In the renewable energy investment market, there are risks such as fossil fuel price fluctuations, environmental risks caused by pollutant emissions, electricity price fluctuations caused by energy policies, and so on, which bring certain difficulties to measure the investment efficiency.

In this regard, the paper applies the portfolio theory to the Data Envelopment Analysis (DEA) model to evaluate investment efficiency. First of all, the Monte Carlo method is used to simulate the four uncertain factors of fuel unit price, feed-in tariff, annual operating hours, and carbon price, so as to quantitatively measure the risk and return of different power generation. According to the portfolio theory, it evaluates the portfolio risks and returns, respectively as input and output indicators, so as to build a Data Envelopment Analysis (DEA) model to estimate investment efficiency.

The simulation and experimental results demonstrate the effectiveness of the presented method. In details, we select a poor efficiency sample, and then, we propose an optimization measure to improve the efficiency. By adjusting the proportion of its investment, the result proves that increasing the proportion of renewable energy can realize optimization and validity of renewable energy investment. Thus, it provides auxiliary support for the investment decision of renewable energy and realizes the coordinated allocation and efficient utilization of renewable energy.