Bidding in Smart Grid PDAs: Theory, Analysis and Strategy (Extended Version)

TL;DR

This paper analyzes bidding strategies in smart grid PDAs, deriving equilibrium insights, proposing a novel strategy, and demonstrating its superior performance in the PowerTAC market benchmark.

Contribution

It introduces a new bidding strategy, MDPLCPBS, based on equilibrium analysis and MDP modeling, improving performance over existing strategies in smart grid PDAs.

Findings

MDPLCPBS follows equilibrium strategies in double auctions.

MDPLCPBS outperforms baseline and state-of-the-art strategies.

The analysis highlights the complexity of multi-agent auction environments.

Abstract

Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in order to balance net demand in smart grids, involving trillions of dollars in the process. A bidder, participating in such PDAs, has to plan for bids in the current auction as well as for the future auctions, which highlights the necessity of good bidding strategies. In this paper, we perform an equilibrium analysis of single unit single-shot double auctions with a certain clearing price and payment rule, which we refer to as ACPR, and find it intractable to analyze as number of participating agents increase. We further derive the best response for a bidder with complete information in a single-shot double auction with ACPR. Leveraging the theory developed for single-shot double auction and taking the PowerTAC wholesale market PDA as our testbed, we proceed by modeling the PDA of PowerTAC as an MDP. We propose a novel bidding strategy, namely MDPLCPBS. We empirically show that MDPLCPBS follows the equilibrium strategy for double auctions that we previously analyze. In addition, we benchmark our strategy against the baseline and the state-of-the-art bidding strategies for the PowerTAC wholesale market PDAs, and show that MDPLCPBS outperforms most of them consistently.