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WIC - DOE Feedback (Topic 5: Big Data)

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v3@whooshh.com View Drop Down
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Joined: 10 Jun 2020
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  Quote v3@whooshh.com Quote  Post ReplyReply Direct Link To This Post Topic: WIC - DOE Feedback (Topic 5: Big Data)
    Posted: 12 Jun 2020 at 4:26pm
As our world relies on data more and more to make decisions in real-time, it is crucial for hydro to make data informed decisions to decrease its environmental impact while improving generation efficiency. New technologies in fisheries data collection could allow for hydro operators to improve water temperature and flows in real-time for migratory species. By understanding when fish runs are approaching downstream, operators can make the proper adjustments in real-time for optimal efficiency and waterway factors. Rather than having to estimate the arrival and choose between environmental benefits and generation efficiency, the industry should be looking to data for both.
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steve.wenke@avistacorp.com View Drop Down
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  Quote steve.wenke@avistacorp.com Quote  Post ReplyReply Direct Link To This Post Posted: 09 Jun 2020 at 11:34am
the concept of using this data to develop digital twins should be investigated as this could help resolve some of the longer term maintenance concerns. As an example, the industry is spending a lot of energy to address start/stop wear and tear. As this is something that often doesn't show up for a number of years, could this twin technology allow users and industry to "see" the results of operational issues today as they might manifest years from now.
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jose.zayas@eaglecreekre.com View Drop Down
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  Quote jose.zayas@eaglecreekre.com Quote  Post ReplyReply Direct Link To This Post Posted: 29 May 2020 at 2:26pm
WIC Community, per their request, we are looking to provide DOE feedback on their current investment profile and priorities. This is a great opportunity to share our industry's thoughts on Ideas, Concerns and Suggestions.
NOTE:
Our formal response will be normalized and not attributed to any company.

Schedule: Due 6/12/2020

Big-Data Access, Analytics and Machine Learning: Data Sharing and Analysis aimed at the hydropower industry ability to manage large, disparate, and dissimilar datasets necessary for resource assessment and project siting, plant and unit performance, operations, costs, maintenance, permitting, and environmental mitigation.   Area also includes Machine Learning and system optimization (O&M, Operations, etc.)

Thank you for sharing your thoughts and helping steer the investments at our Agency(s).

Jose, Steve and Luciana
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