Under the dual pressures of energy crisis and environmental pollution, China’s new energy power industry has become a focal point for environmental management and requires greater investment. In this context, as a significant input of investment projects, discount rate requires a well-calibrated evaluation because new energy power investment projects are highly capital intensive. The main objective of this paper is to evaluate the discount rate of China’s new energy power industry. First, we use Moving Average to correct the parameters of capital asset pricing model (CAPM) and weighted average cost of capital, which extends the literature on the avoidance of CAPM noise information problem. Second, we study the industry-level annual discount rates of mainly China’s new energy power industries, including hydropower, nuclear power, wind power, and photovoltaic power industries for the period of 2014–2019. The results show that discount rates in China’s new energy power industries evolved differently between the years of 2014–2019 with average annual discount rates being 7.56%, 5.83%, 5.60%, and 8.64%, for the hydropower, nuclear power, wind power, and photovoltaic power industries, respectively. In 2019, the four annual discount rates were highest for the photovoltaic power industry (8.66%), followed by hydropower (7.17%), wind power (5.72%), and nuclear power industry (5.26%). Forecasting to 2020 from the 2019 evaluation base period, the discount rates are 6.37%, 5.00%, 6.57%, and 9.05% for the photovoltaic power, hydropower, wind power, and nuclear power industries, respectively. Under the different capital structures, their forecasts for the photovoltaic power, hydropower, wind power, and nuclear power industries in 2020 are, respectively, within [4.35%, 9.24%], [3.92%, 7.10%], [4.58%, 10.40%], [5.46%, 14.81%]. We also discussed more details on capital structure and forecast period of discount rates for China’s new energy power industries. Our analysis shows that it is necessary to establish a new energy power industry database and steadily promote the implementation of policies.