Abstract
In recent years, deep learning and reinforcement learning algorithms have attracted wide attention in the field of power investment and planning. This paper takes the low-carbon power investment model in the process of power investment as the research object, and analyzes the influence of carbon emission and coal burning constraints on power investment. Firstly, the optimal power investment model considering coal supply constraint and carbon emission constraint is established. Then, considering the advantages of deep learning and reinforcement learning algorithms, a deep deterministic policy gradient (DDPG) algorithm is proposed to select and optimize power investment schemes. Finally, the effectiveness of the proposed model and algorithm is verified by the sensitivity analysis of an example.
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