AI and Renewables – How It Will Transform Energy Procurement

Posted on 03 May 2024

Shalika Kapilarathne
Renewable Energy Intern

An Electrical Engineering undergraduate specialised in Machine Learning and Predictive AI.

Introduction 

In recent years, vast applications of machine learning and artificial intelligence have been integrating into many industries. Among them predictive artificial intelligence (AI) is the most promising and impactful technology. Predictive AI together with machine learning (ML) algorithms analyses current and historical data to make predictions about future outcomes. This blog is a deep dive into this Predictive AI and machine learning, outlining its significance, applications and future potential for the Energy Sector.

Understanding Predictive AI and Machine Learning

What is Predictive AI?

Predictive AI uses AI algorithms and models to analyse data and forecast future events of behaviours. Learning from the past data and analysing from the past behaviour patterns, it generates the predictions on future outcomes. This technology is rapidly transforming the industries by enabling them to take the decisions based on those predictions, fostering innovation and optimising their process.

What is Machine Learning?

  • Supervised learning: In supervised learning, the algorithm uses labelled dataset(s) for the learning process. The labelled dataset contains the data where inputs are tagged with corresponding outputs. It uses labelled data to learn the mapping function from the input to the output.
  • Unsupervised learning: Unsupervised learning involves training the model using information that is neither classified nor labelled and allows the algorithm to act on that information without guidance. It aims to find the structure and patterns from input data independently.
  • Reinforcement learning: Reinforcement learning is a type of ML where an agent learns to behave in an environment by performing certain actions and seeing the results of those actions. The agent learns to achieve the goal in an uncertain and potentially complex environment.

How RE24 utilises Machine Learning and Predictive AI

ML and predictive AI is used to get the predictions of the generation and consumption, and to analyse the future conditions in the RE24 Marketplace. Long Short-Term Memory (LSTM) technology is used to analyse the historical consumption/generation along with the weather data to get the future predictions as shown in the figure below. The Optimisation model provides these main features for the customers,

  • Customers will have dynamic forecasts on their future energy consumption.
  • Customers will have secured energy supply for their consumption at the optimum cost.
  • Customers will have an energy profile for every 30 minutes to stay ahead of regulation.

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