A Study on the Optimized Scheduling of Cascade Hydropower -Wind-Solar Complementary Systems Based on a Master-Slave Game Framework

The advancement of integrated cascade hydropower -wind-solar development holds the potential to significantly enhance the reliability of renewable energy supply and accelerate the green, low-carbon transformation of the energy sector. This study introduces the concept of multi-cluster dynamic coordination to fully exploit the flexible regulation capabilities of cascade hydropower, proposing an optimized scheduling method aimed at maximizing the integration of cascade hydropower-wind-solar generation. First, a master-slave game model is established using the clustering concept, where aggregators and wind-solar clusters are the key elements. The upper layer of the model focuses on maximizing the aggregator's benefit through optimal electricity pricing, while the lower layer employs a hybrid grey wolf-particle swarm optimization algorithm (GWO-PSO). This algorithm uses the aggregator's electricity price as a guiding signal for determining the wind-solar output of each cluster. Next, with the goal of maximizing the consumption of cascade hydropower - wind-solar electricity, the wind-solar output from each cluster is used as a supporting factor to optimize the output of cascade hydropower. Finally, a case study of a typical cascade hydropower -wind-solar system in Northwest China is presented, and the effectiveness of the proposed joint scheduling method for hydropower-wind-solar systems is validated through a comparison of multiple scheduling schemes.