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Machine learning model revolutionises energy price forecasting

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CLIENT Energy Retailers, Traders, & Procurement Leaders

INDUSTRY Energy, Utilities, & Wholesalers

BUSINESS SIZE Large Enterprise / Institutional

SOLUTIONS Machine Learning Energy Price Forecasting Model


The changing landscape of energy

The Australian energy sector is facing complex challenges due to the integration of renewable energy sources. Traditional methods are now inadequate for load and price forecasting.

  • Complex load and price forecasting: increased complexity due to renewable energy integration.

  • Accurate predictions needed: organisations and consumers require precise electricity price predictions to optimise operations and manage costs.

  • Critical process optimisation: balancing energy consumption with price fluctuations is vital, especially in industries where production adjusts based on energy costs.

  • Affordability and stability: ensuring affordable and stable electricity supply is a paramount concern for providers and regulators.

  • Decentralised grid: predicting supply, demand and pricing is increasingly difficult using conventional methods.

Innovior's advanced machine learning model

Innovior has developed an advanced machine learning model to predict electricity prices with high accuracy.

Capable of forecasting electricity prices in 30-minute increments for 48 hours.

Our engine can benefit from its selfsupervised learning capability, enabling it to adapt and improve accuracy over time.

Utilises advanced analytical tools to process historical and real-time data.

The model can easily be integrated to existing tools to assist SME to make better decisions or act autonomously.

 

The models are built using MLOps, which streamlines the process of taking machine learning models to production. This involves using a mix of sequential data, such as historical power demands and weather data, with non-sequential data, such as specific events impacting energy consumption and pricing.

Applications and benefits across the energy sector

  • Accurate price predictions allow energy-intensive industries to optimise production schedules and energy consumption, leading to substantial cost savings.
  • Empowers decision-makers with better insights for energy pricing and consumption strategies, increasing stability and affordability in electricity supply.
  • Optimises the integration of renewable energy sources into the power grid, reducing carbon emissions and fostering a resilient, environmentally friendly energy infrastructure.

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