Optimisation and Comprehensive Evaluation of Alternative Energising Paths for Power System Restoration

TL;DR

This paper develops an optimization and evaluation framework for alternative energising paths in power system restoration, enhancing safety and efficiency after blackouts through novel algorithms and comprehensive assessment methods.

Contribution

It introduces a new iterative search method for multiple energising schemes using mixed integer linear programming and a grey relational evaluation for comprehensive comparison.

Findings

Effective in identifying multiple minimal reactive power schemes

Demonstrated on New England and Chinese power systems

Provides decision support for power system restoration

Abstract

Power system restoration after a major blackout is a complex process, in which selection of energising paths is a key issue to realize unit and load restoration safely and efficiently. In general, the energising path scheme made beforehand may not be executed successfully due to the possible faults on the related lines under the extreme system condition, so it is necessary to provide alternative path schemes for system restoration. In view of this, the energising path optimisation based on the minimum cost flow model is investigated, then an iterative searching method for alternative path schemes based on mixed integer linear programming is proposed. The iterative method for alternative path schemes could determine more than one scheme with minimal charging reactive power efficiently. In order to make a comprehensive evaluation of the alternative schemes, an evaluation index set is established, and the method based on similarity to ideal grey relational projection is introduced to achieve the final evaluation. The New England 10-unit 39-bus system and the southern Hebei power system of China are employed to demonstrate the effectiveness of the proposed method. The proposed method can provide more efficient and comprehensive decision support for the dispatchers to select reasonable energising paths.