An Iterative On-Line Mechanism for Demand-Side Aggregation

TL;DR

This paper introduces a novel auction-based mechanism, the staggered clock-proxy auction, for efficient demand-side energy aggregation of small loads, enabling effective inter-temporal bidding and online scheduling.

Contribution

The paper proposes the staggered clock-proxy auction (SCPA), a new two-phase online auction format that improves demand-side energy management for small loads.

Findings

SCPA enables effective inter-temporal bidding for electricity loads.

The proxy phase implements the VCG outcome under mild utility assumptions.

Simulation shows SCPA achieves efficient online energy scheduling.

Abstract

This paper considers a demand-side aggregation scheme specifically for large numbers of small loads, such as households and small and medium-sized businesses. We introduce a novel auction format, called a staggered clock-proxy auction (SCPA), for on-line scheduling of these loads. This is a two phase format, consisting of: a sequence of overlapping iterative ascending-price clock auctions, one for each time-slot over a finite decision horizon, and; a set of proxy auctions that begin at the termination of each individual clock auction, and which determine the final price and allocation for each time-slot. The overlapping design of the clock phases grant bidders the ability to effectively bid on inter-temporal bundles of electricity use, thereby focusing on the most relevant parts of the price-quantity space. Since electricity is a divisible good, the proxy auction uses demand-schedule bids, which the aggregator uses to compute a uniform-price partial competitive equilibrium for each time slot. We show that, under mild assumptions on the bidders' utilities functions, the proxy phase implements the Vickrey-Clarke-Groves outcome, which makes straightforward bidding in the proxy phase a Bayes-Nash equilibrium. Furthermore, we demonstrate the SCPA in a scenario comprised of household agents with three different utility function types, and show how the mechanism enables efficient on-line energy use scheduling.