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Analytics & Optimization for Energy

Analytics & Optimization for Energy

Improve project economics and save customers money using IoT data with advanced analytics.

“FICO’s optimization technology helped us solve one of the most difficult problems in the wind industry. The result is a giant leap forward in protecting the environment with sustainable energy solutions.”

- Klaus Vogstad, Creator of WindFarmDesigns

Solution Details

Reduce nonproductive time, increase margins and return on assets, and free up capital for investment.

Digital transformation in the energy industry is changing project economics and opening up new opportunities to deliver more value to customers. From optimizing wind turbine locations or refinery schedules to telling consumers and businesses how to save money by discharging solar batteries at the best time, optimization rapidly identifies the best decisions among millions of possibilities.

As part of this move to Industry 4.0, FICO decision management solutions are accelerating the already strong trend toward wider use of optimization across energy operations. Putting the power of data science in the hands of more business users, we’re making it easy for even nontechnical stakeholders to understand and act on analytic insights from massive amounts of data streaming in from IoT sensors, machines and mobile worker devices. We help your people see clearly through complex nested processes and across supply chains to spot cost-saving opportunities, risks needing proactive attention and opportunities for performance improvement. And our solutions also reduce the time and money to develop and deploy analytics-driven applications by up to 80%.

Use Cases

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Planning, Forecasting and Scheduling

Know what to do to maximize ROA, margin and profit.

Optimization can help you select the best strategies for meeting asset utilization goals, maintenance requirements, environmental constraints and profit targets amid uncertainties in demand and availability. One company used it to plan wind farm layouts that maximize energy yield and profitability while meeting load compliance regulations — getting the answer in 10% of the time it would otherwise take.

  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Demand and load forecasting
  • Capacity expansion planning
  • Physical-financial asset optimization and risk management
  • Rapid design/deploy of analytics-driven digital applications
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Logistics and Supply Chain Optimization

Streamline the flow of raw materials and components across all stages of your processes.

Optimization and other advanced analytics can help you improve raw material procurement and component transfers between facilities. When supply disruptions occur, they help you adjust production schedules to still meet service-level agreements.

  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Scheduling optimization
  • Transmission and component transfer analyses
  • Spend and supplier mix analyses
  • Vendor contract management and performance analysis
  • Rapid design/deploy of analytics-driven digital applications
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Production Management

Increase production agility and control under changing conditions.

Analytics-driven decision automation is enabling energy innovators to create a new, more flexible generation of advanced process controls. It’s being used, for instance, to balance quality and cost objectives in fuel and chemical blending while accounting for volatility in raw materials price. Plant-level decision makers are able to make more informed choices and use visualization and simulation to quickly explore and balance tradeoffs.

  • Business rules automation and management
  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Predictive maintenance
  • Production scheduling optimization
  • Rapid design/deploy of analytics-driven digital applications
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Equipment Diagnostic

Reduce downtime through predictive asset maintenance.

Decision rules add intelligence to diagnostics systems, reducing time-to-identification of the root causes of production problems. Machine learning and predictive analytics identify machines that are outliers in terms of expected ranges of production, speed or energy consumption—triggering maintenance intervention before failures occur.

  • Streaming data analytic platform
  • Business rules management system
  • Machine learning and explainable AI
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Distribution

Improve access to reliable energy while reducing costs.

Optimization and other advanced analytics can help you improve delivery of energy to utilities and the households and businesses that depend on them. Use them to identify and make best use of spare capacity. Balance a broader range of factors, like wholesale power capacity, system reliability and environmental constraints, that impact your delivery strategies.

  • Streaming data analytic platform
  • Machine learning and explainable AI
  • Transmission and capacity analyses
  • Pricing optimization
  • Rapid design/deploy of analytics-driven digital applications

 

Case Study

WindFarmDesigns

Ever wonder how WindFarmDesigns can reduce C02 emissions by over 20 million metric tons per year?

FICO® Xpress Optimization

SolarCity

SolarCity uses FICO® Xpress Optimization Suite to optimize distributed energy applications.