Model Predictive Control Of Fuel Cell Micro Cogeneration Systems.pdf

09_016.pdf
Preview of Model Predictive Control of Fuel Cell Micro Cogeneration Systems
🔗 Source: dcsc.tudelft.nl
📊 Size: 327 KB
📄 Pages: 7 pages
⬇️ Downloads: 53

Summary

## Model Predictive Control of Fuel Cell Micro Cogeneration Systems: Key Takeaways

This technical report from Delft University of Technology presents a detailed model and decentralized control strategy for household fuel cell micro cogeneration systems (micro-CHP). The focus is on intelligent demand response using model predictive control (MPC), aiming to optimize system performance under varying energy pricing and demand conditions.

Key Points:

Micro-CHP Potential: Micro-CHP, powered by fuel cells, offers significant energy cost savings (10-20%) for households in regions with substantial heat demand and established gas infrastructure. It contributes to sustainability through reduced carbon emissions and reliance on renewable energy sources.

Intelligent Control (MPC): The report highlights the potential of MPC to improve micro-CHP performance by leveraging future knowledge about electricity prices and household energy demands. This allows for more efficient generation scheduling and cost optimization.

Modeling: A comprehensive model is developed for a household system incorporating:
Fuel cell micro-CHP unit (PEMFC)
Heat storage options
Variable electricity and heat demand

Simulation Results: The MPC-controlled PEMFC system demonstrates improved performance compared to traditional thermal-led control under various scenarios:

Electricity Pricing: Beneficial MPC performance is observed with time-varying prices, especially when prices are lower during periods of high heat demand.
Domestic Energy Demand: Accurate forecasting and scheduling of energy use lead to optimal system operation.
System Configuration: Different system configurations (e.g., varying heat storage capacity) are analyzed, showing the flexibility of MPC in adapting to diverse conditions.

* Business & Policy Implications: The report suggests that intelligent control could open new business opportunities for households and energy companies through dynamic pricing and shared cost savings. Governments might also incentivize real-time pricing to encourage MPC adoption.

Description

This technical report from Delft University of Technology's Center for Systems and Control presents a model predictive control approach for fuel cell micro cogeneration systems, published in the 2009 IEEE International Conference on Networking, Sensing and Control.

Technical Information

  • File Format: PDF
  • File Size: 327 KB
  • Pages: 7
  • Language: EN
  • Total Downloads: 53
  • Last Updated: 2 hours ago

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