G. Filios, Ioannis Katsidimas, Emmanouil Kerimakis, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis
{"title":"An IoT based Solar Park Health Monitoring System for PID and Hotspots Effects","authors":"G. Filios, Ioannis Katsidimas, Emmanouil Kerimakis, S. Nikoletseas, Alexandros Souroulagkas, P. Spirakis","doi":"10.1109/DCOSS49796.2020.00069","DOIUrl":null,"url":null,"abstract":"With solar parks being established as one of the most important renewable energy systems, there is a strong need for more efficient use of the services they provide, as well as error detection and performance issues confrontation. Internet of Things (IoT) technology, aims to fill the gap, by offering low cost and sustainable solutions towards the efficient operation of these parks. In this paper, we present an in situ monitoring and alerting system, based on WSN technologies, regarding the early detection of Potential Induced Degradation (PID) and Hotspots failures, that can cause a significant drop in solar panels’ performance. In order to do so, specific non-trivial attributes such as temperature, humidity, irradiance, current and voltage are continuously monitored at panel level, and processed in a cloud based platform to early identify these phenomena. In particular, sensor nodes send data to a centralized local sink module using a multi-hop WSN architecture, in order to establish a robust and large coverage area. Afterwards, the information is propagated to the cloud server, where deterministic diagnostic algorithms are applied. We present the reference architecture of our approach, alongside the corresponding hardware and software structural, individual components, as well as the integration process and the use case that runs over a real solar park.","PeriodicalId":198837,"journal":{"name":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 16th International Conference on Distributed Computing in Sensor Systems (DCOSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCOSS49796.2020.00069","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
With solar parks being established as one of the most important renewable energy systems, there is a strong need for more efficient use of the services they provide, as well as error detection and performance issues confrontation. Internet of Things (IoT) technology, aims to fill the gap, by offering low cost and sustainable solutions towards the efficient operation of these parks. In this paper, we present an in situ monitoring and alerting system, based on WSN technologies, regarding the early detection of Potential Induced Degradation (PID) and Hotspots failures, that can cause a significant drop in solar panels’ performance. In order to do so, specific non-trivial attributes such as temperature, humidity, irradiance, current and voltage are continuously monitored at panel level, and processed in a cloud based platform to early identify these phenomena. In particular, sensor nodes send data to a centralized local sink module using a multi-hop WSN architecture, in order to establish a robust and large coverage area. Afterwards, the information is propagated to the cloud server, where deterministic diagnostic algorithms are applied. We present the reference architecture of our approach, alongside the corresponding hardware and software structural, individual components, as well as the integration process and the use case that runs over a real solar park.