Abstract: Under the background of carbon peaking and carbon neutrality, the proportion of renewable energy in the novel power system continues to increase, and the retained capacity of thermal power will gradually decrease. The source-load balance will be achieved by combining multiple types of energy storage, such as pumped storage and electrochemical storage, with thermal power. This paper proposes an effective method to evaluate the capacity demand of thermal power and multi-type energy storage with given capacities of renewable energy and load demand. First, the discrete Fourier transform (DFT) is performed on the time series of net load and the spectrum is clustered. Then the distribution coefficient is introduced as a continuous variable to enable a single frequency component to be assigned to thermal power units, pumped hydro storage and battery storage. Thus, the dispatching curves in the time domain are obtained by inverse discrete Fourier transform, which are used to evaluate and optimize the capacity of thermal power and energy storage devices. The objective function of the proposed method is convex. Since the continuous distribution coefficient is adopted and the linear constraints are adopted, the whole problem can be transformed into a linear program. The limitation of the cut-off frequency method is overcome, where the flexibility of thermal power is hard to be utilized due to the non-convexity of the optimization model. Case studies are conducted based on the data of Northwest Power Grid, verifying that the proposed model can make full use of the dispatch potential of thermal power and coordinate the joint operation of thermal power and energy storage devices. Different wind-photovoltaic ratios and renewable penetration ratios are compared. The matching results show that the investment cost can be reduced with appropriate ratios.