A Time Decomposition and Coordination Strategy for Power System Multi-Interval Operation

TL;DR

This paper introduces a time decomposition and distributed coordination method to efficiently solve multi-interval economic dispatch problems in power systems, significantly reducing computational complexity and improving convergence.

Contribution

It proposes a novel time decomposition strategy combined with a distributed coordination algorithm for multi-interval economic dispatch, enhancing efficiency and convergence speed.

Findings

Effective reduction in computational complexity.

Fast convergence with the initializing technique.

Successful application to IEEE 118-bus system.

Abstract

This paper presents a time decomposition strategy to reduce the computational complexity of power system multi-interval operation problems. We focus on the economic dispatch problem. The considered scheduling horizon is decomposed into multiple smaller sub-horizons. The first time interval of each sub-horizon is modeled as the coupling interval between two consecutive sub-horizons. The interdependencies between the sub-horizons are mathematically modeled using ramp rates of generating units. A distributed coordination strategy, which is based on auxiliary problem principle, is developed to coordinate the economic dispatch solutions of the sub-horizons to find an optimal solution for the whole operation horizon. We also propose an initializing technique to start the iterative coordination algorithm from a good-enough point. This technique enhances the convergence rate significantly. The proposed algorithm is deployed to solve a week-ahead economic dispatch problem on the IEEE 118-bus system, and promising results are obtained.