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Applied Energy

The joint operation of multiple renewable energies has become a promising approach to promote the penetration of renewables into power systems, where multiple uncertainties are unavoidably involved. Uncertainties caused by emergencies can significantly affect power system operation. However, the traditional single operation trajectory, which only considers pre-scribed uncertainties, is not enough to cope with emergencies. This study aims to propose a robust operation interval to deal with uncertainties caused by emergencies. First, a multi-objective model is developed to derive the robust operation interval considering the economy (power generation), flexibility (robust operation interval width) as well as reliability (portion of feasible solutions). Second, a two-layered nested framework is used by coupling non-dominated sorting genetic algorithm II and discrete differential dynamic programming in a hierarchical structure to improve calculation efficiency. Finally, the stochastic simulations are used to validate the effectiveness of the robust operation interval. Results for a case study using China's Longyangxia hydro–photovoltaic power plant indicated that the proposed method could derive the robust operation interval effectively. The multi-objective optimization revealed that the interval's economy was in conflict with both the flexibility and reliability. The robust operation interval reduced 4.32% loss of annual power generation by adjusting 0.14% annual reservoir discharge compared with the pre-scribed trajectory in a plague emergency, and decreased 8.99% loss of quarterly power generation by adjusting 1.95% quarterly discharge in an earthquake emergency. The proposed robust operation interval effectively deals with uncertainties caused by emergencies.

Robust operation interval of a large-scale hydro-photovoltaic power system to cope with emergencies