Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Operation Strategy of Rail Transit Green Energy System Considering Uncertainty Risk of Photovoltaic Power Output
Author:
Affiliation:

1.State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing102206, China;2.School of Engineering, Qinghai University of Technology, Xining810016, China;3.New Energy (Photovoltaic) Industry Research Center and the Key Laboratory for Smart Operation of New Energy Power System of the Ministry of Education, Qinghai University Xining810016, China;4.Nikola Tesla Electrical Engineering Institute, University of Belgrade, Serbia11000, Belgrade

Fund Project:

This work was supported in part by the National Key Research and Development Program of China (No. 2021YFB2601502) and in part by the Beijing Natural Science Foundation Program (No. L221002).

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    Abstract:

    The integration of photovoltaic power generation is a new development into the traction power supply system (TPSS). However, traditional research on the TPSS operation strategy has not fully considered the risk of uncertainty in photovoltaic power output. To this end, we propose an operation strategy for the rail transit green energy system that considers the uncertainty risk of photovoltaic power output. First, we establish a regenerative braking energy utilization model that considers the impact of time-of-use (TOU) electricity price on the utilization efficiency and economic profit of regenerative braking energy and compensates for non-traction load. Then, we propose an operation strategy based on the balance of power supply and demand that uses an improved light robust (ILR) model to minimize the total cost of the rail transit green energy system, considering the risk of uncertainty in photovoltaic power output. The model incorporates the two-step load check on the second-level time scale to correct the operational results, solve the issue of different time resolutions between photovoltaic power and traction load, and achieve the coordinated optimization of risk cost and operation cost after photovoltaic integration. Case studies demonstrate that the proposed model can effectively consider the impact of the uncertainty in photovoltaic power output on the operation strategy, significantly improving the efficiency and economy of the system operation.

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History
  • Received:October 24,2023
  • Revised:January 11,2024
  • Adopted:
  • Online: December 20,2024
  • Published: