Abstract

The aggregation of operational active and reactive power flexibilities as the feasible operation region (FOR) is a main component of a hierarchical multi-voltage-level grid control as well as the cooperation of transmission and distribution system operators at vertical system interconnections. This article presents a new optimization-based aggregation approach, based on a modified particle swarm optimization (PSO) and compares it to non-linear and linear programming. The approach is to combine the advantages of stochastic and optimization-based methods to achieve an appropriate aggregation of flexibilities while obtaining additional meta information during the iterative solution process. The general principles for sampling an FOR are introduced in a survey of aggregation methods from the literature and the adaptation of the classic optimal power flow problem. The investigations are based on simulations of the Cigré medium voltage test system and are divided into three parts. The improvement of the classic PSO algorithm regarding the determination of the FOR are presented. The most suitable of four sampling strategies from the literature is identified and selected for the comparison of the optimization methods. The analysis of the results reveals a better performance of the modified PSO in sampling the FOR compared to the other optimization methods.

Highlights

  • This article provides a survey on state-of-the-art aggregation methods for the determination of a feasible operation region (FOR) at the vertical system interfaces

  • These are non-linear programming, sequential quadratically constrained linear programming and a newly developed, modified particle swarm optimization (PSO)

  • Before the comparison of the optimization methods four sampling strategies are compared for the non-linear programming

Read more

Summary

Introduction

Measures like grid expansions or the integration of new flexibilities at the transmission grid (e.g., synchronous condenser) are expensive. To avoid this, another option is the coordinated interaction of TSO and distribution system operators (DSO) [1]. Another option is the coordinated interaction of TSO and distribution system operators (DSO) [1] This TSO/DSO cooperation is enabled by an advanced monitoring of the current grid states and the control of distributed flexibilities (e.g., reactive power supply of wind turbines, load management) through the continuous integration of information- and communication technology (ICT) [2]. Flexibilities that are located at the distribution system can potentially be used for the operational management of the TSO [3]

Methods
Discussion
Conclusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.