Comparative Double Auction Approach for Peer-to-Peer Energy Trading on Multiple microgrids

Area of Science:

• Energy Systems Engineering
• Distributed Energy Resources
• Smart Grids

Background:

• Peer-to-peer (P2P) energy trading facilitates renewable energy (RE) integration and loss reduction in distribution networks.
• Microgrids (MGs) offer a decentralized platform for P2P energy trading, optimizing local energy usage.
• Evaluating different auction mechanisms is crucial for enhancing P2P trading efficiency within MGs.

Purpose of the Study:

• To systematically evaluate the suitability of four double auction mechanisms (Average, McAfee, Trade Reduction, VCG) for P2P energy trading in various microgrid types.
• To analyze the impact of user preferences, bidding strategies, and time-of-use tariffs on P2P trading outcomes.
• To identify the most effective auction mechanisms for different microgrid configurations and trading scenarios.

Main Methods:

• Simulation of P2P energy trading across diverse microgrid (MG) types.
• Implementation of four distinct double auction mechanisms: Average, McAfee, Trade Reduction, and Vickrey-Clarke-Groves (VCG).
• Integration of user preferences, bidding strategies, and time-of-use tariffs into the trading algorithm.

Main Results:

• The Average and VCG auction mechanisms demonstrated the highest effectiveness across most MG setups.
• The Average mechanism proved optimal for consumer-centric MGs.
• The VCG mechanism was particularly advantageous for non-peak hour energy trading; however, MG-to-MG P2P trading showed inefficiency due to limited participants.

Conclusions:

• The Average and VCG mechanisms are recommended for optimizing P2P energy trading in microgrids, depending on the specific configuration and trading times.
• This research provides a framework for selecting appropriate auction mechanisms to enhance P2P energy trading efficiency and RE utilization.
• Further investigation into MG-to-MG P2P trading models may be required to address current inefficiencies.