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Crown Capital Management -Dona

Crown Capital Management -Dona

Environment

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  • Better short-time local weather prediction = cheaper renewable energy

    Community, Environmental Design

    Wind-global-market-2017

    Source

    Big deal if we want to incorporate LOTS of renewables in the grid

    There are all kinds of ways to make renewable energy cheaper. Most people focus on things like more efficient solar panels, bigger wind turbines, economies of scale in manufacturing, etc. But because clean sources of power like wind and solar are intermittent, there's also a lot of room for improvement in functionally making them more stable, or at least more predictable.

    To understand why that's the case, you need to look at the power grid as a whole and not just at a wind or solar farm in isolation. Because wind and solar aren't entirely predictable, grid operators need to have backup power plants ready to pick up any slack (usually natural gas peaker plants) quickly. But when these plants run when they are not needed, this increases costs (and pollution). And sometimes if there's an unexpected surge of wind and/or solar, it's possible that the clean energy gets wasted because the grid wasn't ready to absorb it in a useful way.

    Many companies are working on ways to mitigate that, including IBM:

    IBM (NYSE: IBM) today announced an advanced power and weather modeling technology that will help utilities increase the reliability of renewable energy resources. The solution combines weather prediction and analytics to accurately forecast the availability of wind power and solar energy. This will enable utilities to integrate more renewable energy into the power grid [...]

    The solution, named "Hybrid Renewable Energy Forecasting" (HyRef) uses weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements, while sensors on the turbines monitor wind speed, temperature and direction. When combined with analytics technology, the data-assimilation based solution can produce accurate local weather forecasts within a wind farm as far as one month in advance, or in 15-minute increments.

    "Applying analytics and harnessing big data will allow utilities to tackle the intermittent nature of renewable energy and forecast power production from solar and wind, in a way that has never been done before," said Brad Gammons, General Manager IBM's Global Energy and Utilities Industry. "We have developed an intelligent system that combines weather and power forecasting to increase system availability and optimize power grid performance."

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