Utilities and Energy


MATLAB and Simulink for the Utilities and Energy Industry

Design, simulate, and deploy tomorrow’s utility and energy infrastructure

Scientists and engineers in utilities and energy organizations use MATLAB and Simulink for system analysis and design, performance monitoring, optimizing maintenance and business processes, and compliance.

With MATLAB and Simulink, you can:

  • Perform system feasibility and grid integration studies using prebuilt functions and apps
  • Acquire and analyze large data sets in real time
  • Develop optimization algorithms using machine learning and deep learning techniques
  • Develop energy trading and risk management (ETRM) solutions
  • Deploy developed code directly to real-time and embedded systems

“My team’s expertise is in energy modeling or algorithm development, not in deploying software into production. MATLAB saved us months of development time on the models and algorithms, and then made it easy to deploy them as part of a stable, reliable web application without recoding.”

Yunjiao Gu, Shanghai Electric
Image Processing and Deep Learning

Image Processing and Deep Learning

Use MATLAB for geoscience applications like image processing in remote sensing, generation, and processing of digital elevation models. You can import a wide range of GIS and geospatial file formats, and use hundreds of inbuilt functions for signal processing, image analysis, and curve fitting. Applications include overhead/UG T&D network inspection, vegetation management, and fault identification.

Renewables and DER Integration Studies

Evaluate the performance of a system that has high penetration of distributed energy resources (DER) such as renewables, storage, and EVs with Simscape Electrical. Model and run multiple operational scenarios in parallel and assess simulated responses against grid code.

Renewables and DER Integration Studies

Energy Trading and Risk Management (ETRM)

Energy Trading and Risk Management (ETRM)

With MATLAB, you can simplify and automate your energy trading and risk management (ETRM) tasks like importing and visualizing energy data from multiple sources; developing predictive demand, price, and revenue forecasting models using machine learning; and running Monte Carlo simulations for valuation and risk assessment. Deploy your forecast models to enterprise and cloud systems, and connect them to regional wholesale electricity markets, meteorological data, and other data streaming services. The MATLAB API allows you to pick the best language or platform for each part of your workflow. You can call MATLAB algorithms from other programs like Python® and Excel®, and deploy these models on enterprise systems like Power BI, Cloudera®, and Hadoop®.

Energy Management Systems (EMS)

Grid modernization has rapidly increased power system complexity with variable generation assets, such as wind and solar, and added new controllable systems, such as energy storage and grid-scale batteries. Use Model-Based Design to develop energy management systems (EMS) that combine prediction, forecasting, and optimization techniques. Use MATLAB and Simulink to build data-driven and physics-based models; model and simulate equipment performance; design algorithms to optimally control equipment; and deploy algorithms onto embedded and enterprise systems.

Energy Management Systems

Digital Twins in Model-Based Systems

Digital Twins in Model-Based Systems

Use MATLAB and Simulink to create digital replicas or digital image (DI) of your physical assets and systems. Use it to perform predictive maintenance, optimize operations, perform electrical, hydraulic system simulation, and model cyber-physical systems.