## 1 Introduction  
The rapid development of the Chinese economy has resulted in a sharp increase in energy consumption. However, China's fossil-based energy consumption structure has also brought about a severe energy crisis as well as environmental issues. The optimization of the energy consumption structure has already been shown to be an important method for alleviating the above contradiction [1]. Consequently, the importance of wind, solar, and other green renewable energy sources has become increasingly prominent. The Chinese government recently implemented numerous monetary compensation policies to guarantee the sustainable development of renewable energy [2]. The cumulative installed capacities of wind power and photovoltaic power had already reached 169 \(\times\) 10\({}^{6}\) kW and 77.42 \(\times\) 10\({}^{6}\) kW, respectively in 2016. However, owing to the obvious uncertainty and volatility of wind power and solar power, the retained generation of power should be abandoned to ensure stable system operation [3]. In only the first half of 2017, the total abandoned wind and photovoltaic power generation reached 23.5 \(\times\) 10\({}^{9}\) kW\(\cdot\)h and 3.7 \(\times\) 10\({}^{9}\) kW\(\cdot\)h, respectively. Obviously, the solution to the abandoned energy problem has already become an important issue for the promotion of clean energy development and the optimization of the energy consumption structure. Because to the grid-connected system of uncontrollable power sources brings great challenges to the stable operation of power systems, three available research methods have been adopted by domestic and foreign scholars and workers, namely, improving the forecast accuracy, improving energy storage device (ESD) technology, and utilizing complementary power sources [4]. Firstly, improving the forecast accuracy of uncontrollable clean power sources could reduce the output deviation of power generation. [PERSON] et al. [5] designed a new forecast model with an advanced intelligent algorithm, a data preprocessing technique, and a non-negative constraint theory. [PERSON] et al. [6] applied the mixture models of [PERSON]'s self-organizing map and the radial basis functions as the clustering method and the classification method, respectively. Then, ESD could reduce the fluctuations of the power output of intermittent clean energy by utilizing the characteristics of discharging-charging power [7]. [PERSON] et al. [8] designed a new distributed energy generation system by integrating renewable power, air energy storage, and natural gas combustion. [PERSON] et al. [9] analyzed the feasibility of economics and technology when ESDs are applied to a wind farm. Furthermore, [PERSON] et al. [10] discussed the collaborative synthetic effect of ESDs and the demand response in promoting clean energy power generation. The above forecast methods have already been used in practical applications; however, the achievement of high accuracy relies on having an excessively large amount of data, which limits the application space. Meanwhile, ESDs could promote the output of the uncontrollable power source; however, the high investment costs limit the actual application space. Therefore, determining how to utilize complementary but different power sources is key for improving the reliability of the power supply. Correspondingly, developing an optimal capacity configuration scheme for wind power, photovoltaic power, and conventional power sources could better utilize the complementary characteristics of different power sources [11]. [PERSON] et al. [12] developed a multi-input-output fuzzy logic smart controller to achieve the optimal plan for a hybrid power system. [PERSON] et al. [13] constructed a short-term optimal scheduling model for a hybrid power system with wind power plants WPP and photovoltaic power plants (PV). [PERSON] et al. [14] put forward a new hybrid power system including WPP, PV, and fuel cell power generation.