Multi-Agent Deep Reinforcement Learning for Solar-Battery System to Mitigate Solar Curtailment in Real-Time Electricity Market (Papers Track)

Jinhao Li (Monash University); Changlong Wang (Monash University); Hao Wang (Monash University)

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Power & Energy Reinforcement Learning


The increased uptake of solar energy in the energy transition towards decarbonization has caused the issue of solar photovoltaic (PV) curtailments, resulting in significant economic losses and hindering the energy transition. To overcome this issue, battery energy storage systems (BESS) can serve as onsite backup sources for solar farms. However, the backup role of the BESS significantly limits its economic value, disincentivizing the BESS deployment due to high investment costs. Hence, it is essential to effectively reduce solar curtailment while ensuring viable operations of the BESS.