A Center-Point Algorithm for Unit Commitment with Carbon Emission Trading

TL;DR

This paper introduces a novel center-point algorithm that efficiently solves large-scale unit commitment problems with carbon emission trading, outperforming traditional solvers like CPLEX in solution quality and speed.

Contribution

The paper presents a new global optimization method combining linear relaxations and center-cut techniques specifically for UC problems with CET, improving solution quality and scalability.

Findings

Outperforms CPLEX in solution quality and speed

Effective on large-scale UC instances with up to 1560 units

Suitable for real-world large-scale UC with emission trading

Abstract

This paper proposes a global optimization method for it ensures finding good solutions while solving the unit commitment (UC) problem with carbon emission trading (CET). This method con-sists of two parts. In the first part, a sequence of linear inte-ger-relaxed subproblems are first solved to rapidly generate a tight linear relaxation of the original mixed integer nonlinear pro-gramming problem (MINLP) model. In the second part, the algo-rithm introduces the idea of center-cut so that it can quickly find good solutions. The approach tested on 10 test instances with units ranging from 35 to 1560 over a scheduling period of 24h, and compared with state-of-the-art solver CPLEX. The results show that the proposed algorithm can find better solutions than CPLEX in a short time. And it is more suitable to solve large scale UC problem than CPLEX.