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Case Study

  • Writer: Melchior Krijgsman
    Melchior Krijgsman
  • Jun 30
  • 2 min read

Updated: Jul 4

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About the client

โ€œ๐˜ž๐˜ฆ ๐˜ข๐˜ณ๐˜ฆ ๐˜ช๐˜ฎ๐˜ฑ๐˜ณ๐˜ฆ๐˜ด๐˜ด๐˜ฆ๐˜ฅ ๐˜ธ๐˜ช๐˜ต๐˜ฉ ๐˜Œ๐˜ฏ๐˜ต๐˜ณ๐˜ฐ๐˜ฑ๐˜ช๐˜คโ€™๐˜ด ๐˜ข๐˜ฃ๐˜ช๐˜ญ๐˜ช๐˜ต๐˜บ ๐˜ต๐˜ฐ ๐˜ฆ๐˜ฏ๐˜จ๐˜ช๐˜ฏ๐˜ฆ๐˜ฆ๐˜ณ ๐˜ช๐˜ฏ๐˜ฏ๐˜ฐ๐˜ท๐˜ข๐˜ต๐˜ช๐˜ท๐˜ฆ ๐˜ด๐˜ฐ๐˜ญ๐˜ถ๐˜ต๐˜ช๐˜ฐ๐˜ฏ๐˜ด.โ€ Climax Molybdenum


Climax Molybdenum Company, a subsidiary of Freeport-McMoRan, is the world leading molybdenum producer and supplier. For their plant in the Port of Rotterdam, they wanted to research the possibility of increasing the energy efficiency and reducing CO2 emissions.


About the project

The challenge at Climax Molybdenum is to optimize the factoryโ€™s energy efficiency by effectively utilizing available waste heat within its complex heat management system. The factory operates a mix of batch and continuous processes that generate and consume heat, subject to constant fluctuations. These processes involve 25 identified heat and cold sources/sinks, some of which pose difficulties due to factors such as corrosiveness and low temperatures. The goal is to maximize energy savings by integrating heat recovery and

utilization technologies, such as direct heat recovery, heat pumps, mechanical vapor recompression, organic Rankine cycle, steam turbines, and heat storage (molten salt, water, and steam), within the existing infrastructure.



Method

Entropic employed an iterative approach to develop a heat optimization model, using a digital twin of the factoryโ€™s 25 heat and cold sources/sinks. The compact methodology

includes:


1. Data Collection: Gathered design requirements, reviewed prior studies, and

collected measurement data.

2. Data Preparation: Mapped heat sources/sinks, including challenging streams, and

cleaned data for accuracy.

3. Basic Heat Flow Model: Defined source properties, designed initial heat network

layout, conducted pinch analysis, and iterated for optimization.

4. Intermediate Heat Flow Model: Integrated dynamic loads and time-series data,

simulating operational scenarios.

5. Advanced Heat Flow Model: Built dynamic equipment models and simulated

technologies in the digital twin.


This iterative process, with regular factory feedback, ensured quality, adaptability, and tangible results, addressing technical challenges and maximizing energy savings.



Results

The study identified significant opportunities to reduce energy costs and enhance efficiency at the facility through targeted optimizations in two key systems:


System 1

โ— Short-Term Opportunity: Integrating heat provides the quickest and most

substantial cost savings.

โ—‹ Savings: 294.609 mยณ of gas.

โ—‹ Carbon Emissions Reduction: 886 tons of COโ‚‚.

โ— Long-Term Potential: Incorporating heat pump technology offers additional savings:

โ—‹ Savings: 237.501 mยณ of gas.

โ—‹ Carbon Emissions Reduction: 714 tons of COโ‚‚.


System 2

โ— Short-Term Opportunity: Optimizing a drying process using simple heat

exchangers and non-corrosive fluids.

โ—‹ Savings: 166.343 mยณ of gas.

โ—‹ Carbon Emissions Reduction: 296 tons of COโ‚‚.


By implementing these short- and long-term strategies, the facility can achieve substantial energy and cost savings, improve energy efficiency, and significantly reduce carbon.


โ€œWe were impressed with Entropicโ€™s ability to scope innovative solutions at a conceptual levelโ€

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