Supervisors
Dr Muhammad Erza Aminanto, Monash University Indonesia
Prof Taufiq Asyhar, Monash University,
The project
This research proposes a Multi-Agent Deep Reinforcement Learning (MADRL) framework to optimize interdependent consumer solar and utility BESS operations within Indonesia’s regulated market. It aims to design dynamic incentives that maximise consumer surplus and grid stability while respecting administrative pricing. The 3-year plan integrates ensemble forecasting and game theory to identify Pareto-efficient outcomes, validating results via case studies to support Indonesia’s Net Zero 2060 goal.
Status
- In Progress
Student
Expected Start Date
July 2026
Expected End Date
January 2030
Project Code
1146
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