A Multi-Criteria Analytic Hierarchy Process-Based Decision Support Framework for Managing Nonessential Loads to Enhance Substation Resilience Considering Hybrid Renewable Energy Systems

Abstract

The continuous energy supply to critical loads is vital for the resilience of essential infrastructures. The increasing frequency of extreme weather events increases concerns about electrical system reliability, making uninterrupted operation crucial for public safety, health, and economic stability. In this context, hybrid renewable energy systems (HRESs) emerge as a reliable and environmentally solution for backup systems, enabling extended service during main grid contingencies. This paper proposes a multi-criteria Analytic Hierarchy Process (AHP)-based decision support framework for managing non-essential loads in substations during power outages. The method facilitates intelligent decision-making by considering the dynamic availability of HRES resources, which integrate wind and solar power, battery energy storage, and electric vehicles, alongside the critical load. This approach defines three distinct operational modes for nonessential loads, enabling autonomous consumption adjustment and ensuring uninterrupted power supply to essential loads. The tests and simulations confirm the framework's effectiveness in capturing variations in renewable generation and storage system state of charge, optimizing available energy utilization. Results demonstrate the proposed framework's significant potential to support the substation's operational resilience and ensure critical load supply continuity, promoting more effective energy management and increasing system availability during power outages.