An Energy Prediction Model for a Renewable Energy Company
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Problem
Consumer demand, political demand, and improved engineering is moving the world towards greater use of renewable energy. However, reliability — a critical part of any energy source — remains a limiting factor. How much solar energy can you generate on a cloudy day, or when snow blankets the solar panels? How many wind turbines can you operate when it’s not windy? What is the demand & Supply at peak hours? These sound like simple problems, lack of solutions make renewable energy less reliable than fossil fuels.
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Solution Given
Intelytica with its expertise proposes to implement its SPARK solution that places Renewable Energy companies at the forefront. SPARK predictive Analytics solution enables companies to understand accurate energy production forecasts. It also predicts machine breakdowns or glitches thereby optimizing overall operational efficiency. SPARK solution validates the correlation of various parameters like irradiation, wind speed, temperature, humidity, cloud cover, transformer status, etc.. and determines their cause and effect relationship
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Solution Impact
- Our solution helped the client to predict machine breakdowns or glitches thereby optimizing overall operational efficiency.
- The proposed model effectively anticipates high-frequency inverter failures up to almost 7 days in advance, with sensitivity up to 95% and specificity of almost 80%.
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Data Engineering
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