Breaking time-scale boundary: An optimization framework for improving multi-timescale operation characteristics of pumped storage power plant

The multi-timescale operation of pumped storage power plant is crucial for enhancing renewable energy consumption capacity and improving the power system operation characteristics. However, current hour-scale strategies neglect second-scale transients, making it difficult to balance economy, safety, and stability. This study proposes a novel optimization framework that establishes the relationship between the second-scale and hour-scale characteristics of pumped storage power plant to improve the multi-timescale operation characteristics. Firstly, a multi-timescale coupled model is developed, consisting of a second-scale mathematical model and an hour-scale short-term scheduling model. Secondly, the datasets of multi-timescale operation characteristic under different operating conditions are obtained, considering 6 multi-timescale operation characteristics. Thirdly, using a pumped storage power plant in the Southeastern China as an example, the aforesaid multi-timescale operation characteristics are further subdivided into 14 indicators, and coupled to the short-term scheduling model through the datasets. The non-dominated sorting genetic algorithm-III is introduced to solve the short-term scheduling model. Results indicate that compared to the traditional short-term scheduling strategy, the proposed approach significantly improves the second-scale operation characteristics at a small cost. The largest improvement is in the unit status indicator, which increases by 38.18 %–45.81 % across different daily load curve scenarios. In summary, the method proposed in this study maximizes comprehensive operation benefits and offers a new perspective for the operation and management of pumped storage power plant.