Energy

Utilities and Energy

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

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.

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 resource planning (ERP) 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.

Chemicals and Petrochemicals

Process engineers use MATLAB^® and Simulink^® to analyze real-time sensor data, implement control strategies, and create predictive maintenance systems based on big data and machine learning.

MATLAB and Simulink help process engineers:

Develop predictive maintenance systems by applying numerical techniques on high-speed sensor data
Use machine learning with historical data to troubleshoot process problems
Use data modeling to improve process performance
Develop and implement advanced predictive control (APC) strategies
Adopt digitization without depending on data scientists or IT personnel

Optimize Assets with Predictive Maintenance and Signal Processing

MATLAB can help you develop predictive maintenance algorithms customized to the specific operational and architectural profile of your equipment. MATLAB lets you develop predictive maintenance algorithms customized to the specific operational and architectural profile of your equipment. Use Predictive Maintenance Toolbox™ to design condition indicators and estimate the remaining useful life of your rotary equipment.

You can use Signal Processing Toolbox to automate the monitoring of performance of your control loops, remotely determine the extent of corrosion or pitting in your pipelines, and detect the location and quantity of pipeline leaks.

Process Improvement with Data Modeling

Use multivariate analysis tools in MATLAB to determine the independent driving variables affecting process performance.

System Identification Toolbox™ lets you create and use models of dynamic systems that are not easily modeled from first principles or specifications. The toolbox also lets you interactively perform online parameter and state estimation.

Oil and Gas

Geoscientists and engineers in the oil and gas industries choose MATLAB^® and Simulink^® products to:

Model and optimize drilling equipment
Analyze seismic data to determine optimal drilling locations
Run Monte-Carlo simulations for valuation and risk assessment
Model reservoirs to extend the life of oil and gas reserves
Scale their analytics to GPU clusters and the cloud

Geoscience, 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 also develop stratigraphic characterization algorithms.

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.

Save time on tedious seismic interpretation activities like picking complex salt bodies by using deep learning for seismic feature detection and arrival picking.