Enhanced Distributed Self-Healing System for Electrical Distribution Networks Using ADMM

Author(s)

Lopez, Juan CamiIo ; Gcrards, Marco E. T. ; Hurink, Johann L. ; Rider, Marcos J.

• Document type: Journal article
• Source: 2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM; v. N/A, p. 5-pg., 2023-01-01.

Abstract

Unlike centralized versions, a distributed self-healing system (SHS) for electrical distributed systems is less vulnerable to single-point failures (or attacks), requires less information from the agents, and is more scalable. However, optimality is challenging to achieve because binary variables are used in the modelling of the distributed service restoration problem. To deal with this challenge, this paper proposes an enhanced alternating direction method of multipliers (ADMM)-based algorithm used to developed a fully distributed SHS in electrical distribution networks. Hereby, three ADMM-based heuristics are executed in parallel to improve the chances of obtaining a feasible solution. However, if none of the heuristics converge within given reasonable time, the proposed distributed SHS uses a basic restoration plan that is feasible in terms of topology and operational constraints. Results using the IEEE 123-node system show that the proposed distributed SHS is reliable and it always provides a feasible solution. (AU)

• FAPESP's process: 21/11380-5 - CPTEn - São Paulo Center for the Study of Energy Transition
• Grantee: Luiz Carlos Pereira da Silva
• Support Opportunities: Research Grants - Science Centers for Development
• FAPESP's process: 19/01906-0 - Optimal distributed restoration of electrical distribution systems using alternating direction method of multipliers
• Grantee: Juan Camilo Lopez Amezquita
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 21/11310-7 - Application of heuristic techniques to deal with binary variables in optimal distributed restoration
• Grantee: Juan Camilo Lopez Amezquita
• Support Opportunities: Scholarships abroad - Research Internship - Post-doctor