Evaluation of stochastic optimal operation models for hydro–photovoltaic hybrid generation systems

Hybrid generation of hydropower and large-scale solar photovoltaic (PV) power has become an effective way to promote the consumption of the PV energy. Although various stochastic optimization (SO) models have been proposed to derive operating rules for a hydro–PV hybrid generation system (HGS), there is a general lack of understanding regarding which kind of SO model could yield potentially better operating rules. To address this issue, we proposed a methodology to evaluate 3 types of representative SO models for deriving operating rules of a grid-connected hydro–PV HGS. First, the SO models were constructed to derive 10 operating rules using historical hydro-meteorological data. Then, a multivariate stochastic simulation approach was proposed to generate the HGS's uncertain inputs synchronously under historical and various hypothetical climatic conditions. Finally, the performance of these operating rules was evaluated in terms of economy, reliability, vulnerability, resilience, and robustness. China's Longyangxia hydro–PV HGS was selected as a case study. It is shown that parameterization-simulation-optimization model has the capability to produce effective operating rules for the hydro–PV HGS that can balance economy, reliability and robustness under various climatic conditions, and is recommended to use in the long-term operation modelling of the hydro-based HGS.