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Utilities Tech Outlook | Thursday, August 13, 2020
Big data is allowing solar power firms to address the challenges that can slow down the internal processes and operations.
FREMONT, CA: Awareness of climate change is growing. With that, one thing has increasingly become clear that using renewable sources is crucial to reducing harmful greenhouse gas emissions, and energy sources like solar are increasingly valuable in this effort. To further rely on the sun, firms must be able to understand its availability, demand, and the ways to meet consumer demands efficiently. This is where big data comes in. Here is what big data can do to the solar energy industry.
• Streamlining Solar Energy Production and Distribution
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As mentioned before, the primary advantage of big data in the solar industry is that it helps streamline energy production and distribution. Despite the growth in the renewable power generation, the unpredictable and intermittent solar resources often impact the overall energy production process. Big data combined with machine learning (ML) and predictive analytics can gather weather and satellite data. Such data can be used to predict weather conditions in advance, enabling renewable plants to adjust their production.
• Optimizing O&M
The proliferation of solar power has resulted in a growth in energy production. However, it’s increasingly becoming challenging to manage the power plants spread across the globe. A massive solar power plant might contain thousands of sensors, inverters, installers, and a web of complex wires. As a result, the maintenance and operation of such large systems will require significant time, effort, and money. Big data analytics can address the above challenges by streamlining operations and management (O&M) to a large extent.
• Lowering Energy Costs
Renewable energy is gaining momentum due to a constant decline in its production cost. Innovations in big data analytics can contribute immensely to the above cause. Big data enables companies to produce more energy without incurring additional costs.
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