Integrating renewable energy sources into power systems introduces significant challenges due to their uncontrollable and non-dispatchable nature. Ineffective scheduling and management can lead to increased operational costs, power losses, and system blackouts.
This research explores advanced methods and tools for Power System Operators and Energy Regulators to assess risks and vulnerabilities associated with the intermittency of wind and solar photovoltaic (PV) generation. The study focuses on developing a cost-performance evaluation framework for optimal scheduling of a medium-sized isolated hybrid energy system incorporating PVs, wind generation, and battery energy storage systems.
A novel data-driven approach will be employed to support decision-making for energy system operations under renewable intermittency. This work will also involve a comprehensive analysis and comparison of various risk assessment techniques to identify effective strategies for reliable system management.
By investigating data-driven modeling methods and optimization strategies, this research aims to enhance decision-making, ensure operational efficiency, and improve system resiliency under uncertain conditions. The findings will provide valuable insights for energy planners and operators seeking to integrate renewable energy sources more effectively while maintaining reliable power supply and minimizing disruptions during high-impact, low-probability events.
Mehrdad Ghahramani
School of Engineering
Email: m.ghahramani@ecu.edu.au