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A Multi-Time Scale Scheduling Model for Power Generation Systems with a High Proportion of New Energy Including Pumped Storage Power Stations
Received date: 2023-04-07
Revised date: 2023-06-14
Accepted date: 2023-06-16
Online published: 2023-07-10
Aimed at the accommodation problem of a high proportion of new energy connected to the power grid, a multi-time scale coordinated scheduling model for power generation systems with a high proportion of new energy including pumped storage power stations is proposed. Based on the characteristics that the prediction accuracy of wind, photovoltaic (PV) and load power improves step by step with the shortening of time scales, a three-phase coordinated scheduling model is constructed with the goal of minimizing the total operating cost of the system, which includes a 24-hour day-ahead plan, a 1-hour intraday plan and a 15-minute real-time plan. Through the coordination of multiple time scales, the power generation plan is revised step by step, which ensures that the pumped storage power, the wind power, the PV power, and the thermal power output track the load well. Based on the CPLEX commercial optimization software, a mixed integer linear programming method is used to simulate and analyze the wind-PV-thermal-pumped storage complementary power generation system with six pumped storage units. The results show that the pumped storage units can take advantage of short load response time and fast power regulation speed to reduce the regulatory burden of thermal power units and relieve their regulatory pressure effectively. The coordination and cooperation on multiple time scales reduces wind and PV power curtailment and improves new energy accommodation level.
GU Huijie , ZHOU Huafeng , PENG Chaoyi , HU Yaping , ZHAO Xinyi , XIE Jun , SHI Xionghua . A Multi-Time Scale Scheduling Model for Power Generation Systems with a High Proportion of New Energy Including Pumped Storage Power Stations[J]. Journal of Shanghai Jiaotong University, 2024 , 58(12) : 1957 -1967 . DOI: 10.16183/j.cnki.jsjtu.2023.123
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