A New Approach to Electricity Market Clearing With Uniform Purchase Price and Curtailable Block Orders

TL;DR

This paper introduces an exact, non-heuristic method to solve the complex European electricity market clearing problem involving uniform purchase price and curtailable block orders, using a mixed-integer linear programming approach.

Contribution

It presents a novel non-iterative, exact solution method that transforms a complex non-linear bilevel problem into a mixed-integer linear program for market clearing.

Findings

The approach effectively solves real market data instances.

The method avoids iterative heuristics, ensuring exact solutions.

Implementation in Python is publicly available.

Abstract

The European market clearing problem is characterized by a set of heterogeneous orders and rules that force the implementation of heuristic and iterative solving methods. In particular, curtailable block orders and the uniform purchase price (UPP) pose serious difficulties. A block is an order that spans over multiple hours, and can be either fully accepted or fully rejected. The UPP prescribes that all consumers pay a common price, i.e., the UPP, in all the zones, while producers receive zonal prices, which can differ from one zone to another. The market clearing problem in the presence of both the UPP and block orders is a major open issue in the European context. The UPP scheme leads to a non-linear optimization problem involving both primal and dual variables, whereas block orders introduce multi-temporal constraints and binary variables into the problem. As a consequence, the market clearing problem in the presence of both blocks and the UPP can be regarded as a non-linear integer programming problem involving both primal and dual variables with complementary and multi-temporal constraints. The aim of this paper is to present a non-iterative and heuristic-free approach for solving the market clearing problem in the presence of both curtailable block orders and the UPP. The solution is exact, with no approximation up to the level of resolution of current market data. By resorting to an equivalent UPP formulation, the proposed approach results in a mixed-integer linear program, which is built starting from a non-linear integer bilevel programming problem. Numerical results using real market data are reported to show the effectiveness of the proposed approach. The model has been implemented in Python, and the code is freely available on a public repository.