On the Design of Stochastic Electricity Auctions

TL;DR

This paper proposes a new framework for designing stochastic electricity auctions that incorporate uncertainty in renewable energy production, improving efficiency and decision-making in power systems.

Contribution

It introduces a method to condition electricity contracts on the state of the world, defining and computing optimal partitions of possible states for better auction design.

Findings

Contracts conditioned on world states improve auction efficiency.

Optimal partitioning of states can be computed for practical applications.

Case study demonstrates the approach for offshore wind farms in Europe.

Abstract

Electricity is typically traded in day-ahead auctions because many power system decisions, such as unit commitment, must be made in advance. However, when wind and solar generators sell power one day ahead, they face uncertainty about their actual production. In current day-ahead auctions, this uncertainty cannot be directly communicated, leading to inefficient use of renewable energy and suboptimal system decisions. We show how this problem can be addressed using the concept of equilibrium under uncertainty from microeconomic theory. In particular, we demonstrate that electricity contracts should be conditioned not only on the time and location of delivery, but also on the state of the world (e.g., whether it will be windy or calm). This requires a precise definition of the state of the world. Since there are infinitely many possible definitions, criteria are needed to select among them. We develop such criteria and show that the resulting states correspond to solutions of an optimal partitioning problem. Finally, we illustrate how these states can be computed and interpreted using a case study of offshore wind farms in the European North Sea.