Smart Supervision: AI for remote monitoring and key applications of solar parks

AI for remote monitoring and key applications of solar parks

Solar photovoltaic (PV) plants must be constantly protected and supervised to keep them safe and reliable during their working lifetime. Incorporating smart technological equipment including artificial intelligence (AI) and internet of things (IoT) for remote sensing, fault det­ection and diagnosing PV plants can help these plants achieve peak efficiency. Whi­le renewable energy appears to be thriving globally, its intermittent nature creates a need to develop solutions for ensuring grid stability.

The output of solar panels is influenced by a variety of environmental factors such as the amount of solar radiation, proportion of shadow, weather conditions and so on. Constantly monitoring these variables, particularly for off-grid and remote solar energy plants is a tedious task. It is crucial to enable remote monitoring tools in order to have reliable power support without any obstacles. A system may produce less electricity than its capacity because of the module being overly shaded, dirty and damaged among other factors. Thus, de­ploying smart technological tools can help in closely monitoring solar panel production for identifying stumbling blocks.

The smart PV monitoring system is a hybrid of hardware and software. It is an online platform that constantly monitors the solar system in real time using sensors, data loggers and other gadgets. In order to track and monitor the output of solar panels, the solar energy system is made of a number of sensors that are installed in various places. These sensors measure the irradiation, ambient temperature, module temperature, wind speed and other factors affecting the solar panel and its parts. The IoT gateway receives the generated data and uploads it to the cloud for monitoring. The collected data is then transmitted from the solar system’s inverter to the manufacturer’s monitoring database. With the help of IoT, the analysed data is transmitted to an application for predictive maintenance and investigation. The user and installer can quickly access the data that has been uploaded to the cloud at any time through the monitoring application. On the basis of past data patterns, comparative analysis can be done using real-time monitoring data.

Key benefits

The monitoring systems help in displaying energy consumption and generation data. They can assist in detecting defects and re­commend timely repairs that may be needed in the existing set-up. Issues such as solar system trips, drop in panel performance, fall in inverter performance can be duly monitored and notified to the solar in­staller. The system stores the monitored data so that it can be retrieved at any time to assess the solar energy efficiency. The­se cloud-based solutions provide highly interactive, real-time access to key per­for­ma­nce and operations metrics, which en­ab­le plant managers to optimise decisions.

Key barriers

Due to the difficulty in ensuring a centralised data management process, data monitoring systems currently in the market have a number of drawbacks. In re­mote solar parks, it can be challenging to secure a Wi-Fi internet connection, which is required by sensors used in the majority of systems to transmit information. Also, the barrier to modernisation in the en­ergy sector is the outdated infrastructure. Utility companies gather a plethora of information but have no idea about how to manage it. The collected data is freq­uently dispersed, disorganised and stor­ed locally in various formats. Imple­men­ting innovative smart technology in the energy sector may be the best option, but it is far from the cheapest. It takes a lot of time and money to look for an experienced software services provider, develop and customise software, and then manage and monitor it.


Most of the automation and technology solutions for remote monitoring aim to ma­­xi­mise the efficiency of solar plants. Their long-term goal is mainly to reduce and op­timise the cost of operating solar PV plants by undertaking predictive maintenance. Before incorporating AI, machi­ne learning and deep learning into their strategies, businesses in the energy sector must be ready to set aside a budget for and accept the risks of updating their out­dated syste­ms. Apart from remote monitoring of solar plants, AI will be also be used for other key applications within the renewable energy space. For instan­ce, in September 2022, Mi­­crosoft Corpo­ra­tion, Planet Labs PBC and The Nature Conservancy anno­un­ced pl­a­­ns to launch the Global Re­newables Watch, a living atlas intended to map and me­asure all utility-scale solar and wind in­stallations on the earth, using AI and satellite image­ry, allowing users to evaluate the cl­ean en­ergy transition progress and track trends over time. The installations for the same will be done in India as well.

In terms of a business model, software as a service is gradually picking up pace in India. Going forward, more technical training of the workforce, collaboration among domestic and international players and ease in funding for modernising outdated plants can help in equipping smart solar parks with modern tools such as AI.