Industry 4.0 and data generated by IoT devices have had a strong, positive impact on the manufacturing sector. Sensors attached to production equipment, for example, can provide valuable information on its overall health. In the same vein, IoT and data can help solar power plants achieve better and more effective management.
Industry 4.0 and data generated by IoT devices have had a strong, positive impact on the manufacturing sector. Sensors attached to production equipment, for example, can provide valuable information on its overall health. Meters or detectors installed throughout the factory can help detect gas leaks and other types of danger, thus protecting workers from harm. In the same vein, IoT and data can help solar power plants achieve better and more effective management.
“Firms in the energy industry have long been aware of the potential for greater insights to yield operational and efficiency improvements, but have grappled with the challenges of effectively collecting and executing upon such insights. The arrival of IoT technology presents an elegant solution to these challenges – IoT sensors and devices offer the capability to collect vast quantities of information, enabling predictive analytics informed by this big data,” said Steve Cummins, Senior Director of Marketing at
Opengear. “With the IoT, energy firms can achieve the granular oversight that has long been a goal, and can employ data analysis solutions that utilize both historical and real-time data to make accurate projections, enabling improved preparedness for future outcomes.”
One area where IoT and data can be of great help to solar power operators is better, more effective monitoring of individual plants, which are typically spread across a large area of land. “If I'm talking about a large-scale solar plant with a capacity of 100 megawatts, it will be spread across 500 acres of land. So for an operator to know what's happening on the other end which is about 1 or 2 kilometers away, it's practically impossible if you do not have connected devices,” said Agarwal Meenal, Brand Manager at
MachinePulse. “In case of rooftop solar where you have smaller, kilowatt-scale installations spread across multiple buildings, I cannot have an operator sitting at each and every building managing the particular assets. Neither the economics of solar nor the applicability or the usability allows for it. So for that to happen, you need to have a system which can display or feed you with information as to what's happening at a certain time.”
Related to this is the so-called predictive maintenance, whereby the impending failure of equipment or solar panels can be informed to the operator, who can then act accordingly. “Each solar panel can include an IoT sensor that sends constant feedback to automated management systems, and provides alerts to management personnel if attention or maintenance is required,” Cummins said.
“Operating and maintenance costs remain a high priority during the entire lifetime of the plant and predict the output with better confidence. IoT-based solutions help predicting failures based on advanced diagnostics on the data being collected remotely from the connected devices on field. Over a period of time, as the intelligent decision-making capabilities rise based on the proliferation of machine learning algorithms, IoT will help bring down the O&M costs and improve the forecasting related challenges,” said Keshab Panda, CEO and Managing Director at
L&T Technology Services.
Furthermore, compared to other types of power generation, solar is unique in that it relies on yield predictions and long-term forecasting to optimize production, and this is where data can also help. “With gas or coal-fired power plant, the management of power or how much you're exporting to the grid becomes very easy. So for instance if I was an operator at a thermal power plant I'd know what is the stock of coal that I have, and I just need to feed in a particular amount of coal into the boiler and I'll generate a certain amount of steam and power,” said Meenal. “However with solar it's a different use case, because a cloud passing at a pace of 7 to 9 kilometers per hour can make all the difference. There can be conditions that are very different from what's being forecasted. So you need data from various sources and integrate all that data to make accurate forecasts. This is where the power of IoT comes into the picture.”
“Accurately predicting yield to facilitate better long-term forecasting is a primary concern. However, this too can be addressed to a large extent with use of data collection analytics that take into consideration the relevant parameters and throw up insights ensuring better planning. This is particularly helpful in case of hybrid generation where solar power plant is backed up with a conventional generation unit or a Battery Energy storage system,” said Panda.