Deriving operating rules for a large-scale hydro-photovoltaic power system using implicit stochastic optimization

Complementary operation is a new effective way to simultaneously manage hydropower and photovoltaic (PV) power. With the integration of a PV power into an existing hydropower reservoir system, the original operating rules need to be re-designed to improve operational performance. This study focuses on exploring long-term operating rules for such an integrated system using implicit stochastic optimization, which can address uncertainties in reservoir inflow and PV power. First, a long-term multi-objective optimization model for this system is established by maximizing the total energy production and assurance rate (i.e., reliability) simultaneously. The model is then solved using a dynamic programming technique. Operating rules are derived from the obtained optimal trajectory using a linear fitting method. Finally, a simulation-based optimization framework is used to refine the parameters of these rules. Our case study based on China's Longyangxia hybrid power system shows that: (1) a significant linear correlation between available energy and reservoir storage at the end of each time period, with fitting correlation coefficients above 0.9 for each month. Therefore, the available energy and reservoir storage at the end of each time period are selected, respectively, as independent variables and decision variables in the operating rules; (2) an improved average annual energy production and assurance rate are obtained for the hybrid system when considering complementary operations; and (3) the derived operating rules are effective in improving system benefits when compared with conventional operation. These findings are helpful to offer guidelines for the effective operation of the hydro/PV hybrid power system.