A Multi-stage Portfolio Investment Optimization Model for Pumped Storage Power Plants with Total Investment and Optimal Timing Constraints

Pumped storage, as the most mature technology and the largest construction scale energy storage technology in the world, its investment decision is a multi-stage dynamic optimization problem, which needs to ensure the synergistic optimization of the investment benefits and the long-term development strategy of the power system. In order to realize the multi-dimensional comprehensive assessment of investment benefits, this paper proposes a multi-stage investment timing optimization model for pumped storage power plants. Firstly, a pumped storage project investment benefit evaluation index system is constructed systematically, and then a multi-stage dynamic optimization model is established to determine the optimal investment timing scheme by considering key factors such as capital constraints and time value. Empirical studies based on seven planned pumped storage power plants in Qinghai Province, China, show that the model can effectively maximize the overall investment benefits. The research results not only validate the feasibility and effectiveness of the proposed methodology, but also provide a scientific quantitative analysis tool for regional pumped storage project investment planning and decision-making.