Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Security-constrained Transmission Maintenance Optimization Considering Generation and Operational Risk Costs
Author:
Affiliation:

1.Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology, China Electric Power Research Institute, Beijing 100192, China;2.State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University, Chongqing 400044, China

Fund Project:

This work was supported by the Scientific and Technological Project of State Grid Corporation of China “Multilevel maintenance scheduling and its coordination with medium-term and long-term dispatching decision” (No. 5442DZ210012).

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    Abstract:

    With the large-scale integration of renewable energy, the traditional maintenance arrangement during the load valley period cannot satisfy the transmission demand of renewable energy generation. Simultaneously, in a market-oriented operation mode, the power dispatching control center aims to reduce the overall power purchase cost while ensuring the security of the power system. Therefore, a security-constrained transmission maintenance optimization model considering generation and operational risk costs is proposed herein. This model is built on double-layer optimization framework, where the upper-layer model is used for maintenance and generation planning, and the lower-layer model is primarily used to address the operational security risk arising from the random prediction error and N -1 transmission failure. Correspondingly, a generation-maintenance iterative algorithm based on a defined cost feedback is included to increase solution efficiency. Generation cost is determined using long-term security-constrained unit commitment, and the operational risk cost is obtained using a double-layer N-1 risk assessment model. An electrical correlation coupling coefficient is proposed for the solution process to avoid maintenance of associated equipment simultaneously, thereby improving model convergence efficiency. The IEEE 118-bus system is used as a test case for illustration, and test results suggest that the proposed model and algorithm can reduce the total cost of transmission maintenance and system operation while effectively improving the solution efficiency of the joint optimization model.

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History
  • Received:March 07,2023
  • Revised:May 19,2023
  • Adopted:
  • Online: May 20,2024
  • Published: