How IoT and AI/ML are Revolutionizing Renewable Energy Industry

Renewable Energy to Smart Renewable Energy

Energy sectors are transforming, and IoT is at the core of it. Renewable energy like Solar and Wind without IoT cannot be imagined in today’s energy sector. With the emergence of computing technologies and a push for new clean, renewable energy sources with IoT are breaking the barriers and this combination has led to significant innovations in remote connectivity of monitoring smart devices, helping overcome many remote hardware monitoring challenges that would have held the industry back. In addition, smart devices and sensors are constantly collecting data that can be used with Machine Learning and Artificial Intelligence technologies to predict things like preventative maintenance. Another reason that Renewable energy is picking up pace is due to the depletion of fuel levels at an accelerating speed. WHO studies confirm that air pollution above urban skies causes premature death. On the other hand, Renewable energy provides the lowest cost source for power production and is virtually inexhaustible.

IoT and Solar Energy

Today, IoT technologies are making a breakthrough in Solar Farms. Remote monitoring, managing, and predicting are major IoT phenomena that are helping energy companies increase their solar power production by up to 35%. In addition, reduced sensor costs and the emergence of innovative connectivity have enabled the simple and affordable deployment of granular monitoring networks at large-scale solar farms. With such IoT platforms and smart networks, operators can collect critical external factors and production parameters in a central user interface for strategic decision making and also for intelligent decision making through machine learning/AI. The introduction of IoT opens unimaginable possibilities to improve the efficiency and reliability of solar energy systems.

IoT and Wind Energy

The use of IoT has the potential to provide significant benefits to offshore wind power maintenance, while sensor technology can provide consistent data on the performance of turbines. With the help of remote access, IoT is bridging the gap between a wind farm located and a local control center from a distance. Likewise, IoT gives wind-farm operators control to monitor and regulate much of a turbine’s operations no matter how much distance separates the two. An industrial networking system and remote data collection and communication provide real-time troubleshooting and advanced management at wind sites. Any equipment failures that occur at a wind farm, detection and recovery time reduces significantly. Data collection leads to predictive operations and maintenance — or advanced management — of turbines, so failures are caught before causing turbine downtime. Implementation of industrial-grade managed switches at wind farms makes additional software features available through the switch’s Web interface, which improves data flow, network traffic, and equipment performance.

IoT Provides a Reliable and Efficient Ecosystem

Remote Management

Installment of IoT sensors for energy generation, transmission, and distribution, helps energy companies to gather and monitor information remotely. This installation of key IoT equipment helps measure vibration, temperature, and maintenance schedules. To prevent this from happening, the maintenance approach significantly improves reliability by keeping within an optimal threshold and provides the opportunity to act before the system fails proactively.

Similarly, digital twin technology involves creating an advanced digital model of an existing piece of equipment. IoT equipment attached to the physical unit collects data about its performance, then fed into the digital twin. In addition to supporting preventative maintenance programs, digital twin technology enables virtual troubleshooting and support from remote locations to help improve safety.

Distributed Grid

Energy grids are becoming more distributed than ever, thanks to the rise in commercial and residential solar and other renewable energy usages. Residential solar use has grown rapidly in the recent past and is expected to grow by more than three times by 2025. Homeowners and businesses are now generating their electricity by installing solar panels on their homes or even building small wind turbines on their properties. This increased use of distributed renewable energy systems represents a significant change in dynamic energy usage. From managing a few large generators, there is also now a need to order a growing number of small generation resources located across the grid.

Though this is a challenge for grid operators, using smart grid technology powered by the IoT is helping enable distributed energy transformation efficiently. A smart grid compromises IoT technology to detect changes in electricity supply and demand and react autonomously by providing operators with the information they need to manage consumer demand.

Grid Management

The use of IoT devices is enabling the integration of more distributed resources into the grid and improving grid management in many ways. Placement of sensors at substations and along with disk remotely to utilities and customers consumption data that energy companies can use to make decisions, i.e., voltage control, load switching, network configuration, and other vital factors. Some of these decisions have been automated with the help of IoT devices, and sensors on the grid can alert operators of any fluctuations, allowing them to turn off power to damaged lines to prevent hazards. Smart switches help isolate problem areas automatically and reroute power to get the lights back on faster. Notably, Smart Renewable Energy consumption data is also assisting companies to decide where to build new infrastructure and make infrastructure upgrades.

AI-Enabled Renewable Energy Storage and Distribution

With advancements in technologies, AI/ML has become a tool with the capability to transform the Renewable Energy Industry. AI empowers Energy companies to better forecast, manage their grids, and schedule maintenance. Though Renewable Energy is the future, one major challenge is unpredictability, and AI is helping overcome this with its reliable tool for forecasting the weather. Similarly, predictive maintenance notifies consumers of scheduled maintenance and forthcoming power cuts. AI/ML has the potential to reshape the renewable energy industry completely and the differences it has made. In the upcoming years, these technologies are going to impact both power companies and consumers. Energy companies will have a tool for better forecasting, management of grids, and, most importantly, scheduling maintenance. Likewise, for consumers, the impact will be in the form of interrupted green energy, as well as upfront updates about scheduled maintenance in the grid.

Smart Renewable Energy is the Future

IoT is transforming almost every sector of the global economy, including the energy sector. Over the coming years, the renewable energy industry is expected to get smarter, more efficient, more distributed, and more reliable, as it has become a need of the hour with IoT-based technologies at the forefront. Zigron is one of the leading global Renewable Energy engineering service partners and solution providers. Zigron helps companies develop Smart Energy platforms and analyze data with AI/ML. We also provide services around ERP implementation. Moreover, Zigron provides hardcore engineers like Solar PV, Wind, Civil, Geotechnical, CAD, Project, Structural, and Electrical. With Zigron, you can accelerate in your Renewable Energy pursuit. Zigron is based out of Arlington VA USA and also has more than 150 engineers in Islamabad, Pakistan, and can be your strategic outsourcing/offshoring development partner to optimize your costs and increase your speed to success.