Renewable Energy

Big Data is Changing the Outlook of the Renewable Energy Sector

How Big Data is Changing the Outlook of the Renewable Energy Sector?

The renewable energy sector is facing a significant transformation, and all credit goes to the power of big data. With its capability to gather, store, and analyze an immense amount of data in real-time, big data provides unprecedented insights into how we generate and use energy.

This has allowed companies in the renewable energy sector to create innovative solutions supporting us to adopt and create a more sustainable future.

So, let’s check how big data transforms the renewable energy sector and how the sustainable future will look!

Big data is a term used to describe the immense amount of data that organizations accumulate and analyze to achieve better insights into their operations. It can be sourced from various sections like:

  • Customer feedback
  • Transactional records
  • Sensor readings
  • Social media posts
  • Search queries, etc

All these together form a data set that can be utilized to make the most suitable decisions on the basis of analysis of correlations, ongoing patterns, and trends.

We can simply say that big data is a way to convert raw data into actionable insights, and this is what makes it so powerful.

Let’s know how big data functions

As we have already discussed, big data is utilized to collect and analyze vast amounts of data in real-time. This enables companies to understand consumer activities and behavior while optimizing their processes as well as operations.

Also, the analysis of big data can assist in identifying patterns that are unintentionally ignored. This is how companies are able to discover new opportunities and develop strategies accordingly. Not just this, big data also empowers organizations to get a better insight into their operations. 

For instance, energy companies can keep track of energy usage and identify areas where improvement is needed and efficiency can be enhanced.

Here, we can place the example of Tesla powerwall. It collects data from its solar panels to observe the production and consumption of electricity in real-time. Tesla’s power wall can be utilized to optimize energy usage by offering customers with customized options.

Three ways through which big data is transforming the renewable energy sector

So, at least, we have some knowledge of big data. Now, let’s find out how it is changing the renewable energy sector.

1. Improved Efficiency:

Big data analysis can support companies by identifying areas where efficiency can be enhanced in energy systems. For example, it helps in reducing wastage and optimizing output. This will ultimately improve the entire profitability produced by renewable energy businesses. This supports both seller and buyer as they can save energy costs and use the same to invest in other green-based projects or initiatives.

The skyrocketing cost of traditional energy sources has unveiled the importance of renewable energy. It has made it more attractive, and the involvement of big data can aid in making it more efficient. Big data will not only make renewable energy more feasible but will also make it a more attractive alternative for buyers.

2. Presaging Demand and Supply:

Big data can also be utilized to foretell the demand and supply of renewable energy.

By analyzing historical data, businesses can understand the market pattern and behavior and can easily calculate the present demand for distinct types of renewable energy resources. Therefore, they can change, shift, or adjust their production as per the need. In this way, companies can target a specific customer base, leading to more conversions and ultimately adding more profits. On the other hand, customers will also get whatever they want, so it turns out to be a win-win situation for everyone involved.

Other than predicting demand and supply, big data are also used to forecast weather conditions, which will allow businesses to plan their production of renewable energy resources.

For instance, the Tesla power wall can forewarn the weather conditions and shift energy production consequently.

3. Automation of a few processes:

In the end, we can say that the most significant advantage of having big data in the renewable energy sector is automation. By automating specific processes, organizations can save time as well as resources while making their operations more efficient.

For instance, solar panel systems can be linked to the internet and designed to adjust their output depending on weather conditions on a real-time basis. In this way, consumers can cut down their electricity bills by generating more energy when the sun is shining bright in the sky.

Besides this, companies can also utilize big data to automate the maintenance of their assets involved in renewable energy systems. By tracking and analyzing real-time data, they can interpret any issues and take action before they turn out to be a significant problem in the process.


With rising global temperatures and increasing greenhouse gases in the environment, it has become necessary to bend toward renewable resources for energy generation. The shortage of non-renewable resources and by-products it offers, like pollution, greenhouse gases, etc, is another reason to shift toward renewable energy resources.

In this initiation, the addition of big data is causing an immense impact on the renewable energy sector. It is making renewable energy more efficient by predicting demand and supply and automating a few processes to reduce time and cost. With the advancement of technology, in the coming years, big data will become an integral part of the renewable energy sector and churn the best result while promising a green and sustainable future.

How Edge Computing is Revolutionizing the Energy Industry

How Edge Computing is Revolutionizing the Energy Industry

The energy industry is experiencing consequential changes as it encounters numerous challenges with an increasing population, like increasing demand for electricity, integration of renewable energy sources, and emerging electric vehicles. The best way to address these issues is by embracing edge computing and using it potentially. It is a distributed computing paradigm that allows data processing and analysis nearer to the source.

In this blog, we will understand how edge computing can change the outlook of the energy industry, making it more reliable, efficient, and sustainable.

Challenges faced by the current Energy Industry

The existing traditional power grid is one of the most necessary infrastructures in our day-to-day lives. It powers our homes, hospitals, schools, industries, and other essential things for our daily routines. However, power grids face numerous challenges because of the increasing electricity demand, the integration of renewable energy sources, and the growing market for electric vehicles. These challenges can be solved using innovative solutions to optimize the grid’s operation, improve its resilience, and diminish energy waste.

What is Edge Computing?

Edge computing can be explained as a distributed computing paradigm that allows data processing and analysis closer to the source. It can be installed in various locations in the power grid, like substations, to process and analyze the data generated by the sensors in real time. Edge can also support optimizing the power grid’s operation, improving its resilience, and cutting off energy waste.

3 essential Pillars of Edge Computing

  • Improved scalability: Edge computing allocates storage and processes it over many locations, reducing the investment cost for infrastructure and capacity for a higher traffic volume or better algorithm.
  • Better data security and sovereignty: As data remains at its original location, the risks for illegal access or theft are decreased automatically.
  • High amount of data processed with less latency: Frequency analysis allows it to work with thousands of data almost instantly, with just milliseconds required for analysis and response. This solved the near real-time use cases- something impossible in Cloud Environments that are more inclined to offline analysis of batch information.

The IDC’s report on ”Edge Computing Solution Driving the Fourth Industrial Revolution”- emphasizes the need for the pillars mentioned above. A survey was conducted in which around 802 industry leaders who adopted Edge Computing – almost 30% stated that their primary motivation was bandwidth costs, 27% data protection, 19% latency constraints, and 12% surveyed were from the energy sector.

Introducing Smart Power Grid with Edge Computing

In a smart grid system, multiple sensors are installed to gather data related to the health condition and performance of the power grid. These sensors create immense amounts of data that need to be processed and analyzed in real-time to make reasonable decisions. Rather than sending all the generated data to a centralized data center, edge computing is data processing at the network’s edge, closer to the source.

Edge computing supports optimizing the power grid’s operation, improving its resilience, and lowering energy waste.

For example, a power-consuming company can install edge servers at different locations in the power grid, like substations, to process and analyze the data created by the sensors in real time. The edge servers use machine learning algorithms to anticipate the power demand and supply, detect faults, and effectively manage electricity distribution.

Edge computing also enhances the power grid’s resiliency by allowing autonomous decision-making at the edge in case of network disruptions.

For example, assume any substation loses connectivity with the central control system. In that case, the edge servers can return to a backup mode and continue to function autonomously using locally stored data.

The Advantages of Edge Computing

Edge computing can bring change to the energy industry and make it more reliable, sustainable, and efficient. By opting for edge computing, power utilities can optimize their processes, lower energy waste, and offer higher-quality services to their customers. Edge computing can resolve the power grid’s challenges, such as growing demand for electricity, incorporating renewable energy sources, and emerging electric vehicles.

Besides this, edge computing can allow energy utilities and municipalities to develop and deploy data processed quickly and efficiently, allowing them to churn profit from edge computing solutions more effectively.

Users with no or low programming experience can design and deploy data processes promptly and efficiently using a convenient, low-code tool. This can assist in streamlining the deployment of edge computing solutions and allow energy utilities and municipalities to resolve the power grid challenges.

Main issues of IoT Edge Computing for the Energy Sector?

IoT Edge is powered by solid investment by technology manufacturers in cutting-edge solutions with smaller, lower-powered, and lower-priced microcomputers that can operate as IoT Edge Computing nodes at scale.

Similarly, operating systems and software are also created to give these nodes the capacity to conduct algorithms in a cyber secure way, generally packaged in virtual software “containers” like Docker.


Today, if we look into the energy industry, we’ll find out that the energy industry encounters many challenges, like increasing demand for electricity, incorporating renewable energy sources, and overflowing of electric vehicles in the market. With the increasing population and development of industries, it has become necessary to adopt and embrace technology that cannot just solve the problem but also does not negotiate with the quality of operations.

Edge computing has the prospect of revolutionizing the energy industry, making it more dependable, sustainable, and efficient. By embracing edge computing, power utilities can enhance their operations and reduce the risk of energy wastage.

Energy Harvesting and IIoT- Sustainability for the IIoT

Energy Harvesting and IIoT: Sustainability for the Industrial IoT

The world is encountering tremendous economic and ecological changes along with challenges. The futuristic technologies are all set to transform the outlook of Internet of Things (IoT). Today energy supply to millions of communicating devices is a key issue. 

On a large scale, renewable energies have become a major source of energy generation. Fields embracing solar cells that generate energy using sunlight or wind turbines dominate the landscape. This renewable energy for energy generation is also embraced on a small scale. This entire concept is called “energy harvesting.” 

Small energy converters harvest energy from light, movement, or temperature differences. These harvested energies are enough to power a wireless sensor and transmit data using radio. 

Energy harvesting for radio-based products that are already part of mass production includes four different sources:

  • Motion – the press on a switch, moving machine parts, the rotary motion of a handle.
  • Light– the sunlight coming inside a room.
  • Temperature differences – existing between a heat source like a boiler, radiator, or pipes and the environment and variation between day and night.
  • Electromagnetic field – a contactless coil in a cage clamp around a cable controls the meter and calculates the line current.

For each source, different energy converters with different power parameters are present. The energy generation type and the corresponding power yield determine the possible sensor applications.

Enhanced Sustainability:

With the introduction of energy harvesting technology, radio sensors are sustainable as they don’t require cabling or battery power. They are environment friendly as well as cut expenditure.

Replacing a single battery typically costs around $300 US dollars in an industrial environment. Though changing the battery does not consume much time, traveling to the site, locating the sensor, testing the device, and documenting the process increases the labor cost. It is believed that batteries have a good service life, but in reality, companies are often engaged in changing them within one or two years to avoid early failures.

Today, resource-saving and environmental protection are the top priority. The rising cost of copper, the presence of harmful components, and battery safety are some serious issues. Wireless energy harvesting sensors are the best solution that considers both the financial aspect and environmental protection.

In Process for The Industry:

Sensors play a key role in industrial production. They can be used for quality and process monitoring or condition-based maintenance. A wide range of applications is developing in the direction of an industrial Internet of Things (IIoT) with the increasing usage of wireless sensors. Integrating energy-saving radio with local energy converters,battery-free and maintenance-free sensors can be installed directly on moving parts or in hermetically-sealed environments. For instance, it can be implanted to know the position of moving parts, power consumption, temperature of moving parts, liquids, or gases.

Sensors in Quality Control:

Quality monitoring manages the entire production process and ensures the desired properties of the end product based on different parameters.

For this purpose, environmental factors like temperature, humidity, and air quality or process factors like position or temperature are monitored.

Automated monitoring systems require data generated by sensors; for this purpose, sensors must fit seamlessly into existing production processes. Additionally, they must not need special training or generate follow-up costs in the ongoing operation. Therefore the integration of self-powered and maintenance-free sensors provides benefits.

Condition-based Maintenance with Battery-free Sensors:

Besides products, machines also need proper monitoring to ensure a seamless production process. These are prone to high wear, so it would be best to identify problems as soon as possible and take appropriate actions to maintain continuous quality assurance and protection against production downtime.

A primary problem with maintenance planning is the calculation of the intervals between each maintenance cycle. Normally, the interval between two maintenance dates must be as short as possible to detect deviations before any mishappening occurs. Still, each maintenance involves high costs for personnel and idle machines.

It is often possible to derive valuable information by closely examining a few simple parameters. For instance, a temperature rise can indicate higher friction, thus resulting into wear. Wireless temperature sensors can be installed for measurement processes. Humidity sensors monitor water leakage to prevent water damage. Temperature and humidity sensors also inform about air conditions and guarantee good air quality. That is why wireless energy harvesting sensors are best for various industrial applications. They are low maintenance, flexible, and within budget to install.

That is why wireless energy harvesting sensors are ideal for various industrial applications. They are maintenance-free, flexible, and inexpensive to install – outstanding features for assuring high-quality standards and greater sustainability in the Industry 4.0 environment.

IoT in the Factory Building:

IoT allows significantly efficient, adaptable, and individualized production in manufacturing. Using sensors networked with a smart IoT platform, it is now possible to develop a digital twin, i.e., an exact virtual image of a machine throughout its entire life cycle. Digitalization is becoming a part of buildings and will revolutionize them by providing automated service processes in facility management, higher energy savings, and better individual well-being for users. One important thing for factory buildings and industrial processes is battery-free wireless sensors.