV installations, which enables us to represent subsystems and their components in the form of Web of Things (WoT) Thing Descriptions. We show that our approach results in technical and semantic integration of the PV system into IoT applications, allowing the development of reusable fault detection and optimization programs. This reduces the cost of developing solutions to monitor and optimize the usage of PV systems, thereby bringing benefits to the farming community by improving their livelihood.
TL;DR: A wireless low-cost solution based on long-range (LoRa) technologyable to communicate with remote PV power plants, covering long distances with minimum power consumption and maintenance and offering an extensive monitoring system to exchange data in an Internet-of-Things (IoT) environment is proposed.
Abstract: This paper proposes a wireless low-cost solution based on long-range (LoRa) technology able to communicate with remote PV power plants, covering long distances with minimum power consumption and maintenance. This solution includes a low-cost open-source technology at the sensor layer and a low-power wireless area network (LPWAN) at the communication layer, combining the advantages of long-range coverage and low power demand. Moreover, it offers an extensive monitoring system to exchange data in an Internet-of-Things (IoT) environment. A detailed description of the proposed system at the PV module level of integration is also included in the paper, as well as detailed information regarding LPWAN application to the PV power plant monitoring problem. In order to assess the suitability of the proposed solution, results collected in real PV installations connected to the grid are also included and discussed.
TL;DR: A new technique is proposed as a solution to overcome the limitations of other techniques that uses GSM voice channel for the communication of data, in the form of analog signal between transmitter and receiver, with low initial as well as operating cost.
01 Sep 2016
TL;DR: This article describes a low-cost, long-range IoT framework which takes cost of hardware and services as the main challenge to be addressed as well as flexibility, quick appropriation and customization by third parties.
Abstract: Recent long-range radio technologies are promising to deploy Low Power WAN at a very low-cost for a large variety of IoT applications. However, even though, there are several issues that need to be addressed when considering deploying IoT solutions for low-income developing countries. In this article, we first explain these issues and show how they can be addressed in the context of rural sub-saharan African applications, one of them being smarter villages and farms in a small and micro deployment model. We then describe our low-cost, long-range IoT framework which takes cost of hardware and services as the main challenge to be addressed as well as flexibility, quick appropriation and customization by third parties.
28 Jun 2018
TL;DR: Range and Measurement test results shows that the sensor nodes and wireless technology is a sufficient solution for a WSN that is capable of measuring module-level performance parameters on a utility scale PV plant.
Abstract: Accurate forecasting of PV plants is paramount in ensuring that the electricity grid operates efficiently. This is due to the fact that PV resources have power fluctuations in multiple horizons and the grid has limited storage. An important aspect in creating the forecasting model of a solar PV plant is gathering detailed module-level measurement data. A Wireless Sensor Network (WSN) with sensors that are placed on strategic points on a utility scale PV plant is proposed. The sensors proposed measure module-level performance parameters such as module voltage, current, backside temperature, ambient temperature, and irradiance. Although various wireless module-level sensor approaches exist, the sheer size of a typical solar PV plant presents challenges for the wireless technologies presented in these approaches. Different wireless technologies such as Bluetooth, Zigbee, Wi-Fi, GSM, Sigfox and LoRa were evaluated for the proposed WSN. LoRa was chosen as the wireless technology due to its long range and low power consumption. A couple of sensor nodes and a gateway was designed built and tested. Range test were conducted to ensure that the chosen wireless technology meets the range requirements found on a typical PV plant. Module-level measurements were taken on different solar modules over a period of a few weeks. The measurement data was analysed and evaluated in term of different factors to ensure that the sensors provide accurate data required to assist in creating a more accurate PV plant forecasting model. Range and Measurement test results shows that the sensor nodes and wireless technology is a sufficient solution for a WSN that is capable of measuring module-level performance parameters on a utility scale PV plant.
••01 Jan 2018
TL;DR: This paper discusses the Indian smart metering deployment in both rural and urban scenarios where the short-range IoT solution built-in may not always work best to the needs of long-range expectations, and highlights how emerging LPWAN technologies will help in building a reliable, low-cost, high-power, long- range, last-mile technology for smart energy metering solutions.
Abstract: The last-mile networking for Internet of Things (IoT) applications using short-range networks in ISM band such as IEEE 802.15.4 LoWPAN mesh, WiFi, Zigbee, Bluetooth Low Energy has been studied widely in the last few years with demonstration in many industrial scenarios. However, the reliable connectivity in last-mile scenarios like individual energy meter in the home area network (HAN) connecting to the data concentrator in turn to the meter data management systems (MDMS) through WAN connectivity is considered to be a challenge in certain areas. There are emerging low-power WAN (LPWAN) technologies such as LoRa, Wi-SUN, Sigfox—all operating in unlicensed band, and NB-IoT—in licensed band that can provide alternative long-range connectivity option for realizing IoT networks. In this paper, we discuss the Indian smart metering deployment in both rural and urban scenarios where the short-range IoT solution built-in may not always work best to the needs of long-range expectations. Further, we highlight how emerging LPWAN technologies will help in building a reliable, low-cost, low-power, long-range, last-mile technology for smart energy metering solutions. We also present our prototype implementation of end-to-end LoRa connectivity for smart metering solution and discuss final visualization platform.
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