The use of big data in renewable energy can improve the way we produce and consume energy.

We are actively leveraging different sources of renewable energy on a daily basis. Sun, wind, and water are some of the common sources of renewable energy. Even though there are numerous benefits of using sustainable energy, it comes with its own set of problems. Problems associated with sustainable energy have mostly got to do with the distribution mechanism and the cost involved. As a result, companies producing sustainable power are looking for solutions to such problems. These companies hold tremendous amounts of information that will be useful only when analysed well. Big data analytics is a technology that provides an organization with actionable insights by analyzing the information held in their database. These insights, in turn, ease the decision-making process for a company. Big data is for everyone and is extending its reach to different industries. It won’t be an exaggeration to say that big data for renewable energy can revolutionize the speed at which we produce sustainable energy.

Big Data In Renewable Energy

Power Plants hold tremendous amounts of information. This information includes the amount of power generated and the volume of resources consumed in the process. Big data analytics can use this information from numerous power plants to extract actionable insights, increasing the speed of producing sustainable energy. Here’s how big data can increase the rate at which sustainable energy is produced:

1. Load Balancing

There are numerous houses (microgrids) that are producing sustainable energy with the help of solar cells. These cells are connected to software that stores information, such as the amount of energy generated. With the help of big data analytics, power plants can analyze this information. Upon analysis, authorities can identify localities and their demand for power supply. Next, authorities can quickly decide on which plant’s power needs to be transferred to which specific area. This bi-directional communication decreases the load shedding problem.

2. Virtual Power Plants

With the advent of microgrids, energy storage areas can transmit energy from one end to another. With the help of analytics, multiple grids can act as a single power plant that produces sustainable energy. Big data analytics assists in analysing which grids can be combined for sustainable energy production. Virtual power plants eliminate the need to develop new physical power plants. This in turn can save billions of dollars.

3. Power Generation

If a solar cell does not receive an adequate amount of solar power, it would not generate sufficient amounts of electricity, right? With the use of big data analytics for weather prediction, companies can use these insights to understand when the sources of energy will be at their peak. Authorities can later decide how they can increase the production of energy.

4. Machine Failure Detection

Every machine comes with the condition that it will break down after a specific time. Machines generating sustainable energy often experience breakdowns when they are in operation for long. According to a report, machinery breakdown is the tenth biggest cause for major revenue losses in companies. With big data analytics, authorities can gain actionable insights from the sensors installed in every machine. With these insights, authorities know beforehand the possibility of a machine failure. They can accordingly deploy ground staff to reach out to the machine in time. This not only reduces the downtime but also drastically increases the speed at which sustainable energy is produced.

Authorities must understand that the need of the hour is to increase the speed of sustainable energy production. They should now cater to the challenges obstructing the use of big data for renewable energy, such as hardware issues. CTOs and CIOs can also reach out to companies that offer big data analytics as a service.