Long-term optimized scheduling of hydro-wind-PV complementary systems considering extreme new energy output events

Abstract

[Objective] To address the risks of power shortage or water abandonment in hydro-wind-PV complementary systems under continuous extreme new energy output events, and to coordinate the mid-term scheduling risks and long-term power generation benefits of the system, a long-term optimized scheduling method for hydro-wind-PV complementarity considering extreme new energy output is proposed. [Methods] First, extreme new energy output scenarios were defined, and samples were extracted from multi-year historical data to reveal the characteristics of extreme new energy output. Second, a scheduling risk assessment method for hydro-wind-PV systems under extreme new energy scenarios was developed. Finally, a multi-objective optimization model for hydro-wind-PV complementarity was established, considering both power generation and scheduling risks to enhance the system's response capability to extreme new energy events, and it was validated using the Beipan River Clean Energy Base as a case study. [Results] The result showed that taking a normal year as an example, before optimization, the maximum power shortage risk reached 0.75×10⁸ kWh in the pre-flood stage, while the maximum power curtailment risk reached 0.31×10⁸ kWh in the post-flood stage. Compared with the power-generation-optimal solution, the balanced scheme reduced scheduling risk by 0.48×10⁸ kWh and decreased power generation by 0.17×10⁸ kWh. Compared with the risk-optimal solution, the balanced scheme increased scheduling risk by 0.21×10⁸ kWh while improving power generation by 0.66×10⁸ kWh. The proposed model recommended controlling the water level of Guangzhao Reservoir within 692.15~694.93 m in the pre-flood stage and 743.84~745.00 m in the post-flood stage. [Conclusion] The hydro-wind-PV system shows significant limitations in flexible regulation performance. The proposed multi-objective optimization model can effectively coordinate power generation benefits and scheduling risks under extreme new energy scenarios. The key-node water level intervals corresponding to the Pareto front set can serve as reasonable water level control ranges. The balanced scheme demonstrates excellent performance in balancing power generation benefits and risk control and achieves a significant reduction in scheduling risks at the expense of only a small loss in generation, thereby providing valuable guidance for formulating scheduling strategies against extreme new energy output.

Keywords

hydro-wind-PV complementarity / extreme new energy output / key-node water level control / risk quantification / optimized scheduling / runoff / Pareto / multi-objective optimization