Multi-unit Double Auctions: Equilibrium Analysis and Bidding Strategy using DDPG in Smart-grids

Sanjay Chandlekar (International Institute of Information Technology, Hyderabad), Easwar Subramanian (TCS Innovation Labs), Sanjay Bhat (TCS Innovation Labs), Praveen Paruchuri (International Institute of Information Technology, Hyderabad), Sujit Gujar (International Institute of Information Technology, Hyderabad)

Abstract

We present a Nash equilibrium analysis for single-buyer singleseller multi-unit 𝑘-double auctions for scaling-based bidding strategies. We then design a Deep Deterministic Policy Gradient (DDPG) based learning strategy, DDPGBBS, for a participating agent to suggest bids that approximately achieve the above Nash equilibrium. We expand DDPGBBS to be helpful in more complex settings with multiple buyers/sellers trading multiple units in a Periodic Double Auction (PDA), such as the wholesale market in smart-grids. We demonstrate the efficacy of DDPGBBS with Power Trading Agent Competition's (PowerTAC) wholesale market PDA as a testbed.