Moving from Linear to Conic Markets for Electricity

TL;DR

This paper introduces a conic market framework for electricity trading that captures nonlinearities and uncertainties more accurately than traditional linear models, improving market efficiency and reliability.

Contribution

It develops a conic market model with second-order cone constraints, providing a more realistic and effective approach for integrating renewable energy sources into electricity markets.

Findings

Conic market framework captures nonlinear cost and constraint features.

Proves market efficiency, cost recovery, and revenue adequacy are maintained.

Numerical results show advantages over linear models in uncertainty management.

Abstract

We propose a new forward electricity market framework that admits heterogeneous market participants with second-order cone strategy sets, who accurately express the nonlinearities in their costs and constraints through conic bids, and a network operator facing conic operational constraints. In contrast to the prevalent linear-programming-based electricity markets, we highlight how the inclusion of second-order cone constraints improves uncertainty-, asset- and network-awareness of the market, which is key to the successful transition towards an electricity system based on weather-dependent renewable energy sources. We analyze our general market-clearing proposal using conic duality theory to derive efficient spatially-differentiated prices for the multiple commodities, comprising of energy and flexibility services. Under the assumption of perfect competition, we prove the equivalence of the centrally-solved market-clearing optimization problem to a competitive spatial price equilibrium involving a set of rational and self-interested participants and a price setter. Finally, under common assumptions, we prove that moving towards conic markets does not incur the loss of desirable economic properties of markets, namely market efficiency, cost recovery and revenue adequacy. Our numerical studies focus on the specific use case of uncertainty-aware market design and demonstrate that the proposed conic market brings advantages over existing alternatives within the linear programming market framework.