In the dynamic world of renewable energy, hybrid power plants are emerging as the new superheroes, combining the strengths of multiple renewable sources and storage systems. But even superheroes face challenges, and for these hybrid power plants, reliability in providing balancing services is a significant hurdle. Enter Rujie Zhu, a researcher from the Technical University of Denmark (DTU), who has developed a novel model to optimize the operation of these plants, ensuring they can reliably deliver the energy we need when we need it.
Zhu’s research, published in the International Journal of Electrical Power & Energy Systems, focuses on utility-scale renewable hybrid power plants (HPPs). These plants combine various renewable generation technologies and storage systems, but often, the storage size is smaller than the renewable resources due to overplanting and co-location. This imbalance can make it challenging for HPPs to provide reliable balancing services, which are crucial for maintaining the stability of the power grid.
The model Zhu proposes is a robust two-level optimization approach. The first level focuses on hour-ahead offering and operation, while the second level handles generation re-scheduling. “The key innovation here is the way we handle uncertainties,” Zhu explains. “We consider uncertainties from wind power generation as decision-independent, but also account for decision-dependent uncertainties related to the activation of manual frequency restoration reserve (mFRR) energy.”
The mFRR market is a crucial part of the energy system, providing the flexibility needed to balance supply and demand in real-time. Zhu’s model ensures that HPPs can reliably deliver both upward and downward mFRR, meeting the transmission system operators’ required 90% reliability. In fact, the model shows that HPPs can deliver upward mFRR in 94% of the activated time and downward mFRR in 99% of the activated time.
So, what does this mean for the energy sector? Well, it’s a game-changer. As we transition to a more renewable-based energy system, the ability to reliably balance supply and demand becomes increasingly important. Zhu’s model provides a way to optimize the operation of HPPs, ensuring they can reliably provide the balancing services we need. This could lead to more widespread adoption of HPPs, helping to accelerate the transition to a more sustainable energy system.
But the implications don’t stop there. The model’s ability to handle both decision-independent and decision-dependent uncertainties could have broader applications in the energy sector. As Zhu puts it, “This approach could be applied to other areas where uncertainties play a significant role, such as in the integration of electric vehicles or the development of smart grids.”
The energy sector is on the cusp of a revolution, and research like Zhu’s is at the forefront of this change. By providing a way to optimize the operation of HPPs, Zhu’s model could help to shape the future of the energy sector, making it more reliable, more sustainable, and more resilient. As we look to the future, it’s clear that hybrid power plants, and the innovative models that optimize their operation, will play a crucial role in powering our world.