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Keep shoppingIndustrial Energy Systems Optimization with Python & GAMS
809 students
Industrial Energy Systems Optimization with Python & GAMS
Build real-world optimization models for integrated industrial systems: furnaces, chillers, transformers, batteries, CHP
Created byAlgorithmic Economist, PhD
Last updated 6/2026
English
What you'll learn
- Model and optimize industrial energy systems using both Python (Pyomo) and GAMS
- Build optimization models for furnaces, chillers, transformers, batteries, CHP units, and electric heat pumps
- Progress from simple furnace-chiller systems to complex integrated multi-technology configurations
- Implement forward contracts and demand management in optimization models
- Handle real-world constraints: electricity demand, heating/cooling loads, and operational limits
- Compare Python and GAMS implementations for the same optimization problems
- Minimize operational costs while meeting industrial facility energy demands
- Apply optimization to real industrial scenarios with actual equipment parameters and energy prices
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Course content
8 sections • 27 lectures • 2h 28m total length
Requirements
- Basic Python programming helpful but beginners welcome
- No prior GAMS experience required
- Just need a computer and motivation to learn industrial optimization
Description
WHO I AM: I hold a PhD in Quantitative Economics and Energy from Imperial College London. I teach practical, real-world data science specifically for the energy sector.
REGULAR ENHANCEMENTS: This course is reviewed periodically with updates to reflect the modern energy market.
STUDENT BONUS: Note: Students who enroll in this course will receive access to the Energy Data Scientist community.
What You'll Learn:
How to build mathematical optimization models for industrial energy systems from scratch using Python (Pyomo) and GAMS
How to model and optimize key industrial components: natural gas furnaces, chillers, transformers, batteries, CHP units, and electric heat pumps
How to integrate multiple energy technologies into complex, multi-stage optimization problems
How to handle real-world constraints including forward contracts, energy demand patterns, and operational limits
How to solve industrial scheduling and dispatch problems to minimize costs while meeting heating/cooling demands
How to transition seamlessly between Python and GAMS implementations for the same optimization problem
How to interpret optimization results and make data-driven decisions for industrial energy management
Perfect For:
Industrial engineers and energy system analysts
Operations research professionals in manufacturing and utilities
Energy consultants and sustainability managers
Process engineers in chemical plants and manufacturing facilities
Data scientists working in energy and industrial sectors
Graduate students in operations research, industrial engineering, or energy systems
Energy managers seeking to optimize facility operations
Technical professionals transitioning to energy optimization roles
Why This Matters:
Industrial facilities account for 30% of global energy consumption, and optimizing their energy systems can reduce costs by 15-40% while cutting emissions dramatically. As industries face carbon regulations, volatile energy prices, and sustainability targets, the ability to model and optimize complex energy systems becomes mission-critical. Companies need professionals who can build optimization models that integrate renewable energy, storage, and traditional systems while managing real-time pricing and demand fluctuations. This skill set is essential for the $2 trillion industrial decarbonization market. Whether you're optimizing a single manufacturing plant or designing district energy systems, these modeling skills position you for high-impact roles in energy consulting ($120,000-180,000), industrial optimization ($130,000-200,000), and sustainability leadership ($150,000-250,000+). Master the tools that Fortune 500 companies use to save millions in energy costs annually.
Who this course is for:
- Industrial Engineers optimizing manufacturing plant energy systems and utility costs
- Energy System Analysts designing integrated heating, cooling, and power solutions
- Facility Managers reducing operational costs through optimal equipment scheduling
- Sustainability Consultants implementing decarbonization strategies for industrial clients
- Process Engineers in chemical plants and manufacturing facilities
- Graduate Students & Researchers in industrial engineering, energy systems, or operations research
- Energy Consultants advising on CHP, battery storage, and heat pump installations
- Utility Professionals planning distributed energy resources and demand response programs
- Anyone working with industrial energy systems requiring optimization skills