A unified FLC-blockchain framework for optimized carbon credit trading in multi-microgrid systems

Area of Science:

• Sustainable Energy Systems
• Artificial Intelligence in Energy
• Blockchain Technology Applications

Background:

• Microgrids require optimized energy production and carbon credit trading for sustainable operations.
• Existing systems face challenges in efficiency, security, and adaptability under uncertainty.
• Decentralized energy trading and carbon markets are crucial for future smart grids.

Purpose of the Study:

• To propose a novel hybrid framework for carbon credit trading among microgrids.
• To integrate Interval Type-2 Fuzzy Logic Controllers (IT2-FLC) and blockchain technology.
• To enhance operational efficiency, security, and sustainability in microgrid operations.

Main Methods:

• A framework with three islanded microgrids utilizing IT2-FLCs for decision-making.
• Implementation of a continuous double auction mechanism for decentralized trading.
• Secure transaction settlement via blockchain smart contracts for tamper-proof record-keeping.

Main Results:

• The framework successfully maintains operational balance and reduces carbon emissions.
• IT2-FLCs demonstrated robust real-time control under uncertainty, enhancing adaptability.
• Simulation confirmed trustless, scalable coordination and transparent record-keeping across microgrids.

Conclusions:

• The study presents a significant advancement in integrating fuzzy logic control with blockchain for microgrid carbon credit trading.
• The proposed framework offers a resilient and scalable solution for real-time trading under uncertainty.
• This approach paves the way for future smart grid implementations focused on sustainability and efficiency.