随着可再生能源的快速发展，小水电站作为一种清洁能源，展现出良好的发展前景。然而，目前小水电站面临着规模较小、参与电网调度机制不足以及调峰调频运行模式亟待创新等问题。基于小水电站的运行特点，考虑火电机组的成本与排放，以及小水电站的稳定运行，构建了多级梯度变速控水稳定调节的小水电站模型。同时，提出了改进的雾凇优化算法及多梯度供-储协同调度策略，以探讨实现系统经济效益、环境效益和调度稳定性综合最优决策方案。实验结果表明，与粒子群优化(particle swarm optimization, PSO)算法、灰狼优化(grey wolf optimizer, GWO)算法及冠豪猪(crested porcupine optimizer, CPO)算法相比，改进后的雾凇优化算法在提高系统经济性方面约提升8.7%，减少污染排放约20.6%，并增强小水电站运行稳定性约32.6%。研究结果验证了所提出模型和算法的有效性，为多源能互补系统协调运行优化提供了新的思路。

With the rapid development of renewable energy, small hydropower station, as a kind of clean energy, shows a good development prospect. However, at present, small hydropower stations are faced with problems such as small scale, insufficient mechanism of participating in power grid dispatching and urgent innovation of operation mode of peak and frequency regulation. Based on the operation characteristics of small hydropower station, considering the cost and emission of thermal power units and the stable operation of small hydropower station, a small hydropower station model with multi-level gradient variable speed water control and stability regulation is constructed. At the same time, an improved growth rime algorithm and multi-gradient supply-storage cooperative scheduling strategy are proposed to explore the optimal decision scheme to realize the economic benefit, environmental benefit and scheduling stability of the system. The experimental results show that compared with other algorithms such as particle swarm optimization (PSO), grey wolf optimizer (GWO) and crested porcupine optimizer (CPO), The improved rime optimization algorithm can improve the economy of the system by 8.7%, reduce the pollution emission by 20.6%, and enhance the operation stability of the small hydropower station by 32.6%. The results validate the effectiveness of the proposed model and algorithm, and provide a new idea for the coordinated operation optimization of multi-source energy complementary systems.