Digital Energy and Optimization


OBJECTIVES

At the end of this training course, you will learn to:

  • Apply the data mining methodology for energy usage patterns
  • Effectively utilize Artificial Intelligence algorithms for real-time optimization
  • Identify key areas where the Data Mining and Artificial Intelligence can be utilized
  • Understand the benefits through the example cases
  • Use Data Mining and Artificial Intelligence methods for optimization of spinning reserves

Outline

Data Mining and Pattern Recognition

  • Data Mining Process
  • Data Preparation
  • Association and Pattern Recognition
  • Data Mining in Energy Industry
  • Data Mining-clusters and Outliers

 

Artificial Intelligence Algorithms

  • Artificial Intelligence Development
  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • Support Vector Machine
  • Other Algorithms Applied in Artificial Intelligence (AI)

 

Energy Distribution Planning and Optimization

  • Energy Storage Planning
  • Managing Incidents and Instrument Failures
  • Energy Grid Management
  • Energy Consumption Forecasting

 

Developing Digital Twins

  • Digitization of Industry and Energy
  • Optimal Power Flow Problem Formulation
  • Neural Network Application to Optimal Power Flow
  • Particle Swarm Optimization for Optimal Power Flow
  • Total Transfer Capability Enhancement by Evolutionary Algorithm

 

Simulation, Machine Learning and Smart Contracts

  • Dynamic Simulation of Industry Systems
  • Simulation of Unit Commitment Problem
  • Machine Learning for Renewable Energy
  • Forecasting Renewable Energy Generation
  • Smart Contracts within the Energy Industry

المواعيد المتاحة