Smart Fuzzy Petri Net-Based Temperature Control Framework for Reducing Building Energy Consumption

Area of Science:

• Engineering
• Computer Science
• Energy Systems

Background:

• Growing energy demand in Saudi Arabia necessitates improved energy efficiency.
• Traditional temperature control systems struggle with non-linear, time-varying dynamics.
• Air conditioning systems are major energy consumers, requiring optimized control.

Purpose of the Study:

• To develop an intelligent energy-saving framework for air conditioning systems.
• To optimize energy utilization and maintain indoor comfort using advanced control.
• To address the limitations of traditional controllers in dynamic environments.

Main Methods:

• Proposed a fuzzy petri net (FPN) controller integrating fuzzy logic (FL) and petri nets (PN).
• Implemented user identification for temperature setting authorization.
• Utilized FL and PN to monitor settings and transmit them to a PID controller.
• Integrated the FPN controller with a convertible frequency air conditioning compressor.

Main Results:

• The FPN controller reduced energy consumption by 94% compared to using PN alone.
• The PN controller alone achieved a 25% reduction in energy consumption.
• Fixed-frequency compressors increased energy consumption by 40%.

Conclusions:

• Integrating FL with PN significantly enhances energy efficiency in AC systems.
• The FPN controller offers a promising solution for optimizing energy use and comfort.
• The proposed intelligent framework demonstrates substantial energy savings potential.