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  • Track and monitor growing number of supply, demand, and storage nodes on grid to improve overall reliability and cost of service.
  • Optimize maintenance performance through learning models that account for effectiveness of manual intervention actions.
  • Optimize grid performance in context of variable renewable supply sources, storage assets, demand response and load curve forecasting.
  • Track grid asset performance and improve reliability with proactive performance monitoring.
  • Mitigate grid equipment failure and related outage events through near-term automated alerts.
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Sectors Plutoshift supports:

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Power
Generation

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Distributed
Power

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Battery
Storage

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Wastewater
Treatment

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Grid
Operations

Use Cases

1.
Power generation water treatment
2.
Micro-grid efficiency
3.
Vegetation management
4.
Reliability management
1.
Apply predictive algorithms to equipment and processes to spot maintenance needs and develop optimal maintenance strategies
2.
Optimize power supply and storage assets to improve micro-grid performance
3.
Combine internal and external data sources (eg, satellite imagery, drone-data, precipitation/moisture) to prioritize field activities in context of cost and risk.
4.
Minimize unplanned outages at lower cost of service through predictive maintenance programs.

Use Cases

Power generation water treatment.
Apply predictive algorithms to equipment and processes to spot maintenance needs and develop optimal maintenance strategies
Micro-grid efficiency.
Optimize power supply and storage assets to improve micro-grid performance
Vegetation management.
Combine internal and external data sources (eg, satellite imagery, drone-data, precipitation/moisture) to prioritize field activities in context of cost and risk.
Reliability management.
Minimize unplanned outages at lower cost of service through predictive maintenance programs.

News & Blog

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Bridging The Gap Between AI Promise and Results: 3 Actionable Steps

By Prateek Joshi: Analyst firms like Gartner and Forrester have been advising their clients and the industry at large for several years about the dramatic changes automation and AI...
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Why Manufacturing Companies Continue to Struggle with AI Implementation Projects

By Prateek Joshi  Manufacturing companies know that Artificial Intelligence (AI) can have multiple business advantages for the frontline team and on the overall bottom line. But despite companies’ best...
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Industrial Automation: 4 Industrial AI Predictions for 2020

By Prateek Joshi: 2019 was a banner year for AI! Almost every business magazine and tech publication published a deluge of articles about AI and its impact on the...
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AI for Coffee Manufacturing: 3 Ways AI is Energizing The Coffee Industry

By Prateek Joshi: From bean to barista, the global coffee industry is valued at over $100 billion. For a producer, distributor or manufacturer in this massive industry, the use...

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