Automated Linear Function Submission-based Double Auction as Bottom-up Real-Time Pricing in a Regional Prosumers' Electricity Network

TL;DR

This paper introduces a linear function submission-based double auction mechanism for regional prosumer electricity markets, enabling decentralized real-time pricing and efficient social welfare maximization without central price setters.

Contribution

It proposes the LFS-DA mechanism that achieves exact demand-supply balance and relates it to existing RTP algorithms based on dual decomposition.

Findings

LFS-DA achieves demand-supply balance in each time slot.

LFS-DA can maximize social welfare without a central utility.

Price changes in LFS-DA match those of RTP derived from dual decomposition.

Abstract

A linear function submission-based double-auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market.The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP). This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework except for a constant factor.