Abstract

The global transition to a renewable-powered economy is gaining momentum as renewable energy becomes more cost-effective and energy-efficient. Renewable-energy-integrated Virtual Power Plants (VPPs) are capable of facilitating renewable transition, reducing distributed generator impacts, and creating value for prosumers and communities by producing renewable energy, engaging in the electricity market, and providing electricity network functions. In this paper, we conducted a case study in the City of Greater Bendigo to evaluate the challenges and opportunities of the community-focused renewable energy transition through establishing VPP with community-based renewable generators and storage systems. A reinforcement learning algorithm was formulated to optimise the energy supply, load shifting, and market trading in the VPP system. The proposed VPP system has great potential to improve the economic value and carbon emission reduction performance of local renewable resources: it can reduce 50–70% of the case study city’s carbon emissions in 10 years and lower the electricity price from the current range of 0.15 AUD/kWh (off-peak) −0.30 AUD/kWh (peak) as provided by Victorian Essential Services Committee to 0.05 AUD/kWh (off-peak) (peak). Overall, this study proposed a comprehensive framework to investigate community-based VPP in a complex urban environment and validated the capability of the VPP in supporting the renewable transition for Australian communities.

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