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Comparative Double Auction Approach for Peer-to-Peer Energy Trading on Multiple microgrids
Sweta Malik1, Subhasis Thakur1, Maeve Duffy2
1Insight Centre for Data Analytics, University of Galway, Galway, Ireland.
Abstract:
Peer-to-peer (P2P) energy trading is one of the most effective methods to increase the usage of Renewable Energy (RE) resources in the distribution network and reduce losses by eliminating long transmission and distribution lines. This research aims to enhance the efficiency of P2P energy trading by examining the suitability of four distinct double auction mechanisms: Average, McAfee, Trade Reduction and Vickrey-Clarke-Groves (VCG). We conducted a systematic evaluation of these mechanisms across various microgrid (MG) types. The study algorithm integrates user preferences, bidding strategies and time-of-use tariffs, allowing participants to indicate their willingness to pay for different energy qualities and specific time periods. Notably, both the Average and VCG mechanisms emerged as the most effective across a majority of MG setups. Specifically, the average mechanism was found to be optimal for a consumer-centric MG, while the VCG mechanism was predominantly advantageous during non-peak hours trading. However, it was observed that P2P energy trading from MG to MG was inefficient due to the lesser number of peers. In conclusion, this work offers a comprehensive solution that adeptly identifies and recommends the most fitting auction mechanisms for diverse MG configurations and usage timings, paving the way for more efficient P2P energy trading.
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