Multiobjective optimization for hydro-photovoltaic hybrid power system considering both energy generation and energy consumption

Hydropower can be an ideal compensation for fluctuant photovoltaic (PV) power due to its flexibility. In this study, a multiobjective optimization model considering energy generation and consumption simultaneously for a hydro-PV hybrid power system is proposed. With the daily mean radiation intensity and temperature, the PV power output is calculated. Taking reservoir release as the decision variable, the total energy generation of the hydro-PV system is maximized. Meanwhile, the gap between the energy generation and the energy consumption is minimized to reduce the abandoned PV power or hydropower. The proposed multiobjective model is optimized by Non-dominated Sorting Genetic Algorithms-II (NSGA-II). The Longyangxia Project, the largest hydro-photovoltaic hybrid power system in the world is taken as the study case to estimate the optimal operational strategies for different objectives in wet year, normal year, and dry year, respectively. The optimal operation process of the reservoir is presented, which is instructive for the operation in the future.