Optimization of a photovoltaic–wind–pumped hydro co-generation system using an improved artificial hummingbird algorithm

Given the rapid development and integration of renewable energy into the grid, there is an urgent need to design and develop storage systems that can effectively complement electricity generation from renewable energy sources. To address the fluctuations in photovoltaic (PV) and wind power generation, a co-generation system of PV, wind, and pumped hydropower was established. This study primarily aims to maximize the daily revenue of the integrated power generation system while limiting it through system constraints. By introducing Circle chaos mapping, the Sine Cosine algorithm (SCA), and Cauchy perturbation, an improved artificial hummingbird algorithm (C–SCA–AHA) was established. To validate the effectiveness of the proposed algorithm, a series of tests were conducted on 23 standard benchmark functions. Subsequently, C–SCA–AHA was evaluated by optimizing the co-generation system. A comparative analysis of the results in the four scenarios demonstrated the superior performance of C–SCA–AHA over other algorithms. In Scenarios 1–4, the benefits achieved by C–SCA–AHA were CNY 1.52, 1.53, 1.57, and 1.54 million, respectively. These results represent increases of 26 %, 28 %, 29 %, and 27 %, respectively, compared to the benefits derived from PV and wind power generation.